diff --git "a/test.jsonl" "b/test.jsonl" new file mode 100644--- /dev/null +++ "b/test.jsonl" @@ -0,0 +1,1628 @@ +{"id": "T1_all_20251226_0002", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DBB"], "decision_date": "2025-12-26", "context_summary": "DBB over past 60 days: cumulative return +7.9%, annualized vol 14.0%. Market regime: sideways.", "question": "Asset: DBB\nHistorical prices (past 60 trading days): start=20.40, end=22.01, cumulative_return=+7.9%, annualized_volatility=14.0%\nMacro context: {'fed_funds_rate': 3.64, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.68, 't10y3m_spread': 0.46, 'breakeven_10y': 2.24, 'hy_oas': 2.84, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.18, 'vix': 13.470000267028809}\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": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for DBB starting 2025-12-26 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.078641, "annualized_vol": 0.140096, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251027_0004", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-10-27", "context_summary": "XLF over past 60 days: cumulative return +3.7%, annualized vol 13.9%. Market regime: bull.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=50.79, end=52.65, cumulative_return=+3.7%, annualized_volatility=13.9%\nMacro context: {'fed_funds_rate': 4.11, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.54, 't10y3m_spread': 0.09, 'breakeven_10y': 2.29, 'hy_oas': 2.88, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.19, 'vix': 16.3700008392334}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q PG 2025-10-24] pg-20250930 0000080424 6/30 2026 Q1 false http://fasb.org/us-gaap/2025#OtherAssetsNoncurrent http://fasb.org/us-gaap/2025#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2025#OtherAssetsNoncurrent http://fasb.org/us-gaap/2025#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2025#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2025#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2025#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2025#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2025#AccountsPayableCurrent http://fasb.org/us-gaap/2025#AccountsPayableCurrent xbrli:shares iso4217:USD iso4217:USD xbrli:shares pg:segment xbrli:pure pg:country pg:taxable_jurisdiction pg:audit pg:employee 0000080424 2025-07-01 2025-09-30 0000080424 us-gaap:CommonStockMember 2025-07-01 2025-09-30 0000080424 pg:A0.110NotesDue2026Member 2025-07-01 2025-09-30 0000080424 pg:A3.250EURNotesDue2026Member 2025-07-01 2025-09-30 0000080424 pg:A4.875EURNotesDueMay2027Member 2025-07-01 2025-09-30 0000080424 pg:A1.200NotesDue2028Member 2025-07-01 2025-09-30 0000080424 pg:A3.150EURONotesDue2028Member 2025-07-01 2025-09-30 0000080424 pg:A1.250NotesDue2029Member 2025-07-01 2025-09-30 0000080424 pg:A1.800NotesDue2029Member 2025-07-01 2025-09-30 0000080424 pg:A6.250GBPNotesDueJanuary2030Member 2025-07-01 2025-09-30 0000080424 pg:A0.350NotesDue2030Member 2025-07-01 2025-09-30 0000080424 pg:A0.230NotesDue2031Member 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0000080424 us-gaap:AdditionalPaidInCapitalMember 2024-06-30 0000080424 pg:ReserveforESOPDebtRetirementMember 2024-06-30 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-06-30 0000080424 us-gaap:TreasuryStockCommonMember 2024-06-30 0000080424 us-gaap:RetainedEarningsMember 2024-06-30 0000080424 us-gaap:NoncontrollingInterestMember 2024-06-30 0000080424 2024-06-30 0000080424 us-gaap:RetainedEarningsMember 2024-07-01 2024-09-30 0000080424 us-gaap:NoncontrollingInterestMember 2024-07-01 2024-09-30 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-01 2024-09-30 0000080424 us-gaap:CommonStockMember 2024-07-01 2024-09-30 0000080424 us-gaap:TreasuryStockCommonMember 2024-07-01 2024-09-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2024-07-01 2024-09-30 0000080424 us-gaap:PreferredStockMember 2024-07-01 2024-09-30 0000080424 pg:ReserveforESOPDebtRetirementMember 2024-07-01 2024-09-30 0000080424 us-gaap:CommonStockMember 2024-09-30 0000080424 us-gaap:PreferredStockMember 2024-09-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2024-09-30 0000080424 pg:ReserveforESOPDebtRetirementMember 2024-09-30 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-09-30 0000080424 us-gaap:TreasuryStockCommonMember 2024-09-30 0000080424 us-gaap:RetainedEarningsMember 2024-09-30 0000080424 us-gaap:NoncontrollingInterestMember 2024-09-30 0000080424 2024-09-30 0000080424 us-gaap:OperatingSegmentsMember us-gaap:ProductConcentrationRiskMember pg:FabricCareMember us-gaap:SalesRevenueNetMember pg:FabricHomeCareSegmentMember 2025-07-01 2025-09-30 0000080424 us-gaap:OperatingSegmentsMember us-gaap:ProductConcentrationRiskMember pg:FabricCareMember us-gaap:SalesRevenueNetMember pg:FabricHomeCareSegmentMember 2024-07-01 2024-09-30 0000080424 us-gaap:OperatingSegmentsMember us-gaap:ProductConcentrationRiskMember pg:HomeCareMember us-gaap:SalesRevenueNetMember pg:FabricHomeCareSegmentMember 2025-07-01 2025-09-30 0000080424 us-gaap:OperatingSegmentsMember us-gaap:ProductConcentrationRiskMember pg:HomeCareMember us-gaap:SalesRevenueNetMember pg:FabricHomeCareSegmentMember 2024-07-01 2024-09-30 0000080424 us-gaap:OperatingSegmentsMember us-gaap:ProductConcentrationRiskMember pg:HairCareMember us-gaap:SalesRevenueNetMember pg:BeautySegmentMember 2025-07-01 2025-09-30 0000080424 us-gaap:OperatingSegmentsMember us-gaap:ProductConcentrationRiskMember pg:HairCareMember us-gaap:SalesRevenueNetMember pg:BeautySegmentMember 2024-07-01 2024-09-30 0000080424 us-gaap:OperatingSegmentsMember us-gaap:ProductConcentrationRiskMember pg:Baby [...TRUNCATED...] ectors on December 13, 2022, pursuant to authority granted by shareholders at the annual meeting on October 13, 2009) (Incorporated by reference to Exhibit (3-2) of the Company’s Current Report on Form 8-K filed December 13, 2022) 4.1 Indenture, dated as of September 3, 2009, between the Company and Deutsche Bank Trust Company Americas, as Trustee (Incorporated by reference to Exhibit (4-1) of the Company's Annual Report on Form 10-K for the year ended June 30, 2015) 10.1 The Procter & Gamble Company 2025 Stock and Incentive Compensation Plan *+ 10.2 Short-Term Achievement Reward Program *+ 10.3 Performance Stock Program Summary *+ 10.4 Long-Term Incentive Program Summary *+ 10.5 Regulations of the Compensation and Leadership Development Committee for The Procter & Gamble 2025 Stock and incentive Compensation Plan, The Procter & Gamble 2019 Stock and Incentive Compensation Plan and The Procter & Gamble 2014 Stock and Incentive Compensation Plan. *+ 10.6 Retirement Plan Restoration Program Summary *+ 10.7 Form of STAR Stock Option Award Agreement *+ 10.8 Form of Director Annual RSU Award Agreement *+ 10.9 Form of Director Annual RSU Award Agreement (Deferred) *+ 10.10 Form of Director RSU Award Agreement (Quarterly Fees) *+ 10.11 Form of PSU Award Agreement *+ 10.12 Form of Deferred PSU Award Agreement *+ 10.13 Form of LTIP RSU Award Agreement *+ 10.14 Form of LTIP Stock Option Award Agreement *+ 10.15 Form of Special RSU Award Agreement *+ 10.16 Form of Retirement Restoration Plan RSU Award Agreement *+ 31.1 Rule 13a-14(a)/15d-14(a) Certification – Chief Executive Officer + 31.2 Rule 13a-14(a)/15d-14(a) Certification – Chief Financial Officer + 32.1 Section 1350 Certifications – Chief Executive Officer + 32.2 Section 1350 Certifications – Chief Financial Officer + 101.SCH (1) Inline XBRL Taxonomy Extension Schema Document 101.CAL (1) Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF (1) Inline XBRL Taxonomy Definition Linkbase Document 101.LAB (1) Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE (1) Inline XBRL Taxonomy Extension Presentation Linkbase Document 104  Cover Page Interactive Data File (formatted in Inline XBRL and contained in Exhibit 101) The Procter & Gamble Company 27 * Compensatory plan or arrangement + Filed herewith (1) Pursuant to Rule 406T of Regulation S-T, this information is furnished and not filed for purposes of Sections 11 or 12 of the Securities Act of 1933 and Section 18 of the Securities Exchange Act of 1934, and otherwise is not subject to liability under these sections. Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this Report to be signed on its behalf by the undersigned thereunto duly authorized. THE PROCTER & GAMBLE COMPANY October 24, 2025 /s/ MATTHEW W. JANZARUK Date (Matthew W. Janzaruk) Senior Vice President - Chief Accounting Officer (Principal Accounting Officer)\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": -0.014813, "explanation": "The actual 21-day forward return for XLF starting 2025-10-27 was -1.48%, which classifies as 'negative'.", "metadata": {"future_return": -0.014813, "horizon_days": 21, "hist_return": 0.03667, "annualized_vol": 0.138577, "has_text": true, "text_chars": 9044}} +{"id": "T1_all_20251209_0007", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-12-09", "context_summary": "DOT-USD over past 60 days: cumulative return +0.0%, annualized vol 88.2%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=3.54, end=3.54, cumulative_return=+0.0%, annualized_volatility=88.2%\nMacro context: {'fed_funds_rate': 3.89, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.6, 't10y3m_spread': 0.44, 'breakeven_10y': 2.26, 'hy_oas': 2.89, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.19, 'vix': 16.65999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for DOT-USD starting 2025-12-09 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.881576, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250716_0010", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["HAUZ"], "decision_date": "2025-07-16", "context_summary": "HAUZ over past 60 days: cumulative return +8.1%, annualized vol 11.5%. Market regime: bull.", "question": "Asset: HAUZ\nHistorical prices (past 60 trading days): start=20.25, end=21.89, cumulative_return=+8.1%, annualized_volatility=11.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.55, 't10y3m_spread': 0.08, 'breakeven_10y': 2.41, 'hy_oas': 2.95, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 17.3799991607666}\nMarket regime: bull\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": 0.040871, "explanation": "The actual 21-day forward return for HAUZ starting 2025-07-16 was +4.09%, which classifies as 'positive'.", "metadata": {"future_return": 0.040871, "horizon_days": 21, "hist_return": 0.081403, "annualized_vol": 0.115247, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250424_0013", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2025-04-24", "context_summary": "QUAL over past 60 days: cumulative return -10.7%, annualized vol 21.1%. Market regime: bear.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=181.50, end=162.07, cumulative_return=-10.7%, annualized_volatility=21.1%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.59, 't10y3m_spread': 0.07, 'breakeven_10y': 2.29, 'hy_oas': 3.75, 'ig_oas': 1.08, 'ted_spread': 0.09, 'mortgage_30y': 6.83, 'vix': 28.450000762939453}\nMarket regime: bear\nRecent filing/news:\n[SEC 10-Q BA 2025-04-23] ba-20250331 FALSE 2025 Q1 0000012927 --12-31 http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 155 151 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure ba:extension_period ba:aircraft ba:tanker ba:lot ba:simulator ba:segment 0000012927 2025-01-01 2025-03-31 0000012927 us-gaap:CommonStockMember 2025-01-01 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ba:AntidilutiveOrPerformanceConditionNotMetMember 2025-01-01 2025-03-31 0000012927 us-gaap:PerformanceSharesMember ba:AntidilutiveOrPerformanceConditionNotMetMember 2024-01-01 2024-03-31 0000012927 us-gaap:RestrictedStockUnitsRSUMember ba:AntidilutiveOrPerformanceConditionNotMetMember 2025-01-01 2025-03-31 0000012927 us-gaap:RestrictedStockUnitsRSUMember ba:AntidilutiveOrPerformanceConditionNotMetMember 2024-01-01 2024-03-31 0000012927 us-gaap:EmployeeStockOptionMember ba:AntidilutiveOrPerformanceConditionNotMetMember 2025-01-01 2025-03-31 0000012927 us-gaap:Employee [...TRUNCATED...] 160;Yet be Purchased Under the Plans or Programs 1/1/2025 thru 1/31/2025 33,204  $171.87  2/1/2025 thru 2/28/2025 46,784  183.15  3/1/2025 thru 3/31/2025 842  158.96  Total 80,830  $178.26  (1) A total of 80,830 shares were transferred to us from employees in satisfaction of minimum tax withholding obligations associated with the vesting of restricted stock units during the period. We did not purchase any shares of our common stock in the open market pursuant to a repurchase program. Item 3. Defaults Upon Senior Securities Not applicable. Item 4. Mine Safety Disclosures Not applicable. 51 Table of Contents Item 5. Other Information During the three months ended March 31, 2025, none of our directors or officers adopted , modified or terminated a “Rule 10b5-1 trading arrangement” or a “non-Rule 10b5-1 trading arrangement” as such terms are defined under Item 408 of Regulation S-K. 52 Table of Contents Item 6. Exhibits 10.1 Form of U.S. Notice of Terms of Long-Term Incentive Non-Qualified Premium-Priced Stock Option* 10.2 Form of Non-U.S. Notice of Terms of Long-Term Incentive Non-Qualified Premium-Priced Stock Option* 10.3 Form of U.S. Notice of Terms of Long-Term Incentive Restricted Stock Units* 10.4 Form of Non-U.S. Notice of Terms of Long-Term Incentive Restricted Stock Units* 10.5 Form of U.S. Notice of Terms of Supplemental Restricted Stock Units* 15 Letter from Independent Registered Public Accounting Firm regarding unaudited interim financial information 31.1 Certification of Chief Executive Officer pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certification of Chief Executive Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 32.2 Certification of Chief Financial Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File (formatted as inline XBRL and contained in Exhibit 101) * Management contract or compensatory plan 53 Table of Contents Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. THE BOEING COMPANY (Registrant) April 23, 2025 /s/ Michael J. Cleary (Date) Michael J. Cleary Senior Vice President and Controller 54\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": 0.0431, "explanation": "The actual 21-day forward return for QUAL starting 2025-04-24 was +4.31%, which classifies as 'positive'.", "metadata": {"future_return": 0.0431, "horizon_days": 21, "hist_return": -0.107068, "annualized_vol": 0.210807, "has_text": true, "text_chars": 9044}} +{"id": "T1_all_20250711_0016", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2025-07-11", "context_summary": "SCHP over past 60 days: cumulative return +2.1%, annualized vol 4.6%. Market regime: sideways.", "question": "Asset: SCHP\nHistorical prices (past 60 trading days): start=25.35, end=25.90, cumulative_return=+2.1%, annualized_volatility=4.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.49, 't10y3m_spread': -0.07, 'breakeven_10y': 2.34, 'hy_oas': 2.92, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 15.779999732971191}\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": "positive", "answer_numeric": 0.012027, "explanation": "The actual 21-day forward return for SCHP starting 2025-07-11 was +1.20%, which classifies as 'positive'.", "metadata": {"future_return": 0.012027, "horizon_days": 21, "hist_return": 0.021399, "annualized_vol": 0.045789, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250421_0019", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-04-21", "context_summary": "XRP-USD over past 60 days: cumulative return -14.9%, annualized vol 105.9%. Market regime: bear.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=2.44, end=2.08, cumulative_return=-14.9%, annualized_volatility=105.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.53, 't10y3m_spread': 0.0, 'breakeven_10y': 2.23, 'hy_oas': 4.02, 'ig_oas': 1.11, 'ted_spread': 0.09, 'mortgage_30y': 6.83, 'vix': 29.64999961853028}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.169838, "explanation": "The actual 21-day forward return for XRP-USD starting 2025-04-21 was +16.98%, which classifies as 'positive'.", "metadata": {"future_return": 0.169838, "horizon_days": 21, "hist_return": -0.148671, "annualized_vol": 1.059217, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250425_0022", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLE"], "decision_date": "2025-04-25", "context_summary": "XLE over past 60 days: cumulative return -7.3%, annualized vol 29.5%. Market regime: bear.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=43.12, end=39.99, cumulative_return=-7.3%, annualized_volatility=29.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.55, 't10y3m_spread': 0.0, 'breakeven_10y': 2.3, 'hy_oas': 3.73, 'ig_oas': 1.06, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 26.46999931335449}\nMarket regime: bear\nRecent filing/news:\n[SEC 10-Q PG 2025-04-24] pg-20250331 0000080424 6/30 2025 Q3 false http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2024#AccountsPayableCurrent http://fasb.org/us-gaap/2024#AccountsPayableCurrent xbrli:shares iso4217:USD iso4217:USD xbrli:shares pg:segment xbrli:pure pg:country pg:taxable_jurisdiction pg:audit 0000080424 2024-07-01 2025-03-31 0000080424 us-gaap:CommonStockMember 2024-07-01 2025-03-31 0000080424 pg:A1.375NotesDue2025Member 2024-07-01 2025-03-31 0000080424 pg:A0.110NotesDue2026Member 2024-07-01 2025-03-31 0000080424 pg:A3.250EURNotesDue2026Member 2024-07-01 2025-03-31 0000080424 pg:A4.875EURNotesDueMay2027Member 2024-07-01 2025-03-31 0000080424 pg:A1.200NotesDue2028Member 2024-07-01 2025-03-31 0000080424 pg:A3.150EURONotesDue2028Member 2024-07-01 2025-03-31 0000080424 pg:A1.250NotesDue2029Member 2024-07-01 2025-03-31 0000080424 pg:A1.800NotesDue2029Member 2024-07-01 2025-03-31 0000080424 pg:A6.250GBPNotesDueJanuary2030Member 2024-07-01 2025-03-31 0000080424 pg:A0.350NotesDue2030Member 2024-07-01 2025-03-31 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us-gaap:NoncontrollingInterestMember 2025-03-31 0000080424 us-gaap:CommonStockMember 2024-06-30 0000080424 us-gaap:PreferredStockMember 2024-06-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2024-06-30 0000080424 pg:ReserveforESOPDebtRetirementMember 2024-06-30 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-06-30 0000080424 us-gaap:TreasuryStockCommonMember 2024-06-30 0000080424 us-gaap:RetainedEarningsMember 2024-06-30 0000080424 us-gaap:NoncontrollingInterestMember 2024-06-30 0000080424 us-gaap:RetainedEarningsMember 2024-07-01 2025-03-31 0000080424 us-gaap:NoncontrollingInterestMember 2024-07-01 2025-03-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-01 2025-03-31 0000080424 us-gaap:CommonStockMember 2024-07-01 2025-03-31 0000080424 us-gaap:TreasuryStockCommonMember 2024-07-01 2025-03-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2024-07-01 2025-03-31 0000080424 us-gaap:PreferredStockMember 2024-07-01 2025-03-31 0000080424 pg:ReserveforESOPDebtRetirementMember 2024-07-01 2025-03-31 0000080424 us-gaap:CommonStockMember 2023-12-31 0000080424 us-gaap:PreferredStockMember 2023-12-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-12-31 0000080424 pg:ReserveforESOPDebtRetirementMember 2023-12-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-12-31 0000080424 us-gaap:TreasuryStockCommonMember 2023-12-31 0000080424 us-gaap:RetainedEarningsMember 2023-12-31 0000080424 us-gaap:NoncontrollingInterestMember 2023-12-31 0000080424 2023-12-31 0000080424 us-gaap:RetainedEarningsMember 2024-01-01 2024-03-31 0000080424 us-gaap:NoncontrollingInterestMember 2024-01-01 2024-03-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-01 2024-03-31 0000080424 us-gaap:CommonStockMember 2024-01-01 2024-03-31 0000080424 us-gaap:TreasuryStockCommonMember 2024-01-01 2024-03-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2024-01-01 2024-03-31 0000080424 us-gaap:PreferredStockMember 2024-01-01 2024-03-31 0000080424 pg:ReserveforESOPDebtRetirementMember 2024-01-01 2024-03-31 0000080424 us-gaap:CommonStockMember 2024-03-31 0000080424 us-gaap:PreferredStockMember 2024-03-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2024-03-31 0000080424 pg:ReserveforESOPDebtRetirementMember 2024-03-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-03-31 0000080424 us-gaap:TreasuryStockCommonMember 2024-03-31 0000080424 us-gaap:RetainedEarningsMember 2024-03-31 0000080424 us-gaap:NoncontrollingInterestMember 2024-03-31 0000080424 2024-03-31 0000080424 us-gaap:CommonStockMe [...TRUNCATED...] ket and/or private transactions and purchases may be increased, decreased or discontinued at any time without prior notice. The share repurchases are authorized pursuant to a resolution issued by the Company's Board of Directors and are expected to be financed by a combination of operating cash flows and issuance of debt.      Item 5. Other Information During the three months ended March 31, 2025, none of our directors or officers adopted or terminated a \"Rule 10b5-1 trading arrangement\" or \"non-Rule 10b5-1 trading arrangement\" as defined in Item 408 of Regulation S-K. Amounts in millions of dollars unless otherwise specified. 30 The Procter & Gamble Company Item 6. Exhibits 3.1 Amended Articles of Incorporation (as amended by shareholders at the annual meeting on October 11, 2011 and consolidated by the Board of Directors on April 8, 2016) (Incorporated by reference to Exhibit (3-1) of the Company's Form 10-K for the year ended June 30, 2016) 3.2 Regulations (as approved by the Board of Directors on December 13, 2022, pursuant to authority granted by shareholders at the annual meeting on October 13, 2009) (Incorporated by reference to Exhibit (3-2) of the Company’s Current Report on Form 8-K filed December 13, 2022) 4.1 Indenture, dated as of September 3, 2009, between the Company and Deutsche Bank Trust Company Americas, as Trustee (Incorporated by reference to Exhibit (4-1) of the Company's Annual Report on Form 10-K for the year ended June 30, 2015) 10.1 Company's Form of Separation Agreement & Release *+ 31.1 Rule 13a-14(a)/15d-14(a) Certification – Chief Executive Officer + 31.2 Rule 13a-14(a)/15d-14(a) Certification – Chief Financial Officer + 32.1 Section 1350 Certifications – Chief Executive Officer + 32.2 Section 1350 Certifications – Chief Financial Officer + 101.SCH (1) Inline XBRL Taxonomy Extension Schema Document 101.CAL (1) Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF (1) Inline XBRL Taxonomy Definition Linkbase Document 101.LAB (1) Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE (1) Inline XBRL Taxonomy Extension Presentation Linkbase Document 104  Cover Page Interactive Data File (formatted in Inline XBRL and contained in Exhibit 101) * Compensatory plan or arrangement + Filed herewith (1) Pursuant to Rule 406T of Regulation S-T, this information is furnished and not filed for purposes of Sections 11 or 12 of the Securities Act of 1933 and Section 18 of the Securities Exchange Act of 1934, and otherwise is not subject to liability under these sections. Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this Report to be signed on its behalf by the undersigned thereunto duly authorized. THE PROCTER & GAMBLE COMPANY April 24, 2025 /s/ MATTHEW W. JANZARUK Date (Matthew W. Janzaruk) Senior Vice President - Chief Accounting Officer (Principal Accounting Officer)\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": -0.004855, "explanation": "The actual 21-day forward return for XLE starting 2025-04-25 was -0.49%, which classifies as 'flat'.", "metadata": {"future_return": -0.004855, "horizon_days": 21, "hist_return": -0.072645, "annualized_vol": 0.294631, "has_text": true, "text_chars": 9044}} +{"id": "T1_all_20250521_0025", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2025-05-21", "context_summary": "IVV over past 60 days: cumulative return +0.1%, annualized vol 22.9%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=587.94, end=588.28, cumulative_return=+0.1%, annualized_volatility=22.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.51, 't10y3m_spread': 0.1, 'breakeven_10y': 2.35, 'hy_oas': 3.2, 'ig_oas': 0.9, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 18.09000015258789}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-20] [\"Alphabet Traders Look to Developer Event to Shift AI Narrative (Bloomberg) -- Alphabet Inc.\\u2019s investors are looking to this week\\u2019s developer conference to see if the company can reset the narrative amid fears that its long-standing market dominance is on shaky ground. Most Read from Bloomberg America, \\u2018Nation of Porches\\u2019 Can Frank Gehry\\u2019s \\u2018Grand LA\\u2019 Make Downtown Feel Like a Neighborhood? NJ Transit Train Engineers Strike, Disrupting Travel to NYC NJ Transit Makes Deal With Engineers, Ending Three-Day Strike The Google I/O event, which begins Tuesday, is expected to showcase the company\\u2019s latest advancements in artificial intelligence. Positive updates could help ease concerns about the rivals nipping at its heels and eating away at its dominant position in web search, even as the company spends heavily on AI. \\u201cThe hope is that it will provide a roadmap for a strong future, because right now everyone is waiting for a shoe to drop and has their finger on the trigger for any negative headline,\\u201d said David Katz, chief investment officer at Matrix Asset Advisors. \\u201cI think it is far stronger than the stock is currently discounting, so view the negativity as a buying opportunity, but it definitely faces more headwinds with AI than it ever did with legacy search.\\u201d The stock is down 12.5% this year, compared with a gain of 1.6% for the Nasdaq 100 Index. Meta Platforms Inc., the other significant player in online advertising, is up almost 9%. Alphabet fell 0.3% on Tuesday. Recent weakness in Alphabet came after an Apple Inc. executive said during court testimony that searches on its Safari web browser fell for the first time in April. Alphabet disputed this, and pointed to I/O as a place where it can address concerns by sharing its latest innovations. Last week, The Information reported that Alphabet will unveil an AI agent for software development at the event, along with a Pinterest-like feature, among other updates to its Gemini AI chatbot. However, an underwhelming presentation may be a cause for further weakness. \\u201cA good story may not be enough at I/O this time around to sway investors given we\\u2019re now armed with recent data points around slower paid click growth, Safari search volume declining for the first time in 22 years, and ChatGPT and Meta AI\\u2019s march to a billion users,\\u201d Bernstein analyst Mark Shmulik wrote. Since ChatGPT emerged in late 2022, Alphabet has seen repeated selloffs on concerns it is falling behind in AI. The issue, along with heightened antitrust uncertainty, has weighed on Alphabet\\u2019s multiple, making it the cheapest big-tech stock by far. Alphabet is still viewed as a central player in AI in terms of both talent and intellectual property, and the stock has repeatedly bounced back from slumps. The company\\u2019s most recent results beat expectations and showed AI-related demand, while an April event focused on the company\\u2019s cloud business w\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": 0.021946, "explanation": "The actual 21-day forward return for IVV starting 2025-05-21 was +2.19%, which classifies as 'positive'.", "metadata": {"future_return": 0.021946, "horizon_days": 21, "hist_return": 0.000571, "annualized_vol": 0.229416, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250131_0028", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DBA"], "decision_date": "2025-01-31", "context_summary": "DBA over past 60 days: cumulative return +12.7%, annualized vol 12.3%. Market regime: sideways.", "question": "Asset: DBA\nHistorical prices (past 60 trading days): start=23.62, end=26.62, cumulative_return=+12.7%, annualized_volatility=12.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.34, 't10y3m_spread': 0.22, 'breakeven_10y': 2.38, 'hy_oas': 2.67, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 15.84000015258789}\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": "negative", "answer_numeric": -0.039521, "explanation": "The actual 21-day forward return for DBA starting 2025-01-31 was -3.95%, which classifies as 'negative'.", "metadata": {"future_return": -0.039521, "horizon_days": 21, "hist_return": 0.12711, "annualized_vol": 0.122851, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250228_0031", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2025-02-28", "context_summary": "ACWI over past 60 days: cumulative return -0.9%, annualized vol 12.6%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=118.74, end=117.72, cumulative_return=-0.9%, annualized_volatility=12.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.22, 't10y3m_spread': -0.03, 'breakeven_10y': 2.37, 'hy_oas': 2.81, 'ig_oas': 0.85, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 21.1299991607666}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K PFE 2025-02-27] pfe-20241231 0000078003 2024 FY false P4Y Consolidated Statements of Operations Consolidated Statements of Operations Consolidated Statements of Operations http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent 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ITEM 16. FORM 10-K SUMMARY None. SIGNATURES Under the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, this report was signed on behalf of the Registrant by the authorized person named below. Pfizer Inc. Dated: February 27, 2025 By: /S/    MARGARET M. MADDEN Margaret M. Madden Senior Vice President and Corporate Secretary Chief Governance Counsel We, the undersigned directors and officers of Pfizer Inc., hereby severally constitute Douglas M. Lankler and Margaret M. Madden, and each of them singly, our true and lawful attorneys with full power to them and each of them to sign for us, in our names in the capacities indicated below, any and all amendments to this Annual Report on Form 10-K filed with the Securities and Exchange Commission. Under the requirements of the Securities Exchange Act of 1934, this report was signed by the following persons on behalf of the Registrant and in the capacities and on the date indicated . Pfizer Inc. 2024 Form 10-K 113 Signature Title Date /S/    ALBERT BOURLA Albert Bourla Chairman, Chief Executive Officer and Director (Principal Executive Officer) February 27, 2025 /S/    DAVID M. DENTON David M. Denton Chief Financial Officer, Executive Vice President (Principal Financial Officer) February 27, 2025 /S/    JENNIFER B. DAMICO Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer) February 27, 2025 /S/    RONALD E. BLAYLOCK Ronald E. Blaylock Director February 27, 2025 /S/    MORTIMER J. BUCKLEY Mortimer J. Buckley Director February 27, 2025 /S/    SUSAN DESMOND-HELLMANN Susan Desmond-Hellmann Director February 27, 2025 /S/    JOSEPH J. ECHEVARRIA Joseph J. Echevarria Director February 27, 2025 /S/    SCOTT GOTTLIEB Scott Gottlieb Director February 27, 2025 /S/    HELEN H. HOBBS Helen H. Hobbs Director February 27, 2025 /S/    SUSAN HOCKFIELD Susan Hockfield Director February 27, 2025 /S/    DAN R. LITTMAN Dan R. Littman Director February 27, 2025 /S/    SHANTANU NARAYEN Shantanu Narayen Director February 27, 2025 /S/    SUZANNE NORA JOHNSON Suzanne Nora Johnson Director February 27, 2025 /S/    JAMES QUINCEY James Quincey Director February 27, 2025 /S/    JAMES C. SMITH James C. Smith Director February 27, 2025 /S/    CYRUS TARAPOREVALA Cyrus Taraporevala Director February 27, 2025 Pfizer Inc. 2024 Form 10-K 114\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": -0.036746, "explanation": "The actual 21-day forward return for ACWI starting 2025-02-28 was -3.67%, which classifies as 'negative'.", "metadata": {"future_return": -0.036746, "horizon_days": 21, "hist_return": -0.008605, "annualized_vol": 0.125831, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250327_0034", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-03-27", "context_summary": "XRP-USD over past 60 days: cumulative return -3.7%, annualized vol 103.7%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=2.44, end=2.35, cumulative_return=-3.7%, annualized_volatility=103.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.37, 't10y3m_spread': 0.02, 'breakeven_10y': 2.37, 'hy_oas': 3.19, 'ig_oas': 0.91, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 18.32999992370605}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.116265, "explanation": "The actual 21-day forward return for XRP-USD starting 2025-03-27 was -11.63%, which classifies as 'negative'.", "metadata": {"future_return": -0.116265, "horizon_days": 21, "hist_return": -0.037147, "annualized_vol": 1.037009, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250225_0036", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2025-02-25", "context_summary": "MATIC-USD over past 60 days: cumulative return -44.3%, annualized vol 67.3%. Market regime: sideways.", "question": "Asset: MATIC-USD\nHistorical prices (past 60 trading days): start=0.48, end=0.27, cumulative_return=-44.3%, annualized_volatility=67.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.27, 't10y3m_spread': 0.09, 'breakeven_10y': 2.42, 'hy_oas': 2.78, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.85, 'vix': 18.979999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of MATIC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.223131, "explanation": "The actual 21-day forward return for MATIC-USD starting 2025-02-25 was -22.31%, which classifies as 'negative'.", "metadata": {"future_return": -0.223131, "horizon_days": 21, "hist_return": -0.442713, "annualized_vol": 0.673398, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250520_0039", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-05-20", "context_summary": "AVAX-USD over past 60 days: cumulative return +16.3%, annualized vol 79.4%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=19.15, end=22.27, cumulative_return=+16.3%, annualized_volatility=79.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.49, 't10y3m_spread': 0.07, 'breakeven_10y': 2.36, 'hy_oas': 3.21, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 18.13999938964844}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.001767, "explanation": "The actual 21-day forward return for AVAX-USD starting 2025-05-20 was -0.18%, which classifies as 'flat'.", "metadata": {"future_return": -0.001767, "horizon_days": 21, "hist_return": 0.162807, "annualized_vol": 0.793824, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250725_0042", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-07-25", "context_summary": "EEM over past 60 days: cumulative return +14.9%, annualized vol 12.8%. 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Registrant’s 3.875% notes due 2045 Current Report on Form 8-K (File No. 001-37580) May 06, 2025 4.06 Form of Global Note representing the Registrant’s 4.000% notes due 2054 Current Report on Form 8-K (File No. 001-37580) May 06, 2025 4.07 Form of Global Note representing the Registrant’s 4.000% notes due 2030 Current Report on Form 8-K (File No. 001-37580) May 01, 2025 4.08 Form of Global Note representing the Registrant’s 4.500% notes due 2035 Current Report on Form 8-K (File No. 001-37580) May 01, 2025 4.09 Form of Global Note representing the Registrant’s 5.250% notes due 2055 Current Report on Form 8-K (File No. 001-37580) May 01, 2025 4.10 Form of Global Note representing the Registrant’s 5.300% notes due 2065 Current Report on Form 8-K (File No. 001-37580) May 01, 2025 31.01 * Certification of Chief Executive Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.02 * Certification of Chief Financial Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.01 ‡ Certifications of Chief Executive Officer and Chief Financial Officer pursuant to 18 U.S.C. Section 1350, as adopted pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS * Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH * Inline XBRL Taxonomy Extension Schema Document 101.CAL * Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF * Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB * Inline XBRL Taxonomy Extension Label Linkbase Document 54 101.PRE * Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 * Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) __________________________  * Filed herewith. ‡ Furnished herewith. 55 SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. ALPHABET INC. July 23, 2025 By: /s/ ANAT ASHKENAZI Anat Ashkenazi Senior Vice President, Chief Financial Officer ALPHABET INC. July 23, 2025 By: /s/    AMIE THUENER O'TOOLE         Amie Thuener O'Toole Vice President, Corporate Controller and Principal Accounting Officer 56\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": 0.016764, "explanation": "The actual 21-day forward return for EEM starting 2025-07-25 was +1.68%, which classifies as 'positive'.", "metadata": {"future_return": 0.016764, "horizon_days": 21, "hist_return": 0.148707, "annualized_vol": 0.128102, "has_text": true, "text_chars": 9047}} +{"id": "T1_all_20250917_0045", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BNDX"], "decision_date": "2025-09-17", "context_summary": "BNDX over past 60 days: cumulative return +0.6%, annualized vol 2.9%. Market regime: bull.", "question": "Asset: BNDX\nHistorical prices (past 60 trading days): start=47.57, end=47.87, cumulative_return=+0.6%, annualized_volatility=2.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.53, 't10y3m_spread': 0.0, 'breakeven_10y': 2.37, 'hy_oas': 2.79, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.35, 'vix': 16.360000610351562}\nMarket regime: bull\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": 0.010637, "explanation": "The actual 21-day forward return for BNDX starting 2025-09-17 was +1.06%, which classifies as 'positive'.", "metadata": {"future_return": 0.010637, "horizon_days": 21, "hist_return": 0.006304, "annualized_vol": 0.028613, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250221_0048", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-02-21", "context_summary": "USMV over past 60 days: cumulative return +0.8%, annualized vol 9.7%. Market regime: sideways.", "question": "Asset: USMV\nHistorical prices (past 60 trading days): start=91.27, end=91.96, cumulative_return=+0.8%, annualized_volatility=9.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.22, 't10y3m_spread': 0.17, 'breakeven_10y': 2.45, 'hy_oas': 2.66, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.85, 'vix': 15.65999984741211}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K KO 2025-02-20] ko-20241231 0000021344 2024 FY False http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#ProfitLoss 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2021-12-31 0000021344 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-01 2024-12-31 0000021344 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-01 2023-12-31 0000021344 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2022-01-01 2022-12-31 0000021344 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-12-31 0000021344 us-gaap:TreasuryStockCommonMember 2023-12-31 0000021344 us-gaap:TreasuryStockCommonMember 2022-12-31 0000021344 us-gaap:TreasuryStockCommonMember 2021-12-31 0000021344 us-gaap:TreasuryStockCommonMember 2024-01-01 20 [...TRUNCATED...] la Company, and by John Murphy, President and Chief Financial Officer of The Coca-Cola Company. 97 The Coca-Cola Company Incentive Based Compensation Recoupment Policy — incorporated herein by reference to Exhibit 97 to the Company’s Annual Report on Form 10-K for the year ended December 31, 2023. 134 101 The following financial information from The Coca-Cola Company’s Annual Report on Form 10-K for the year ended December 31, 2024, formatted in iXBRL (Inline Extensible Business Reporting Language): (i) Consolidated Statements of Income for the years ended December 31, 2024, 2023 and 2022; (ii) Consolidated Statements of Comprehensive Income for the years ended December 31, 2024, 2023 and 2022; (iii) Consolidated Balance Sheets as of December 31, 2024 and 2023; (iv) Consolidated Statements of Cash Flows for the years ended December 31, 2024, 2023 and 2022; (v) Consolidated Statements of Shareowners’ Equity for the years ended December 31, 2024, 2023 and 2022; and (vi) Notes to Consolidated Financial Statements. 104 Cover Page Interactive Data File (the cover page XBRL tags are embedded within the iXBRL document). *Management contracts and compensatory plans and arrangements required to be filed as exhibits pursuant to Item 15(b) of Form 10-K. ITEM 16.  FORM 10-K SUMMARY None. 135 Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   THE COCA-COLA COMPANY   (Registrant) By: /s/ JAMES QUINCEY   James Quincey Chairman of the Board of Directors and Chief Executive Officer     Date: February 20, 2025 Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities and on the dates indicated. /s/ JAMES QUINCEY   /s/ JOHN MURPHY James Quincey Chairman of the Board of Directors and Chief Executive Officer (Principal Executive Officer)   John Murphy President and Chief Financial Officer (Principal Financial Officer) February 20, 2025   February 20, 2025 /s/ ERIN L. MAY   Erin L. May Senior Vice President, Controller and Chief Accounting Officer (Principal Accounting Officer) February 20, 2025 * * Herb Allen Director   Christopher C. Davis Director February 20, 2025   February 20, 2025 *   * Bela Bajaria Director   Carolyn Everson Director February 20, 2025   February 20, 2025 *   * Ana Botín Director   Thomas S. Gayner Director February 20, 2025   February 20, 2025 136 * * Maria Elena Lagomasino Director Caroline J. Tsay Director February 20, 2025 February 20, 2025 * * Amity Millhiser Director David B. Weinberg Director February 20, 2025 February 20, 2025 *By: /s/ JENNIFER D. MANNING Jennifer D. Manning Attorney-in-fact   February 20, 2025 137\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": 0.003282, "explanation": "The actual 21-day forward return for USMV starting 2025-02-21 was +0.33%, which classifies as 'flat'.", "metadata": {"future_return": 0.003282, "horizon_days": 21, "hist_return": 0.007502, "annualized_vol": 0.097214, "has_text": true, "text_chars": 9044}} +{"id": "T1_all_20250317_0051", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["BIL"], "decision_date": "2025-03-17", "context_summary": "BIL over past 60 days: cumulative return +0.7%, annualized vol 0.2%. Market regime: bear.", "question": "Asset: BIL\nHistorical prices (past 60 trading days): start=87.14, end=87.73, cumulative_return=+0.7%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.29, 't10y3m_spread': -0.02, 'breakeven_10y': 2.3, 'hy_oas': 3.25, 'ig_oas': 0.94, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 21.770000457763672}\nMarket regime: bear\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": 0.002307, "explanation": "The actual 21-day forward return for BIL starting 2025-03-17 was +0.23%, which classifies as 'flat'.", "metadata": {"future_return": 0.002307, "horizon_days": 21, "hist_return": 0.006738, "annualized_vol": 0.002397, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250324_0054", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["INDS"], "decision_date": "2025-03-24", "context_summary": "INDS over past 60 days: cumulative return +2.7%, annualized vol 17.2%. Market regime: sideways.", "question": "Asset: INDS\nHistorical prices (past 60 trading days): start=33.81, end=34.72, cumulative_return=+2.7%, annualized_volatility=17.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.31, 't10y3m_spread': -0.08, 'breakeven_10y': 2.33, 'hy_oas': 3.21, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 19.280000686645508}\nMarket regime: sideways\n\nPredict whether the return of INDS over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.031753, "explanation": "The actual 21-day forward return for INDS starting 2025-03-24 was -3.18%, which classifies as 'negative'.", "metadata": {"future_return": -0.031753, "horizon_days": 21, "hist_return": 0.027085, "annualized_vol": 0.171757, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250206_0057", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-02-06", "context_summary": "DOT-USD over past 60 days: cumulative return -54.9%, annualized vol 85.0%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=10.41, end=4.69, cumulative_return=-54.9%, annualized_volatility=85.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.26, 't10y3m_spread': 0.1, 'breakeven_10y': 2.42, 'hy_oas': 2.69, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 15.770000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.096444, "explanation": "The actual 21-day forward return for DOT-USD starting 2025-02-06 was +9.64%, which classifies as 'positive'.", "metadata": {"future_return": 0.096444, "horizon_days": 21, "hist_return": -0.549344, "annualized_vol": 0.849711, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251111_0060", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2025-11-11", "context_summary": "XLRE over past 60 days: cumulative return +1.5%, annualized vol 13.5%. Market regime: bull.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=39.92, end=40.52, cumulative_return=+1.5%, annualized_volatility=13.5%\nMacro context: {'fed_funds_rate': 3.87, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.55, 't10y3m_spread': 0.18, 'breakeven_10y': 2.29, 'hy_oas': 3.02, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.22, 'vix': 17.600000381469727}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q CVX 2025-11-06] cvx-20250930 0000093410 12/31 2025 Q3 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cvx:segment cvx:lawsuit cvx:state cvx:tribe cvx:parish 0000093410 2025-01-01 2025-09-30 0000093410 2025-09-30 0000093410 2025-07-01 2025-09-30 0000093410 2024-07-01 2024-09-30 0000093410 2024-01-01 2024-09-30 0000093410 2024-12-31 0000093410 2023-12-31 0000093410 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-06-30 0000093410 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us-gaap:RetainedEarningsMember 2025-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-09-30 0000093410 us-gaap:ParentMember 2025-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2023-12-31 0000093410 us-gaap:RetainedEarningsMember 2023-12-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-12-31 0000093410 us-gaap:TreasuryStockCommonMember 2023-12-31 0000093410 us-gaap:ParentMember 2023-12-31 0000093410 us-gaap:NoncontrollingInterestMember 2023-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-01-01 2024-09-30 0000093410 us-gaap:ParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 2024-01-01 2024-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-01 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-01-01 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-12-31 0000093410 us-gaap:RetainedEarningsMember 2024-12-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-12-31 0000093410 us-gaap:TreasuryStockCommonMember 2024-12-31 0000093410 us-gaap:ParentMember 2024-12-31 0000093410 us-gaap:NoncontrollingInterestMember 2024-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-01-01 2025-09-30 0000093410 us-gaap:ParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-01-01 2025-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-01-01 2025-09-30 0000093410 us-gaap:RetainedEarningsMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-09-30 0000093410 [...TRUNCATED...] 160; $154.38 16,620,000   (1) Includes common shares repurchased from participants in the company’s executive compensation plans for personal income tax withholdings. (2) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections During the three months ended September 30, 2025, none of our directors or executive officers adopted, modified or terminated a Rule 10b5-1 trading arrangement or a non-Rule 10b5-1 trading arrangement, as such terms are defined in Item 408 of Regulation S-K. 47 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 4.1 Fourth Supplemental Indenture, dated as of August 13, 2025, among Chevron U.S.A. Inc., Chevron Corporation, as guarantor, and Deutsche Bank Trust Company Americas, as trustee, filed as Exhibit 4. 2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 4.2 Forms of 3.950% Notes Due 2027, 4.050% Notes Due 2028, Floating Rate Notes Due 2028-B, 4.300% Notes Due 2030, Floating Rate Notes due 2030, 4.500% Notes Due 2032 and 4.850% Notes Due 2035, contained in Exhibit 4.2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 10.1+* Aircraft Time-Sharing Agreement, dated as of February 24, 2015, between Hess Corporation and John B. Hess. 10.2* Transition Services Agreement, dated as of July 14, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.3* Amendment One to Transition Services Agreement, dated as of August 27, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.4* Membership Interest Purchase Agreement, dated as of September 10, 2025, between Hess Corporation and JBH Ventures, LLC . 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ + Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 48 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 6, 2025 49\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": -0.021583, "explanation": "The actual 21-day forward return for XLRE starting 2025-11-11 was -2.16%, which classifies as 'negative'.", "metadata": {"future_return": -0.021583, "horizon_days": 21, "hist_return": 0.015016, "annualized_vol": 0.135025, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250203_0062", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-02-03", "context_summary": "BNB-USD over past 60 days: cumulative return -13.5%, annualized vol 40.0%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=714.32, end=617.60, cumulative_return=-13.5%, annualized_volatility=40.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.36, 't10y3m_spread': 0.27, 'breakeven_10y': 2.42, 'hy_oas': 2.68, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 16.43000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.005117, "explanation": "The actual 21-day forward return for BNB-USD starting 2025-02-03 was -0.51%, which classifies as 'flat'.", "metadata": {"future_return": -0.005117, "horizon_days": 21, "hist_return": -0.135403, "annualized_vol": 0.399579, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251008_0064", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BIL"], "decision_date": "2025-10-08", "context_summary": "BIL over past 60 days: cumulative return +0.7%, annualized vol 0.2%. Market regime: bull.", "question": "Asset: BIL\nHistorical prices (past 60 trading days): start=89.21, end=89.80, cumulative_return=+0.7%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 4.09, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.57, 't10y3m_spread': 0.13, 'breakeven_10y': 2.35, 'hy_oas': 2.82, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.34, 'vix': 17.239999771118164}\nMarket regime: bull\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": 0.002294, "explanation": "The actual 21-day forward return for BIL starting 2025-10-08 was +0.23%, which classifies as 'flat'.", "metadata": {"future_return": 0.002294, "horizon_days": 21, "hist_return": 0.006604, "annualized_vol": 0.002231, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250108_0067", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["GLD"], "decision_date": "2025-01-08", "context_summary": "GLD over past 60 days: cumulative return -1.0%, annualized vol 15.8%. Market regime: sideways.", "question": "Asset: GLD\nHistorical prices (past 60 trading days): start=247.15, end=244.56, cumulative_return=-1.0%, annualized_volatility=15.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.37, 't10y3m_spread': 0.32, 'breakeven_10y': 2.38, 'hy_oas': 2.79, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.91, 'vix': 17.81999969482422}\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": "positive", "answer_numeric": 0.074311, "explanation": "The actual 21-day forward return for GLD starting 2025-01-08 was +7.43%, which classifies as 'positive'.", "metadata": {"future_return": 0.074311, "horizon_days": 21, "hist_return": -0.010479, "annualized_vol": 0.157634, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250212_0070", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["GLD"], "decision_date": "2025-02-12", "context_summary": "GLD over past 60 days: cumulative return +8.4%, annualized vol 13.5%. Market regime: sideways.", "question": "Asset: GLD\nHistorical prices (past 60 trading days): start=246.66, end=267.39, cumulative_return=+8.4%, annualized_volatility=13.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.25, 't10y3m_spread': 0.19, 'breakeven_10y': 2.46, 'hy_oas': 2.66, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.89, 'vix': 16.020000457763672}\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": 0.009938, "explanation": "The actual 21-day forward return for GLD starting 2025-02-12 was +0.99%, which classifies as 'flat'.", "metadata": {"future_return": 0.009938, "horizon_days": 21, "hist_return": 0.084043, "annualized_vol": 0.134814, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251105_0073", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-11-05", "context_summary": "BNB-USD over past 60 days: cumulative return +0.0%, annualized vol 67.4%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=714.32, end=714.32, cumulative_return=+0.0%, annualized_volatility=67.4%\nMacro context: {'fed_funds_rate': 3.87, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.52, 't10y3m_spread': 0.14, 'breakeven_10y': 2.29, 'hy_oas': 3.13, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.17, 'vix': 19.0}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for BNB-USD starting 2025-11-05 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.673598, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251106_0075", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-11-06", "context_summary": "ADA-USD over past 60 days: cumulative return -34.6%, annualized vol 67.5%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.84, end=0.55, cumulative_return=-34.6%, annualized_volatility=67.5%\nMacro context: {'fed_funds_rate': 3.87, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.54, 't10y3m_spread': 0.21, 'breakeven_10y': 2.3, 'hy_oas': 3.05, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.17, 'vix': 18.010000228881836}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.18324, "explanation": "The actual 21-day forward return for ADA-USD starting 2025-11-06 was -18.32%, which classifies as 'negative'.", "metadata": {"future_return": -0.18324, "horizon_days": 21, "hist_return": -0.34598, "annualized_vol": 0.675481, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250318_0078", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2025-03-18", "context_summary": "XLRE over past 60 days: cumulative return +0.5%, annualized vol 19.2%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=40.30, end=40.50, cumulative_return=+0.5%, annualized_volatility=19.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.25, 't10y3m_spread': -0.03, 'breakeven_10y': 2.29, 'hy_oas': 3.18, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 20.51000022888184}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-03-17] 3 Growth Companies With High Insider Ownership Achieving 17% Revenue Growth In a volatile market where major indexes have experienced declines for several consecutive weeks, investors are keenly observing growth companies that demonstrate resilience and potential. High insider ownership often signals confidence from those closest to the company, making it an appealing factor for investors seeking stability and growth in uncertain times. Click here to see the full list of 206 stocks from our Fast Growing US Companies With High Insider Ownership screener. Let's dive into some prime choices out of the screener. Simply Wall St Growth Rating: \u2605\u2605\u2605\u2605\u2606\u2606 Overview: Futu Holdings Limited operates as a digitalized securities brokerage and wealth management product distributor in Hong Kong and internationally, with a market cap of approximately $16.34 billion. Operations: The company's revenue is primarily generated from its online brokerage and margin financing services, totaling HK$11.97 billion. Insider Ownership: 36.6% Revenue Growth Forecast: 17.5% p.a. Futu Holdings demonstrates potential as a growth company with high insider ownership. The company's revenue is forecast to grow at 17.5% annually, outpacing the US market's 8.5%. Recent earnings results show substantial growth, with fourth-quarter revenue reaching HK$4.43 billion and net income at HK$1.87 billion, both significantly higher than the previous year. While not expected to achieve significant annual earnings growth, Futu's return on equity is projected to be strong in three years at 21.2%. Navigate through the intricacies of Futu Holdings with our comprehensive analyst estimates report here. Our valuation report unveils the possibility Futu Holdings' shares may be trading at a premium. Simply Wall St Growth Rating: \u2605\u2605\u2605\u2605\u2605\u2606 Overview: Atlassian Corporation, with a market cap of $57.23 billion, designs, develops, licenses, and maintains various software products worldwide through its subsidiaries. Operations: The company's revenue primarily comes from its Software & Programming segment, which generated $4.79 billion. Insider Ownership: 37.8% Revenue Growth Forecast: 15.6% p.a. Atlassian's insider ownership is complemented by recent substantial insider selling, yet the company remains a strong growth contender. Its revenue is forecast to grow at 15.6% annually, surpassing the US market average. The company reported a significant reduction in net loss for the latest quarter with revenue reaching US$1.29 billion. Analysts project Atlassian will achieve profitability within three years, and its return on equity is expected to be very high at 43.4%. Delve into the full analysis future growth report here for a deeper understanding of Atlassian. In light of our recent valuation report, it seems possible that Atlassian is trading behind its estimated value. Simply Wall St Growth Rating: \u2605\u2605\u2605\u2605\u2606\u2606 Overview: Tesla, Inc. is involved in the design, development, manufacturing, leasing, and sale of electric vehicle\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": -0.044015, "explanation": "The actual 21-day forward return for XLRE starting 2025-03-18 was -4.40%, which classifies as 'negative'.", "metadata": {"future_return": -0.044015, "horizon_days": 21, "hist_return": 0.005036, "annualized_vol": 0.191645, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251121_0081", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2025-11-21", "context_summary": "CSHI over past 60 days: cumulative return +0.7%, annualized vol 1.1%. Market regime: sideways.", "question": "Asset: CSHI\nHistorical prices (past 60 trading days): start=48.28, end=48.62, cumulative_return=+0.7%, annualized_volatility=1.1%\nMacro context: {'fed_funds_rate': 3.88, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.55, 't10y3m_spread': 0.16, 'breakeven_10y': 2.24, 'hy_oas': 3.17, 'ig_oas': 0.85, 'ted_spread': 0.09, 'mortgage_30y': 6.26, 'vix': 26.420000076293945}\nMarket regime: sideways\n\nPredict whether the return of CSHI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.003521, "explanation": "The actual 21-day forward return for CSHI starting 2025-11-21 was +0.35%, which classifies as 'flat'.", "metadata": {"future_return": 0.003521, "horizon_days": 21, "hist_return": 0.00698, "annualized_vol": 0.01074, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250326_0084", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2025-03-26", "context_summary": "VNQ over past 60 days: cumulative return +1.1%, annualized vol 17.4%. Market regime: sideways.", "question": "Asset: VNQ\nHistorical prices (past 60 trading days): start=85.34, end=86.28, cumulative_return=+1.1%, annualized_volatility=17.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.35, 't10y3m_spread': -0.02, 'breakeven_10y': 2.35, 'hy_oas': 3.09, 'ig_oas': 0.9, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 17.149999618530273}\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": -0.033866, "explanation": "The actual 21-day forward return for VNQ starting 2025-03-26 was -3.39%, which classifies as 'negative'.", "metadata": {"future_return": -0.033866, "horizon_days": 21, "hist_return": 0.010949, "annualized_vol": 0.17366, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250529_0087", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-05-29", "context_summary": "XLU over past 60 days: cumulative return +3.9%, annualized vol 19.2%. Market regime: sideways.", "question": "Asset: XLU\nHistorical prices (past 60 trading days): start=37.67, end=39.15, cumulative_return=+3.9%, annualized_volatility=19.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.51, 't10y3m_spread': 0.12, 'breakeven_10y': 2.32, 'hy_oas': 3.23, 'ig_oas': 0.9, 'ted_spread': 0.09, 'mortgage_30y': 6.86, 'vix': 19.309999465942383}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2025-05-28] nvda-20250427 0001045810 1/25 2026 Q1 FALSE http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 385 134 286 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:segment 0001045810 2025-01-27 2025-04-27 0001045810 2025-05-23 0001045810 2024-01-29 2024-04-28 0001045810 2025-04-27 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 2025-01-26 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-01-26 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-26 0001045810 us-gaap:RetainedEarningsMember 2025-01-26 0001045810 us-gaap:RetainedEarningsMember 2025-01-27 2025-04-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-27 2025-04-27 0001045810 us-gaap:CommonStockMember 2025-01-27 2025-04-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-01-27 2025-04-27 0001045810 us-gaap:CommonStockMember 2025-04-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-04-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-27 0001045810 us-gaap:RetainedEarningsMember 2025-04-27 0001045810 us-gaap:CommonStockMember 2024-01-28 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-01-28 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-28 0001045810 us-gaap:RetainedEarningsMember 2024-01-28 0001045810 2024-01-28 0001045810 us-gaap:RetainedEarningsMember 2024-01-29 2024-04-28 0001045810 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0001045810 nvda:RSUsPSUsandMarketbasedPSUsMember 2025-01-27 2025-04-27 0001045810 nvda:RSUsPSUsandMarketbasedPSUsMember 2025-04-27 0001045810 us-gaap:EmployeeStockMember 2025-01-27 2025-04-27 0001045810 us-gaap:USTreasurySecuritiesMember 2025-04-27 0001045810 us-gaap:CorporateDebtSecuritiesMember 2025-04-27 0001045810 us-gaap:MoneyMarketFundsMember 2025-04-27 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-04-27 0001045810 us-gaap:CertificatesOfDepositMember 2025-04-27 0001045810 us-gaap:ForeignGovernmentDebtMember 2025-04-27 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:ForeignGovernmentDebtMember 2025-04-27 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2025-04-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2025-04-27 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2025-04-27 0001045810 nvda:CoreWeaveInc.Member nvda:PubliclyHeldEquitySecuritiesMember 2025-04-27 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2025-01-27 2025-04-27 0001045810 us-gaap:CorporateDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:USTreasurySecuritiesMember 2025-01-26 0001045810 us-gaap:MoneyMarketFundsMember 2025-01-26 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:ForeignGovernmentDebtMember 2025-01-26 0001045810 us-gaap:CertificatesOfDepositMember 2025-01-26 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2025-01-26 0001045810 us-gaap:FairValueInputsLevel1Member nvda:PubliclyHeldEquitySecuritiesMember 2025-01-26 0001045810 us-gaap:FairValueInputsLevel1Member 2025-01-26 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2025-01-26 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2025-04-27 0001045810 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2025-01-26 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasurySecuritiesMember 2025-04-27 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasurySecuritiesMember 2025-01-26 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:CorporateDebtSecuritiesMember 2025-04-27 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:CorporateDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-04-27 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:CertificatesOfDepositMember 2025-04-27 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:CertificatesOfDepositMember 2025-01-26 0001045810 us-gaap:FairValueInputsLevel2Member us-gaap:ForeignGovernmentDebtMember 2025-01-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-04-27 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-01-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-04-27 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:CustomerOneMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-04-27 0001045810 nvda:CustomerTwoMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-04-27 0001045810 nvda:CustomerThreeMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-04-27 0001045810 nvda:CustomerOneMember us [...TRUNCATED...] 6,000,000 December 31, 2025 *    Estimated assuming our closing stock price as of April 25, 2025. The number of shares is based on an estimate because the plan specifies a formulaic dollar amount of shares to be sold. 37 Item 6. Exhibits Incorporated by Reference Exhibit No.  Exhibit Description Schedule/Form Exhibit Filing Date 10.1+ Variable Compensation Plan - Fiscal Year 2026 8-K 10.1 3/7/2025 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 38 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: May 28, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 39\n\nPredict whether the return of XLU over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.009923, "explanation": "The actual 21-day forward return for XLU starting 2025-05-29 was +0.99%, which classifies as 'flat'.", "metadata": {"future_return": 0.009923, "horizon_days": 21, "hist_return": 0.039231, "annualized_vol": 0.192045, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20251205_0089", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-12-05", "context_summary": "XLY over past 60 days: cumulative return +0.5%, annualized vol 19.3%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=118.02, end=118.60, cumulative_return=+0.5%, annualized_volatility=19.3%\nMacro context: {'fed_funds_rate': 3.89, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.59, 't10y3m_spread': 0.4, 'breakeven_10y': 2.26, 'hy_oas': 2.88, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.19, 'vix': 15.779999732971191}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-10-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-10-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-10-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-10-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-10-31 0000104169 2025-12-02 0000104169 2025-08-01 2025-10-31 0000104169 2024-08-01 2024-10-31 0000104169 2024-02-01 2024-10-31 0000104169 2025-10-31 0000104169 2025-01-31 0000104169 2024-10-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-30 0000104169 us-gaap:ParentMember 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-04-30 0000104169 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-05-01 2025-07-31 0000104169 us-gaap:ParentMember 2025-05-01 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-05-01 2025-07-31 0000104169 2025-05-01 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-05-01 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-31 0000104169 us-gaap:ParentMember 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-08-01 2025-10-31 0000104169 us-gaap:ParentMember 2025-08-01 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-08-01 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-08-01 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of XLY over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.000696, "explanation": "The actual 21-day forward return for XLY starting 2025-12-05 was -0.07%, which classifies as 'flat'.", "metadata": {"future_return": -0.000696, "horizon_days": 21, "hist_return": 0.004886, "annualized_vol": 0.193229, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20251031_0093", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-10-31", "context_summary": "ADA-USD over past 60 days: cumulative return -24.9%, annualized vol 64.3%. Market regime: bull.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.80, end=0.60, cumulative_return=-24.9%, annualized_volatility=64.3%\nMacro context: {'fed_funds_rate': 3.87, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.5, 't10y3m_spread': 0.19, 'breakeven_10y': 2.29, 'hy_oas': 2.85, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.17, 'vix': 16.90999984741211}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.328348, "explanation": "The actual 21-day forward return for ADA-USD starting 2025-10-31 was -32.83%, which classifies as 'negative'.", "metadata": {"future_return": -0.328348, "horizon_days": 21, "hist_return": -0.248771, "annualized_vol": 0.643228, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250603_0098", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2025-06-03", "context_summary": "EWJ over past 60 days: cumulative return +6.9%, annualized vol 21.0%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=67.10, end=71.75, cumulative_return=+6.9%, annualized_volatility=21.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.52, 't10y3m_spread': 0.02, 'breakeven_10y': 2.33, 'hy_oas': 3.27, 'ig_oas': 0.91, 'ted_spread': 0.09, 'mortgage_30y': 6.89, 'vix': 18.36000061035156}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-02] [\"2 Profitable Stocks to Target This Week and 1 to Ignore A company with profits isn\\u2019t always a great investment. Some struggle to maintain growth, face looming threats, or fail to reinvest wisely, limiting their future potential. Not all profitable companies are created equal, and that\\u2019s why we built StockStory - to help you find the ones that truly shine bright. That said, here are two profitable companies that balance growth and profitability and one best left off your watchlist. Trailing 12-Month GAAP Operating Margin: 5.2% Founded in 1983 in California, Mission Produce (NASDAQ:AVO) grows, packages, and distributes avocados. Why Is AVO Risky? At $11.19 per share, Mission Produce trades at 9.9x forward EV-to-EBITDA. Check out our free in-depth research report to learn more about why AVO doesn\\u2019t pass our bar. Trailing 12-Month GAAP Operating Margin: 9.6% Founded in 1969 by a group of former Fairchild semiconductor executives led by Jerry Sanders, Advanced Micro Devices (NASDAQ:AMD) is one of the leading designers of computer processors and graphics chips used in PCs and data centers. Why Are We Positive On AMD? AMD\\u2019s stock price of $110.51 implies a valuation ratio of 24.1x forward P/E. Is now the time to initiate a position? Find out in our full research report, it\\u2019s free. Trailing 12-Month GAAP Operating Margin: 25.2% Sporting a global footprint of facilities, Photronics (NASDAQ:PLAB) is a manufacturer of photomasks, templates used to transfer patterns onto semiconductor wafers. Why Do We Like PLAB? Photronics is trading at $16.75 per share, or 8.1x forward P/E. Is now the right time to buy? See for yourself in our in-depth research report, it\\u2019s free. Donald Trump\\u2019s victory in the 2024 U.S. Presidential Election sent major indices to all-time highs, but stocks have retraced as investors debate the health of the economy and the potential impact of tariffs. While this leaves much uncertainty around 2025, a few companies are poised for long-term gains regardless of the political or macroeconomic climate, like our Top 5 Strong Momentum Stocks for this week. This is a curated list of our High Quality stocks that have generated a market-beating return of 183% over the last five years (as of March 31st 2025). Stocks that made our list in 2020 include now familiar names such as Nvidia (+1,545% between March 2020 and March 2025) as well as under-the-radar businesses like the once-small-cap company Exlservice (+354% five-year return). Find your next big winner with StockStory today for free.\", \"Nvidia rival Groq makes a bold prediction on what's next for AI Listen and subscribe to Opening Bid on Apple Podcasts, Spotify, Amazon Music, YouTube or wherever you find your favorite podcasts. The next big breakthrough in AI could be one that channels the spirit of famed scientist Albert Einstein. \\\"The problem is that large language models [LLMs] make mistakes. And they're always going to make mistakes, but they're going to \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": 0.014486, "explanation": "The actual 21-day forward return for EWJ starting 2025-06-03 was +1.45%, which classifies as 'positive'.", "metadata": {"future_return": 0.014486, "horizon_days": 21, "hist_return": 0.069403, "annualized_vol": 0.209928, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250430_0101", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2025-04-30", "context_summary": "CSHI over past 60 days: cumulative return +0.5%, annualized vol 5.1%. Market regime: bear.", "question": "Asset: CSHI\nHistorical prices (past 60 trading days): start=46.94, end=47.19, cumulative_return=+0.5%, annualized_volatility=5.1%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.54, 't10y3m_spread': -0.12, 'breakeven_10y': 2.23, 'hy_oas': 3.74, 'ig_oas': 1.06, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 24.170000076293945}\nMarket regime: bear\n\nPredict whether the return of CSHI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.005118, "explanation": "The actual 21-day forward return for CSHI starting 2025-04-30 was +0.51%, which classifies as 'flat'.", "metadata": {"future_return": 0.005118, "horizon_days": 21, "hist_return": 0.005472, "annualized_vol": 0.051327, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251218_0104", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-12-18", "context_summary": "DOT-USD over past 60 days: cumulative return +0.0%, annualized vol 78.6%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=3.54, end=3.54, cumulative_return=+0.0%, annualized_volatility=78.6%\nMacro context: {'fed_funds_rate': 3.64, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.67, 't10y3m_spread': 0.52, 'breakeven_10y': 2.24, 'hy_oas': 2.99, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.22, 'vix': 17.6200008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for DOT-USD starting 2025-12-18 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.786358, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250303_0106", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2025-03-03", "context_summary": "IYR over past 60 days: cumulative return -1.7%, annualized vol 16.7%. Market regime: sideways.", "question": "Asset: IYR\nHistorical prices (past 60 trading days): start=97.43, end=95.77, cumulative_return=-1.7%, annualized_volatility=16.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.25, 't10y3m_spread': -0.08, 'breakeven_10y': 2.38, 'hy_oas': 2.87, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 19.6299991607666}\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": -0.027612, "explanation": "The actual 21-day forward return for IYR starting 2025-03-03 was -2.76%, which classifies as 'negative'.", "metadata": {"future_return": -0.027612, "horizon_days": 21, "hist_return": -0.017005, "annualized_vol": 0.166875, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251017_0109", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-10-17", "context_summary": "EEM over past 60 days: cumulative return +9.1%, annualized vol 14.5%. Market regime: bull.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=48.96, end=53.43, cumulative_return=+9.1%, annualized_volatility=14.5%\nMacro context: {'fed_funds_rate': 4.11, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.58, 't10y3m_spread': -0.03, 'breakeven_10y': 2.28, 'hy_oas': 3.04, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.27, 'vix': 25.309999465942383}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": 0.002399, "explanation": "The actual 21-day forward return for EEM starting 2025-10-17 was +0.24%, which classifies as 'flat'.", "metadata": {"future_return": 0.002399, "horizon_days": 21, "hist_return": 0.09122, "annualized_vol": 0.14516, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251009_0112", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["TLH"], "decision_date": "2025-10-09", "context_summary": "TLH over past 60 days: cumulative return +5.1%, annualized vol 8.0%. Market regime: bull.", "question": "Asset: TLH\nHistorical prices (past 60 trading days): start=95.78, end=100.70, cumulative_return=+5.1%, annualized_volatility=8.0%\nMacro context: {'fed_funds_rate': 4.1, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.55, 't10y3m_spread': 0.12, 'breakeven_10y': 2.35, 'hy_oas': 2.84, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.34, 'vix': 16.299999237060547}\nMarket regime: bull\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": 0.007373, "explanation": "The actual 21-day forward return for TLH starting 2025-10-09 was +0.74%, which classifies as 'flat'.", "metadata": {"future_return": 0.007373, "horizon_days": 21, "hist_return": 0.051346, "annualized_vol": 0.08008, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250602_0115", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-06-02", "context_summary": "SOL-USD over past 60 days: cumulative return +34.8%, annualized vol 66.0%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=117.06, end=157.78, cumulative_return=+34.8%, annualized_volatility=66.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.52, 't10y3m_spread': 0.05, 'breakeven_10y': 2.34, 'hy_oas': 3.32, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.89, 'vix': 18.56999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.077398, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-06-02 was -7.74%, which classifies as 'negative'.", "metadata": {"future_return": -0.077398, "horizon_days": 21, "hist_return": 0.347878, "annualized_vol": 0.660117, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250523_0118", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["PALL"], "decision_date": "2025-05-23", "context_summary": "PALL over past 60 days: cumulative return +9.0%, annualized vol 23.8%. Market regime: sideways.", "question": "Asset: PALL\nHistorical prices (past 60 trading days): start=84.50, end=92.08, cumulative_return=+9.0%, annualized_volatility=23.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.54, 't10y3m_spread': 0.17, 'breakeven_10y': 2.34, 'hy_oas': 3.32, 'ig_oas': 0.92, 'ted_spread': 0.09, 'mortgage_30y': 6.86, 'vix': 20.280000686645508}\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": 0.051535, "explanation": "The actual 21-day forward return for PALL starting 2025-05-23 was +5.15%, which classifies as 'positive'.", "metadata": {"future_return": 0.051535, "horizon_days": 21, "hist_return": 0.089704, "annualized_vol": 0.237578, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251216_0120", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2025-12-16", "context_summary": "QQQ over past 60 days: cumulative return +1.4%, annualized vol 17.7%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=600.67, end=608.99, cumulative_return=+1.4%, annualized_volatility=17.7%\nMacro context: {'fed_funds_rate': 3.64, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.67, 't10y3m_spread': 0.53, 'breakeven_10y': 2.25, 'hy_oas': 2.91, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.22, 'vix': 16.5}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-10-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-10-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-10-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-10-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-10-31 0000104169 2025-12-02 0000104169 2025-08-01 2025-10-31 0000104169 2024-08-01 2024-10-31 0000104169 2024-02-01 2024-10-31 0000104169 2025-10-31 0000104169 2025-01-31 0000104169 2024-10-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 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0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-05-01 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-31 0000104169 us-gaap:ParentMember 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-08-01 2025-10-31 0000104169 us-gaap:ParentMember 2025-08-01 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-08-01 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-08-01 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 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us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\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": 0.005479, "explanation": "The actual 21-day forward return for QQQ starting 2025-12-16 was +0.55%, which classifies as 'flat'.", "metadata": {"future_return": 0.005479, "horizon_days": 21, "hist_return": 0.013849, "annualized_vol": 0.177075, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250109_0123", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2025-01-09", "context_summary": "XLK over past 60 days: cumulative return +0.2%, annualized vol 19.4%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=115.85, end=116.07, cumulative_return=+0.2%, annualized_volatility=19.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.39, 't10y3m_spread': 0.32, 'breakeven_10y': 2.4, 'hy_oas': 2.84, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.91, 'vix': 17.700000762939453}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 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us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of XLK over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.017659, "explanation": "The actual 21-day forward return for XLK starting 2025-01-09 was +1.77%, which classifies as 'positive'.", "metadata": {"future_return": 0.017659, "horizon_days": 21, "hist_return": 0.001896, "annualized_vol": 0.19416, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20251223_0126", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2025-12-23", "context_summary": "XLP over past 60 days: cumulative return +0.5%, annualized vol 11.5%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=77.05, end=77.44, cumulative_return=+0.5%, annualized_volatility=11.5%\nMacro context: {'fed_funds_rate': 3.64, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.73, 't10y3m_spread': 0.53, 'breakeven_10y': 2.23, 'hy_oas': 2.88, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.21, 'vix': 14.079999923706056}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 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us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\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": 0.002193, "explanation": "The actual 21-day forward return for XLP starting 2025-12-23 was +0.22%, which classifies as 'flat'.", "metadata": {"future_return": 0.002193, "horizon_days": 21, "hist_return": 0.005055, "annualized_vol": 0.115429, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250924_0128", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-09-24", "context_summary": "ETH-USD over past 60 days: cumulative return +9.0%, annualized vol 60.3%. Market regime: bull.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=3741.40, end=4079.06, cumulative_return=+9.0%, annualized_volatility=60.3%\nMacro context: {'fed_funds_rate': 4.09, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.59, 't10y3m_spread': 0.12, 'breakeven_10y': 2.37, 'hy_oas': 2.71, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.26, 'vix': 16.639999389648438}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.022456, "explanation": "The actual 21-day forward return for ETH-USD starting 2025-09-24 was -2.25%, which classifies as 'negative'.", "metadata": {"future_return": -0.022456, "horizon_days": 21, "hist_return": 0.09025, "annualized_vol": 0.60284, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250721_0131", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-07-21", "context_summary": "XLY over past 60 days: cumulative return +17.0%, annualized vol 18.3%. Market regime: bull.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=94.41, end=110.45, cumulative_return=+17.0%, annualized_volatility=18.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.56, 't10y3m_spread': 0.04, 'breakeven_10y': 2.41, 'hy_oas': 2.93, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.75, 'vix': 16.40999984741211}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-18] [\"MP Materials (MP) Completes US$650 Million Equity Offering MP Materials has made significant announcements recently, including the completion of a follow-on equity offering of nearly $650 million and new high-profile partnerships with Apple and the Department of Defense. These developments coincide with a remarkable share price increase of 122% over the last quarter. The equity offering indicates strong market confidence, while the strategic partnerships bolster MP's long-term prospects in the rare earth sector. The broader market, with major indexes reaching record highs, provides a favorable backdrop, further enhancing MP's upward momentum. Such positive corporate maneuvers align well with the ongoing bullish trends in stock markets. Every company has risks, and we've spotted 1 warning sign for MP Materials you should know about. AI is about to change healthcare. These 27 stocks are working on everything from early diagnostics to drug discovery. The best part - they are all under $10b in market cap - there's still time to get in early. The recent announcements of MP Materials' successful equity offering and strategic partnerships with Apple and the Department of Defense could significantly impact its long-term narrative as it positions itself strongly within the rare earths sector. These developments are expected to enhance production capabilities and revenue opportunities, aligning with the company's strategy to expand into ex-China markets. Potential advancements in efficiency and sales volumes could positively influence future earnings and revenue forecasts, which analysts anticipate to grow robustly over the next three years. Over a five-year period, MP Materials has achieved a total return of 293.48%, which underscores its substantial growth trajectory. Notably, over the past year, its performance surpassed the US Metals and Mining industry, which returned 6.1%. However, despite recent impressive share price gains, the current price of US$58.55 contrasts with the consensus price target of US$38. This discrepancy highlights a potential overvaluation according to analysts, suggesting investors might benefit from tempering expectations in light of market factors and the company's execution of future growth plans. The strategic moves could help mitigate risks associated with heavy reliance on NdPr pricing and variable Chinese policies. However, executing its growth strategy without significant revenue or margin interruptions remains crucial. Although the company's long-term viability appears promising, as evidenced by planned expansions in the Upstream and Midstream segments, immediate financial forecasts also depend on external factors and successful integration of new processes. Thus, MP Materials' future prospects will largely depend on its ability to navigate these challenges effectively while aligning with analyst earnings forecasts and market expectations. Explore historical data to track MP Materials' performance over time in our past\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": 0.029702, "explanation": "The actual 21-day forward return for XLY starting 2025-07-21 was +2.97%, which classifies as 'positive'.", "metadata": {"future_return": 0.029702, "horizon_days": 21, "hist_return": 0.169832, "annualized_vol": 0.183129, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250319_0134", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-03-19", "context_summary": "BNB-USD over past 60 days: cumulative return -11.5%, annualized vol 51.1%. Market regime: bear.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=709.42, end=628.13, cumulative_return=-11.5%, annualized_volatility=51.1%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.25, 't10y3m_spread': -0.05, 'breakeven_10y': 2.3, 'hy_oas': 3.23, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 21.700000762939453}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.059568, "explanation": "The actual 21-day forward return for BNB-USD starting 2025-03-19 was -5.96%, which classifies as 'negative'.", "metadata": {"future_return": -0.059568, "horizon_days": 21, "hist_return": -0.114587, "annualized_vol": 0.511148, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250804_0136", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["PDBC"], "decision_date": "2025-08-04", "context_summary": "PDBC over past 60 days: cumulative return +1.2%, annualized vol 15.9%. Market regime: bull.", "question": "Asset: PDBC\nHistorical prices (past 60 trading days): start=12.52, end=12.67, cumulative_return=+1.2%, annualized_volatility=15.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.54, 't10y3m_spread': -0.12, 'breakeven_10y': 2.33, 'hy_oas': 3.13, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 20.3799991607666}\nMarket regime: bull\n\nPredict whether the return of PDBC over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.025915, "explanation": "The actual 21-day forward return for PDBC starting 2025-08-04 was +2.59%, which classifies as 'positive'.", "metadata": {"future_return": 0.025915, "horizon_days": 21, "hist_return": 0.01153, "annualized_vol": 0.159278, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250826_0139", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-08-26", "context_summary": "XLB over past 60 days: cumulative return +6.7%, annualized vol 15.6%. Market regime: bull.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=42.34, end=45.18, cumulative_return=+6.7%, annualized_volatility=15.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.55, 't10y3m_spread': -0.01, 'breakeven_10y': 2.41, 'hy_oas': 2.8, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.58, 'vix': 14.789999961853027}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-08-25] Who\u2019s the Next Apple? 3 Breakout Stocks That Point the Way Editor\u2019s Note: Every investing era has its defining moment. In the 1980s, Apple squared off against IBM. In the 1990s, Amazon reshaped retail. And now, it\u2019s AI transforming industries at a breakneck pace. It\u2019s a force that\u2019s fundamentally changing how fast companies can grow, scale, and generate profits. It is therefore producing an unusual class of stock breakouts. InvestorPlace Senior Analyst Luke Lango calls these \u201cAI Income Events\u201d \u2013 moments when hype flips into adoption-driven growth. InvestorPlace - Stock Market News, Stock Advice & Trading Tips A few recent AI Income Events include\u2026 Super Micro Computer (SMCI) \u2013 233% in just 2 months SoundHound AI Inc. (SOUN) \u2013 300% in a few months BigBear.ai Holdings, Inc. (BBAI) \u2013 100% in weeks Palantir Technologies Inc. (PLTR) \u2013 290% in 5 months AppLovin Corporation (APP) \u2013 500% in 5 months But what history shows us is clear\u2026 The biggest breakthroughs \u2013 and the biggest stock market winners \u2013 almost never come from the incumbents. They come from the upstarts. So, Luke is joining us today to share how three little-known companies triggered \u201cAI Income Events\u201d\u2026 and how you can turn a $5,000 stake into $30,000 within six months by capturing a series of these events. Take it away, Luke\u2026 One August morning in 1981, Steve Jobs sat at Apple Inc.\u2019s (AAPL) headquarters with a Wall Street Journal folded under his arm. The headline: IBM Corp. (IBM) was entering the personal computer market. Apple, barely 5 years old, suddenly found itself up against Big Blue. With trademark audacity, Jobs turned the moment into theater. Apple ran a cheeky full-page WSJ ad: \u201cWelcome, IBM. Seriously.\u201d Later, in a 1983 speech, Jobs cast Apple as the rebel, warning \u201cIBM wants it all.\u201d That spirit paid off. The Macintosh, launched in 1984 with its iconic Super Bowl ad, made Apple the symbol of insurgent tech. Since then, Apple stock has soared nearly 175,000%, while IBM is up just about 2,500%. Apple isn\u2019t alone in this story. History shows transformational breakthroughs usually come from upstarts, not incumbents. Each innovation cycle produces Davids that topple Goliaths. Now that we\u2019re in the AI innovation cycle, let\u2019s look at three Davids whose \u201cAI Income Events\u201d rewarded investors with huge gains. Their biggest moves are likely largely past \u2014 so I\u2019ll also show you how my team is spotting the next round\u2026 AI has become the great equalizer. Any small firm can now harness it to leap ahead of giants. The challenge is spotting when hype (Phase 1) flips to adoption-driven growth (Phase 2). That\u2019s where my Nexus system comes in. I\u2019ll tell you more about Nexus in a minute, but first let\u2019s take a look at three AI Income Events it uncovered\u2026 Case Study #1: Back in October 2023, most investors had never heard of our first case study. It was a Microsoft partner in cloud software \u2014 a solid business, sure, but hardly front-page material. Then on October 10, this company unveiled an AI-power\n\nPredict whether the return of XLB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.04007, "explanation": "The actual 21-day forward return for XLB starting 2025-08-26 was -4.01%, which classifies as 'negative'.", "metadata": {"future_return": -0.04007, "horizon_days": 21, "hist_return": 0.067141, "annualized_vol": 0.156011, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251030_0142", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-10-30", "context_summary": "AVAX-USD over past 60 days: cumulative return -16.0%, annualized vol 75.7%. Market regime: bull.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=23.41, end=19.66, cumulative_return=-16.0%, annualized_volatility=75.7%\nMacro context: {'fed_funds_rate': 4.12, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.49, 't10y3m_spread': 0.15, 'breakeven_10y': 2.3, 'hy_oas': 2.76, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.19, 'vix': 16.920000076293945}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.238464, "explanation": "The actual 21-day forward return for AVAX-USD starting 2025-10-30 was -23.85%, which classifies as 'negative'.", "metadata": {"future_return": -0.238464, "horizon_days": 21, "hist_return": -0.16023, "annualized_vol": 0.756598, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250709_0145", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-07-09", "context_summary": "USMV over past 60 days: cumulative return +5.9%, annualized vol 12.6%. Market regime: sideways.", "question": "Asset: USMV\nHistorical prices (past 60 trading days): start=87.25, end=92.42, cumulative_return=+5.9%, annualized_volatility=12.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.52, 't10y3m_spread': 0.0, 'breakeven_10y': 2.35, 'hy_oas': 2.92, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 16.809999465942383}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-07-08] [\"Analysis: 'Trump Effect' website takes credit for US investment made under Biden By Jarrett Renshaw (Reuters) -Within hours of taking office in January, President Donald Trump boasted about attracting $3 trillion in new corporate investments to the United States. Since then, Trump has said the investments have swelled to $14 trillion, or roughly half of the nation's annual gross domestic product. The White House calls it \\\"The Trump Effect\\\" and features a rolling list on its website of more than 70 projects it says Trump's economic policies spurred, from a new bakery plant in Texas to a LEGO facility in Virginia and a microchip plant in Arizona. As of July 2, the website listed more than $2.6 trillion in U.S. investments, well short of the $14 trillion Trump boasts about. But a Reuters review found that just under half of the claimed spending on the website - totaling more than $1.3 trillion - originated under former President Joe Biden or represented routine spending repackaged to promote domestic investments. At least eight of the projects touted by the White House had sought or secured critical local incentive packages before Trump took office while at least a half dozen other projects had already been announced by local officials or the companies themselves, Reuters found. Two of the Trump Effect projects were aided by Biden's legislative efforts to boost domestic manufacturing, the review found. One company on the list, Swiss-based Roche, warned that Trump's plans to equalize U.S. and international drug prices now threatens its promised $50 billion in U.S. investments. Asked about taking credit for projects already underway before Trump came into office, the White House said the final investment decisions were announced under his watch and prove his economic policies are triggering U.S. investment. \\u201cPresident Trump is the greatest closer in modern history, and his leadership and policies are a critical catalyst converting hypothetical discussions into firm investment commitments and ground being broken for new plants and offices,\\\" White House spokesman Kush Desai said. The Reuters review included interviewing local officials and reviewing public records and corporate statements. It was not clear in many cases what role, if any, Trump or his policies played in getting the deals across the line. Mark Zandi, the chief economist at Moody's Analytics, said his economic forecast - along with the consensus estimates - for investment in the economy has remained relatively unchanged despite the White House's claims of new historic investments. \\\"I think despite all the announcements it hasn't translated into any change in expectations,\\\" Zandi said. \\\"The fundamentals that ultimately drive investment spending, broadly, if anything, appear to have weakened since the start of the year.\\\" Trump's push to impose sweeping tariffs on dozens of trading partners has injected uncertainty into global markets, lowering economic projections and freezing\n\nPredict whether the return of USMV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.012163, "explanation": "The actual 21-day forward return for USMV starting 2025-07-09 was -1.22%, which classifies as 'negative'.", "metadata": {"future_return": -0.012163, "horizon_days": 21, "hist_return": 0.059332, "annualized_vol": 0.126339, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250120_0148", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2025-01-20", "context_summary": "EWJ over past 60 days: cumulative return -1.2%, annualized vol 15.4%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=64.08, end=63.28, cumulative_return=-1.2%, annualized_volatility=15.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.34, 't10y3m_spread': 0.27, 'breakeven_10y': 2.41, 'hy_oas': 2.66, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 7.04, 'vix': 15.970000267028809}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 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0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 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The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of EWJ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.035348, "explanation": "The actual 21-day forward return for EWJ starting 2025-01-20 was +3.53%, which classifies as 'positive'.", "metadata": {"future_return": 0.035348, "horizon_days": 21, "hist_return": -0.012434, "annualized_vol": 0.154287, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20251229_0150", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2025-12-29", "context_summary": "XLP over past 60 days: cumulative return +1.2%, annualized vol 11.7%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=76.89, end=77.79, cumulative_return=+1.2%, annualized_volatility=11.7%\nMacro context: {'fed_funds_rate': 3.64, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.68, 't10y3m_spread': 0.5, 'breakeven_10y': 2.23, 'hy_oas': 2.86, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.18, 'vix': 13.600000381469728}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 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Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\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": -0.007665, "explanation": "The actual 21-day forward return for XLP starting 2025-12-29 was -0.77%, which classifies as 'flat'.", "metadata": {"future_return": -0.007665, "horizon_days": 21, "hist_return": 0.011773, "annualized_vol": 0.116695, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250812_0153", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2025-08-12", "context_summary": "ACWI over past 60 days: cumulative return +7.4%, annualized vol 9.9%. Market regime: bull.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=121.44, end=130.36, cumulative_return=+7.4%, annualized_volatility=9.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.51, 't10y3m_spread': -0.07, 'breakeven_10y': 2.4, 'hy_oas': 2.94, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 16.25}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q UNH 2025-08-11] unh-20250630 false 2025 Q2 0000731766 12/31 50 xbrli:shares iso4217:USD iso4217:USD xbrli:shares utr:Rate xbrli:pure unh:reportableSegments 0000731766 2025-01-01 2025-06-30 0000731766 2025-07-31 0000731766 2025-06-30 0000731766 2024-12-31 0000731766 2025-04-01 2025-06-30 0000731766 2024-04-01 2024-06-30 0000731766 2024-01-01 2024-06-30 0000731766 us-gaap:ProductMember 2025-04-01 2025-06-30 0000731766 us-gaap:ProductMember 2024-04-01 2024-06-30 0000731766 us-gaap:ProductMember 2025-01-01 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2024-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2024-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2024-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2024-12-31 0000731766 us-gaap:DebtSecuritiesMember 2025-06-30 0000731766 us-gaap:DebtSecuritiesMember 2024-12-31 0000731766 us-gaap:FairValueInputsLevel1Member 2025-06-30 0000731766 us-gaap:FairValueInputsLevel2Member 2025-06-30 0000731766 us-gaap:FairValueInputsLevel3Member 2025-06-30 0000731766 us-gaap:USTr [...TRUNCATED...] #8217;s Current Report on Form 8-K filed on February 26, 2021) 4.1 Amended and Restated Indenture, dated as of April 27, 2023, between UnitedHealth Group Incorporated and Wilmington Trust Company, as successor trustee (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) * 10. 1 Employment Agreeme nt, effective as of May 12, 2025, between United HealthC are Services, Inc. and Stephen Hemsely 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Denotes management contracts and compensation plans in which certain directors and named executive officers participate and which are being filed pursuant to Item 601(b)(10)(iii)(A) of Regulation S-K. ** Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ S TEPHEN H EMSLEY Chair and Chief Executive Officer (principal executive officer) Dated: August 11, 2025 Stephen Hemsley    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 11, 2025 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 11, 2025 Thomas Roos    28\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": 0.027078, "explanation": "The actual 21-day forward return for ACWI starting 2025-08-12 was +2.71%, which classifies as 'positive'.", "metadata": {"future_return": 0.027078, "horizon_days": 21, "hist_return": 0.073517, "annualized_vol": 0.098681, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250915_0156", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2025-09-15", "context_summary": "MTUM over past 60 days: cumulative return +10.1%, annualized vol 12.3%. Market regime: bull.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=228.90, end=252.01, cumulative_return=+10.1%, annualized_volatility=12.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.5, 't10y3m_spread': -0.02, 'breakeven_10y': 2.36, 'hy_oas': 2.79, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.35, 'vix': 14.760000228881836}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": 0.000409, "explanation": "The actual 21-day forward return for MTUM starting 2025-09-15 was +0.04%, which classifies as 'flat'.", "metadata": {"future_return": 0.000409, "horizon_days": 21, "hist_return": 0.100968, "annualized_vol": 0.12315, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250819_0158", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["TLT"], "decision_date": "2025-08-19", "context_summary": "TLT over past 60 days: cumulative return +2.1%, annualized vol 11.3%. Market regime: bull.", "question": "Asset: TLT\nHistorical prices (past 60 trading days): start=81.96, end=83.65, cumulative_return=+2.1%, annualized_volatility=11.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.57, 't10y3m_spread': 0.01, 'breakeven_10y': 2.38, 'hy_oas': 2.88, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.58, 'vix': 14.989999771118164}\nMarket regime: bull\n\nPredict whether the return of TLT over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.046665, "explanation": "The actual 21-day forward return for TLT starting 2025-08-19 was +4.67%, which classifies as 'positive'.", "metadata": {"future_return": 0.046665, "horizon_days": 21, "hist_return": 0.020678, "annualized_vol": 0.113226, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250130_0161", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-01-30", "context_summary": "LINK-USD over past 60 days: cumulative return +25.1%, annualized vol 97.5%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=18.89, end=23.62, cumulative_return=+25.1%, annualized_volatility=97.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.34, 't10y3m_spread': 0.24, 'breakeven_10y': 2.4, 'hy_oas': 2.68, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.96, 'vix': 16.559999465942383}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.252313, "explanation": "The actual 21-day forward return for LINK-USD starting 2025-01-30 was -25.23%, which classifies as 'negative'.", "metadata": {"future_return": -0.252313, "horizon_days": 21, "hist_return": 0.250553, "annualized_vol": 0.97452, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250630_0164", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-06-30", "context_summary": "AVAX-USD over past 60 days: cumulative return -13.4%, annualized vol 70.7%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=21.65, end=18.74, cumulative_return=-13.4%, annualized_volatility=70.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.56, 't10y3m_spread': -0.1, 'breakeven_10y': 2.29, 'hy_oas': 3.02, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 6.77, 'vix': 16.31999969482422}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.416085, "explanation": "The actual 21-day forward return for AVAX-USD starting 2025-06-30 was +41.61%, which classifies as 'positive'.", "metadata": {"future_return": 0.416085, "horizon_days": 21, "hist_return": -0.134147, "annualized_vol": 0.707165, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250307_0167", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-03-07", "context_summary": "XLY over past 60 days: cumulative return -11.3%, annualized vol 20.6%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=114.95, end=101.94, cumulative_return=-11.3%, annualized_volatility=20.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.33, 't10y3m_spread': -0.05, 'breakeven_10y': 2.34, 'hy_oas': 2.99, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 24.8700008392334}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K PFE 2025-02-27] pfe-20241231 0000078003 2024 FY false P4Y Consolidated Statements of Operations Consolidated Statements of Operations Consolidated Statements of Operations http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent 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ITEM 16. FORM 10-K SUMMARY None. SIGNATURES Under the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, this report was signed on behalf of the Registrant by the authorized person named below. Pfizer Inc. Dated: February 27, 2025 By: /S/    MARGARET M. MADDEN Margaret M. Madden Senior Vice President and Corporate Secretary Chief Governance Counsel We, the undersigned directors and officers of Pfizer Inc., hereby severally constitute Douglas M. Lankler and Margaret M. Madden, and each of them singly, our true and lawful attorneys with full power to them and each of them to sign for us, in our names in the capacities indicated below, any and all amendments to this Annual Report on Form 10-K filed with the Securities and Exchange Commission. Under the requirements of the Securities Exchange Act of 1934, this report was signed by the following persons on behalf of the Registrant and in the capacities and on the date indicated . Pfizer Inc. 2024 Form 10-K 113 Signature Title Date /S/    ALBERT BOURLA Albert Bourla Chairman, Chief Executive Officer and Director (Principal Executive Officer) February 27, 2025 /S/    DAVID M. DENTON David M. Denton Chief Financial Officer, Executive Vice President (Principal Financial Officer) February 27, 2025 /S/    JENNIFER B. DAMICO Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer) February 27, 2025 /S/    RONALD E. BLAYLOCK Ronald E. Blaylock Director February 27, 2025 /S/    MORTIMER J. BUCKLEY Mortimer J. Buckley Director February 27, 2025 /S/    SUSAN DESMOND-HELLMANN Susan Desmond-Hellmann Director February 27, 2025 /S/    JOSEPH J. ECHEVARRIA Joseph J. Echevarria Director February 27, 2025 /S/    SCOTT GOTTLIEB Scott Gottlieb Director February 27, 2025 /S/    HELEN H. HOBBS Helen H. Hobbs Director February 27, 2025 /S/    SUSAN HOCKFIELD Susan Hockfield Director February 27, 2025 /S/    DAN R. LITTMAN Dan R. Littman Director February 27, 2025 /S/    SHANTANU NARAYEN Shantanu Narayen Director February 27, 2025 /S/    SUZANNE NORA JOHNSON Suzanne Nora Johnson Director February 27, 2025 /S/    JAMES QUINCEY James Quincey Director February 27, 2025 /S/    JAMES C. SMITH James C. Smith Director February 27, 2025 /S/    CYRUS TARAPOREVALA Cyrus Taraporevala Director February 27, 2025 Pfizer Inc. 2024 Form 10-K 114\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": -0.119331, "explanation": "The actual 21-day forward return for XLY starting 2025-03-07 was -11.93%, which classifies as 'negative'.", "metadata": {"future_return": -0.119331, "horizon_days": 21, "hist_return": -0.113228, "annualized_vol": 0.205736, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250512_0169", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-05-12", "context_summary": "VTI over past 60 days: cumulative return -7.6%, annualized vol 22.9%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=297.31, end=274.72, cumulative_return=-7.6%, annualized_volatility=22.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.49, 't10y3m_spread': 0.03, 'breakeven_10y': 2.29, 'hy_oas': 3.53, 'ig_oas': 1.02, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 21.89999961853028}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-09] [\"Cathie Wood Just Bought These 2 Stocks Down 42% and 87%. Should You? Airbnb looks like a value stock today, but it's planning a new launch next week that could boost its position. Roku is still reporting strong growth, but investors are still waiting for profits. 10 stocks we like better than Airbnb \\u203a Cathie Wood has made a name for herself as a top growth investor. She has made some bold moves as head of investing company Ark Invest. Although some of Ark's exchange-traded funds (ETFs) have a spotty track record, some of them have outperformed the market, and she has drawn attention to her company's trades, which are reported daily. Although Wood has a specific, innovation-driven approach to investing, her model is the same \\\"buy low, sell high\\\" model that underpins most successful investing. When stocks she likes go on sale, you're more likely to see them in Ark's shopping cart. Airbnb (NASDAQ: ABNB) and Roku (NASDAQ: ROKU) are two disruptive, high-opportunity stocks Ark just bought. Should they be in your shopping cart, too? Airbnb is a top brand name in travel, but its stock has been in the doldrums for quite a while. It's a case of skyrocketing too quickly based on market hype, and the stock has never been able to find its ground. Each time it looks compelling, the stock soars before dropping down in the aftermath. With all that volatility, it's only gained 84% since its first-day closing price. Will things finally start changing for this beleaguered stock? There are a lot of things happening at Airbnb, and the time might be ripe for taking off. Performance-wise, things have only been so-so. Revenue increased 6% year over year in the 2025 first quarter, which doesn't sound like a growth stock. Airbnb has made the jump from unprofitable growth stock to profitable industry leader, which is when many value investors might jump in if the price is right. Net income was lower in Q1, but the company is generating lots of cash, and trailing 12-month free cash flow is $4.4 billion with a 39% margin. The question is how much bigger Airbnb can grow. Management is expecting revenue to increase about 10% year over year in the second quarter, which would be a welcome acceleration. It's keeping a lid on a major launch that it's unveiling next week, but that's going to expand \\\"beyond the core,\\\" something it's been talking about for years already. As the platform it is today, investors can expect continued growth from tech enhancements, more hosts, and better features, but these are likely to be incremental. A huge shift in business could boost growth potential, so investors should follow what the company announced on May 13. At the current price, Airbnb stock trades at a forward, 1-year price-to-earnings (P/E) ratio of 25, and price-to-free cash flow is a strong value at 18. I wouldn't call it bargain territory, but it doesn't look overvalued. If you have a long time horizon, Airbnb stock should eventually find its footing and reward investors, but\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": 0.030842, "explanation": "The actual 21-day forward return for VTI starting 2025-05-12 was +3.08%, which classifies as 'positive'.", "metadata": {"future_return": 0.030842, "horizon_days": 21, "hist_return": -0.075967, "annualized_vol": 0.229075, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250530_0171", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-05-30", "context_summary": "XLF over past 60 days: cumulative return +1.6%, annualized vol 22.7%. Market regime: sideways.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=49.27, end=50.08, cumulative_return=+1.6%, annualized_volatility=22.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.51, 't10y3m_spread': 0.07, 'breakeven_10y': 2.32, 'hy_oas': 3.22, 'ig_oas': 0.9, 'ted_spread': 0.09, 'mortgage_30y': 6.89, 'vix': 19.18000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-29] [\"Microsoft Shares Go From Laggard to Leader as AI Growth Improves (Bloomberg) -- After languishing for months, Microsoft Corp. shares are back within striking distance of a record high amid signs that performance in its Azure cloud-computing business is back on track. Most Read from Bloomberg NYC Congestion Toll Brings In $216 Million in First Four Months NY Wins Order Against US Funding Freeze in Congestion Fight Now With Colorful Blocks, Tirana\\u2019s Pyramid Represents a Changing Albania The Economic Benefits of Paying Workers to Move NY Congestion Pricing Is Likely to Stay Until Year End During Court Case The software giant\\u2019s shares are about 1.5% shy of the record reached last July, with their 16% advance in May putting them on track for the best month in more than three years. The rally has been fueled by the broader rebound in US equities, as well as better-than-expected results from Azure, which investors are betting will continue as artificial intelligence drives more business. \\u201cAI is becoming a bigger and bigger component of those revenues,\\u201d said Nancy Tengler, chief executive officer at Laffer Tengler Investments. \\u201cI do think it\\u2019s a sustainer.\\u201d The strength in Microsoft shares is a stark reversal from last year, when concerns about its position in the AI race and disappointing Azure growth weighed on the stock. Microsoft\\u2019s 12% advance in 2024 made it the worst performer among the so-called Magnificent Seven stocks, which also includes Apple Inc., Nvidia Corp., Alphabet Inc., Amazon.com Inc., Meta Platforms Inc. and Tesla Inc. This year, Microsoft\\u2019s 9% advance has outperformed all of those peers save for Meta, which is up 10%. In addition to benefiting from limited exposure to President Donald Trump\\u2019s tariffs, Microsoft emerged as one of the biggest winners from a mostly strong earnings season for Big Tech. The Redmond, Washington-based company reported revenue and profit in its fiscal third quarter that beat Wall Street estimates. Azure was the standout, with revenue growth of 33% exceeding expectations. Azure\\u2019s sales include both AI services \\u2014 the computing power that backs OpenAI\\u2019s ChatGPT and similar tools \\u2014 and other products like databases and on-demand storage. Microsoft Chief Financial Officer Amy Hood said last month that it was those non-AI businesses that outperformed expectations in the most recent quarter. This week, TD Cowen analysts led by Derrick Wood projected that AI-related Azure revenue would rise to about $24 billion in the 2026 fiscal year, from roughly $4 billion in fiscal 2024. The analysts, who have a buy rating on the stock, raised their price target to $540 from $490, implying a potential gain of about 18% from Wednesday\\u2019s closing price. Of the 72 analysts tracked by Bloomberg that cover Microsoft, only 6 have hold ratings and none recommend selling. \\u201cA return to Azure upside trends and firmer growth in the mid-30% level should help dr\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": 0.031191, "explanation": "The actual 21-day forward return for XLF starting 2025-05-30 was +3.12%, which classifies as 'positive'.", "metadata": {"future_return": 0.031191, "horizon_days": 21, "hist_return": 0.016425, "annualized_vol": 0.227372, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250129_0174", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-01-29", "context_summary": "EFA over past 60 days: cumulative return +0.6%, annualized vol 12.5%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=75.92, end=76.40, cumulative_return=+0.6%, annualized_volatility=12.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.36, 't10y3m_spread': 0.24, 'breakeven_10y': 2.42, 'hy_oas': 2.66, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.96, 'vix': 16.40999984741211}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q PG 2025-01-22] pg-20241231 0000080424 6/30 2025 Q2 false http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2024#AccountsPayableCurrent http://fasb.org/us-gaap/2024#AccountsPayableCurrent xbrli:shares iso4217:USD iso4217:USD xbrli:shares pg:segment xbrli:pure pg:country pg:taxable_jurisdiction pg:audit 0000080424 2024-07-01 2024-12-31 0000080424 us-gaap:CommonStockMember 2024-07-01 2024-12-31 0000080424 pg:A1.375NotesDue2025Member 2024-07-01 2024-12-31 0000080424 pg:A0.110NotesDue2026Member 2024-07-01 2024-12-31 0000080424 pg:A3.250EURNotesDue2026Member 2024-07-01 2024-12-31 0000080424 pg:A4.875EURNotesDueMay2027Member 2024-07-01 2024-12-31 0000080424 pg:A1.200NotesDue2028Member 2024-07-01 2024-12-31 0000080424 pg:A3.150EURONotesDue2028Member 2024-07-01 2024-12-31 0000080424 pg:A1.250NotesDue2029Member 2024-07-01 2024-12-31 0000080424 pg:A1.800NotesDue2029Member 2024-07-01 2024-12-31 0000080424 pg:A6.250GBPNotesDueJanuary2030Member 2024-07-01 2024-12-31 0000080424 pg:A0.350NotesDue2030Member 2024-07-01 2024-12-31 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0000080424 us-gaap:PreferredStockMember 2024-06-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2024-06-30 0000080424 pg:ReserveforESOPDebtRetirementMember 2024-06-30 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-06-30 0000080424 us-gaap:TreasuryStockCommonMember 2024-06-30 0000080424 us-gaap:RetainedEarningsMember 2024-06-30 0000080424 us-gaap:NoncontrollingInterestMember 2024-06-30 0000080424 us-gaap:RetainedEarningsMember 2024-07-01 2024-12-31 0000080424 us-gaap:NoncontrollingInterestMember 2024-07-01 2024-12-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-01 2024-12-31 0000080424 us-gaap:CommonStockMember 2024-07-01 2024-12-31 0000080424 us-gaap:TreasuryStockCommonMember 2024-07-01 2024-12-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2024-07-01 2024-12-31 0000080424 us-gaap:PreferredStockMember 2024-07-01 2024-12-31 0000080424 pg:ReserveforESOPDebtRetirementMember 2024-07-01 2024-12-31 0000080424 us-gaap:CommonStockMember 2023-09-30 0000080424 us-gaap:PreferredStockMember 2023-09-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-09-30 0000080424 pg:ReserveforESOPDebtRetirementMember 2023-09-30 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-09-30 0000080424 us-gaap:TreasuryStockCommonMember 2023-09-30 0000080424 us-gaap:RetainedEarningsMember 2023-09-30 0000080424 us-gaap:NoncontrollingInterestMember 2023-09-30 0000080424 2023-09-30 0000080424 us-gaap:RetainedEarningsMember 2023-10-01 2023-12-31 0000080424 us-gaap:NoncontrollingInterestMember 2023-10-01 2023-12-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-10-01 2023-12-31 0000080424 us-gaap:CommonStockMember 2023-10-01 2023-12-31 0000080424 us-gaap:TreasuryStockCommonMember 2023-10-01 2023-12-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-10-01 2023-12-31 0000080424 us-gaap:PreferredStockMember 2023-10-01 2023-12-31 0000080424 us-gaap:CommonStockMember 2023-12-31 0000080424 us-gaap:PreferredStockMember 2023-12-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-12-31 0000080424 pg:ReserveforESOPDebtRetirementMember 2023-12-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-12-31 0000080424 us-gaap:TreasuryStockCommonMember 2023-12-31 0000080424 us-gaap:RetainedEarningsMember 2023-12-31 0000080424 us-gaap:NoncontrollingInterestMember 2023-12-31 0000080424 2023-12-31 0000080424 us-gaap:CommonStockMember 2023-06-30 0000080424 us-gaap:PreferredStockMember 2023-06-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-06-30 0000080424 pg:R [...TRUNCATED...] 7 billion in fiscal year 2025, notwithstanding any purchases under the Company's compensation and benefit plans. Purchases may be made in the open market and/or private transactions and purchases may be increased, decreased or discontinued at any time without prior notice. The share repurchases are authorized pursuant to a resolution issued by the Company's Board of Directors and are expected to be financed by a combination of operating cash flows and issuance of debt.      Item 5. Other Information During the three months ended December 31, 2024, none of our directors or officers adopted or terminated a \"Rule 10b5-1 trading arrangement\" or \"non-Rule 10b5-1 trading arrangement\" as defined in Item 408 of Regulation S-K. 30 The Procter & Gamble Company Item 6. Exhibits 3.1 Amended Articles of Incorporation (as amended by shareholders at the annual meeting on October 11, 2011 and consolidated by the Board of Directors on April 8, 2016) (Incorporated by reference to Exhibit (3-1) of the Company's Form 10-K for the year ended June 30, 2016) 3.2 Regulations (as approved by the Board of Directors on December 13, 2022, pursuant to authority granted by shareholders at the annual meeting on October 13, 2009) (Incorporated by reference to Exhibit (3-2) of the Company’s Current Report on Form 8-K filed December 13, 2022) 4.1 Indenture, dated as of September 3, 2009, between the Company and Deutsche Bank Trust Company Americas, as Trustee (Incorporated by reference to Exhibit (4-1) of the Company's Annual Report on Form 10-K for the year ended June 30, 2015) 31.1 Rule 13a-14(a)/15d-14(a) Certification – Chief Executive Officer + 31.2 Rule 13a-14(a)/15d-14(a) Certification – Chief Financial Officer + 32.1 Section 1350 Certifications – Chief Executive Officer + 32.2 Section 1350 Certifications – Chief Financial Officer + 101.SCH (1) Inline XBRL Taxonomy Extension Schema Document 101.CAL (1) Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF (1) Inline XBRL Taxonomy Definition Linkbase Document 101.LAB (1) Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE (1) Inline XBRL Taxonomy Extension Presentation Linkbase Document 104  Cover Page Interactive Data File (formatted in Inline XBRL and contained in Exhibit 101) + Filed herewith (1) Pursuant to Rule 406T of Regulation S-T, this information is furnished and not filed for purposes of Sections 11 or 12 of the Securities Act of 1933 and Section 18 of the Securities Exchange Act of 1934, and otherwise is not subject to liability under these sections. Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this Report to be signed on its behalf by the undersigned thereunto duly authorized. THE PROCTER & GAMBLE COMPANY January 22, 2025 /s/ MATTHEW W. JANZARUK Date (Matthew W. Janzaruk) Senior Vice President - Chief Accounting Officer (Principal Accounting Officer)\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": 0.031092, "explanation": "The actual 21-day forward return for EFA starting 2025-01-29 was +3.11%, which classifies as 'positive'.", "metadata": {"future_return": 0.031092, "horizon_days": 21, "hist_return": 0.00625, "annualized_vol": 0.125166, "has_text": true, "text_chars": 9044}} +{"id": "T1_all_20250402_0177", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["HAUZ"], "decision_date": "2025-04-02", "context_summary": "HAUZ over past 60 days: cumulative return +3.0%, annualized vol 12.0%. Market regime: bear.", "question": "Asset: HAUZ\nHistorical prices (past 60 trading days): start=18.96, end=19.54, cumulative_return=+3.0%, annualized_volatility=12.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.3, 't10y3m_spread': -0.15, 'breakeven_10y': 2.33, 'hy_oas': 3.5, 'ig_oas': 0.98, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 21.770000457763672}\nMarket regime: bear\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": 0.075195, "explanation": "The actual 21-day forward return for HAUZ starting 2025-04-02 was +7.52%, which classifies as 'positive'.", "metadata": {"future_return": 0.075195, "horizon_days": 21, "hist_return": 0.030242, "annualized_vol": 0.12048, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251118_0180", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2025-11-18", "context_summary": "EMB over past 60 days: cumulative return +3.7%, annualized vol 4.7%. Market regime: sideways.", "question": "Asset: EMB\nHistorical prices (past 60 trading days): start=90.59, end=93.98, cumulative_return=+3.7%, annualized_volatility=4.7%\nMacro context: {'fed_funds_rate': 3.88, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.53, 't10y3m_spread': 0.16, 'breakeven_10y': 2.28, 'hy_oas': 3.13, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.24, 'vix': 22.3799991607666}\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": "flat", "answer_numeric": 0.004166, "explanation": "The actual 21-day forward return for EMB starting 2025-11-18 was +0.42%, which classifies as 'flat'.", "metadata": {"future_return": 0.004166, "horizon_days": 21, "hist_return": 0.037475, "annualized_vol": 0.046723, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250609_0182", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-06-09", "context_summary": "BNB-USD over past 60 days: cumulative return +12.9%, annualized vol 28.7%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=577.41, end=652.15, cumulative_return=+12.9%, annualized_volatility=28.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.47, 't10y3m_spread': 0.08, 'breakeven_10y': 2.31, 'hy_oas': 3.09, 'ig_oas': 0.87, 'ted_spread': 0.09, 'mortgage_30y': 6.85, 'vix': 16.770000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.013407, "explanation": "The actual 21-day forward return for BNB-USD starting 2025-06-09 was -1.34%, which classifies as 'negative'.", "metadata": {"future_return": -0.013407, "horizon_days": 21, "hist_return": 0.129444, "annualized_vol": 0.287376, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250909_0184", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["TLT"], "decision_date": "2025-09-09", "context_summary": "TLT over past 60 days: cumulative return +4.7%, annualized vol 11.0%. Market regime: bull.", "question": "Asset: TLT\nHistorical prices (past 60 trading days): start=83.50, end=87.47, cumulative_return=+4.7%, annualized_volatility=11.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.56, 't10y3m_spread': -0.05, 'breakeven_10y': 2.35, 'hy_oas': 2.84, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.5, 'vix': 15.109999656677246}\nMarket regime: bull\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": 0.003706, "explanation": "The actual 21-day forward return for TLT starting 2025-09-09 was +0.37%, which classifies as 'flat'.", "metadata": {"future_return": 0.003706, "horizon_days": 21, "hist_return": 0.047465, "annualized_vol": 0.109547, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251024_0189", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-10-24", "context_summary": "ETH-USD over past 60 days: cumulative return -5.5%, annualized vol 55.4%. Market regime: bull.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=4079.06, end=3856.03, cumulative_return=-5.5%, annualized_volatility=55.4%\nMacro context: {'fed_funds_rate': 4.11, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.53, 't10y3m_spread': 0.06, 'breakeven_10y': 2.3, 'hy_oas': 2.96, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.19, 'vix': 17.299999237060547}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.211149, "explanation": "The actual 21-day forward return for ETH-USD starting 2025-10-24 was -21.11%, which classifies as 'negative'.", "metadata": {"future_return": -0.211149, "horizon_days": 21, "hist_return": -0.054677, "annualized_vol": 0.553881, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251113_0192", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2025-11-13", "context_summary": "XLK over past 60 days: cumulative return +11.8%, annualized vol 18.6%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=129.40, end=144.70, cumulative_return=+11.8%, annualized_volatility=18.6%\nMacro context: {'fed_funds_rate': 3.87, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.52, 't10y3m_spread': 0.13, 'breakeven_10y': 2.27, 'hy_oas': 3.02, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.22, 'vix': 17.510000228881836}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CVX 2025-11-06] cvx-20250930 0000093410 12/31 2025 Q3 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cvx:segment cvx:lawsuit cvx:state cvx:tribe cvx:parish 0000093410 2025-01-01 2025-09-30 0000093410 2025-09-30 0000093410 2025-07-01 2025-09-30 0000093410 2024-07-01 2024-09-30 0000093410 2024-01-01 2024-09-30 0000093410 2024-12-31 0000093410 2023-12-31 0000093410 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-06-30 0000093410 us-gaap:RetainedEarningsMember 2024-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-06-30 0000093410 us-gaap:ParentMember 2024-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-06-30 0000093410 2024-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-07-01 2024-09-30 0000093410 us-gaap:ParentMember 2024-07-01 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 2024-07-01 2024-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-07-01 2024-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-01 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-07-01 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 2024-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-09-30 0000093410 us-gaap:ParentMember 2024-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-06-30 0000093410 us-gaap:RetainedEarningsMember 2025-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-06-30 0000093410 us-gaap:ParentMember 2025-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-06-30 0000093410 2025-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-07-01 2025-09-30 0000093410 us-gaap:ParentMember 2025-07-01 2025-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-07-01 2025-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-07-01 2025-09-30 0000093410 us-gaap:RetainedEarningsMember 2025-07-01 2025-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-01 2025-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-09-30 0000093410 us-gaap:RetainedEarningsMember 2025-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-09-30 0000093410 us-gaap:ParentMember 2025-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2023-12-31 0000093410 us-gaap:RetainedEarningsMember 2023-12-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-12-31 0000093410 us-gaap:TreasuryStockCommonMember 2023-12-31 0000093410 us-gaap:ParentMember 2023-12-31 0000093410 us-gaap:NoncontrollingInterestMember 2023-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-01-01 2024-09-30 0000093410 us-gaap:ParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 2024-01-01 2024-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-01 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-01-01 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-12-31 0000093410 us-gaap:RetainedEarningsMember 2024-12-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-12-31 0000093410 us-gaap:TreasuryStockCommonMember 2024-12-31 0000093410 us-gaap:ParentMember 2024-12-31 0000093410 us-gaap:NoncontrollingInterestMember 2024-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-01-01 2025-09-30 0000093410 us-gaap:ParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-01-01 2025-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-01-01 2025-09-30 0000093410 us-gaap:RetainedEarningsMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-09-30 0000093410 [...TRUNCATED...] 160; $154.38 16,620,000   (1) Includes common shares repurchased from participants in the company’s executive compensation plans for personal income tax withholdings. (2) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections During the three months ended September 30, 2025, none of our directors or executive officers adopted, modified or terminated a Rule 10b5-1 trading arrangement or a non-Rule 10b5-1 trading arrangement, as such terms are defined in Item 408 of Regulation S-K. 47 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 4.1 Fourth Supplemental Indenture, dated as of August 13, 2025, among Chevron U.S.A. Inc., Chevron Corporation, as guarantor, and Deutsche Bank Trust Company Americas, as trustee, filed as Exhibit 4. 2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 4.2 Forms of 3.950% Notes Due 2027, 4.050% Notes Due 2028, Floating Rate Notes Due 2028-B, 4.300% Notes Due 2030, Floating Rate Notes due 2030, 4.500% Notes Due 2032 and 4.850% Notes Due 2035, contained in Exhibit 4.2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 10.1+* Aircraft Time-Sharing Agreement, dated as of February 24, 2015, between Hess Corporation and John B. Hess. 10.2* Transition Services Agreement, dated as of July 14, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.3* Amendment One to Transition Services Agreement, dated as of August 27, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.4* Membership Interest Purchase Agreement, dated as of September 10, 2025, between Hess Corporation and JBH Ventures, LLC . 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ + Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 48 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 6, 2025 49\n\nPredict whether the return of XLK over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002757, "explanation": "The actual 21-day forward return for XLK starting 2025-11-13 was +0.28%, which classifies as 'flat'.", "metadata": {"future_return": 0.002757, "horizon_days": 21, "hist_return": 0.118234, "annualized_vol": 0.186456, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250528_0195", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-05-28", "context_summary": "ETH-USD over past 60 days: cumulative return +45.7%, annualized vol 72.4%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=1827.32, end=2663.07, cumulative_return=+45.7%, annualized_volatility=72.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.51, 't10y3m_spread': 0.08, 'breakeven_10y': 2.32, 'hy_oas': 3.24, 'ig_oas': 0.91, 'ted_spread': 0.09, 'mortgage_30y': 6.86, 'vix': 18.959999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.058874, "explanation": "The actual 21-day forward return for ETH-USD starting 2025-05-28 was -5.89%, which classifies as 'negative'.", "metadata": {"future_return": -0.058874, "horizon_days": 21, "hist_return": 0.457363, "annualized_vol": 0.724353, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250101_0198", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DBC"], "decision_date": "2025-01-01", "context_summary": "DBC over past 60 days: cumulative return -1.3%, annualized vol 15.2%. Market regime: sideways.", "question": "Asset: DBC\nHistorical prices (past 60 trading days): start=20.95, end=20.68, cumulative_return=-1.3%, annualized_volatility=15.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 317.604, 'unemployment': 4.1, 'gdp_growth_qoq': 23586.542, 't10y2y_spread': 0.33, 't10y3m_spread': 0.21, 'breakeven_10y': 2.34, 'hy_oas': 2.92, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.85, 'vix': 17.350000381469727}\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": 0.029467, "explanation": "The actual 21-day forward return for DBC starting 2025-01-01 was +2.95%, which classifies as 'positive'.", "metadata": {"future_return": 0.029467, "horizon_days": 21, "hist_return": -0.012652, "annualized_vol": 0.151886, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251124_0200", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["CORN"], "decision_date": "2025-11-24", "context_summary": "CORN over past 60 days: cumulative return -0.7%, annualized vol 12.0%. Market regime: sideways.", "question": "Asset: CORN\nHistorical prices (past 60 trading days): start=17.72, end=17.60, cumulative_return=-0.7%, annualized_volatility=12.0%\nMacro context: {'fed_funds_rate': 3.88, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.55, 't10y3m_spread': 0.16, 'breakeven_10y': 2.24, 'hy_oas': 3.19, 'ig_oas': 0.86, 'ted_spread': 0.09, 'mortgage_30y': 6.26, 'vix': 23.43000030517578}\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": "positive", "answer_numeric": 0.019329, "explanation": "The actual 21-day forward return for CORN starting 2025-11-24 was +1.93%, which classifies as 'positive'.", "metadata": {"future_return": 0.019329, "horizon_days": 21, "hist_return": -0.006772, "annualized_vol": 0.119637, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250227_0205", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-02-27", "context_summary": "ETH-USD over past 60 days: cumulative return -30.4%, annualized vol 55.2%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=3349.51, end=2331.45, cumulative_return=-30.4%, annualized_volatility=55.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.2, 't10y3m_spread': -0.06, 'breakeven_10y': 2.36, 'hy_oas': 2.81, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.85, 'vix': 19.100000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.140267, "explanation": "The actual 21-day forward return for ETH-USD starting 2025-02-27 was -14.03%, which classifies as 'negative'.", "metadata": {"future_return": -0.140267, "horizon_days": 21, "hist_return": -0.303943, "annualized_vol": 0.551502, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250613_0207", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2025-06-13", "context_summary": "EMB over past 60 days: cumulative return +1.9%, annualized vol 9.3%. Market regime: sideways.", "question": "Asset: EMB\nHistorical prices (past 60 trading days): start=86.04, end=87.69, cumulative_return=+1.9%, annualized_volatility=9.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.46, 't10y3m_spread': -0.1, 'breakeven_10y': 2.25, 'hy_oas': 3.17, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 6.84, 'vix': 18.020000457763672}\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": 0.013618, "explanation": "The actual 21-day forward return for EMB starting 2025-06-13 was +1.36%, which classifies as 'positive'.", "metadata": {"future_return": 0.013618, "horizon_days": 21, "hist_return": 0.019155, "annualized_vol": 0.093408, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250121_0210", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-01-21", "context_summary": "EEM over past 60 days: cumulative return -5.9%, annualized vol 14.2%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=43.69, end=41.10, cumulative_return=-5.9%, annualized_volatility=14.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.34, 't10y3m_spread': 0.27, 'breakeven_10y': 2.41, 'hy_oas': 2.66, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 7.04, 'vix': 15.970000267028809}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 2024-12-04 0000104169 2024-08-01 2024-10-31 0000104169 2023-08-01 2023-10-31 0000104169 2023-02-01 2023-10-31 0000104169 2024-10-31 0000104169 2024-01-31 0000104169 2023-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-08-01 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\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": 0.058533, "explanation": "The actual 21-day forward return for EEM starting 2025-01-21 was +5.85%, which classifies as 'positive'.", "metadata": {"future_return": 0.058533, "horizon_days": 21, "hist_return": -0.059328, "annualized_vol": 0.141722, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250926_0213", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-09-26", "context_summary": "BTC-USD over past 60 days: cumulative return +0.0%, annualized vol 25.2%. Market regime: bull.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=103998.57, end=103998.57, cumulative_return=+0.0%, annualized_volatility=25.2%\nMacro context: {'fed_funds_rate': 4.09, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.54, 't10y3m_spread': 0.14, 'breakeven_10y': 2.38, 'hy_oas': 2.76, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.3, 'vix': 16.739999771118164}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for BTC-USD starting 2025-09-26 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.251642, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251204_0216", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-12-04", "context_summary": "XLB over past 60 days: cumulative return -1.4%, annualized vol 15.4%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=44.71, end=44.07, cumulative_return=-1.4%, annualized_volatility=15.4%\nMacro context: {'fed_funds_rate': 3.89, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.57, 't10y3m_spread': 0.34, 'breakeven_10y': 2.24, 'hy_oas': 2.89, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.23, 'vix': 16.079999923706055}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-10-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-10-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-10-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-10-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-10-31 0000104169 2025-12-02 0000104169 2025-08-01 2025-10-31 0000104169 2024-08-01 2024-10-31 0000104169 2024-02-01 2024-10-31 0000104169 2025-10-31 0000104169 2025-01-31 0000104169 2024-10-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-30 0000104169 us-gaap:ParentMember 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-04-30 0000104169 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-05-01 2025-07-31 0000104169 us-gaap:ParentMember 2025-05-01 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-05-01 2025-07-31 0000104169 2025-05-01 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-05-01 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-31 0000104169 us-gaap:ParentMember 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-08-01 2025-10-31 0000104169 us-gaap:ParentMember 2025-08-01 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-08-01 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-08-01 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\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": 0.030498, "explanation": "The actual 21-day forward return for XLB starting 2025-12-04 was +3.05%, which classifies as 'positive'.", "metadata": {"future_return": 0.030498, "horizon_days": 21, "hist_return": -0.014306, "annualized_vol": 0.153738, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250417_0218", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-04-17", "context_summary": "EEM over past 60 days: cumulative return -2.3%, annualized vol 21.7%. Market regime: bear.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=41.57, end=40.62, cumulative_return=-2.3%, annualized_volatility=21.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.52, 't10y3m_spread': -0.04, 'breakeven_10y': 2.17, 'hy_oas': 4.16, 'ig_oas': 1.13, 'ted_spread': 0.09, 'mortgage_30y': 6.62, 'vix': 32.63999938964844}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-16] Big banks report Q1 beats, China stops taking Boeing deliveries: Morning Buzz The major averages were fractionally higher near noon, adding slightly to yesterday\u2019s gains as investors reacted to fresh headlines on U.S.-China trade tensions and a new round of corporate earnings. Markets are attempting to stabilize after a rocky stretch, but much of the tone is being shaped by President Trump\u2019s latest tariff decisions. After last week\u2019s escalation, he\u2019s now backing off slightly, offering temporary relief on key consumer electronics and signaling possible concessions for the auto sector. Discover outperforming stocks and invest smarter with Top Smart Score Stocks. Filter, analyze, and streamline your search for investment opportunities using Tipranks' Stock Screener. Looking to commodities, gold shares are up marginally, still hovering above the $3,200 threshold. Meanwhile, oil prices are lower, but only fractionally. Get caught up quickly on the top news and calls moving stocks with these five Top Five lists. 1. STOCK NEWS: Bank of America (BAC) reported better-than-expected Q1 results, with the company saying it grew commercial loans in every line of business in the quarter Citi (C) reported upbeat Q1 earnings and revenue and provided revenue guidance for FY25 Johnson & Johnson (JNJ) reported better-than-expected Q1 results, raised its FY25 operational sales outlook, and increased its quarterly dividend about 5% Lowe\u2019s (LOW) agreed to acquire Artisan Design Group for $1.325B China has ordered airlines to halt further deliveries of Boeing (BA) jets, Bloomberg reports 2. WALL STREET CALLS: General Motors (GM) downgraded to Equal Weight from Overweight at Barclays HubSpot (HUBS) upgraded to Buy from Neutral at UBS PepsiCo (PEP) downgraded to Neutral at BofA on slower snacks growth Nike (NKE) initiated with neutral view at Berenberg, here\u2019s why Benchmark starts \u201cdominant regional leader\u201d MercadoLibre (MELI) with a Buy 3. AROUND THE WEB: Elliott Investment Management has built a large position worth more than $1.5B in HP Enterprise (HPE), Bloomberg says Honda (HMC) is considering plans to relocate the production of models to the U.S. from Mexico and Canada in response to an additional 25% tariff imposed by the Trump Administration, Nikkei reports AMD (AMD) CEO says the company plans to build more AI servers in U.S., Bloomberg says LVMH (LVMUY) is considering moving some of its manufacturing to the U.S. amid Donald Trump\u2019s tariff threats, Business Insider says According to people who attended Netflix\u2019s (NFLX) annual business review meeting last month, the company aims to reach a $1T market capitalization and double its revenue by 2030, WSJ reports 4. MOVERS: Rezolve AI (RZLV) increases after securing a $9.8M annual contract with Liverpool Mexico Eos Energy (EOSE) gains after signing a MOU with Frontier Power Rocket Pharmaceuticals (RCKT) higher after its CEO bought $101.6K of the company\u2019s stock Allegro MicroSystems (ALGM) lower after On Semi (ON) withdr\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": 0.103531, "explanation": "The actual 21-day forward return for EEM starting 2025-04-17 was +10.35%, which classifies as 'positive'.", "metadata": {"future_return": 0.103531, "horizon_days": 21, "hist_return": -0.022786, "annualized_vol": 0.217033, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251104_0221", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-11-04", "context_summary": "AVAX-USD over past 60 days: cumulative return -32.0%, annualized vol 79.6%. Market regime: bull.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=24.48, end=16.65, cumulative_return=-32.0%, annualized_volatility=79.6%\nMacro context: {'fed_funds_rate': 3.87, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.53, 't10y3m_spread': 0.15, 'breakeven_10y': 2.31, 'hy_oas': 3.04, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.17, 'vix': 17.170000076293945}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.115738, "explanation": "The actual 21-day forward return for AVAX-USD starting 2025-11-04 was -11.57%, which classifies as 'negative'.", "metadata": {"future_return": -0.115738, "horizon_days": 21, "hist_return": -0.319753, "annualized_vol": 0.795962, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250801_0224", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-08-01", "context_summary": "ADA-USD over past 60 days: cumulative return +7.3%, annualized vol 58.1%. Market regime: bull.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.69, end=0.74, cumulative_return=+7.3%, annualized_volatility=58.1%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.43, 't10y3m_spread': -0.04, 'breakeven_10y': 2.39, 'hy_oas': 2.86, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 16.719999313354492}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.299377, "explanation": "The actual 21-day forward return for ADA-USD starting 2025-08-01 was +29.94%, which classifies as 'positive'.", "metadata": {"future_return": 0.299377, "horizon_days": 21, "hist_return": 0.073053, "annualized_vol": 0.580669, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251014_0226", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["WEAT"], "decision_date": "2025-10-14", "context_summary": "WEAT over past 60 days: cumulative return -8.4%, annualized vol 14.1%. Market regime: bull.", "question": "Asset: WEAT\nHistorical prices (past 60 trading days): start=22.60, end=20.70, cumulative_return=-8.4%, annualized_volatility=14.1%\nMacro context: {'fed_funds_rate': 4.1, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.53, 't10y3m_spread': 0.03, 'breakeven_10y': 2.3, 'hy_oas': 3.18, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.3, 'vix': 19.030000686645508}\nMarket regime: bull\n\nPredict whether the return of WEAT over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.036232, "explanation": "The actual 21-day forward return for WEAT starting 2025-10-14 was +3.62%, which classifies as 'positive'.", "metadata": {"future_return": 0.036232, "horizon_days": 21, "hist_return": -0.084071, "annualized_vol": 0.1413, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250617_0229", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-06-17", "context_summary": "VLUE over past 60 days: cumulative return +3.6%, annualized vol 21.4%. Market regime: sideways.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=104.58, end=108.36, cumulative_return=+3.6%, annualized_volatility=21.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.49, 't10y3m_spread': 0.03, 'breakeven_10y': 2.3, 'hy_oas': 3.1, 'ig_oas': 0.87, 'ted_spread': 0.09, 'mortgage_30y': 6.84, 'vix': 19.11000061035156}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-16] [\"My Top 5 AI Stocks to Buy Before the Second Half AI stocks drove market gains over the past two years, but earlier this year they led declines. Investors, worried about the potential impact of import tariffs on the economy, avoided growth stocks. Since, pressure has eased, opening up the door to more possible gains for AI players. 10 stocks we like better than Nvidia \\u203a The first half of the year was a turbulent one for stocks in general amid concern President Trump's planned import tariffs would hurt the economy. And this problem weighed most heavily on stocks that depend on growth and investment -- such as those in the field of artificial intelligence (AI). These particular players led indexes higher over the past two years on optimism about spending and the technology's potential, but they lost momentum in March and April. Since, though, the U.S. has made progress on trade talks, and this has lifted market sentiment. Meanwhile, tech companies' earnings reports show no signs of a slowdown in AI spending. This has spurred new gains in AI stocks, and if the U.S. trade situation resolves without excessively high tariffs, these players could continue to advance. With this in mind, here are my top five AI stocks to buy before the second half. Nvidia (NASDAQ: NVDA) soared more than 800% over the past two years as investors piled into this stock driving the AI revolution. The company dominates the AI chip market, and these chips are used for the most essential AI tasks. Nvidia hasn't had to wait to benefit from the AI market. The company already has delivered double- or triple-digit growth, with revenue attaining record levels. This momentum is likely to continue as Nvidia is well positioned to power AI across every stage of development, from training through the creation of humanoid robots. I'm confident about this thanks to Nvidia's commitment to innovation -- it's already set out a calendar of chip updates through 2028. This makes it very difficult for rivals to upset its position. Now is a great time to get in on this high-potential player as it's on sale, trading for 33 times forward earnings estimates -- down from more than 50 earlier in the year. Amazon (NASDAQ: AMZN), which sells some imported goods on its e-commerce site and also works with sellers that import goods, may benefit as trade tensions ease. The company also is winning from AI in two ways: Amazon uses AI tools to streamline operations, resulting in lower costs and greater efficiency. And Amazon, through its cloud unit Amazon Web Services (AWS), sells AI services to customers. AI services already have helped AWS reach a $117 billion annual revenue run rate. All of this could make Amazon a winner in the second half of this year and beyond. On top of this, the company already has demonstrated its earnings strength, growing revenue and profit over time. And its overhaul of its cost structure in recent years should drive even more gains moving forward. Amazon's valuation has falle\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": 0.045405, "explanation": "The actual 21-day forward return for VLUE starting 2025-06-17 was +4.54%, which classifies as 'positive'.", "metadata": {"future_return": 0.045405, "horizon_days": 21, "hist_return": 0.036135, "annualized_vol": 0.214157, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250522_0232", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-05-22", "context_summary": "EEM over past 60 days: cumulative return +3.4%, annualized vol 21.9%. Market regime: sideways.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=43.63, end=45.10, cumulative_return=+3.4%, annualized_volatility=21.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.58, 't10y3m_spread': 0.22, 'breakeven_10y': 2.35, 'hy_oas': 3.25, 'ig_oas': 0.91, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 20.8700008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-21] [\"China AI Rally Laggard Baidu Faces Low Bar for Earnings Boost (Bloomberg) -- The current earnings season has largely been a letdown for China\\u2019s big tech stocks, lowering the hurdle for Baidu Inc. to impress investors seeking a fresh angle on the artificial intelligence theme. Most Read from Bloomberg Can Frank Gehry\\u2019s \\u2018Grand LA\\u2019 Make Downtown Feel Like a Neighborhood? Chicago\\u2019s O\\u2019Hare Airport Seeks Up to $4.3 Billion of Muni Debt NJ Transit Makes Deal With Engineers, Ending Three-Day Strike China\\u2019s top search engine had made early advances in AI but fell behind as DeepSeek shocked the world with its low-cost model and Alibaba Group Holding Ltd. grabbed headlines as well. Baidu\\u2019s shares are up 6% in Hong Kong this year, while Alibaba has surged 48% and the Hang Seng Tech Index has climbed 19%. The street has drastically lowered its view on Baidu ahead of its results due later Wednesday, with the average 12-month analyst price target for the stock down 26% over the past year. It\\u2019s also now trading at a big discount relative to peers and historical levels. In a similar vein to Alphabet Inc.\\u2019s results beat last month, \\u201cif Baidu can build a strong case that search is not an ex-growth business and GenAI can boost its existing business including search, that will make the low expectation into the earnings play in favor of the stock price,\\u201d said Xiadong Bao, a fund manager at Edmond de Rothschild Asset Management. China tech stocks have lost some steam since March\\u2019s DeepSeek-fueled peak amid concerns over tensions with the US, the health of China\\u2019s economy and Beijing\\u2019s stimulus plans. Recent earnings from Alibaba and Tencent Holdings Ltd. underwhelmed investors looking for a new catalyst. Advertising still accounts for the bulk of Baidu\\u2019s revenue, and investors will be closely watching for clear signs of improvement in the macro-dependent business. UBS AG estimates its ad revenue declined 5.7%, a smaller drop than in the December quarter. The slow ad recovery has been weighing on Baidu\\u2019s shares the most, said Kai Wang, a Morningstar Inc. analyst. \\u201cOnce advertising comes back, Baidu\\u2019s valuation should come up pretty quickly, as that\\u2019s likely holding the AI business back,\\u201d he said. \\u201cIt\\u2019s one of the few players in China that can actually build out the data centers and AI infrastructure, while its AI offerings with the Ernie model have improved.\\u201d The stock\\u2019s underperformance has made it cheaper, currently trading at 8.6 times forward earnings estimates, well below its longer-term averages as well as the Hang Seng Tech Index\\u2019s 16 times. On the positive side, UBS, Morgan Stanley and others expect Baidu to post robust cloud sales growth of more than 20% for the three months ended March, extending the December period\\u2019s AI-driven momentum. Analysts project it will report a narrower decline in overall quarterly revenue and retur\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": 0.016047, "explanation": "The actual 21-day forward return for EEM starting 2025-05-22 was +1.60%, which classifies as 'positive'.", "metadata": {"future_return": 0.016047, "horizon_days": 21, "hist_return": 0.033796, "annualized_vol": 0.219301, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250314_0235", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-03-14", "context_summary": "DOT-USD over past 60 days: cumulative return -37.8%, annualized vol 78.8%. Market regime: bear.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=6.40, end=3.98, cumulative_return=-37.8%, annualized_volatility=78.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.33, 't10y3m_spread': -0.07, 'breakeven_10y': 2.29, 'hy_oas': 3.4, 'ig_oas': 0.97, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 24.65999984741211}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.035402, "explanation": "The actual 21-day forward return for DOT-USD starting 2025-03-14 was -3.54%, which classifies as 'negative'.", "metadata": {"future_return": -0.035402, "horizon_days": 21, "hist_return": -0.377645, "annualized_vol": 0.787839, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250218_0238", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-02-18", "context_summary": "AVAX-USD over past 60 days: cumulative return -37.1%, annualized vol 72.6%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=39.82, end=25.03, cumulative_return=-37.1%, annualized_volatility=72.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.21, 't10y3m_spread': 0.13, 'breakeven_10y': 2.43, 'hy_oas': 2.66, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.87, 'vix': 14.770000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.256024, "explanation": "The actual 21-day forward return for AVAX-USD starting 2025-02-18 was -25.60%, which classifies as 'negative'.", "metadata": {"future_return": -0.256024, "horizon_days": 21, "hist_return": -0.371408, "annualized_vol": 0.725813, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250516_0241", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IAU"], "decision_date": "2025-05-16", "context_summary": "IAU over past 60 days: cumulative return +10.0%, annualized vol 21.4%. Market regime: sideways.", "question": "Asset: IAU\nHistorical prices (past 60 trading days): start=55.39, end=60.93, cumulative_return=+10.0%, annualized_volatility=21.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.49, 't10y3m_spread': 0.07, 'breakeven_10y': 2.34, 'hy_oas': 3.2, 'ig_oas': 0.94, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 17.829999923706055}\nMarket regime: sideways\n\nPredict whether the return of IAU over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.075415, "explanation": "The actual 21-day forward return for IAU starting 2025-05-16 was +7.54%, which classifies as 'positive'.", "metadata": {"future_return": 0.075415, "horizon_days": 21, "hist_return": 0.100018, "annualized_vol": 0.214103, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250825_0243", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-08-25", "context_summary": "AVAX-USD over past 60 days: cumulative return +49.3%, annualized vol 65.5%. Market regime: bull.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=17.23, end=25.73, cumulative_return=+49.3%, annualized_volatility=65.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.58, 't10y3m_spread': -0.01, 'breakeven_10y': 2.41, 'hy_oas': 2.88, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.58, 'vix': 14.220000267028809}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.276535, "explanation": "The actual 21-day forward return for AVAX-USD starting 2025-08-25 was +27.65%, which classifies as 'positive'.", "metadata": {"future_return": 0.276535, "horizon_days": 21, "hist_return": 0.493291, "annualized_vol": 0.655493, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250328_0245", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-03-28", "context_summary": "ADA-USD over past 60 days: cumulative return -20.9%, annualized vol 94.7%. Market regime: sideways.", "question": "Asset: ADA-USD\nHistorical prices (past 60 trading days): start=0.93, end=0.74, cumulative_return=-20.9%, annualized_volatility=94.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.41, 't10y3m_spread': 0.05, 'breakeven_10y': 2.39, 'hy_oas': 3.27, 'ig_oas': 0.91, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 18.690000534057617}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ADA-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.110702, "explanation": "The actual 21-day forward return for ADA-USD starting 2025-03-28 was -11.07%, which classifies as 'negative'.", "metadata": {"future_return": -0.110702, "horizon_days": 21, "hist_return": -0.209306, "annualized_vol": 0.946877, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250710_0247", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-07-10", "context_summary": "SOL-USD over past 60 days: cumulative return -9.1%, annualized vol 52.8%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=173.03, end=157.28, cumulative_return=-9.1%, annualized_volatility=52.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.48, 't10y3m_spread': -0.08, 'breakeven_10y': 2.33, 'hy_oas': 2.94, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 15.9399995803833}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.050966, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-07-10 was +5.10%, which classifies as 'positive'.", "metadata": {"future_return": 0.050966, "horizon_days": 21, "hist_return": -0.090997, "annualized_vol": 0.527922, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251219_0249", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-12-19", "context_summary": "ETH-USD over past 60 days: cumulative return -29.0%, annualized vol 54.6%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=3980.76, end=2827.07, cumulative_return=-29.0%, annualized_volatility=54.6%\nMacro context: {'fed_funds_rate': 3.64, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.66, 't10y3m_spread': 0.5, 'breakeven_10y': 2.24, 'hy_oas': 2.95, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.21, 'vix': 16.8700008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": -0.003671, "explanation": "The actual 21-day forward return for ETH-USD starting 2025-12-19 was -0.37%, which classifies as 'flat'.", "metadata": {"future_return": -0.003671, "horizon_days": 21, "hist_return": -0.289817, "annualized_vol": 0.545606, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250506_0252", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2025-05-06", "context_summary": "VEA over past 60 days: cumulative return +7.5%, annualized vol 18.3%. Market regime: sideways.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=48.44, end=52.06, cumulative_return=+7.5%, annualized_volatility=18.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.53, 't10y3m_spread': 0.03, 'breakeven_10y': 2.28, 'hy_oas': 3.6, 'ig_oas': 1.05, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 23.63999938964844}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q PFE 2025-05-05] pfe-20250330 0000078003 12/31 2025 Q1 false P1Y P3Y P5Y P7Y xbrli:shares iso4217:USD iso4217:USD xbrli:shares pfe:segment xbrli:pure pfe:company pfe:patent pfe:complaint pfe:treatment_course 0000078003 2025-01-01 2025-03-30 0000078003 us-gaap:CommonStockMember 2025-01-01 2025-03-30 0000078003 pfe:NotesDue20271.000Member 2025-01-01 2025-03-30 0000078003 2025-04-30 0000078003 us-gaap:ProductMember 2025-01-01 2025-03-30 0000078003 us-gaap:ProductMember 2024-01-01 2024-03-31 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pfe:BiopharmaSegmentMember 2025-03-30 0000078003 pfe:ManufacturingOptimizationProgramMember pfe:BiopharmaSegmentMember 2025-03-30 0000078003 us-gaap:OtherNonoperatingIncomeExpenseMember 2025-01-01 2025-03-30 0000078003 us-gaap:OtherNonoperatingIncomeExpenseMember 2024-01-01 2024-03-31 0000078003 us-gaap:CostOfSalesMember 2025-01-01 2025-03-30 0000078003 us-gaap:CostOfSalesMember 2024-01-01 2024-03-31 0000078003 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2025-01-01 2025-03-30 0000078003 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2024-01-01 2024-03-31 0000078003 us-gaap:ResearchAnd [...TRUNCATED...] f Shares Purchased as Part of Publicly Announced Plan Approximate Value of Shares That May Yet Be Purchased Under the Plan (b) January 1 through January 26, 2025 25,387  $ 26.65  —  $ 3,292,882,444  January 27 through February 23, 2025 1,107,921  $ 26.29  —  $ 3,292,882,444  February 24 through March 30, 2025 8,191,799  $ 26.23  —  $ 3,292,882,444  Total 9,325,107  $ 26.24  —  50 (a) Represents (i) 9,321,821 shares of common stock surrendered to the Company to satisfy tax withholding obligations in connection with the vesting of awards under our long-term incentive programs and (ii) the open market purchase by the trustee of 3,286 shares of common stock in connection with the reinvestment of dividends paid on common stock held in trust for employees who deferred receipt of performance share awards. (b) See Note 12 in our 2024 Form 10-K. ITEM 5. OTHER INFORMATION During the three months ended March 30, 2025, none of our directors or officers adopted or terminated a “Rule 10b5-1 trading arrangement” or “non-Rule 10b5-1 trading arrangement,” as each term is defined in Item 408 of Regulation S-K. ITEM 6. EXHIBITS   Exhibit 31.1 Certification by the Chief Executive Officer Pursuant to Section 302 of the Sarbanes-Oxley Act of 2002.   Exhibit 31.2 Certification by the Chief Financial Officer Pursuant to Section 302 of the Sarbanes-Oxley Act of 2002.   Exhibit 32.1 Certification by the Chief Executive Officer Pursuant to 18 U.S.C. Section 1350, as Adopted Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002.   Exhibit 32.2 Certification by the Chief Financial Officer Pursuant to 18 U.S.C. Section 1350, as Adopted Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002.   Exhibit 101:     EX-101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document.   EX-101.SCH EX-101.CAL EX-101.LAB EX-101.PRE EX-101.DEF   Inline XBRL Taxonomy Extension Schema Inline XBRL Taxonomy Extension Calculation Linkbase Inline XBRL Taxonomy Extension Label Linkbase Inline XBRL Taxonomy Extension Presentation Linkbase Inline XBRL Taxonomy Extension Definition Document Exhibit 104 Cover Page Interactive Data File––the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   Pfizer Inc.   (Registrant)         Dated: May 5, 2025 /s/ Jennifer B. Damico   Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) 51\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": 0.044693, "explanation": "The actual 21-day forward return for VEA starting 2025-05-06 was +4.47%, which classifies as 'positive'.", "metadata": {"future_return": 0.044693, "horizon_days": 21, "hist_return": 0.074653, "annualized_vol": 0.18339, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250107_0254", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2025-01-07", "context_summary": "QUAL over past 60 days: cumulative return +0.2%, annualized vol 11.9%. Market regime: sideways.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=177.56, end=177.84, cumulative_return=+0.2%, annualized_volatility=11.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.34, 't10y3m_spread': 0.27, 'breakeven_10y': 2.34, 'hy_oas': 2.76, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.91, 'vix': 16.040000915527344}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 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us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of QUAL over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.023903, "explanation": "The actual 21-day forward return for QUAL starting 2025-01-07 was +2.39%, which classifies as 'positive'.", "metadata": {"future_return": 0.023903, "horizon_days": 21, "hist_return": 0.001542, "annualized_vol": 0.118698, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250918_0257", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-09-18", "context_summary": "XLU over past 60 days: cumulative return +3.4%, annualized vol 12.5%. Market regime: bull.", "question": "Asset: XLU\nHistorical prices (past 60 trading days): start=39.94, end=41.29, cumulative_return=+3.4%, annualized_volatility=12.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.54, 't10y3m_spread': 0.04, 'breakeven_10y': 2.38, 'hy_oas': 2.79, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.35, 'vix': 15.720000267028809}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": 0.068154, "explanation": "The actual 21-day forward return for XLU starting 2025-09-18 was +6.82%, which classifies as 'positive'.", "metadata": {"future_return": 0.068154, "horizon_days": 21, "hist_return": 0.033828, "annualized_vol": 0.124619, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250306_0260", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-03-06", "context_summary": "ETH-USD over past 60 days: cumulative return -38.3%, annualized vol 68.5%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=3634.10, end=2241.98, cumulative_return=-38.3%, annualized_volatility=68.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.29, 't10y3m_spread': -0.07, 'breakeven_10y': 2.34, 'hy_oas': 2.88, 'ig_oas': 0.87, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 21.93000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.090861, "explanation": "The actual 21-day forward return for ETH-USD starting 2025-03-06 was -9.09%, which classifies as 'negative'.", "metadata": {"future_return": -0.090861, "horizon_days": 21, "hist_return": -0.383073, "annualized_vol": 0.684566, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250401_0262", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2025-04-01", "context_summary": "ACWI over past 60 days: cumulative return -0.8%, annualized vol 14.8%. Market regime: bear.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=115.36, end=114.49, cumulative_return=-0.8%, annualized_volatility=14.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.34, 't10y3m_spread': -0.09, 'breakeven_10y': 2.38, 'hy_oas': 3.55, 'ig_oas': 0.97, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 22.280000686645508}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-03-31] LTRX Transforms Edge AI Computing by Unveiling Open-Q 8550CS SOM Lantronix, Inc. LTRX introduced its latest offering, the Open-Q 8550CS System-on-Module (SOM). Powered by Qualcomm\u2019s Dragonwing QCS8550 processor, this production-ready module is designed to bring low-power, high-performance AI and Machine Learning capabilities to the Edge computing. This innovation aims to accelerate the development of AI-driven applications across a broad spectrum of industries like smart warehousing, manufacturing, transportation, logistics and retail. Lantronix\u2019s Open-Q 8550CS SOM is built specifically to meet the extreme Edge AI demands, making it an ideal solution for advanced video applications, robotics, drones, industrial automation and smart warehousing. This Lantronix platform exhibits characteristics similar to all its embedded compute technology and delivers a full solution with hardware, software, Device Management, and services, allowing customers to accelerate time to market. Lantronix Open-Q solutions are TAA and NDAA-compliant, ensuring a minimum of 10 years of longevity with strict quality control. With more than 20 years of expertise, LTRX has delivered more than 1,200 hardware and software projects, fostering reliability and innovation. The state-of-the-art solution is a high-performance, power-efficient computing platform designed with best-in-class AI capabilities, security and connectivity. It has a powerful 4nm Octa-core CPU (up to 3.2 GHz), Adreno A740 GPU, dual AI engines, and strong security. Supports Wi-Fi 7 (5.8Gbps), up to 8GB LPDDR5 RAM, 128GB UFS storage, and runs Android 13 & Linux Yocto Kirkstone. It also features a Computer Vision Engine, multiple camera/display ports, and Qualcomm Sensing Hub 3.0 for top-tier AI, multimedia, and connectivity performance. This platform boosts video conferencing, AGV pathing, smart camera quality and Edge AI scalability with octa-core computing and 48 AI TOPS tensor performance. The platform handles 3D rendering and computer vision with Adreno 740 GPU, ray tracing and 4K/8K video support while enabling Edge AI with 2.5G and 10G Ethernet. To support developers in evaluating and integrating the Open-Q 8550CS SOM, Lantronix offers a comprehensive Development Kit. This kit provides a fully-featured carrier board exposing all I/O interfaces, support for multiple camera configurations (C-PHY and D-PHY MIPI CSI, GMSL), AI accelerators for always-on applications (voice, contextual data, sensors) and comprehensive connectivity options, including Gigabit Ethernet, GNSS and DisplayPort. This kit is designed to reduce development time, allowing developers to quickly test, validate and deploy AI-powered solutions. Apart from hardware and software, Lantronix Engineering Services provides turn-key product development support for Open-Q platforms and kits. With expertise in more than 1,500 successful products, the team specializes in camera tuning, voice control, machine learning, RF and mechanical design and powe\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": 0.005308, "explanation": "The actual 21-day forward return for ACWI starting 2025-04-01 was +0.53%, which classifies as 'flat'.", "metadata": {"future_return": 0.005308, "horizon_days": 21, "hist_return": -0.007504, "annualized_vol": 0.148473, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250407_0264", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2025-04-07", "context_summary": "CSHI over past 60 days: cumulative return -0.8%, annualized vol 4.2%. Market regime: bear.", "question": "Asset: CSHI\nHistorical prices (past 60 trading days): start=46.81, end=46.45, cumulative_return=-0.8%, annualized_volatility=4.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.33, 't10y3m_spread': -0.27, 'breakeven_10y': 2.18, 'hy_oas': 4.45, 'ig_oas': 1.14, 'ted_spread': 0.09, 'mortgage_30y': 6.64, 'vix': 43.34999847412109}\nMarket regime: bear\n\nPredict whether the return of CSHI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.016505, "explanation": "The actual 21-day forward return for CSHI starting 2025-04-07 was +1.65%, which classifies as 'positive'.", "metadata": {"future_return": 0.016505, "horizon_days": 21, "hist_return": -0.007687, "annualized_vol": 0.042453, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250514_0267", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-05-14", "context_summary": "XLY over past 60 days: cumulative return -4.6%, annualized vol 29.9%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=111.99, end=106.80, cumulative_return=-4.6%, annualized_volatility=29.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.47, 't10y3m_spread': 0.08, 'breakeven_10y': 2.32, 'hy_oas': 3.09, 'ig_oas': 0.94, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 18.21999931335449}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-13] Alnylam Pharmaceuticals (NasdaqGS:ALNY) To Present Pivotal TTR Franchise Data At Heart Failure Congress In May 2025, Alnylam Pharmaceuticals announced its plan to present new data from its transthyretin amyloidosis (TTR) franchise at the Heart Failure 2025 Congress, alongside securing broader international approvals for its therapeutic vutrisiran (AMVUTTRA). During the same month, the overall market rallied due to positive developments in U.S.-China trade relations, with major indexes experiencing substantial gains. Alnylam's 5.63% rise over the period likely reflects investor optimism towards its recent product announcements and earnings improvements, aligning with broader market upward trends driven by eased international trade tensions. Alnylam Pharmaceuticals has 1 warning sign we think you should know about. Find companies with promising cash flow potential yet trading below their fair value. The recent announcement by Alnylam Pharmaceuticals about presenting new data at Heart Failure 2025 Congress and gaining wider international approvals for vutrisiran could significantly bolster investor confidence in the company's growth trajectory. Given the expanded indication for AMVUTTRA in ATTR cardiomyopathy, the potential for increased revenue is substantial. This aligns with the company's aim to achieve sustainable profitability, despite current earnings being at US$269.7 million. Additionally, analysts forecast future earnings to improve, with expected revenue reaching several billion dollars, indicating growth prospects fueled by new product launches and expanding market share. Over the past three years, Alnylam's total shareholder return, including share price and dividends, was 101.13%. This robust performance compares favorably against the market's 8% return over the past year. Additionally, Alnylam outperformed the US Biotechs industry, which experienced a 15.3% decline in the same time frame. These figures underscore Alnylam's relative strength and investor optimism toward its pipeline and strategic initiatives. The enthusiasm generated by Alnylam's recent developments is also reflected in the stock's price movement. The shares currently trade at a discount to the consensus analyst price target of US$320.56, suggesting potential upside if future earnings and revenue growth materialize as expected. However, despite the positive sentiment, the stock's price-to-sales ratio remains above both industry and peer averages, indicating a premium valuation. As such, the price movement in conjunction with analyst forecasts highlights both potential growth opportunities and the inherent risks associated with Alnylam's current market positioning. Navigate through the intricacies of Alnylam Pharmaceuticals with our comprehensive balance sheet health report here. This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to \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": -0.020221, "explanation": "The actual 21-day forward return for XLY starting 2025-05-14 was -2.02%, which classifies as 'negative'.", "metadata": {"future_return": -0.020221, "horizon_days": 21, "hist_return": -0.046373, "annualized_vol": 0.299458, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250527_0269", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-05-27", "context_summary": "SOL-USD over past 60 days: cumulative return +35.1%, annualized vol 67.8%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=129.42, end=174.91, cumulative_return=+35.1%, annualized_volatility=67.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.51, 't10y3m_spread': 0.15, 'breakeven_10y': 2.33, 'hy_oas': 3.4, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.86, 'vix': 22.290000915527344}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.164383, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-05-27 was -16.44%, which classifies as 'negative'.", "metadata": {"future_return": -0.164383, "horizon_days": 21, "hist_return": 0.351442, "annualized_vol": 0.677911, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251112_0272", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-11-12", "context_summary": "DOT-USD over past 60 days: cumulative return -21.4%, annualized vol 85.5%. Market regime: bull.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=4.50, end=3.54, cumulative_return=-21.4%, annualized_volatility=85.5%\nMacro context: {'fed_funds_rate': 3.87, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.55, 't10y3m_spread': 0.18, 'breakeven_10y': 2.29, 'hy_oas': 3.02, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.22, 'vix': 17.280000686645508}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for DOT-USD starting 2025-11-12 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": -0.213537, "annualized_vol": 0.855248, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251028_0275", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2025-10-28", "context_summary": "XLRE over past 60 days: cumulative return +3.4%, annualized vol 11.6%. Market regime: bull.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=40.60, end=42.00, cumulative_return=+3.4%, annualized_volatility=11.6%\nMacro context: {'fed_funds_rate': 4.12, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.53, 't10y3m_spread': 0.12, 'breakeven_10y': 2.28, 'hy_oas': 2.8, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.19, 'vix': 15.789999961853027}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q PG 2025-10-24] pg-20250930 0000080424 6/30 2026 Q1 false http://fasb.org/us-gaap/2025#OtherAssetsNoncurrent http://fasb.org/us-gaap/2025#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2025#OtherAssetsNoncurrent http://fasb.org/us-gaap/2025#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2025#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2025#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2025#AccruedLiabilitiesCurrent 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us-gaap:OperatingSegmentsMember us-gaap:ProductConcentrationRiskMember pg:HomeCareMember us-gaap:SalesRevenueNetMember pg:FabricHomeCareSegmentMember 2024-07-01 2024-09-30 0000080424 us-gaap:OperatingSegmentsMember us-gaap:ProductConcentrationRiskMember pg:HairCareMember us-gaap:SalesRevenueNetMember pg:BeautySegmentMember 2025-07-01 2025-09-30 0000080424 us-gaap:OperatingSegmentsMember us-gaap:ProductConcentrationRiskMember pg:HairCareMember us-gaap:SalesRevenueNetMember pg:BeautySegmentMember 2024-07-01 2024-09-30 0000080424 us-gaap:OperatingSegmentsMember us-gaap:ProductConcentrationRiskMember pg:Baby [...TRUNCATED...] ectors on December 13, 2022, pursuant to authority granted by shareholders at the annual meeting on October 13, 2009) (Incorporated by reference to Exhibit (3-2) of the Company’s Current Report on Form 8-K filed December 13, 2022) 4.1 Indenture, dated as of September 3, 2009, between the Company and Deutsche Bank Trust Company Americas, as Trustee (Incorporated by reference to Exhibit (4-1) of the Company's Annual Report on Form 10-K for the year ended June 30, 2015) 10.1 The Procter & Gamble Company 2025 Stock and Incentive Compensation Plan *+ 10.2 Short-Term Achievement Reward Program *+ 10.3 Performance Stock Program Summary *+ 10.4 Long-Term Incentive Program Summary *+ 10.5 Regulations of the Compensation and Leadership Development Committee for The Procter & Gamble 2025 Stock and incentive Compensation Plan, The Procter & Gamble 2019 Stock and Incentive Compensation Plan and The Procter & Gamble 2014 Stock and Incentive Compensation Plan. *+ 10.6 Retirement Plan Restoration Program Summary *+ 10.7 Form of STAR Stock Option Award Agreement *+ 10.8 Form of Director Annual RSU Award Agreement *+ 10.9 Form of Director Annual RSU Award Agreement (Deferred) *+ 10.10 Form of Director RSU Award Agreement (Quarterly Fees) *+ 10.11 Form of PSU Award Agreement *+ 10.12 Form of Deferred PSU Award Agreement *+ 10.13 Form of LTIP RSU Award Agreement *+ 10.14 Form of LTIP Stock Option Award Agreement *+ 10.15 Form of Special RSU Award Agreement *+ 10.16 Form of Retirement Restoration Plan RSU Award Agreement *+ 31.1 Rule 13a-14(a)/15d-14(a) Certification – Chief Executive Officer + 31.2 Rule 13a-14(a)/15d-14(a) Certification – Chief Financial Officer + 32.1 Section 1350 Certifications – Chief Executive Officer + 32.2 Section 1350 Certifications – Chief Financial Officer + 101.SCH (1) Inline XBRL Taxonomy Extension Schema Document 101.CAL (1) Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF (1) Inline XBRL Taxonomy Definition Linkbase Document 101.LAB (1) Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE (1) Inline XBRL Taxonomy Extension Presentation Linkbase Document 104  Cover Page Interactive Data File (formatted in Inline XBRL and contained in Exhibit 101) The Procter & Gamble Company 27 * Compensatory plan or arrangement + Filed herewith (1) Pursuant to Rule 406T of Regulation S-T, this information is furnished and not filed for purposes of Sections 11 or 12 of the Securities Act of 1933 and Section 18 of the Securities Exchange Act of 1934, and otherwise is not subject to liability under these sections. Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this Report to be signed on its behalf by the undersigned thereunto duly authorized. THE PROCTER & GAMBLE COMPANY October 24, 2025 /s/ MATTHEW W. JANZARUK Date (Matthew W. Janzaruk) Senior Vice President - Chief Accounting Officer (Principal Accounting Officer)\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": -0.007657, "explanation": "The actual 21-day forward return for XLRE starting 2025-10-28 was -0.77%, which classifies as 'flat'.", "metadata": {"future_return": -0.007657, "horizon_days": 21, "hist_return": 0.034251, "annualized_vol": 0.11575, "has_text": true, "text_chars": 9044}} +{"id": "T1_all_20250414_0278", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["BIL"], "decision_date": "2025-04-14", "context_summary": "BIL over past 60 days: cumulative return +0.7%, annualized vol 0.2%. Market regime: bear.", "question": "Asset: BIL\nHistorical prices (past 60 trading days): start=87.42, end=88.01, cumulative_return=+0.7%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.52, 't10y3m_spread': 0.14, 'breakeven_10y': 2.2, 'hy_oas': 4.26, 'ig_oas': 1.18, 'ted_spread': 0.09, 'mortgage_30y': 6.62, 'vix': 37.560001373291016}\nMarket regime: bear\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": 0.002317, "explanation": "The actual 21-day forward return for BIL starting 2025-04-14 was +0.23%, which classifies as 'flat'.", "metadata": {"future_return": 0.002317, "horizon_days": 21, "hist_return": 0.006793, "annualized_vol": 0.002007, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250219_0280", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2025-02-19", "context_summary": "ACWI over past 60 days: cumulative return +4.7%, annualized vol 11.9%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=116.59, end=122.11, cumulative_return=+4.7%, annualized_volatility=11.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.26, 't10y3m_spread': 0.21, 'breakeven_10y': 2.45, 'hy_oas': 2.66, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.87, 'vix': 15.350000381469728}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K CAT 2025-02-14] cat-20241231 0000018230 FALSE 2024 FY 50 33.33 33.33 33.33 33.33 33.33 33.33 http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligationsCurrent http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligationsCurrent http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligations http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligations http://fasb.org/us-gaap/2024#AccountsPayableCurrent http://fasb.org/us-gaap/2024#AccountsPayableCurrent 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us-gaap:EmployeeStockOptionMember 2024-01-01 2024-12-31 0000018230 us-gaap:EmployeeStockOptionMember 2023-01-01 2023-12-31 0000018230 us-gaap:EmployeeStockOptionMember 2022-01-01 2022-12-31 0000018230 us-gaap:RestrictedStockUnitsRSUMember 2023-12-31 0000018230 us-gaap:PerformanceSharesMember 2023-12-31 0000018230 us-gaap:RestrictedStockUnitsRSUMember 2024-12-31 0000018230 us-gaap:PerformanceSharesMember 2024-12-31 0000018230 cat:StockOptionsandShareAppreciationRightsSARsMember 2024-01-01 2024-12-31 0000018230 cat:StockOptionsandShareAppreciationRightsSARsMember 2023-01-01 2023-12-31 0000018230 cat:StockOptionsandShareApprecia [...TRUNCATED...] ulation Linkbase Document 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive File (embedded within the Inline XBRL document and included in Exhibit 101) _________________________________________ *Management contracts and compensatory plans and arrangements required to be filed as exhibits pursuant to Item 15(b) of this report. The agreements and other documents filed as exhibits to this report are not intended to provide factual information or other disclosure other than with respect to the terms of the agreements or other documents themselves, and you should not rely on them for that purpose. In particular, any representations and warranties made by us in these agreements or other documents were made solely within the specific context of the relevant agreement or document and may not describe the actual state of affairs as of the date they were made or at any other time. Item 16.  Form 10-K Summary. None. 129 Table of Contents Form 10-K   SIGNATURES   Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.     CATERPILLAR INC.   Registrant     February 14, 2025 By: /s/ Derek Owens     Derek Owens Chief Legal Officer and General Counsel   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities and on the dates indicated.       Chairman of the Board  and Chief Executive Officer February 14, 2025 /s/ D. James Umpleby III   D. James Umpleby III       February 14, 2025 /s/ Andrew R.J. Bonfield Chief Financial Officer Andrew R.J. Bonfield     February 14, 2025 /s/ William E. Schaupp Vice President and Chief Accounting Officer   William E. Schaupp             February 14, 2025 /s/ Daniel M. Dickinson Director   Daniel M. Dickinson   February 14, 2025 /s/ James C. Fish, Jr. Director James C. Fish, Jr.       130 Table of Contents February 14, 2025 /s/ Gerald Johnson Director   Gerald Johnson   February 14, 2025 /s/ Nazzic S. Keene Director Nazzic S. Keene       February 14, 2025 /s/ David W. MacLennan Director   David W. MacLennan   February 14, 2025 /s/ Judith F. Marks Director Judith F. Marks February 14, 2025 /s/ Debra L. Reed-Klages Presiding Director Debra L. Reed-Klages       February 14, 2025 /s/ Susan C. Schwab Director   Susan C. Schwab             February 14, 2025 /s/ Rayford Wilkins, Jr. Director   Rayford Wilkins, Jr.   131\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": -0.046378, "explanation": "The actual 21-day forward return for ACWI starting 2025-02-19 was -4.64%, which classifies as 'negative'.", "metadata": {"future_return": -0.046378, "horizon_days": 21, "hist_return": 0.047352, "annualized_vol": 0.118881, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250115_0283", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-01-15", "context_summary": "XRP-USD over past 60 days: cumulative return +118.0%, annualized vol 114.7%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=1.12, end=2.44, cumulative_return=+118.0%, annualized_volatility=114.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.41, 't10y3m_spread': 0.42, 'breakeven_10y': 2.44, 'hy_oas': 2.8, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.93, 'vix': 18.709999084472656}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.023527, "explanation": "The actual 21-day forward return for XRP-USD starting 2025-01-15 was -2.35%, which classifies as 'negative'.", "metadata": {"future_return": -0.023527, "horizon_days": 21, "hist_return": 1.180088, "annualized_vol": 1.147076, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250827_0286", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["PALL"], "decision_date": "2025-08-27", "context_summary": "PALL over past 60 days: cumulative return +9.7%, annualized vol 36.1%. Market regime: bull.", "question": "Asset: PALL\nHistorical prices (past 60 trading days): start=91.66, end=100.58, cumulative_return=+9.7%, annualized_volatility=36.1%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.65, 't10y3m_spread': -0.02, 'breakeven_10y': 2.42, 'hy_oas': 2.78, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.58, 'vix': 14.619999885559082}\nMarket regime: bull\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": 0.152721, "explanation": "The actual 21-day forward return for PALL starting 2025-08-27 was +15.27%, which classifies as 'positive'.", "metadata": {"future_return": 0.152721, "horizon_days": 21, "hist_return": 0.097316, "annualized_vol": 0.361037, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250304_0288", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-03-04", "context_summary": "LINK-USD over past 60 days: cumulative return -38.2%, annualized vol 88.0%. Market regime: sideways.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=23.40, end=14.45, cumulative_return=-38.2%, annualized_volatility=88.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.2, 't10y3m_spread': -0.19, 'breakeven_10y': 2.36, 'hy_oas': 2.94, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 22.780000686645508}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.038969, "explanation": "The actual 21-day forward return for LINK-USD starting 2025-03-04 was +3.90%, which classifies as 'positive'.", "metadata": {"future_return": 0.038969, "horizon_days": 21, "hist_return": -0.382427, "annualized_vol": 0.880245, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251126_0290", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2025-11-26", "context_summary": "^VIX over past 60 days: cumulative return +13.5%, annualized vol 123.8%. Market regime: sideways.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=16.35, end=18.56, cumulative_return=+13.5%, annualized_volatility=123.8%\nMacro context: {'fed_funds_rate': 3.88, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.58, 't10y3m_spread': 0.11, 'breakeven_10y': 2.22, 'hy_oas': 3.1, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.26, 'vix': 18.559999465942383}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2025-11-19] nvda-20251026 0001045810 1/25 2026 Q3 FALSE 478 469 278 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:investment nvda:segment 0001045810 2025-01-27 2025-10-26 0001045810 2025-11-14 0001045810 2025-07-28 2025-10-26 0001045810 2024-07-29 2024-10-27 0001045810 2024-01-29 2024-10-27 0001045810 2025-10-26 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 2025-07-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-27 0001045810 us-gaap:RetainedEarningsMember 2025-07-27 0001045810 2025-07-27 0001045810 us-gaap:RetainedEarningsMember 2025-07-28 2025-10-26 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-28 2025-10-26 0001045810 us-gaap:CommonStockMember 2025-07-28 2025-10-26 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-28 2025-10-26 0001045810 us-gaap:CommonStockMember 2025-10-26 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-10-26 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-26 0001045810 us-gaap:RetainedEarningsMember 2025-10-26 0001045810 us-gaap:CommonStockMember 2024-07-28 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-07-28 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-28 0001045810 us-gaap:RetainedEarningsMember 2024-07-28 0001045810 2024-07-28 0001045810 us-gaap:RetainedEarningsMember 2024-07-29 2024-10-27 0001045810 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us-gaap:ForeignGovernmentDebtMember 2025-10-26 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2025-10-26 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2025-10-26 0001045810 2025-01-27 2025-04-27 0001045810 us-gaap:CorporateDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:USTreasurySecuritiesMember 2025-01-26 0001045810 us-gaap:MoneyMarketFundsMember 2025-01-26 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:ForeignGovernmentDebtMember 2025-01-26 0001045810 us-gaap:CertificatesOfDepositMember 2025-01-26 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2025-01-26 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2025-01-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-10-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-01-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-10-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:CustomerOneMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerTwoMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerThreeMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerFourMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:Cust [...TRUNCATED...] President, Operations Adoption 9/9/2025 309,840 12/31/2026 Donald Robertson Vice President and Chief Accounting Officer Adoption 9/18/2025 138,042 * 12/31/2026 Ajay Puri Executive Vice President, Worldwide Field Operations Adoption 9/19/2025 1,000,000 6/24/2026 * Includes 38,042 shares from future vests of equity awards, and the actual number of shares to be sold will be net of shares withheld by the Company for taxes. 42 Item 6. Exhibits Exhibit No.  Exhibit Description 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 43 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 19, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 44\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": -0.208842, "explanation": "The actual 21-day forward return for ^VIX starting 2025-11-26 was -20.88%, which classifies as 'negative'.", "metadata": {"future_return": -0.208842, "horizon_days": 21, "hist_return": 0.135168, "annualized_vol": 1.238117, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20250818_0293", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-08-18", "context_summary": "BNB-USD over past 60 days: cumulative return +10.8%, annualized vol 28.6%. Market regime: bull.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=644.68, end=714.32, cumulative_return=+10.8%, annualized_volatility=28.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.58, 't10y3m_spread': 0.03, 'breakeven_10y': 2.38, 'hy_oas': 2.88, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.58, 'vix': 15.09000015258789}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for BNB-USD starting 2025-08-18 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.108024, "annualized_vol": 0.285969, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250320_0295", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2025-03-20", "context_summary": "VNQ over past 60 days: cumulative return +5.0%, annualized vol 17.5%. Market regime: sideways.", "question": "Asset: VNQ\nHistorical prices (past 60 trading days): start=82.83, end=86.95, cumulative_return=+5.0%, annualized_volatility=17.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.26, 't10y3m_spread': -0.08, 'breakeven_10y': 2.31, 'hy_oas': 3.19, 'ig_oas': 0.91, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 19.89999961853028}\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": -0.038869, "explanation": "The actual 21-day forward return for VNQ starting 2025-03-20 was -3.89%, which classifies as 'negative'.", "metadata": {"future_return": -0.038869, "horizon_days": 21, "hist_return": 0.049786, "annualized_vol": 0.17463, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250616_0297", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2025-06-16", "context_summary": "CSHI over past 60 days: cumulative return +1.3%, annualized vol 1.4%. Market regime: sideways.", "question": "Asset: CSHI\nHistorical prices (past 60 trading days): start=47.00, end=47.62, cumulative_return=+1.3%, annualized_volatility=1.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.45, 't10y3m_spread': -0.04, 'breakeven_10y': 2.28, 'hy_oas': 3.18, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 6.84, 'vix': 20.81999969482422}\nMarket regime: sideways\n\nPredict whether the return of CSHI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002914, "explanation": "The actual 21-day forward return for CSHI starting 2025-06-16 was +0.29%, which classifies as 'flat'.", "metadata": {"future_return": 0.002914, "horizon_days": 21, "hist_return": 0.013212, "annualized_vol": 0.013761, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250610_0300", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2025-06-10", "context_summary": "IYR over past 60 days: cumulative return +0.8%, annualized vol 20.8%. Market regime: sideways.", "question": "Asset: IYR\nHistorical prices (past 60 trading days): start=92.09, end=92.86, cumulative_return=+0.8%, annualized_volatility=20.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.48, 't10y3m_spread': 0.05, 'breakeven_10y': 2.31, 'hy_oas': 3.12, 'ig_oas': 0.87, 'ted_spread': 0.09, 'mortgage_30y': 6.85, 'vix': 17.15999984741211}\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": 0.000832, "explanation": "The actual 21-day forward return for IYR starting 2025-06-10 was +0.08%, which classifies as 'flat'.", "metadata": {"future_return": 0.000832, "horizon_days": 21, "hist_return": 0.00831, "annualized_vol": 0.208121, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250704_0303", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2025-07-04", "context_summary": "IYR over past 60 days: cumulative return +14.0%, annualized vol 17.3%. Market regime: sideways.", "question": "Asset: IYR\nHistorical prices (past 60 trading days): start=82.52, end=94.07, cumulative_return=+14.0%, annualized_volatility=17.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.47, 't10y3m_spread': -0.07, 'breakeven_10y': 2.33, 'hy_oas': 2.8, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 16.3799991607666}\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": 0.007262, "explanation": "The actual 21-day forward return for IYR starting 2025-07-04 was +0.73%, which classifies as 'flat'.", "metadata": {"future_return": 0.007262, "horizon_days": 21, "hist_return": 0.139932, "annualized_vol": 0.172587, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251225_0306", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNO"], "decision_date": "2025-12-25", "context_summary": "BNO over past 60 days: cumulative return -1.9%, annualized vol 24.0%. Market regime: sideways.", "question": "Asset: BNO\nHistorical prices (past 60 trading days): start=29.28, end=28.71, cumulative_return=-1.9%, annualized_volatility=24.0%\nMacro context: {'fed_funds_rate': 3.64, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.68, 't10y3m_spread': 0.46, 'breakeven_10y': 2.24, 'hy_oas': 2.84, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.18, 'vix': 13.470000267028809}\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": "flat", "answer_numeric": 0.008188, "explanation": "The actual 21-day forward return for BNO starting 2025-12-25 was +0.82%, which classifies as 'flat'.", "metadata": {"future_return": 0.008188, "horizon_days": 21, "hist_return": -0.019467, "annualized_vol": 0.239622, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250701_0308", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-07-01", "context_summary": "SOL-USD over past 60 days: cumulative return +4.5%, annualized vol 56.8%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=148.05, end=154.74, cumulative_return=+4.5%, annualized_volatility=56.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.52, 't10y3m_spread': -0.17, 'breakeven_10y': 2.29, 'hy_oas': 2.96, 'ig_oas': 0.86, 'ted_spread': 0.09, 'mortgage_30y': 6.77, 'vix': 16.729999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.400022, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-07-01 was +40.00%, which classifies as 'positive'.", "metadata": {"future_return": 0.400022, "horizon_days": 21, "hist_return": 0.045155, "annualized_vol": 0.567587, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250214_0311", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-02-14", "context_summary": "VLUE over past 60 days: cumulative return +1.5%, annualized vol 12.9%. Market regime: sideways.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=107.09, end=108.73, cumulative_return=+1.5%, annualized_volatility=12.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.21, 't10y3m_spread': 0.18, 'breakeven_10y': 2.44, 'hy_oas': 2.66, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.87, 'vix': 15.100000381469728}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K JNJ 2025-02-13] jnj-20241229 0000200406 2024 FY false Johnson & Johnson http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2024#AccountsPayableCurrent 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reference to Exhibit 19 of the Registrant’s Form 10-K Annual Report for the fiscal year ended December 31, 2023. 21 Subsidiaries — Filed with this document. 23 Consent of Independent Registered Public Accounting Firm — Filed with this document. 31.1 Certification of Chief Executive Officer Pursuant to Section 302 of the Sarbanes-Oxley Act — Filed with this document. 31.2 Certification of Chief Financial Officer Pursuant to Section 302 of the Sarbanes-Oxley Act — Filed with this document. 32.1 Certification of Chief Executive Officer Pursuant to Section 906 of the Sarbanes-Oxley Act — Furnished with this document. 32.2 Certification of Chief Financial Officer Pursuant to Section 906 of the Sarbanes-Oxley Act — Furnished with this document. 97 Johnson & Johnson Clawback Policy (effective as of August 8, 2023) — Incorporated herein by reference to Exhibit 97 of the Registrant’s Form 10-K Annual Report for the fiscal year ended December 31, 2023. Exhibit 101: EX-101.INS Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document EX-101.SCH Inline XBRL Taxonomy Extension Schema EX-101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase EX-101.LAB Inline XBRL Taxonomy Extension Label Linkbase EX-101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase EX-101.DEF Inline XBRL Taxonomy Extension Definition Document Exhibit 104: Cover Page Interactive Data File––the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Management contract or compensatory plan. ** Paper filing. † Certain exhibits and schedules have been omitted pursuant to Item 601(b)(2)(ii) or 601(b)(10)(iv) of Regulation S-K, as applicable. A copy of any of the Exhibits listed above will be provided without charge to any shareholder submitting a written request specifying the desired exhibit(s) to the Secretary at the principal executive offices of the Company. Pursuant to Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed as exhibits to this Form 10-K certain long-term debt instruments, under which the total amount of securities authorized does not exceed 10% of the total assets of the Company and its subsidiaries on a consolidated basis. The Company hereby agrees to furnish a copy of any such instrument to the SEC upon request. 2024 Annual Report 121\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": -0.032586, "explanation": "The actual 21-day forward return for VLUE starting 2025-02-14 was -3.26%, which classifies as 'negative'.", "metadata": {"future_return": -0.032586, "horizon_days": 21, "hist_return": 0.015343, "annualized_vol": 0.129282, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250910_0314", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VEA"], "decision_date": "2025-09-10", "context_summary": "VEA over past 60 days: cumulative return +6.5%, annualized vol 12.1%. Market regime: bull.", "question": "Asset: VEA\nHistorical prices (past 60 trading days): start=54.45, end=58.01, cumulative_return=+6.5%, annualized_volatility=12.1%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.54, 't10y3m_spread': -0.02, 'breakeven_10y': 2.36, 'hy_oas': 2.87, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.5, 'vix': 15.039999961853027}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": 0.02018, "explanation": "The actual 21-day forward return for VEA starting 2025-09-10 was +2.02%, which classifies as 'positive'.", "metadata": {"future_return": 0.02018, "horizon_days": 21, "hist_return": 0.065376, "annualized_vol": 0.121069, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251003_0317", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ITB"], "decision_date": "2025-10-03", "context_summary": "ITB over past 60 days: cumulative return +8.1%, annualized vol 28.4%. Market regime: bull.", "question": "Asset: ITB\nHistorical prices (past 60 trading days): start=99.75, end=107.87, cumulative_return=+8.1%, annualized_volatility=28.4%\nMacro context: {'fed_funds_rate': 4.09, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.55, 't10y3m_spread': 0.08, 'breakeven_10y': 2.34, 'hy_oas': 2.81, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.34, 'vix': 16.6299991607666}\nMarket regime: bull\n\nPredict whether the return of ITB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.096485, "explanation": "The actual 21-day forward return for ITB starting 2025-10-03 was -9.65%, which classifies as 'negative'.", "metadata": {"future_return": -0.096485, "horizon_days": 21, "hist_return": 0.081408, "annualized_vol": 0.283953, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250908_0320", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-09-08", "context_summary": "XLB over past 60 days: cumulative return +5.0%, annualized vol 15.5%. Market regime: bull.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=43.17, end=45.33, cumulative_return=+5.0%, annualized_volatility=15.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.59, 't10y3m_spread': 0.03, 'breakeven_10y': 2.37, 'hy_oas': 2.83, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.5, 'vix': 15.18000030517578}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\n\nPredict whether the return of XLB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.023855, "explanation": "The actual 21-day forward return for XLB starting 2025-09-08 was -2.39%, which classifies as 'negative'.", "metadata": {"future_return": -0.023855, "horizon_days": 21, "hist_return": 0.049846, "annualized_vol": 0.155315, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251201_0322", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2025-12-01", "context_summary": "IVV over past 60 days: cumulative return +5.6%, annualized vol 12.4%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=644.51, end=680.59, cumulative_return=+5.6%, annualized_volatility=12.4%\nMacro context: {'fed_funds_rate': 3.89, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.55, 't10y3m_spread': 0.14, 'breakeven_10y': 2.23, 'hy_oas': 2.92, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.23, 'vix': 16.350000381469727}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2025-11-19] nvda-20251026 0001045810 1/25 2026 Q3 FALSE 478 469 278 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:investment nvda:segment 0001045810 2025-01-27 2025-10-26 0001045810 2025-11-14 0001045810 2025-07-28 2025-10-26 0001045810 2024-07-29 2024-10-27 0001045810 2024-01-29 2024-10-27 0001045810 2025-10-26 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 2025-07-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-27 0001045810 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2025-10-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:CustomerOneMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerTwoMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerThreeMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerFourMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:Cust [...TRUNCATED...] President, Operations Adoption 9/9/2025 309,840 12/31/2026 Donald Robertson Vice President and Chief Accounting Officer Adoption 9/18/2025 138,042 * 12/31/2026 Ajay Puri Executive Vice President, Worldwide Field Operations Adoption 9/19/2025 1,000,000 6/24/2026 * Includes 38,042 shares from future vests of equity awards, and the actual number of shares to be sold will be net of shares withheld by the Company for taxes. 42 Item 6. Exhibits Exhibit No.  Exhibit Description 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 43 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 19, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 44\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": 0.001697, "explanation": "The actual 21-day forward return for IVV starting 2025-12-01 was +0.17%, which classifies as 'flat'.", "metadata": {"future_return": 0.001697, "horizon_days": 21, "hist_return": 0.05598, "annualized_vol": 0.12387, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20250606_0325", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2025-06-06", "context_summary": "ACWI over past 60 days: cumulative return +7.1%, annualized vol 19.4%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=114.59, end=122.76, cumulative_return=+7.1%, annualized_volatility=19.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.48, 't10y3m_spread': -0.04, 'breakeven_10y': 2.29, 'hy_oas': 3.18, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 6.85, 'vix': 18.479999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-05] [\"A Prominent Tech Analyst Adds a New Role: Pitching a Stock Fund The IVES ETF includes 30 AI-focused tech stocks. It puts analyst Dan Ives in the unusual position of covering tech companies while pitching a fund full of their stocks.\", \"Apple downgrade, Guidewire guidance, Thor Industries Q3 sales Yahoo Finance host Julie Hyman tracks today's top moving stocks and biggest market stories in this Market Minute, including Apple's (AAPL) downgrade to a Hold rating by Needham analysts, Guidewire Software (GWRE) raising its full-year revenue guidance, and RV manufacturer Thor Industries (THO) topping fiscal third quarter sales estimates in its latest earnings print. Stay up to date on the latest market action, minute-by-minute, with Yahoo Finance's Market Minute. It's time for Yahoo Finance's Market Minute. Wall Street digesting a slowdown in private sector hiring growth with one eye still on US-China trade talks. Apple hit with a downgrade by Needham analysts, lowering their rating on the stock to hold from buy. Needham said the stock's overvalued amid growing AI competition. And Guidewire shares surging as it tops third quarter earnings and revenue estimates. The insurance software maker also raising its got, uh, revenue guidance for the full year, topping Wall Street's expectations. Analysts at Needham noting that Guidewire's competitive positioning continues to strengthen. Thor Industries reporting a beat on net sales for the third quarter. The manufacturer of recreational vehicles did say it expects the fourth quarter of fiscal year 2025 and the first quarter of then fiscal 2026 to be challenging. Thor saying downward pressures due to current macroeconomic concerns, but the shares are higher. And that's your Yahoo Finance Market Minute. For more and watch trading, scan the QR code below. 02:20 China's Recovery 'Has Legs': Franklin Templeton's Tan Bloomberg \\u2022 1 hour ago 04:27 Small caps soar, CPI data on deck, bitcoin: Market takeaways Yahoo Finance Video \\u2022 7 hours ago 01:38 Here is what the markets need to power higher this year Yahoo Finance Video \\u2022 7 hours ago 02:55 IPO market shows 'cautious optimism' amid market uncertainty Yahoo Finance Video \\u2022 8 hours ago\", \"My 3 Favorite Stocks to Buy Right Now PepsiCo and Coca-Cola have been moving in opposite directions for a couple of years. Time for a change. Apple shares have underperformed for a pair of obvious reasons, but the future is much more promising than the recent past. With Warren Buffett close to retiring, companies similar to Berkshire Hathaway are drawing new interest. 10 stocks we like better than Apple \\u203a Has recent (and not-so-recent) volatility gotten your portfolio's allocation a little out of whack? Maybe it's time to reassess each of your existing holdings and replace the ones that no longer offer enough upside with more promising names. My needs are not exactly the same as yours. However, there are some stocks that keep making their way back onto my radar \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": 0.030961, "explanation": "The actual 21-day forward return for ACWI starting 2025-06-06 was +3.10%, which classifies as 'positive'.", "metadata": {"future_return": 0.030961, "horizon_days": 21, "hist_return": 0.071337, "annualized_vol": 0.194323, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250717_0328", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-07-17", "context_summary": "BTC-USD over past 60 days: cumulative return +0.0%, annualized vol 27.0%. Market regime: bull.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=103998.57, end=103998.57, cumulative_return=+0.0%, annualized_volatility=27.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.58, 't10y3m_spread': 0.05, 'breakeven_10y': 2.41, 'hy_oas': 3.0, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 17.15999984741211}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for BTC-USD starting 2025-07-17 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.270413, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250626_0330", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-06-26", "context_summary": "SOL-USD over past 60 days: cumulative return -3.2%, annualized vol 54.9%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=148.25, end=143.51, cumulative_return=-3.2%, annualized_volatility=54.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.55, 't10y3m_spread': -0.09, 'breakeven_10y': 2.28, 'hy_oas': 3.04, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 16.760000228881836}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.264154, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-06-26 was +26.42%, which classifies as 'positive'.", "metadata": {"future_return": 0.264154, "horizon_days": 21, "hist_return": -0.031979, "annualized_vol": 0.549355, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250313_0334", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2025-03-13", "context_summary": "SGOV over past 60 days: cumulative return +0.7%, annualized vol 0.2%. Market regime: bear.", "question": "Asset: SGOV\nHistorical prices (past 60 trading days): start=95.59, end=96.23, cumulative_return=+0.7%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.31, 't10y3m_spread': -0.03, 'breakeven_10y': 2.33, 'hy_oas': 3.2, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 24.229999542236328}\nMarket regime: bear\n\nPredict whether the return of SGOV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.00245, "explanation": "The actual 21-day forward return for SGOV starting 2025-03-13 was +0.24%, which classifies as 'flat'.", "metadata": {"future_return": 0.00245, "horizon_days": 21, "hist_return": 0.006749, "annualized_vol": 0.002305, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250916_0337", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-09-16", "context_summary": "SOL-USD over past 60 days: cumulative return +16.3%, annualized vol 65.3%. Market regime: bull.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=177.38, end=206.25, cumulative_return=+16.3%, annualized_volatility=65.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.51, 't10y3m_spread': -0.01, 'breakeven_10y': 2.37, 'hy_oas': 2.75, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.35, 'vix': 15.6899995803833}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-09-16 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.162762, "annualized_vol": 0.653319, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250625_0340", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2025-06-25", "context_summary": "QUAL over past 60 days: cumulative return +6.1%, annualized vol 20.9%. Market regime: sideways.", "question": "Asset: QUAL\nHistorical prices (past 60 trading days): start=167.95, end=178.24, cumulative_return=+6.1%, annualized_volatility=20.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.55, 't10y3m_spread': -0.08, 'breakeven_10y': 2.29, 'hy_oas': 3.06, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 17.479999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-24] [\"Trump\\u2019s Chip Tariff Threat Sparks Pushback From Auto Industry to Tech (Bloomberg) -- Blowback to President Donald Trump\\u2019s idea of tariffs on imported semiconductors is proving to be broad and deep, stretching from auto companies and boat makers to the technology industry and crypto enthusiasts, according to a review of more than 150 public comments on the proposal. Most Read from Bloomberg Bezos Wedding Draws Protests, Soul-Searching Over Tourism in Venice US State Budget Wounds Intensify From Trump, DOGE Policy Shifts US Renters Face Storm of Rising Costs Commuters Are Caught in Johannesburg's Taxi Feuds as Transit Lags The possible levy of up to 25% has united rivals like Tesla Inc., General Motors Co. and Ford Motor Co. in voicing reservations. It\\u2019s brought together industry lobbies from the Crypto Council for Innovation to the National Marine Manufacturers Association. Even Taiwan and the People\\u2019s Republic of China are finding common cause, along with predictable parts of the tech sector including chipmakers and wireless providers. The reason is that chips are now in almost everything: refrigerators and microwaves, tire pressure sensors and navigation systems, electronic bidets and sonar equipment and, of course, smartphones and computers. Tariffs threaten to snarl supply lines and jack up costs for consumers. \\u201cThere\\u2019s a large mismatch between the amount of chips we use in this country in various products and the supply created here in the US,\\u201d JoAnne Feeney, a partner and portfolio manager at Advisors Capital Management, said in an interview. \\u201cPutting a tax on those imports will simply raise the cost, and that\\u2019s not a good thing for consumers.\\u201d Case in point is the marine association, which warns the impact would be felt by more than 1,300 manufacturers who face higher expenses for essentials like propulsion technology, engines and GPS systems. \\u201cThese systems are not optional luxuries \\u2014 they are fundamental to safety, function and performance,\\u201d the association said. \\u201cMany components have no US equivalent or are only available from highly concentrated suppliers overseas.\\u201d The boating sector\\u2019s concerns were among comments from 154 stakeholders submitted to a Commerce Department review of whether to slap tariffs on chips as part of Trump\\u2019s campaign to redraw global supply lines and boost domestic manufacturing. Predictable tech sources weighed in, including chipmakers Taiwan Semiconductor Manufacturing Co. and Intel Corp. But feedback also landed from a wide spectrum of sectors, along with trading partners like Japan and Brazil. The companies, trade groups and individuals who commented on the chips investigation largely signaled support for the president\\u2019s vision of deepening the US manufacturing base and expanding the American workforce. Yet most expressed concern over the potential consequences and urged making any levies that emerge as targeted as pos\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": 0.041925, "explanation": "The actual 21-day forward return for QUAL starting 2025-06-25 was +4.19%, which classifies as 'positive'.", "metadata": {"future_return": 0.041925, "horizon_days": 21, "hist_return": 0.061268, "annualized_vol": 0.209077, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250821_0343", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2025-08-21", "context_summary": "ICSH over past 60 days: cumulative return +0.9%, annualized vol 0.5%. Market regime: bull.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=48.79, end=49.24, cumulative_return=+0.9%, annualized_volatility=0.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.55, 't10y3m_spread': -0.01, 'breakeven_10y': 2.35, 'hy_oas': 2.94, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.58, 'vix': 15.6899995803833}\nMarket regime: bull\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": 0.003401, "explanation": "The actual 21-day forward return for ICSH starting 2025-08-21 was +0.34%, which classifies as 'flat'.", "metadata": {"future_return": 0.003401, "horizon_days": 21, "hist_return": 0.009232, "annualized_vol": 0.005203, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250707_0346", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-07-07", "context_summary": "XLY over past 60 days: cumulative return +25.7%, annualized vol 23.7%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=87.48, end=109.97, cumulative_return=+25.7%, annualized_volatility=23.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.47, 't10y3m_spread': -0.07, 'breakeven_10y': 2.33, 'hy_oas': 2.8, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 16.3799991607666}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-07-03] [\"Social Buzz: Wallstreetbets Stocks Mixed Premarket Thursday; Webull to Advance, Robinhood Markets to Decline The most-talked-about stocks in the Reddit subforum Wallstreetbets were mixed hours before Thursday'\", \"AustralianSuper Boosts Private Equity With Four New Deals Coming (Bloomberg) -- AustralianSuper is increasing its allocation to unlisted assets as the country\\u2019s biggest pension fund works to finalize four private equity deals by the end of the year, according to the firm\\u2019s investment chief. Most Read from Bloomberg NYC Commutes Resume After Midtown Bus Terminal Crash Chaos Struggling Downtowns Are Looking to Lure New Crowds Massachusetts to Follow NYC in Making Landlords Pay Broker Fees What Gothenburg Got Out of Congestion Pricing California Exempts Building Projects From Environmental Law \\u201cWe are looking to put on four new private equity managers over this calendar year period and it looks like that is well in train,\\u201d Mark Delaney said in an interview on Thursday. \\u201cThe team know these managers from working previously with them and they have really good long-term track records in straight-down-the-line, conventional, private equity.\\u201d Delaney didn\\u2019t specify details of the arrangements or names of the fund managers. The deals follow a build-out of AustralianSuper\\u2019s New York office that now has around 60 people who are partly tasked with developing relationships with private markets fund managers. Delaney held meetings with private equity firms on two trips to New York this year, he said. \\u201cCapital raising is very low and generally investing in vintages when raising is low is the best strategy for private equity, so we think it\\u2019s a more attractive asset class,\\u201d Delaney said. AustralianSuper said in May the private equity allocation of its balanced investment option could grow to 8% from 5%. The move comes after a challenging period for the pension\\u2019s listed equity portfolio as returns were skewed to a handful of companies including the Magnificent Seven group of mega-cap tech firms. The dynamic \\u201chas not suited our style of portfolio,\\u201d but performance may improve over time given the fund\\u2019s \\u201clong-term diversification,\\u201d across asset classes, he said. Australia\\u2019s giant pensions have weathered heightened volatility through the year as President Donald Trump\\u2019s trade agenda and pockets of global conflict have rocked global markets. US stocks initially tumbled after Trump\\u2019s \\u2018Liberation Day\\u2019 tariff announcement but have since reversed declines and on Wednesday set a fresh all-time high. Delaney, who oversees the fund\\u2019s more than A$365 billion ($240 billion) in assets, said while US tariffs would likely slow growth in the economy and corporate profits, that does not warrant a reduced exposure to equities. \\u201cThere is a strong consensus that tariffs will cause a meaningful slowdown in the US economy but no recession,\\u201d Delaney sai\n\nPredict whether the return of XLY over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002335, "explanation": "The actual 21-day forward return for XLY starting 2025-07-07 was +0.23%, which classifies as 'flat'.", "metadata": {"future_return": 0.002335, "horizon_days": 21, "hist_return": 0.257119, "annualized_vol": 0.237042, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250624_0349", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["UNG"], "decision_date": "2025-06-24", "context_summary": "UNG over past 60 days: cumulative return -18.6%, annualized vol 58.0%. Market regime: sideways.", "question": "Asset: UNG\nHistorical prices (past 60 trading days): start=20.70, end=16.84, cumulative_return=-18.6%, annualized_volatility=58.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.5, 't10y3m_spread': -0.04, 'breakeven_10y': 2.3, 'hy_oas': 3.12, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 19.82999992370605}\nMarket regime: sideways\n\nPredict whether the return of UNG over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.156308, "explanation": "The actual 21-day forward return for UNG starting 2025-06-24 was -15.63%, which classifies as 'negative'.", "metadata": {"future_return": -0.156308, "horizon_days": 21, "hist_return": -0.186473, "annualized_vol": 0.580034, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251016_0352", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2025-10-16", "context_summary": "^VIX over past 60 days: cumulative return +34.3%, annualized vol 109.5%. Market regime: bull.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=15.37, end=20.64, cumulative_return=+34.3%, annualized_volatility=109.5%\nMacro context: {'fed_funds_rate': 4.1, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.55, 't10y3m_spread': 0.02, 'breakeven_10y': 2.29, 'hy_oas': 2.95, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.3, 'vix': 20.63999938964844}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": -0.216515, "explanation": "The actual 21-day forward return for ^VIX starting 2025-10-16 was -21.65%, which classifies as 'negative'.", "metadata": {"future_return": -0.216515, "horizon_days": 21, "hist_return": 0.342876, "annualized_vol": 1.094664, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251211_0355", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2025-12-11", "context_summary": "IVV over past 60 days: cumulative return +3.7%, annualized vol 12.4%. Market regime: sideways.", "question": "Asset: IVV\nHistorical prices (past 60 trading days): start=656.49, end=680.59, cumulative_return=+3.7%, annualized_volatility=12.4%\nMacro context: {'fed_funds_rate': 3.89, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.59, 't10y3m_spread': 0.44, 'breakeven_10y': 2.25, 'hy_oas': 2.91, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.19, 'vix': 15.770000457763672}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-10-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-10-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-10-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-10-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-10-31 0000104169 2025-12-02 0000104169 2025-08-01 2025-10-31 0000104169 2024-08-01 2024-10-31 0000104169 2024-02-01 2024-10-31 0000104169 2025-10-31 0000104169 2025-01-31 0000104169 2024-10-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-30 0000104169 us-gaap:ParentMember 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-04-30 0000104169 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-05-01 2025-07-31 0000104169 us-gaap:ParentMember 2025-05-01 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-05-01 2025-07-31 0000104169 2025-05-01 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-05-01 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-31 0000104169 us-gaap:ParentMember 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-08-01 2025-10-31 0000104169 us-gaap:ParentMember 2025-08-01 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-08-01 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-08-01 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of IVV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for IVV starting 2025-12-11 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.036711, "annualized_vol": 0.123618, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250724_0358", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-07-24", "context_summary": "SOL-USD over past 60 days: cumulative return +7.9%, annualized vol 55.4%. Market regime: bull.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=175.73, end=189.54, cumulative_return=+7.9%, annualized_volatility=55.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.52, 't10y3m_spread': -0.01, 'breakeven_10y': 2.37, 'hy_oas': 2.83, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.75, 'vix': 15.369999885559082}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.054653, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-07-24 was +5.47%, which classifies as 'positive'.", "metadata": {"future_return": 0.054653, "horizon_days": 21, "hist_return": 0.078631, "annualized_vol": 0.554149, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250404_0361", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-04-04", "context_summary": "BTC-USD over past 60 days: cumulative return -18.0%, annualized vol 46.3%. Market regime: bear.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=101405.42, end=83102.83, cumulative_return=-18.0%, annualized_volatility=46.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.35, 't10y3m_spread': -0.25, 'breakeven_10y': 2.28, 'hy_oas': 4.01, 'ig_oas': 1.06, 'ted_spread': 0.09, 'mortgage_30y': 6.64, 'vix': 30.020000457763672}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.129726, "explanation": "The actual 21-day forward return for BTC-USD starting 2025-04-04 was +12.97%, which classifies as 'positive'.", "metadata": {"future_return": 0.129726, "horizon_days": 21, "hist_return": -0.180489, "annualized_vol": 0.463206, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251001_0364", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-10-01", "context_summary": "EEM over past 60 days: cumulative return +10.4%, annualized vol 10.3%. Market regime: bull.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=47.69, end=52.65, cumulative_return=+10.4%, annualized_volatility=10.3%\nMacro context: {'fed_funds_rate': 4.09, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.56, 't10y3m_spread': 0.14, 'breakeven_10y': 2.36, 'hy_oas': 2.8, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.3, 'vix': 16.280000686645508}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": 0.016537, "explanation": "The actual 21-day forward return for EEM starting 2025-10-01 was +1.65%, which classifies as 'positive'.", "metadata": {"future_return": 0.016537, "horizon_days": 21, "hist_return": 0.10399, "annualized_vol": 0.102758, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251128_0366", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2025-11-28", "context_summary": "MTUM over past 60 days: cumulative return +1.4%, annualized vol 15.2%. Market regime: sideways.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=243.48, end=246.79, cumulative_return=+1.4%, annualized_volatility=15.2%\nMacro context: {'fed_funds_rate': 3.88, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.55, 't10y3m_spread': 0.08, 'breakeven_10y': 2.23, 'hy_oas': 3.0, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.23, 'vix': 17.190000534057617}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2025-11-19] nvda-20251026 0001045810 1/25 2026 Q3 FALSE 478 469 278 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:investment nvda:segment 0001045810 2025-01-27 2025-10-26 0001045810 2025-11-14 0001045810 2025-07-28 2025-10-26 0001045810 2024-07-29 2024-10-27 0001045810 2024-01-29 2024-10-27 0001045810 2025-10-26 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 2025-07-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-27 0001045810 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2025-10-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:CustomerOneMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerTwoMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerThreeMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerFourMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:Cust [...TRUNCATED...] President, Operations Adoption 9/9/2025 309,840 12/31/2026 Donald Robertson Vice President and Chief Accounting Officer Adoption 9/18/2025 138,042 * 12/31/2026 Ajay Puri Executive Vice President, Worldwide Field Operations Adoption 9/19/2025 1,000,000 6/24/2026 * Includes 38,042 shares from future vests of equity awards, and the actual number of shares to be sold will be net of shares withheld by the Company for taxes. 42 Item 6. Exhibits Exhibit No.  Exhibit Description 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 43 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 19, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 44\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": 0.015691, "explanation": "The actual 21-day forward return for MTUM starting 2025-11-28 was +1.57%, which classifies as 'positive'.", "metadata": {"future_return": 0.015691, "horizon_days": 21, "hist_return": 0.013591, "annualized_vol": 0.152387, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20250807_0369", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-08-07", "context_summary": "XLY over past 60 days: cumulative return +5.4%, annualized vol 18.5%. Market regime: bull.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=105.40, end=111.09, cumulative_return=+5.4%, annualized_volatility=18.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.53, 't10y3m_spread': -0.1, 'breakeven_10y': 2.34, 'hy_oas': 2.98, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 16.770000457763672}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q CAT 2025-08-06] cat-20250630 0000018230 FALSE 12/31 2025 Q2 50 338 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cat:entity cat:group_president cat:segment 0000018230 2025-01-01 2025-06-30 0000018230 us-gaap:CommonStockMember 2025-01-01 2025-06-30 0000018230 cat:A5.3DebenturesDueSeptember152035Member 2025-01-01 2025-06-30 0000018230 2025-06-30 0000018230 cat:MachineryEnergyTransportationMember 2025-04-01 2025-06-30 0000018230 cat:MachineryEnergyTransportationMember 2024-04-01 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Exhibits 4.1 Form of 5.200% Senior Note due 2035 (incorporated by reference from Exhibit 4.1 to the Company’s Current Report on Form 8-K filed May 15, 2025) 4.2 Form of 5.500% Senior Note due 2055 (incorporated by reference from Exhibit 4.2 to the Company’s Current Report on Form 8-K filed May 15, 2025) 10.1 First Amended and Restated Aircraft Time Sharing Agreement, dated as of April 28, 2025. 10.2 Aircraft Time Sharing Agreement, dated as of May 7, 2025. 31.1 Certification of Chief Executive Officer of Caterpillar Inc., as required pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer of Caterpillar Inc., as required pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32 Certification of Chief Executive Officer of Caterpillar Inc. and Chief Financial Officer of Caterpillar Inc., as required pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS Inline XBRL Instance Document (the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document) 101.SCH   Inline XBRL Taxonomy Extension Schema Document 101.CAL   Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF   Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB   Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE   Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive File (embedded within the Inline XBRL document and included in Exhibit 101) The agreements and other documents filed as exhibits to this report are not intended to provide factual information or other disclosure other than with respect to the terms of the agreements or other documents themselves, and you should not rely on them for that purpose. In particular, any representations and warranties made by us in these agreements or other documents were made solely within the specific context of the relevant agreement or document and may not describe the actual state of affairs as of the date they were made or at any other time. 80 Table of Contents SIGNATURES   Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       CATERPILLAR INC.               August 6, 2025 /s/ Joseph E. Creed Chief Executive Officer   Joseph E. Creed         August 6, 2025 /s/ Andrew R.J. Bonfield Chief Financial Officer   Andrew R.J. Bonfield               August 6, 2025 /s/ Derek Owens Chief Legal Officer and General Counsel   Derek Owens             August 6, 2025 /s/ William E. Schaupp Vice President and Chief Accounting Officer   William E. Schaupp   81\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": 0.052464, "explanation": "The actual 21-day forward return for XLY starting 2025-08-07 was +5.25%, which classifies as 'positive'.", "metadata": {"future_return": 0.052464, "horizon_days": 21, "hist_return": 0.053961, "annualized_vol": 0.185103, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250311_0372", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-03-11", "context_summary": "VLUE over past 60 days: cumulative return -2.5%, annualized vol 14.5%. Market regime: sideways.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=106.79, end=104.08, cumulative_return=-2.5%, annualized_volatility=14.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.33, 't10y3m_spread': -0.11, 'breakeven_10y': 2.31, 'hy_oas': 3.16, 'ig_oas': 0.91, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 27.86000061035156}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K PFE 2025-02-27] pfe-20241231 0000078003 2024 FY false P4Y Consolidated Statements of Operations Consolidated Statements of Operations Consolidated Statements of Operations http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent 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ITEM 16. FORM 10-K SUMMARY None. SIGNATURES Under the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, this report was signed on behalf of the Registrant by the authorized person named below. Pfizer Inc. Dated: February 27, 2025 By: /S/    MARGARET M. MADDEN Margaret M. Madden Senior Vice President and Corporate Secretary Chief Governance Counsel We, the undersigned directors and officers of Pfizer Inc., hereby severally constitute Douglas M. Lankler and Margaret M. Madden, and each of them singly, our true and lawful attorneys with full power to them and each of them to sign for us, in our names in the capacities indicated below, any and all amendments to this Annual Report on Form 10-K filed with the Securities and Exchange Commission. Under the requirements of the Securities Exchange Act of 1934, this report was signed by the following persons on behalf of the Registrant and in the capacities and on the date indicated . Pfizer Inc. 2024 Form 10-K 113 Signature Title Date /S/    ALBERT BOURLA Albert Bourla Chairman, Chief Executive Officer and Director (Principal Executive Officer) February 27, 2025 /S/    DAVID M. DENTON David M. Denton Chief Financial Officer, Executive Vice President (Principal Financial Officer) February 27, 2025 /S/    JENNIFER B. DAMICO Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer) February 27, 2025 /S/    RONALD E. BLAYLOCK Ronald E. Blaylock Director February 27, 2025 /S/    MORTIMER J. BUCKLEY Mortimer J. Buckley Director February 27, 2025 /S/    SUSAN DESMOND-HELLMANN Susan Desmond-Hellmann Director February 27, 2025 /S/    JOSEPH J. ECHEVARRIA Joseph J. Echevarria Director February 27, 2025 /S/    SCOTT GOTTLIEB Scott Gottlieb Director February 27, 2025 /S/    HELEN H. HOBBS Helen H. Hobbs Director February 27, 2025 /S/    SUSAN HOCKFIELD Susan Hockfield Director February 27, 2025 /S/    DAN R. LITTMAN Dan R. Littman Director February 27, 2025 /S/    SHANTANU NARAYEN Shantanu Narayen Director February 27, 2025 /S/    SUZANNE NORA JOHNSON Suzanne Nora Johnson Director February 27, 2025 /S/    JAMES QUINCEY James Quincey Director February 27, 2025 /S/    JAMES C. SMITH James C. Smith Director February 27, 2025 /S/    CYRUS TARAPOREVALA Cyrus Taraporevala Director February 27, 2025 Pfizer Inc. 2024 Form 10-K 114\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": -0.036337, "explanation": "The actual 21-day forward return for VLUE starting 2025-03-11 was -3.63%, which classifies as 'negative'.", "metadata": {"future_return": -0.036337, "horizon_days": 21, "hist_return": -0.025306, "annualized_vol": 0.145017, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250708_0375", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SHV"], "decision_date": "2025-07-08", "context_summary": "SHV over past 60 days: cumulative return +0.9%, annualized vol 0.2%. Market regime: sideways.", "question": "Asset: SHV\nHistorical prices (past 60 trading days): start=106.02, end=106.99, cumulative_return=+0.9%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.5, 't10y3m_spread': -0.02, 'breakeven_10y': 2.35, 'hy_oas': 2.86, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 17.790000915527344}\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": 0.00359, "explanation": "The actual 21-day forward return for SHV starting 2025-07-08 was +0.36%, which classifies as 'flat'.", "metadata": {"future_return": 0.00359, "horizon_days": 21, "hist_return": 0.009111, "annualized_vol": 0.001949, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250729_0378", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DBA"], "decision_date": "2025-07-29", "context_summary": "DBA over past 60 days: cumulative return -2.4%, annualized vol 11.4%. Market regime: bull.", "question": "Asset: DBA\nHistorical prices (past 60 trading days): start=25.93, end=25.32, cumulative_return=-2.4%, annualized_volatility=11.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.51, 't10y3m_spread': 0.02, 'breakeven_10y': 2.44, 'hy_oas': 2.82, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.74, 'vix': 15.029999732971191}\nMarket regime: bull\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": 0.060361, "explanation": "The actual 21-day forward return for DBA starting 2025-07-29 was +6.04%, which classifies as 'positive'.", "metadata": {"future_return": 0.060361, "horizon_days": 21, "hist_return": -0.023818, "annualized_vol": 0.113874, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250409_0380", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-04-09", "context_summary": "USMV over past 60 days: cumulative return -2.8%, annualized vol 11.9%. Market regime: bear.", "question": "Asset: USMV\nHistorical prices (past 60 trading days): start=86.50, end=84.10, cumulative_return=-2.8%, annualized_volatility=11.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.55, 't10y3m_spread': -0.05, 'breakeven_10y': 2.22, 'hy_oas': 4.57, 'ig_oas': 1.18, 'ted_spread': 0.09, 'mortgage_30y': 6.64, 'vix': 43.34999847412109}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-08] Trump Trade: Trump claims \u2018no inflation,\u2019 Medicare won\u2019t cover obesity drugs Catch up on the top industries and stocks that were impacted, or were predicted to be impacted, by the comments, actions and policies of President Donald Trump with this daily recap compiled by The Fly: Discover outperforming stocks and invest smarter with Top Smart Score Stocks. Filter, analyze, and streamline your search for investment opportunities using Tipranks' Stock Screener. TRUMP SAYS NO INFLATION: President Trump said via Truth Social, \u201cOil prices are down, interest rates are down (the slow moving Fed should cut rates!), food prices are down, there is NO INFLATION, and the long time abused USA is bringing in Billions of Dollars a week from the abusing countries on Tariffs that are already in place. This is despite the fact that the biggest abuser of them all, China, whose markets are crashing, just raised its Tariffs by 34%, on top of its long term ridiculously high Tariffs (Plus!), not acknowledging my warning for abusing countries not to retaliate. They\u2019ve made enough, for decades, taking advantage of the Good OL\u2019 USA! Our past \u2018leaders\u2019 are to blame for allowing this, and so much else, to happen to our Country.\u201d The President also said, \u201cThe United States has a chance to do something that should have been done DECADES AGO. Don\u2019t be Weak! Don\u2019t be Stupid! Don\u2019t be a PANICAN (A new party based on Weak and Stupid people!). Be Strong, Courageous, and Patient, and GREATNESS will be the result!\u201d Trump told reporters aboard Air Force One Sunday night, \u201cI don\u2019t want anything to go down, but sometimes you have to take medicine to fix something.\u201d He added, \u201cI\u2019m willing to deal with China, but they have to solve their surplus.\u201d On Truth Social earlier, Trump said, \u201cWe have massive Financial Deficits with China, the European Union, and many others. The only way this problem can be cured is with TARIFFS, which are now bringing Tens of Billions of Dollars into the U.S.A. They are already in effect, and a beautiful thing to behold. The Surplus with these Countries has grown during the \u2018Presidency\u2019 of Sleepy Joe Biden. We are going to reverse it, and reverse it QUICKLY. Some day people will realize that Tariffs, for the United States of America, are a very beautiful thing!\u201d The U.S. President said via Truth Social, \u201cCountries from all over the World are talking to us. Tough but fair parameters are being set. Spoke to the Japanese Prime Minister this morning. He is sending a top team to negotiate! They have treated the U.S. very poorly on Trade. They don\u2019t take our cars, but we take MILLIONS of theirs. Likewise Agriculture, and many other \u201cthings.\u201d It all has to change, but especially with CHINA!!!\u201d READY TO NEGOTIATE: Ursula von der Leyen, President of the European Union Commission, said via X: \u201cEurope is ready to negotiate with the US. We have offered zero-for-zero tariffs for industrial goods. Because we\u2019re always ready for a good deal. But we\u2019re also prepared to respond \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": 0.025262, "explanation": "The actual 21-day forward return for USMV starting 2025-04-09 was +2.53%, which classifies as 'positive'.", "metadata": {"future_return": 0.025262, "horizon_days": 21, "hist_return": -0.027801, "annualized_vol": 0.119185, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251007_0383", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-10-07", "context_summary": "DOT-USD over past 60 days: cumulative return +10.3%, annualized vol 59.4%. Market regime: bull.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=3.98, end=4.39, cumulative_return=+10.3%, annualized_volatility=59.4%\nMacro context: {'fed_funds_rate': 4.09, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.58, 't10y3m_spread': 0.16, 'breakeven_10y': 2.34, 'hy_oas': 2.76, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.34, 'vix': 16.3700008392334}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.146247, "explanation": "The actual 21-day forward return for DOT-USD starting 2025-10-07 was -14.62%, which classifies as 'negative'.", "metadata": {"future_return": -0.146247, "horizon_days": 21, "hist_return": 0.102872, "annualized_vol": 0.593506, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251127_0386", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-11-27", "context_summary": "XLB over past 60 days: cumulative return -2.2%, annualized vol 15.6%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=45.01, end=44.02, cumulative_return=-2.2%, annualized_volatility=15.6%\nMacro context: {'fed_funds_rate': 3.88, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.55, 't10y3m_spread': 0.08, 'breakeven_10y': 2.23, 'hy_oas': 3.0, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.23, 'vix': 17.190000534057617}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2025-11-19] nvda-20251026 0001045810 1/25 2026 Q3 FALSE 478 469 278 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:investment nvda:segment 0001045810 2025-01-27 2025-10-26 0001045810 2025-11-14 0001045810 2025-07-28 2025-10-26 0001045810 2024-07-29 2024-10-27 0001045810 2024-01-29 2024-10-27 0001045810 2025-10-26 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 2025-07-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-27 0001045810 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2025-10-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:CustomerOneMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerTwoMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerThreeMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerFourMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:Cust [...TRUNCATED...] President, Operations Adoption 9/9/2025 309,840 12/31/2026 Donald Robertson Vice President and Chief Accounting Officer Adoption 9/18/2025 138,042 * 12/31/2026 Ajay Puri Executive Vice President, Worldwide Field Operations Adoption 9/19/2025 1,000,000 6/24/2026 * Includes 38,042 shares from future vests of equity awards, and the actual number of shares to be sold will be net of shares withheld by the Company for taxes. 42 Item 6. Exhibits Exhibit No.  Exhibit Description 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 43 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 19, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 44\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": 0.036869, "explanation": "The actual 21-day forward return for XLB starting 2025-11-27 was +3.69%, which classifies as 'positive'.", "metadata": {"future_return": 0.036869, "horizon_days": 21, "hist_return": -0.02199, "annualized_vol": 0.155949, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20250128_0389", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["HYG"], "decision_date": "2025-01-28", "context_summary": "HYG over past 60 days: cumulative return +2.0%, annualized vol 4.4%. Market regime: sideways.", "question": "Asset: HYG\nHistorical prices (past 60 trading days): start=72.76, end=74.25, cumulative_return=+2.0%, annualized_volatility=4.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.36, 't10y3m_spread': 0.21, 'breakeven_10y': 2.4, 'hy_oas': 2.66, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.96, 'vix': 17.899999618530273}\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": 0.008062, "explanation": "The actual 21-day forward return for HYG starting 2025-01-28 was +0.81%, which classifies as 'flat'.", "metadata": {"future_return": 0.008062, "horizon_days": 21, "hist_return": 0.020473, "annualized_vol": 0.044381, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251107_0392", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2025-11-07", "context_summary": "XLP over past 60 days: cumulative return -7.0%, annualized vol 11.2%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=80.20, end=74.58, cumulative_return=-7.0%, annualized_volatility=11.2%\nMacro context: {'fed_funds_rate': 3.87, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.54, 't10y3m_spread': 0.18, 'breakeven_10y': 2.28, 'hy_oas': 3.13, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.22, 'vix': 19.5}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CVX 2025-11-06] cvx-20250930 0000093410 12/31 2025 Q3 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cvx:segment cvx:lawsuit cvx:state cvx:tribe cvx:parish 0000093410 2025-01-01 2025-09-30 0000093410 2025-09-30 0000093410 2025-07-01 2025-09-30 0000093410 2024-07-01 2024-09-30 0000093410 2024-01-01 2024-09-30 0000093410 2024-12-31 0000093410 2023-12-31 0000093410 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-06-30 0000093410 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(2) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections During the three months ended September 30, 2025, none of our directors or executive officers adopted, modified or terminated a Rule 10b5-1 trading arrangement or a non-Rule 10b5-1 trading arrangement, as such terms are defined in Item 408 of Regulation S-K. 47 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 4.1 Fourth Supplemental Indenture, dated as of August 13, 2025, among Chevron U.S.A. Inc., Chevron Corporation, as guarantor, and Deutsche Bank Trust Company Americas, as trustee, filed as Exhibit 4. 2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 4.2 Forms of 3.950% Notes Due 2027, 4.050% Notes Due 2028, Floating Rate Notes Due 2028-B, 4.300% Notes Due 2030, Floating Rate Notes due 2030, 4.500% Notes Due 2032 and 4.850% Notes Due 2035, contained in Exhibit 4.2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 10.1+* Aircraft Time-Sharing Agreement, dated as of February 24, 2015, between Hess Corporation and John B. Hess. 10.2* Transition Services Agreement, dated as of July 14, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.3* Amendment One to Transition Services Agreement, dated as of August 27, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.4* Membership Interest Purchase Agreement, dated as of September 10, 2025, between Hess Corporation and JBH Ventures, LLC . 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ + Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 48 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 6, 2025 49\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": 0.01434, "explanation": "The actual 21-day forward return for XLP starting 2025-11-07 was +1.43%, which classifies as 'positive'.", "metadata": {"future_return": 0.01434, "horizon_days": 21, "hist_return": -0.070129, "annualized_vol": 0.111706, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250123_0395", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-01-23", "context_summary": "EFA over past 60 days: cumulative return -1.2%, annualized vol 12.6%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=76.34, end=75.45, cumulative_return=-1.2%, annualized_volatility=12.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.31, 't10y3m_spread': 0.24, 'breakeven_10y': 2.4, 'hy_oas': 2.66, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 7.04, 'vix': 15.100000381469728}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q PG 2025-01-22] pg-20241231 0000080424 6/30 2025 Q2 false http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 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2023-09-30 0000080424 us-gaap:PreferredStockMember 2023-09-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-09-30 0000080424 pg:ReserveforESOPDebtRetirementMember 2023-09-30 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-09-30 0000080424 us-gaap:TreasuryStockCommonMember 2023-09-30 0000080424 us-gaap:RetainedEarningsMember 2023-09-30 0000080424 us-gaap:NoncontrollingInterestMember 2023-09-30 0000080424 2023-09-30 0000080424 us-gaap:RetainedEarningsMember 2023-10-01 2023-12-31 0000080424 us-gaap:NoncontrollingInterestMember 2023-10-01 2023-12-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-10-01 2023-12-31 0000080424 us-gaap:CommonStockMember 2023-10-01 2023-12-31 0000080424 us-gaap:TreasuryStockCommonMember 2023-10-01 2023-12-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-10-01 2023-12-31 0000080424 us-gaap:PreferredStockMember 2023-10-01 2023-12-31 0000080424 us-gaap:CommonStockMember 2023-12-31 0000080424 us-gaap:PreferredStockMember 2023-12-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-12-31 0000080424 pg:ReserveforESOPDebtRetirementMember 2023-12-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-12-31 0000080424 us-gaap:TreasuryStockCommonMember 2023-12-31 0000080424 us-gaap:RetainedEarningsMember 2023-12-31 0000080424 us-gaap:NoncontrollingInterestMember 2023-12-31 0000080424 2023-12-31 0000080424 us-gaap:CommonStockMember 2023-06-30 0000080424 us-gaap:PreferredStockMember 2023-06-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-06-30 0000080424 pg:R [...TRUNCATED...] 7 billion in fiscal year 2025, notwithstanding any purchases under the Company's compensation and benefit plans. Purchases may be made in the open market and/or private transactions and purchases may be increased, decreased or discontinued at any time without prior notice. The share repurchases are authorized pursuant to a resolution issued by the Company's Board of Directors and are expected to be financed by a combination of operating cash flows and issuance of debt.      Item 5. Other Information During the three months ended December 31, 2024, none of our directors or officers adopted or terminated a \"Rule 10b5-1 trading arrangement\" or \"non-Rule 10b5-1 trading arrangement\" as defined in Item 408 of Regulation S-K. 30 The Procter & Gamble Company Item 6. Exhibits 3.1 Amended Articles of Incorporation (as amended by shareholders at the annual meeting on October 11, 2011 and consolidated by the Board of Directors on April 8, 2016) (Incorporated by reference to Exhibit (3-1) of the Company's Form 10-K for the year ended June 30, 2016) 3.2 Regulations (as approved by the Board of Directors on December 13, 2022, pursuant to authority granted by shareholders at the annual meeting on October 13, 2009) (Incorporated by reference to Exhibit (3-2) of the Company’s Current Report on Form 8-K filed December 13, 2022) 4.1 Indenture, dated as of September 3, 2009, between the Company and Deutsche Bank Trust Company Americas, as Trustee (Incorporated by reference to Exhibit (4-1) of the Company's Annual Report on Form 10-K for the year ended June 30, 2015) 31.1 Rule 13a-14(a)/15d-14(a) Certification – Chief Executive Officer + 31.2 Rule 13a-14(a)/15d-14(a) Certification – Chief Financial Officer + 32.1 Section 1350 Certifications – Chief Executive Officer + 32.2 Section 1350 Certifications – Chief Financial Officer + 101.SCH (1) Inline XBRL Taxonomy Extension Schema Document 101.CAL (1) Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF (1) Inline XBRL Taxonomy Definition Linkbase Document 101.LAB (1) Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE (1) Inline XBRL Taxonomy Extension Presentation Linkbase Document 104  Cover Page Interactive Data File (formatted in Inline XBRL and contained in Exhibit 101) + Filed herewith (1) Pursuant to Rule 406T of Regulation S-T, this information is furnished and not filed for purposes of Sections 11 or 12 of the Securities Act of 1933 and Section 18 of the Securities Exchange Act of 1934, and otherwise is not subject to liability under these sections. Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this Report to be signed on its behalf by the undersigned thereunto duly authorized. THE PROCTER & GAMBLE COMPANY January 22, 2025 /s/ MATTHEW W. JANZARUK Date (Matthew W. Janzaruk) Senior Vice President - Chief Accounting Officer (Principal Accounting Officer)\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": 0.034903, "explanation": "The actual 21-day forward return for EFA starting 2025-01-23 was +3.49%, which classifies as 'positive'.", "metadata": {"future_return": 0.034903, "horizon_days": 21, "hist_return": -0.011667, "annualized_vol": 0.125507, "has_text": true, "text_chars": 9044}} +{"id": "T1_all_20250416_0398", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-04-16", "context_summary": "DOT-USD over past 60 days: cumulative return -29.5%, annualized vol 68.3%. Market regime: bear.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=5.02, end=3.54, cumulative_return=-29.5%, annualized_volatility=68.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.51, 't10y3m_spread': 0.02, 'breakeven_10y': 2.19, 'hy_oas': 4.09, 'ig_oas': 1.14, 'ted_spread': 0.09, 'mortgage_30y': 6.62, 'vix': 30.1200008392334}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.11518, "explanation": "The actual 21-day forward return for DOT-USD starting 2025-04-16 was +11.52%, which classifies as 'positive'.", "metadata": {"future_return": 0.11518, "horizon_days": 21, "hist_return": -0.295433, "annualized_vol": 0.682723, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250102_0401", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2025-01-02", "context_summary": "QQQ over past 60 days: cumulative return +6.2%, annualized vol 17.5%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=478.29, end=508.01, cumulative_return=+6.2%, annualized_volatility=17.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.33, 't10y3m_spread': 0.21, 'breakeven_10y': 2.34, 'hy_oas': 2.92, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.85, 'vix': 17.350000381469727}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 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us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of QQQ over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.023636, "explanation": "The actual 21-day forward return for QQQ starting 2025-01-02 was +2.36%, which classifies as 'positive'.", "metadata": {"future_return": 0.023636, "horizon_days": 21, "hist_return": 0.062133, "annualized_vol": 0.174568, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250305_0404", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VCIT"], "decision_date": "2025-03-05", "context_summary": "VCIT over past 60 days: cumulative return +0.8%, annualized vol 5.1%. Market regime: sideways.", "question": "Asset: VCIT\nHistorical prices (past 60 trading days): start=77.14, end=77.75, cumulative_return=+0.8%, annualized_volatility=5.1%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.26, 't10y3m_spread': -0.12, 'breakeven_10y': 2.35, 'hy_oas': 2.99, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 23.51000022888184}\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": "flat", "answer_numeric": 0.00958, "explanation": "The actual 21-day forward return for VCIT starting 2025-03-05 was +0.96%, which classifies as 'flat'.", "metadata": {"future_return": 0.00958, "horizon_days": 21, "hist_return": 0.007888, "annualized_vol": 0.051135, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250220_0406", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNDX"], "decision_date": "2025-02-20", "context_summary": "BNDX over past 60 days: cumulative return -0.2%, annualized vol 3.8%. Market regime: sideways.", "question": "Asset: BNDX\nHistorical prices (past 60 trading days): start=46.79, end=46.70, cumulative_return=-0.2%, annualized_volatility=3.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.25, 't10y3m_spread': 0.19, 'breakeven_10y': 2.45, 'hy_oas': 2.68, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.87, 'vix': 15.270000457763672}\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": -0.00442, "explanation": "The actual 21-day forward return for BNDX starting 2025-02-20 was -0.44%, which classifies as 'flat'.", "metadata": {"future_return": -0.00442, "horizon_days": 21, "hist_return": -0.001878, "annualized_vol": 0.037774, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250213_0408", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2025-02-13", "context_summary": "XLRE over past 60 days: cumulative return -1.3%, annualized vol 17.2%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=40.79, end=40.23, cumulative_return=-1.3%, annualized_volatility=17.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.26, 't10y3m_spread': 0.27, 'breakeven_10y': 2.46, 'hy_oas': 2.66, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.89, 'vix': 15.890000343322754}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K AMZN 2025-02-07] amzn-20241231 false 2024 FY 0001018724 P3Y P1Y P1Y http://fasb.org/us-gaap/2024#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2024#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 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0001018724 us-gaap:ShareBasedCompensationAwardTrancheOneMember 2024-01-01 2024-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2022-01-01 2022-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2023-01-01 2023-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2024-01-01 2024-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2024-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsoli [...TRUNCATED...] Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy (incorporated by reference to the Company's Annual Report on Form 10-K for the Year ended December 31, 2023). 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2024, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2024, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 76 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 6, 2025.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 6, 2025.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Andrew Y. Ng Andrew Y. Ng Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 77\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": -0.01847, "explanation": "The actual 21-day forward return for XLRE starting 2025-02-13 was -1.85%, which classifies as 'negative'.", "metadata": {"future_return": -0.01847, "horizon_days": 21, "hist_return": -0.013496, "annualized_vol": 0.172114, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20251023_0411", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-10-23", "context_summary": "XLV over past 60 days: cumulative return +9.3%, annualized vol 15.0%. Market regime: bull.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=132.47, end=144.75, cumulative_return=+9.3%, annualized_volatility=15.0%\nMacro context: {'fed_funds_rate': 4.11, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.52, 't10y3m_spread': 0.01, 'breakeven_10y': 2.29, 'hy_oas': 3.01, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.27, 'vix': 18.600000381469727}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q JNJ 2025-10-22] jnj-20250928 0000200406 12/28 2025 Q3 FALSE 33 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:EUR jnj:segment jnj:intangibleAsset jnj:claimant jnj:cases 0000200406 2024-12-30 2025-09-28 0000200406 us-gaap:CommonStockMember 2024-12-30 2025-09-28 0000200406 jnj:A1.150NotesDueNovember2028Member 2024-12-30 2025-09-28 0000200406 jnj:A2.700NotesDueFebruary2029Member 2024-12-30 2025-09-28 0000200406 jnj:A3.20NotesDueJune2032Member 2024-12-30 2025-09-28 0000200406 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purchased as part of a systematic plan to meet the needs of the Company’s compensation programs. 58   Table of Contents Item 5 — Other information Securities trading plans of Directors and Executive Officers . During the fiscal third quarter of 2025, none of our directors or officers (as defined in Rule 16a-1(f) of the Exchange Act) informed us of the adoption or termination of a “Rule 10b5-1 trading arrangement” or “non-Rule 10b5-1 trading arrangement,” each as defined in Item 408 of Regulation S-K. Item 6 — Exhibits Exhibit 31.1 Certification of Chief Executive Officer under Rule 13a-14(a) of the Securities Exchange Act pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 — Filed with this document. Exhibit 31.2 Certification of Chief Financial Officer under Rule 13a-14(a) of the Securities Exchange Act pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 — Filed with this document. Exhibit 32.1 Certification of Chief Executive Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 — Furnished with this document. Exhibit 32.2 Certification of Chief Financial Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 — Furnished with this document. Exhibit 101: EX-101.INS Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document EX-101.SCH Inline XBRL Taxonomy Extension Schema EX-101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase EX-101.LAB Inline XBRL Taxonomy Extension Label Linkbase EX-101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase EX-101.DEF Inline XBRL Taxonomy Extension Definition Document Exhibit 104: Cover Page Interactive Data File––the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. Form 10-Q 59 Table of Contents Signatures Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: October 22, 2025 Date: October 22, 2025 JOHNSON & JOHNSON (Registrant) By  /s/ J. J. Wolk J. J. Wolk , Executive Vice President, Chief Financial Officer (Principal Financial Officer)  By  /s/  R. J. Decker Jr. R. J. Decker Jr. , Controller (Principal Accounting Officer) 60  \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": 0.051588, "explanation": "The actual 21-day forward return for XLV starting 2025-10-23 was +5.16%, which classifies as 'positive'.", "metadata": {"future_return": 0.051588, "horizon_days": 21, "hist_return": 0.092686, "annualized_vol": 0.150389, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20251013_0413", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-10-13", "context_summary": "XLY over past 60 days: cumulative return +3.1%, annualized vol 16.6%. Market regime: sideways.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=110.45, end=113.92, cumulative_return=+3.1%, annualized_volatility=16.6%\nMacro context: {'fed_funds_rate': 4.1, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.53, 't10y3m_spread': 0.03, 'breakeven_10y': 2.3, 'hy_oas': 3.18, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.3, 'vix': 21.65999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": 0.024331, "explanation": "The actual 21-day forward return for XLY starting 2025-10-13 was +2.43%, which classifies as 'positive'.", "metadata": {"future_return": 0.024331, "horizon_days": 21, "hist_return": 0.031433, "annualized_vol": 0.165961, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250604_0416", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2025-06-04", "context_summary": "SGOV over past 60 days: cumulative return +0.7%, annualized vol 0.2%. Market regime: sideways.", "question": "Asset: SGOV\nHistorical prices (past 60 trading days): start=96.52, end=97.17, cumulative_return=+0.7%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.5, 't10y3m_spread': 0.03, 'breakeven_10y': 2.32, 'hy_oas': 3.19, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 6.89, 'vix': 17.690000534057617}\nMarket regime: sideways\n\nPredict whether the return of SGOV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.00239, "explanation": "The actual 21-day forward return for SGOV starting 2025-06-04 was +0.24%, which classifies as 'flat'.", "metadata": {"future_return": 0.00239, "horizon_days": 21, "hist_return": 0.006717, "annualized_vol": 0.002338, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250122_0418", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2025-01-22", "context_summary": "XLK over past 60 days: cumulative return +3.5%, annualized vol 20.0%. Market regime: sideways.", "question": "Asset: XLK\nHistorical prices (past 60 trading days): start=113.18, end=117.15, cumulative_return=+3.5%, annualized_volatility=20.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.28, 't10y3m_spread': 0.21, 'breakeven_10y': 2.38, 'hy_oas': 2.66, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 7.04, 'vix': 15.0600004196167}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 2024-12-04 0000104169 2024-08-01 2024-10-31 0000104169 2023-08-01 2023-10-31 0000104169 2023-02-01 2023-10-31 0000104169 2024-10-31 0000104169 2024-01-31 0000104169 2023-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-08-01 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of XLK over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.02701, "explanation": "The actual 21-day forward return for XLK starting 2025-01-22 was -2.70%, which classifies as 'negative'.", "metadata": {"future_return": -0.02701, "horizon_days": 21, "hist_return": 0.035095, "annualized_vol": 0.200461, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250806_0421", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-08-06", "context_summary": "AVAX-USD over past 60 days: cumulative return +5.9%, annualized vol 61.5%. Market regime: bull.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=20.68, end=21.90, cumulative_return=+5.9%, annualized_volatility=61.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.5, 't10y3m_spread': -0.12, 'breakeven_10y': 2.36, 'hy_oas': 2.98, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 17.850000381469727}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.098637, "explanation": "The actual 21-day forward return for AVAX-USD starting 2025-08-06 was +9.86%, which classifies as 'positive'.", "metadata": {"future_return": 0.098637, "horizon_days": 21, "hist_return": 0.059408, "annualized_vol": 0.614551, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250901_0424", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2025-09-01", "context_summary": "CSHI over past 60 days: cumulative return +0.8%, annualized vol 0.9%. Market regime: bull.", "question": "Asset: CSHI\nHistorical prices (past 60 trading days): start=47.76, end=48.13, cumulative_return=+0.8%, annualized_volatility=0.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.64, 't10y3m_spread': 0.0, 'breakeven_10y': 2.41, 'hy_oas': 2.84, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.56, 'vix': 15.359999656677246}\nMarket regime: bull\n\nPredict whether the return of CSHI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.003017, "explanation": "The actual 21-day forward return for CSHI starting 2025-09-01 was +0.30%, which classifies as 'flat'.", "metadata": {"future_return": 0.003017, "horizon_days": 21, "hist_return": 0.007742, "annualized_vol": 0.00892, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250929_0427", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-09-29", "context_summary": "XLV over past 60 days: cumulative return +0.5%, annualized vol 15.3%. Market regime: bull.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=133.76, end=134.37, cumulative_return=+0.5%, annualized_volatility=15.3%\nMacro context: {'fed_funds_rate': 4.09, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.57, 't10y3m_spread': 0.18, 'breakeven_10y': 2.38, 'hy_oas': 2.75, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.3, 'vix': 15.289999961853027}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": 0.070272, "explanation": "The actual 21-day forward return for XLV starting 2025-09-29 was +7.03%, which classifies as 'positive'.", "metadata": {"future_return": 0.070272, "horizon_days": 21, "hist_return": 0.004573, "annualized_vol": 0.15283, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250502_0430", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-05-02", "context_summary": "ETH-USD over past 60 days: cumulative return -14.3%, annualized vol 72.5%. Market regime: bear.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=2145.57, end=1839.22, cumulative_return=-14.3%, annualized_volatility=72.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.55, 't10y3m_spread': -0.06, 'breakeven_10y': 2.25, 'hy_oas': 3.78, 'ig_oas': 1.09, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 24.600000381469727}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.371049, "explanation": "The actual 21-day forward return for ETH-USD starting 2025-05-02 was +37.10%, which classifies as 'positive'.", "metadata": {"future_return": 0.371049, "horizon_days": 21, "hist_return": -0.142783, "annualized_vol": 0.725005, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250509_0432", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-05-09", "context_summary": "SOL-USD over past 60 days: cumulative return +38.6%, annualized vol 73.9%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=118.29, end=163.96, cumulative_return=+38.6%, annualized_volatility=73.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.47, 't10y3m_spread': 0.03, 'breakeven_10y': 2.29, 'hy_oas': 3.51, 'ig_oas': 1.02, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 22.479999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.096012, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-05-09 was -9.60%, which classifies as 'negative'.", "metadata": {"future_return": -0.096012, "horizon_days": 21, "hist_return": 0.386071, "annualized_vol": 0.739158, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251114_0435", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2025-11-14", "context_summary": "ICSH over past 60 days: cumulative return +0.7%, annualized vol 0.4%. Market regime: sideways.", "question": "Asset: ICSH\nHistorical prices (past 60 trading days): start=49.44, end=49.77, cumulative_return=+0.7%, annualized_volatility=0.4%\nMacro context: {'fed_funds_rate': 3.88, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.53, 't10y3m_spread': 0.15, 'breakeven_10y': 2.28, 'hy_oas': 3.09, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.24, 'vix': 20.0}\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": 0.003143, "explanation": "The actual 21-day forward return for ICSH starting 2025-11-14 was +0.31%, which classifies as 'flat'.", "metadata": {"future_return": 0.003143, "horizon_days": 21, "hist_return": 0.006675, "annualized_vol": 0.003631, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251202_0438", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-12-02", "context_summary": "AVAX-USD over past 60 days: cumulative return -59.3%, annualized vol 74.0%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=31.36, end=12.78, cumulative_return=-59.3%, annualized_volatility=74.0%\nMacro context: {'fed_funds_rate': 3.89, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.55, 't10y3m_spread': 0.28, 'breakeven_10y': 2.24, 'hy_oas': 2.94, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.23, 'vix': 17.239999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.107343, "explanation": "The actual 21-day forward return for AVAX-USD starting 2025-12-02 was -10.73%, which classifies as 'negative'.", "metadata": {"future_return": -0.107343, "horizon_days": 21, "hist_return": -0.592565, "annualized_vol": 0.739677, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250312_0441", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["REZ"], "decision_date": "2025-03-12", "context_summary": "REZ over past 60 days: cumulative return +1.5%, annualized vol 18.9%. Market regime: sideways.", "question": "Asset: REZ\nHistorical prices (past 60 trading days): start=81.54, end=82.73, cumulative_return=+1.5%, annualized_volatility=18.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.34, 't10y3m_spread': -0.06, 'breakeven_10y': 2.31, 'hy_oas': 3.22, 'ig_oas': 0.94, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 26.920000076293945}\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": -0.061065, "explanation": "The actual 21-day forward return for REZ starting 2025-03-12 was -6.11%, which classifies as 'negative'.", "metadata": {"future_return": -0.061065, "horizon_days": 21, "hist_return": 0.014614, "annualized_vol": 0.188963, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250722_0444", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-07-22", "context_summary": "EEM over past 60 days: cumulative return +14.6%, annualized vol 12.8%. Market regime: bull.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=42.50, end=48.70, cumulative_return=+14.6%, annualized_volatility=12.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.53, 't10y3m_spread': -0.03, 'breakeven_10y': 2.4, 'hy_oas': 2.89, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.75, 'vix': 16.649999618530273}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-21] [\"Crypto Whales Drive $4 Trillion Market Revival on Policy Optimism (Bloomberg) -- A relentless wave of optimism is sweeping the nearly $4 trillion crypto market, driven by a frenzy of Washington policy moves accelerating its assimilation into regulated finance. The passage of a landmark stablecoin law and broader legislative momentum have injected new legitimacy into the sector, lifting prices and rekindling risk appetite across digital assets. Most Read from Bloomberg Why the Federal Reserve\\u2019s Building Renovation Costs $2.5 Billion Milan Corruption Probe Casts Shadow Over Property Boom How San Jose\\u2019s Mayor Is Working to Build an AI Capital Signs of retail re-engagement are resurfacing. Coinbase\\u2019s app surged to fifth place in Apple\\u2019s Finance category, up from 25th a month earlier, according to data tracker Sensor Tower. Google searches for \\u201cBitcoin\\u201d are climbing. Telegram groups and Discord forums saw spirited activity during Washington\\u2019s \\u201cCrypto Week,\\u201d a highly choreographed policy blitz that culminated in President Donald Trump signing the first major US stablecoin framework into law. That spike in visibility, however, belies a more complex picture of who\\u2019s actually driving flows. While consumer interest is returning, the rally\\u2019s architecture is distinctly institutional. Large private holders \\u2014 those controlling 10,000 Bitcoin or more \\u2014 acquired roughly 47,000 tokens ahead of Bitcoin\\u2019s all-time high of about $123,000 on July 14, 10x Research data show. Since then, these substantial holders have begun to unwind positions, contributing to a pullback to around $118,600. Much of the re-engagement started about a month ago, after stablecoin issuer Circle Internet Group Inc.\\u2019s blockbuster June initial public offering, according to Chris Rhine, head of liquid active strategies at Galaxy Digital. \\u201cIt\\u2019s encouraged all investors to get re-engaged\\u2014 small retail to large institutions,\\u201d Rhine said. \\u201cWe have institutions calling us now, asking how to position around stablecoins. The sense of urgency is there.\\u201d That urgency, however, is not translating into core retail metrics yet \\u2014 at least as it comes to quarterly results. Coinbase Global Inc., which reports on July 31, likely saw its second-quarter trading volumes fall 44% from the previous quarter and 3% year-on-year, according to Oppenheimer & Co. Wallet app downloads for the exchange\\u2019s recently re-named other main app, Coinbase Wallet, dropped 51% quarter-on-quarter, with similar declines observed across other major exchanges, according to Sensor Tower. Much of the speculative attention once directed at tokens has shifted elsewhere. Analysts note retail investors have pivoted towards AI-linked equities and crypto-adjacent names such as Strategy, where volatility and narrative appeal remain high. Some retail participants have exited the market entirely, citing macroeconomic concerns and \\u2\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": 0.006474, "explanation": "The actual 21-day forward return for EEM starting 2025-07-22 was +0.65%, which classifies as 'flat'.", "metadata": {"future_return": 0.006474, "horizon_days": 21, "hist_return": 0.145843, "annualized_vol": 0.127748, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251125_0447", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-11-25", "context_summary": "VLUE over past 60 days: cumulative return +8.9%, annualized vol 15.7%. Market regime: sideways.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=117.21, end=127.65, cumulative_return=+8.9%, annualized_volatility=15.7%\nMacro context: {'fed_funds_rate': 3.88, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.58, 't10y3m_spread': 0.13, 'breakeven_10y': 2.23, 'hy_oas': 3.15, 'ig_oas': 0.85, 'ted_spread': 0.09, 'mortgage_30y': 6.26, 'vix': 20.520000457763672}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2025-11-19] nvda-20251026 0001045810 1/25 2026 Q3 FALSE 478 469 278 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:investment nvda:segment 0001045810 2025-01-27 2025-10-26 0001045810 2025-11-14 0001045810 2025-07-28 2025-10-26 0001045810 2024-07-29 2024-10-27 0001045810 2024-01-29 2024-10-27 0001045810 2025-10-26 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 2025-07-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-27 0001045810 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us-gaap:ResearchAndDevelopmentExpenseMember 2024-01-29 2024-10-27 0001045810 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2025-07-28 2025-10-26 0001045810 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2024-07-29 2024-10-27 0001045810 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2025-01-27 2025-10-26 0001045810 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2024-01-29 2024-10-27 0001045810 nvda:RSUsPSUsandMarketbasedPSUsMember 2025-01-26 0001045810 nvda:RSUsPSUsandMarketbasedPSUsMember 2025-01-27 2025-10-26 0001045810 nvda:RSUsPSUsandMarketbasedPSUsMember 2025-10-26 0001045810 us-gaap:EmployeeStockMember 2025-01-27 2025-10-26 0001045810 us-gaap:USTreasurySecuritiesMember 2025-10-26 0001045810 us-gaap:CorporateDebtSecuritiesMember 2025-10-26 0001045810 us-gaap:MoneyMarketFundsMember 2025-10-26 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-10-26 0001045810 us-gaap:CertificatesOfDepositMember 2025-10-26 0001045810 us-gaap:ForeignGovernmentDebtMember 2025-10-26 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2025-10-26 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2025-10-26 0001045810 2025-01-27 2025-04-27 0001045810 us-gaap:CorporateDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:USTreasurySecuritiesMember 2025-01-26 0001045810 us-gaap:MoneyMarketFundsMember 2025-01-26 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:ForeignGovernmentDebtMember 2025-01-26 0001045810 us-gaap:CertificatesOfDepositMember 2025-01-26 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2025-01-26 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2025-01-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-10-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-01-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-10-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:CustomerOneMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerTwoMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerThreeMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerFourMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:Cust [...TRUNCATED...] President, Operations Adoption 9/9/2025 309,840 12/31/2026 Donald Robertson Vice President and Chief Accounting Officer Adoption 9/18/2025 138,042 * 12/31/2026 Ajay Puri Executive Vice President, Worldwide Field Operations Adoption 9/19/2025 1,000,000 6/24/2026 * Includes 38,042 shares from future vests of equity awards, and the actual number of shares to be sold will be net of shares withheld by the Company for taxes. 42 Item 6. Exhibits Exhibit No.  Exhibit Description 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 43 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 19, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 44\n\nPredict whether the return of VLUE over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.004815, "explanation": "The actual 21-day forward return for VLUE starting 2025-11-25 was +0.48%, which classifies as 'flat'.", "metadata": {"future_return": 0.004815, "horizon_days": 21, "hist_return": 0.08905, "annualized_vol": 0.157236, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20251119_0450", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-11-19", "context_summary": "EFA over past 60 days: cumulative return +1.0%, annualized vol 10.6%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=90.26, end=91.15, cumulative_return=+1.0%, annualized_volatility=10.6%\nMacro context: {'fed_funds_rate': 3.88, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.54, 't10y3m_spread': 0.18, 'breakeven_10y': 2.27, 'hy_oas': 3.2, 'ig_oas': 0.85, 'ted_spread': 0.09, 'mortgage_30y': 6.24, 'vix': 24.690000534057617}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CVX 2025-11-06] cvx-20250930 0000093410 12/31 2025 Q3 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cvx:segment cvx:lawsuit cvx:state cvx:tribe cvx:parish 0000093410 2025-01-01 2025-09-30 0000093410 2025-09-30 0000093410 2025-07-01 2025-09-30 0000093410 2024-07-01 2024-09-30 0000093410 2024-01-01 2024-09-30 0000093410 2024-12-31 0000093410 2023-12-31 0000093410 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-06-30 0000093410 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2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-09-30 0000093410 [...TRUNCATED...] 160; $154.38 16,620,000   (1) Includes common shares repurchased from participants in the company’s executive compensation plans for personal income tax withholdings. (2) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections During the three months ended September 30, 2025, none of our directors or executive officers adopted, modified or terminated a Rule 10b5-1 trading arrangement or a non-Rule 10b5-1 trading arrangement, as such terms are defined in Item 408 of Regulation S-K. 47 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 4.1 Fourth Supplemental Indenture, dated as of August 13, 2025, among Chevron U.S.A. Inc., Chevron Corporation, as guarantor, and Deutsche Bank Trust Company Americas, as trustee, filed as Exhibit 4. 2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 4.2 Forms of 3.950% Notes Due 2027, 4.050% Notes Due 2028, Floating Rate Notes Due 2028-B, 4.300% Notes Due 2030, Floating Rate Notes due 2030, 4.500% Notes Due 2032 and 4.850% Notes Due 2035, contained in Exhibit 4.2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 10.1+* Aircraft Time-Sharing Agreement, dated as of February 24, 2015, between Hess Corporation and John B. Hess. 10.2* Transition Services Agreement, dated as of July 14, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.3* Amendment One to Transition Services Agreement, dated as of August 27, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.4* Membership Interest Purchase Agreement, dated as of September 10, 2025, between Hess Corporation and JBH Ventures, LLC . 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ + Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 48 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 6, 2025 49\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": 0.030048, "explanation": "The actual 21-day forward return for EFA starting 2025-11-19 was +3.00%, which classifies as 'positive'.", "metadata": {"future_return": 0.030048, "horizon_days": 21, "hist_return": 0.009793, "annualized_vol": 0.105663, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250715_0452", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLE"], "decision_date": "2025-07-15", "context_summary": "XLE over past 60 days: cumulative return +11.5%, annualized vol 20.8%. Market regime: bull.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=38.61, end=43.05, cumulative_return=+11.5%, annualized_volatility=20.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.53, 't10y3m_spread': 0.01, 'breakeven_10y': 2.39, 'hy_oas': 2.95, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 17.200000762939453}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-14] [\"1 Small-Cap Stock on Our Buy List and 2 to Turn Down Small-cap stocks can be incredibly lucrative investments because their lack of analyst coverage leads to frequent mispricings. However, these businesses (and their stock prices) often stay small because their subscale operations make it harder to expand their competitive moats. These trade-offs can cause headaches for even the most seasoned professionals, which is why we started StockStory - to help you separate the good companies from the bad. That said, here is one small-cap stock that could amplify your portfolio\\u2019s returns and two best left ignored. Market Cap: $3.30 billion Co-founded by former Apple CEO John Sculley, Zeta Global (NYSE:ZETA) provides software and data analytics tools that help companies market their products to billions of customers. Why Does ZETA Give Us Pause? Zeta\\u2019s stock price of $13.92 implies a valuation ratio of 2.3x forward price-to-sales. To fully understand why you should be careful with ZETA, check out our full research report (it\\u2019s free). Market Cap: $2.85 billion Constructing electrical and phone lines in the American Midwest dating back to the 1890s, MYR Group (NASDAQ:MYRG) is a specialty contractor in the electrical construction industry. Why Is MYRG Risky? At $183.66 per share, MYR Group trades at 29.3x forward P/E. Read our free research report to see why you should think twice about including MYRG in your portfolio, it\\u2019s free. Market Cap: $1.53 billion Pioneering the intersection of traditional banking and financial technology in the Pacific Northwest, Coastal Financial (NASDAQ:CCB) operates as a bank holding company that provides traditional banking services and Banking-as-a-Service (BaaS) solutions to consumers and businesses. Why Are We Bullish on CCB? Coastal Financial is trading at $101.56 per share, or 3.1x forward P/B. Is now the time to initiate a position? Find out in our full research report, it\\u2019s free. The market surged in 2024 and reached record highs after Donald Trump\\u2019s presidential victory in November, but questions about new economic policies are adding much uncertainty for 2025. While the crowd speculates what might happen next, we\\u2019re homing in on the companies that can succeed regardless of the political or macroeconomic environment. Put yourself in the driver\\u2019s seat and build a durable portfolio by checking out our Top 6 Stocks for this week. This is a curated list of our High Quality stocks that have generated a market-beating return of 183% over the last five years (as of March 31st 2025). Stocks that made our list in 2020 include now familiar names such as Nvidia (+1,545% between March 2020 and March 2025) as well as under-the-radar businesses like the once-micro-cap company Tecnoglass (+1,754% five-year return). Find your next big winner with StockStory today for free. Find your next big winner with StockStory today. Find your next big winner with StockStory today StockStory is growing and hi\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": -0.014273, "explanation": "The actual 21-day forward return for XLE starting 2025-07-15 was -1.43%, which classifies as 'negative'.", "metadata": {"future_return": -0.014273, "horizon_days": 21, "hist_return": 0.11502, "annualized_vol": 0.207512, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250718_0455", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2025-07-18", "context_summary": "^VIX over past 60 days: cumulative return -46.0%, annualized vol 99.6%. Market regime: bull.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=30.57, end=16.52, cumulative_return=-46.0%, annualized_volatility=99.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.56, 't10y3m_spread': 0.06, 'breakeven_10y': 2.43, 'hy_oas': 2.91, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.75, 'vix': 16.520000457763672}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-17] [\"DraftKings Drops \\u2018Diverse\\u2019 and \\u2018Inclusive\\u2019 From Public Statement, Internal Emails Show The firm said it was \\u201cdisappointed that Barron\\u2019s is reporting on a confidential internal email exchange on which a reporter was mistakenly copied.\\u201d\", \"Intel\\u2019s Fall Was Two Decades In the Making. Can It Turn Things Around? Once the king of chipmaking, Intel\\u2019s decline has been one for the ages, with its stock down two-thirds from its 2020 high. Almost two decades ago, new technologies slowly began to challenge Intel dominance: Arm -based CPUs and Nvidia accelerated GPU computing. Intel\\u2019s customers mostly said that they weren\\u2019t interested in those alternatives.\", \"These Were the 2 Best-Performing Stocks in the Nasdaq-100 in June 2025 The Nasdaq-100 Index performed very well in the month of June. The two top performers saw their prices increase nearly 5 times the index. Micron Technology and Arm Holdings were major winners for their shareholders. 10 stocks we like better than Micron Technology \\u203a The Nasdaq-100 index had an outstanding month in June. The index, consisting of the 100 largest non-financial stocks listed on the Nasdaq stock market, gained 6.3% in June. The two powerhouse technology stocks below, however, performed even better. Here's how well they did -- and why. Micron Technology's (NASDAQ: MU) share price increased 30.5% last month. That made it the Nasdaq-100's top performer. Micron designs and manufactures data storage products that have uses in generative artificial intelligence (AI), an area that has garnered plenty of investors' interest lately given that it's in the early days of what many believe is a massive growth opportunity. In late June, the company reported fiscal third-quarter results for the period ended on May 29. Micron Technology reported revenue of $9.3 billion, a 15.5% increase from the previous quarter and up 36.6% from a year ago. The company's high-bandwidth memory (HBM) used for AI training had quarter-over-quarter revenue growth of 50%. Management forecasts revenue of $10.4 billion to $11 billion for the fourth quarter, a 15% rise from the third quarter at the midpoint of its guidance. Arm Holdings (NASDAQ: ARM) stock appreciated by 29.9% in June. The company designs, develops, and licenses central processing units (CPUs) for semiconductor and original equipment manufacturing companies like Apple and Nvidia. Arm Holdings' stock price has been volatile this year, with the shares dropping from about $122 to $85 in April after large across-the-board tariffs were announced. The shares subsequently recovered and closed at nearly $146 on July 11. June's price movement appears tied to broader positive sentiment after the Trump administration delayed some tariff implementations. Arm Holdings reported fiscal fourth-quarter results in early May. Revenue for the period ended on March 31 grew 34% year over year to $1.2 billion. Before you buy stock in Micron Technology, consid\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": -0.086533, "explanation": "The actual 21-day forward return for ^VIX starting 2025-07-18 was -8.65%, which classifies as 'negative'.", "metadata": {"future_return": -0.086533, "horizon_days": 21, "hist_return": -0.459601, "annualized_vol": 0.996346, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250820_0457", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-08-20", "context_summary": "XLY over past 60 days: cumulative return +9.3%, annualized vol 16.6%. Market regime: bull.", "question": "Asset: XLY\nHistorical prices (past 60 trading days): start=104.50, end=114.27, cumulative_return=+9.3%, annualized_volatility=16.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.55, 't10y3m_spread': 0.0, 'breakeven_10y': 2.35, 'hy_oas': 2.9, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.58, 'vix': 15.56999969482422}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-08-19] [\"Arm hires Amazon AI exec to boost plans to build its own chips SAN FRANCISCO (Reuters) -Arm Holdings (ARM) has hired Amazon.com (AMZN) artificial intelligence chip director Rami Sinno to bolster its plans to develop its own complete chips, a person familiar with the matter said on Monday. Sinno was responsible for helping to develop Amazon's homegrown AI chips called Trainium and Inferentia that are designed to help build and run large AI applications. Until now, Arm has not built its own chips. Instead, it designs the core architecture and instruction set for processors that it sells to customers. Chip designers like Apple (AAPL) and Nvidia (NVDA) use Arm technology in their chips. In July, Arm disclosed plans to invest a portion of its profit into building its own chips and other components. CEO Rene Haas discussed the possibility of moving beyond designs and building chiplets - smaller, function-specific versions of a chip that are stitched together - and complete systems. The company, which is majority-owned by the SoftBank Group (9984.T, SFTBY), collects royalty payments on the chips its customers sell. Arm-based devices power nearly every smartphone in the world and server chips based on its intellectual property have made significant inroads in the data center market long dominated by Advanced Micro Devices (AMD) and Intel (INTC). As part of a broad plan to increase its business, Arm has sought to expand beyond supplying crucial chip intellectual property to building its own complete designs. Reuters first reported on the company's plans outlined in sealed exhibits from a December trial, and its effort to hire executives from rivals in February. In recent years, Arm has sought to bolster its teams focused on building complete chips and systems. The company has hired Nicolas Dube, an executive from HPE with large-scale systems design experience, and Steve Halter, a chip engineer from Intel and Qualcomm, as part of the effort, the person familiar with the matter said. Sinno's effort at Amazon was part of the company's effort to design chips that would be cheaper and offer superior performance to Nvidia's graphics processors used for AI work. (Reporting by Max A. Cherney in San Francisco; Editing by Matthew Lewis)\", \"How Ethereum Treasury Companies are Following the BTC Playbook \\u201cA journey of a thousand miles begins with a single step.\\u201d ~ Lao Tzu Did you know that, since its inception, Bitcoin has been the best-performing asset class worldwide? In fact, at its current $2.27 trillion valuation, Bitcoin has even surpassed silver to become the world\\u2019s fifth largest asset class \\u2013 only behind Nvidia (NVDA), Microsoft (MSFT), Apple (AAPL), Alphabet (GOOGL), Amazon (AMZN), and gold! However, until the past few years, bold and daring retail investors enjoyed most of Bitcoin\\u2019s meteoric rise while most public companies, outside of crypto exchange giant Coinbase Global (COIN), have cashed in on the move. That is, until Strateg\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": 0.056126, "explanation": "The actual 21-day forward return for XLY starting 2025-08-20 was +5.61%, which classifies as 'positive'.", "metadata": {"future_return": 0.056126, "horizon_days": 21, "hist_return": 0.093466, "annualized_vol": 0.166315, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250805_0459", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-08-05", "context_summary": "XRP-USD over past 60 days: cumulative return +12.8%, annualized vol 58.9%. Market regime: bull.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=2.16, end=2.44, cumulative_return=+12.8%, annualized_volatility=58.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.53, 't10y3m_spread': -0.13, 'breakeven_10y': 2.37, 'hy_oas': 3.02, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 17.520000457763672}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for XRP-USD starting 2025-08-05 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.128241, "annualized_vol": 0.589393, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251224_0462", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2025-12-24", "context_summary": "TLH over past 60 days: cumulative return -0.5%, annualized vol 6.6%. Market regime: sideways.", "question": "Asset: TLH\nHistorical prices (past 60 trading days): start=101.00, end=100.52, cumulative_return=-0.5%, annualized_volatility=6.6%\nMacro context: {'fed_funds_rate': 3.64, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.7, 't10y3m_spread': 0.53, 'breakeven_10y': 2.24, 'hy_oas': 2.83, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.21, 'vix': 14.0}\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": -0.003919, "explanation": "The actual 21-day forward return for TLH starting 2025-12-24 was -0.39%, which classifies as 'flat'.", "metadata": {"future_return": -0.003919, "horizon_days": 21, "hist_return": -0.004731, "annualized_vol": 0.066083, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250106_0464", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DBA"], "decision_date": "2025-01-06", "context_summary": "DBA over past 60 days: cumulative return +6.8%, annualized vol 12.9%. Market regime: sideways.", "question": "Asset: DBA\nHistorical prices (past 60 trading days): start=23.93, end=25.57, cumulative_return=+6.8%, annualized_volatility=12.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.32, 't10y3m_spread': 0.26, 'breakeven_10y': 2.34, 'hy_oas': 2.81, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.91, 'vix': 16.1299991607666}\nMarket regime: sideways\n\nPredict whether the return of DBA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.043511, "explanation": "The actual 21-day forward return for DBA starting 2025-01-06 was +4.35%, which classifies as 'positive'.", "metadata": {"future_return": 0.043511, "horizon_days": 21, "hist_return": 0.068304, "annualized_vol": 0.129238, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251222_0467", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2025-12-22", "context_summary": "XLE over past 60 days: cumulative return -4.0%, annualized vol 18.4%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=45.27, end=43.47, cumulative_return=-4.0%, annualized_volatility=18.4%\nMacro context: {'fed_funds_rate': 3.64, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.68, 't10y3m_spread': 0.54, 'breakeven_10y': 2.24, 'hy_oas': 2.9, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.21, 'vix': 14.90999984741211}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 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0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-30 0000104169 us-gaap:ParentMember 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-04-30 0000104169 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-05-01 2025-07-31 0000104169 us-gaap:ParentMember 2025-05-01 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-05-01 2025-07-31 0000104169 2025-05-01 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-05-01 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-31 0000104169 us-gaap:ParentMember 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-08-01 2025-10-31 0000104169 us-gaap:ParentMember 2025-08-01 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-08-01 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-08-01 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\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": 0.01131, "explanation": "The actual 21-day forward return for XLE starting 2025-12-22 was +1.13%, which classifies as 'positive'.", "metadata": {"future_return": 0.01131, "horizon_days": 21, "hist_return": -0.039729, "annualized_vol": 0.183553, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20251217_0470", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2025-12-17", "context_summary": "QQQ over past 60 days: cumulative return +2.3%, annualized vol 17.7%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=596.68, end=610.19, cumulative_return=+2.3%, annualized_volatility=17.7%\nMacro context: {'fed_funds_rate': 3.64, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.67, 't10y3m_spread': 0.51, 'breakeven_10y': 2.23, 'hy_oas': 2.98, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.22, 'vix': 16.479999542236328}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-10-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-10-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-10-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-10-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-10-31 0000104169 2025-12-02 0000104169 2025-08-01 2025-10-31 0000104169 2024-08-01 2024-10-31 0000104169 2024-02-01 2024-10-31 0000104169 2025-10-31 0000104169 2025-01-31 0000104169 2024-10-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-30 0000104169 us-gaap:ParentMember 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-04-30 0000104169 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-05-01 2025-07-31 0000104169 us-gaap:ParentMember 2025-05-01 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-05-01 2025-07-31 0000104169 2025-05-01 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-05-01 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-31 0000104169 us-gaap:ParentMember 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-08-01 2025-10-31 0000104169 us-gaap:ParentMember 2025-08-01 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-08-01 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-08-01 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\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": 0.024469, "explanation": "The actual 21-day forward return for QQQ starting 2025-12-17 was +2.45%, which classifies as 'positive'.", "metadata": {"future_return": 0.024469, "horizon_days": 21, "hist_return": 0.022651, "annualized_vol": 0.17673, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20251117_0473", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DBA"], "decision_date": "2025-11-17", "context_summary": "DBA over past 60 days: cumulative return -4.9%, annualized vol 12.0%. Market regime: sideways.", "question": "Asset: DBA\nHistorical prices (past 60 trading days): start=26.47, end=25.18, cumulative_return=-4.9%, annualized_volatility=12.0%\nMacro context: {'fed_funds_rate': 3.88, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.52, 't10y3m_spread': 0.19, 'breakeven_10y': 2.28, 'hy_oas': 3.07, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.24, 'vix': 19.82999992370605}\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": "flat", "answer_numeric": -0.00681, "explanation": "The actual 21-day forward return for DBA starting 2025-11-17 was -0.68%, which classifies as 'flat'.", "metadata": {"future_return": -0.00681, "horizon_days": 21, "hist_return": -0.048505, "annualized_vol": 0.120158, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250410_0476", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2025-04-10", "context_summary": "XLRE over past 60 days: cumulative return -1.4%, annualized vol 20.9%. Market regime: bear.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=38.43, end=37.89, cumulative_return=-1.4%, annualized_volatility=20.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.43, 't10y3m_spread': -0.01, 'breakeven_10y': 2.27, 'hy_oas': 4.37, 'ig_oas': 1.21, 'ted_spread': 0.09, 'mortgage_30y': 6.64, 'vix': 33.619998931884766}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-09] Trump Trade: U.S. President threatens additional tariffs on China of 50% Catch up on the top industries and stocks that were impacted, or were predicted to be impacted, by the comments, actions and policies of President Donald Trump with this daily recap compiled by The Fly: Discover outperforming stocks and invest smarter with Top Smart Score Stocks. Filter, analyze, and streamline your search for investment opportunities using Tipranks' Stock Screener. ADDITIONAL TARIFFS: In a post to Truth Social, President Donald Trump stated, \u201cYesterday, China issued Retaliatory Tariffs of 34%, on top of their already record setting Tariffs, Non-Monetary Tariffs, Illegal Subsidization of companies, and massive long term Currency Manipulation, despite my warning that any country that Retaliates against the U.S. by issuing additional Tariffs, above and beyond their already existing long term Tariff abuse of our Nation, will be immediately met with new and substantially higher Tariffs, over and above those initially set. Therefore, if China does not withdraw its 34% increase above their already long term trading abuses by tomorrow, April 8th, 2025, the United States will impose ADDITIONAL Tariffs on China of 50%, effective April 9th. Additionally, all talks with China concerning their requested meetings with us will be terminated! Negotiations with other countries, which have also requested meetings, will begin taking place immediately. Thank you for your attention to this matter!\u201d EXPORTER TAX CREDIT: Trump administration officials are debating the merits of creating a new exporter tax credit, which would be geared toward boosting U.S. manufacturers and issued at the end of the year to offset the effects of retaliatory tariffs as American companies seek to sell their goods in foreign markets, sources familiar with the matter told Bloomberg\u2019s Nancy Cook and Saleha Mohsin. COUNTER-TARIFFS: The European Commission proposed counter-tariffs of 25% on a range of U.S. goods on Monday in response to President Donald Trump\u2019s tariffs on steel and aluminum, a document seen by Reuters showed. The tariffs on some goods will come into effect May 16 and others on December 1, according to the document, which also showed that bourbon was removed from the original list the Commission was weighing in March. GREAT CALL WITH SOUTH KOREA: President Trump said via Truth Social, \u201cI just had a great call with the Acting President of South Korea. We talked about their tremendous and unsustainable Surplus, Tariffs, Shipbuilding, large scale purchase of U.S. LNG, their joint venture in an Alaska Pipeline, and payment for the big time Military Protection we provide to South Korea. They began these Military payments during my first term, Billions of Dollars, but Sleepy Joe Biden, for reasons unknown, terminated the deal. That was a shocker to all! In any event, we have the confines and probability of a great DEAL for both countries. Their top TEAM is on a plane heading to the U.S., and thi\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": 0.084158, "explanation": "The actual 21-day forward return for XLRE starting 2025-04-10 was +8.42%, which classifies as 'positive'.", "metadata": {"future_return": 0.084158, "horizon_days": 21, "hist_return": -0.013969, "annualized_vol": 0.208774, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251010_0478", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2025-10-10", "context_summary": "MTUM over past 60 days: cumulative return +6.5%, annualized vol 10.5%. Market regime: bull.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=237.84, end=253.31, cumulative_return=+6.5%, annualized_volatility=10.5%\nMacro context: {'fed_funds_rate': 4.1, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.54, 't10y3m_spread': 0.11, 'breakeven_10y': 2.34, 'hy_oas': 2.95, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.3, 'vix': 16.43000030517578}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": 0.010601, "explanation": "The actual 21-day forward return for MTUM starting 2025-10-10 was +1.06%, which classifies as 'positive'.", "metadata": {"future_return": 0.010601, "horizon_days": 21, "hist_return": 0.065008, "annualized_vol": 0.10499, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250808_0481", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-08-08", "context_summary": "SOL-USD over past 60 days: cumulative return +8.9%, annualized vol 56.9%. Market regime: bull.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=161.09, end=175.49, cumulative_return=+8.9%, annualized_volatility=56.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.51, 't10y3m_spread': -0.09, 'breakeven_10y': 2.35, 'hy_oas': 2.95, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 16.56999969482422}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.160988, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-08-08 was +16.10%, which classifies as 'positive'.", "metadata": {"future_return": 0.160988, "horizon_days": 21, "hist_return": 0.089372, "annualized_vol": 0.569135, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251120_0484", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-11-20", "context_summary": "DOT-USD over past 60 days: cumulative return -17.1%, annualized vol 84.6%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=4.27, end=3.54, cumulative_return=-17.1%, annualized_volatility=84.6%\nMacro context: {'fed_funds_rate': 3.88, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.55, 't10y3m_spread': 0.18, 'breakeven_10y': 2.27, 'hy_oas': 3.17, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.24, 'vix': 23.65999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for DOT-USD starting 2025-11-20 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": -0.171219, "annualized_vol": 0.846296, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250903_0486", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-09-03", "context_summary": "VLUE over past 60 days: cumulative return +9.7%, annualized vol 12.8%. Market regime: bull.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=106.85, end=117.21, cumulative_return=+9.7%, annualized_volatility=12.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.62, 't10y3m_spread': 0.08, 'breakeven_10y': 2.41, 'hy_oas': 2.92, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.56, 'vix': 17.170000076293945}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-02] [\"Citi Initiates Lumentum With Buy Rating On AI Data Center Growth Citigroup initiated coverage of Lumentum with a buy rating on AI data center growth. Lumentum stock has surged 55% in 2025.\", \"Big Tech\\u2019s Market Dominance Stirs Debate on Concentration Risks (Bloomberg) \\u2014 The unprecedented level of concentration in a handful of tech stocks provokes strong feelings on Wall Street. Some investors fear the top-heaviness means the bull run is on quicksand, and will sink the minute an AI-frenzy-fueled Nvidia Corp. (NVDA) or Microsoft Corp. (MSFT) stumbles. The dominance also leads to portfolio risks, with diversification suffering. For others, the worries are overblown, gains have historically been powered by a small group of megacaps, and this is simply tech\\u2019s latest time to shine. Most Read from Bloomberg Sydney\\u2019s New Airport Will Take Travelers Into the Wild One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Amtrak Debuts New High-Speed Acela Trains After Years of Delays Trump Signs Order to \\u2018Make Federal Architecture Beautiful Again\\u2019 Parents Mobilize to Protect School Commutes Amid Trump Deployment in DC The debate is becoming more urgent as Nividia, Microsoft (MSFT), Apple Inc. (AAPL), Alphabet Inc. (GOOG, GOOGL), Amazon.com Inc. and Meta Platforms Inc. (META) account for more than 30% of the benchmark index, more than three times their weighting from a decade ago. Gains for Nividia, Microsoft and Meta alone account for about 270 points of the S&P 500\\u2019s (^GSPC) 579-point advance in 2025, or nearly half of this year\\u2019s 9.8% rally. For Scott Chronert, Citi Research\\u2019s managing director, the concentration is a badge of honor, well-deserved for a group that continues to deliver unparalleled growth in sales and earnings. The five biggest \\u2014 Nvidia, Microsoft, Apple, Alphabet and Amazon \\u2014 increased profits by 26% in the second quarter, compared with estimates for 15%, according to data compiled by Bloomberg Intelligence. The S&P 500 as a whole saw earnings rise by 11% from a year ago. The biggest tech companies have \\u201cearned\\u201d their weightings as a function of growth metrics, Chronert said. To him, valuations aren\\u2019t stretched based on the profit forecasts that they have consistently been able to meet. On a price/earnings to growth basis, no cause for alarm exists, he said. \\u201cThe PEG ratio for the Mag 7 is not materially different than for the rest of the market,\\u201d Chronert said. Valuation isn\\u2019t an issue, he adds, \\u201cso long as earnings growth expectations are met or beat\\u201d \\u2014 a bar he conceded could be getting harder to surpass as targets swell. Still, there are reasons why the tech megacap domination is likely to persist without incident. They generate vast amount of cash in good economic times and bad, making them growth and defensive plays at the same time. They also stand to get outsize benefits from recent Trump administration policy changes, \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": 0.075068, "explanation": "The actual 21-day forward return for VLUE starting 2025-09-03 was +7.51%, which classifies as 'positive'.", "metadata": {"future_return": 0.075068, "horizon_days": 21, "hist_return": 0.096961, "annualized_vol": 0.127811, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250919_0489", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-09-19", "context_summary": "XLU over past 60 days: cumulative return +4.9%, annualized vol 12.4%. Market regime: bull.", "question": "Asset: XLU\nHistorical prices (past 60 trading days): start=39.41, end=41.32, cumulative_return=+4.9%, annualized_volatility=12.4%\nMacro context: {'fed_funds_rate': 4.08, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.54, 't10y3m_spread': 0.08, 'breakeven_10y': 2.38, 'hy_oas': 2.71, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.26, 'vix': 15.699999809265137}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": 0.061364, "explanation": "The actual 21-day forward return for XLU starting 2025-09-19 was +6.14%, which classifies as 'positive'.", "metadata": {"future_return": 0.061364, "horizon_days": 21, "hist_return": 0.048571, "annualized_vol": 0.124384, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250623_0492", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2025-06-23", "context_summary": "XLP over past 60 days: cumulative return +1.4%, annualized vol 15.4%. Market regime: sideways.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=77.75, end=78.84, cumulative_return=+1.4%, annualized_volatility=15.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.48, 't10y3m_spread': -0.01, 'breakeven_10y': 2.33, 'hy_oas': 3.13, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 20.6200008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-20] [\"Alibaba\\u2019s (BABA) New Qwen3 AI Models Now Compatible With Apple Devices Alibaba Group Holding Limited (NYSE:BABA) is one of the 10 AI Stocks Getting Wall Street\\u2019s Attention. On June 17, South China Morning Post reported that the company updated its Qwen3 family of artificial intelligence (AI) models that could signal the potential roll-out in China of machine-learning technology on a range of Apple devices, including iPhones, iPads, and MacBooks. Alibaba announced the launch of new Qwen3 artificial intelligence models for Apple\\u2019s MLX architecture, announcing in a post on Wechat that the models will be able to run on a range of Apple devices, including iPhone, iPad, MacBook, and Mac. A busy sidewalk filled with people using Apple devices like iPhones, iPads and Apple Watches. The MLX framework is designed to be user-friendly and efficient in training and deploying AI models on Apple\\u2019s silicon hardware. Through this development, Apple is aiming to expand the availability of its Apple Intelligence suite to China. Alibaba Group Holding Limited (NYSE:BABA) is an internet giant that offers e-commerce services in China and internationally. While we acknowledge the potential of BABA as an investment, we believe certain AI stocks offer greater upside potential and carry less downside risk. If you\\u2019re looking for an extremely undervalued AI stock that also stands to benefit significantly from Trump-era tariffs and the onshoring trend, see our free report on the best short-term AI stock. READ NEXT: 10 AI Stocks on Wall Street\\u2019s Radar and 15 AI Stocks Making Waves on Wall Street. Disclosure: None.\", \"Trump Hints He\\u2019ll Hold Off Iran Strike, Give Diplomacy Time (Bloomberg) -- US President Donald Trump signaled he would give diplomacy a chance before deciding whether to strike Iran, dialing back on recent comments that suggested military action could be imminent. Most Read from Bloomberg Security Concerns Hit Some of the World\\u2019s \\u2018Most Livable Cities\\u2019 One Architect\\u2019s Quest to Save Mumbai\\u2019s Heritage From Disappearing JFK AirTrain Cuts Fares 50% This Summer to Lure Riders Off Roads NYC Congestion Toll Cuts Manhattan Gridlock by 25%, RPA Reports Taser-Maker Axon Triggers a NIMBY Backlash in its Hometown \\u201cBased on the fact that there\\u2019s a substantial chance of negotiations that may or may not take place with Iran in the near future, I will make my decision whether or not to go within the next two weeks,\\u201d Trump said in a dictated message, according to White House spokeswoman Karoline Leavitt. Subscribe to the Bloomberg Daybreak Podcast on Apple, Spotify and other Podcast Platforms. Iran maintained Friday it won\\u2019t negotiate with the US while an Israeli assault continues. The only way to end the imposed war is to \\u201cunconditionally stop\\u201d the enemy\\u2019s aggression, Iranian President Masoud Pezeshkian said Friday in a post on X. Oil prices fell following a report from Reuters that Ir\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": 0.003071, "explanation": "The actual 21-day forward return for XLP starting 2025-06-23 was +0.31%, which classifies as 'flat'.", "metadata": {"future_return": 0.003071, "horizon_days": 21, "hist_return": 0.014017, "annualized_vol": 0.153743, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251230_0494", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-12-30", "context_summary": "AVAX-USD over past 60 days: cumulative return -32.1%, annualized vol 65.4%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=18.19, end=12.36, cumulative_return=-32.1%, annualized_volatility=65.4%\nMacro context: {'fed_funds_rate': 3.64, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.67, 't10y3m_spread': 0.44, 'breakeven_10y': 2.22, 'hy_oas': 2.87, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.18, 'vix': 14.199999809265137}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.02044, "explanation": "The actual 21-day forward return for AVAX-USD starting 2025-12-30 was -2.04%, which classifies as 'negative'.", "metadata": {"future_return": -0.02044, "horizon_days": 21, "hist_return": -0.32074, "annualized_vol": 0.653994, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250224_0496", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2025-02-24", "context_summary": "EWJ over past 60 days: cumulative return +2.6%, annualized vol 16.2%. Market regime: sideways.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=64.42, end=66.06, cumulative_return=+2.6%, annualized_volatility=16.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.23, 't10y3m_spread': 0.1, 'breakeven_10y': 2.42, 'hy_oas': 2.78, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.85, 'vix': 18.209999084472656}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K CVX 2025-02-21] cvx-20241231 0000093410 false 2024 FY 367 http://fasb.org/us-gaap/2024#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2024#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#ShortTermBorrowings 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us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2021-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2021-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2022-01-01 2022-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-01-01 2022-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2022-01-01 2022-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2022-01-01 2022-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2022-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2022-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2022-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealized [...TRUNCATED...] Power of Attorney for certain directors of Chevron Corporation, authorizing the signing of the Annual Report on Form 10-K on their behalf. 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer (page E-3). 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer (page E-4).   32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer (page E-5).   32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer (page E-6). 97.1+ Chevron Corporation Dodd-Frank Clawback Policy , filed as Exh i bit 97.1 to Ch ev ron Corporation ’ s Annual Report on Form 10-K for the year ended December 31, 2023, and incorporated herein by r eference . 99.1* Definitions of Selected Energy and Financial Terms (pages E-7 through E-10). 101* Interactive data files (formatted as Inline XBRL). 104* Cover Page Interactive Data File (contained in Exhibit 101).   ___________________________________________ + Indicates a management contract or compensatory plan or arrangement. *      Filed herewith. **      Furnished herewith. Pursuant to Item 601(b)(4) of Regulation S-K, certain instruments with respect to the company’s long-term debt are not filed with this Annual Report on Form 10-K. A copy of any such instrument will be furnished to the Securities and Exchange Commission upon request. 120 Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on the 21st day of February, 2025.  Chevron Corporation   By: /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities indicated on the 21st day of February, 2025.   Principal Executive Officer (and Director) /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer Principal Financial Officer /s/ EIMEAR P. BONNER Eimear P. Bonner, Vice President and Chief Financial Officer Principal Accounting Officer /s/ ALANA K. KNOWLES Alana K. Knowles, Vice President and Controller * By:  /s/ MARY A. FRANCIS Mary A. Francis, Attorney-in-Fact Directors WANDA M. AUSTIN * Wanda M. Austin JOHN B. FRANK * John B. Frank ALICE P. GAST * Alice P. Gast ENRIQUE HERNANDEZ, JR. * Enrique Hernandez, Jr. MARILLYN A. HEWSON * Marillyn A. Hewson JON M. HUNTSMAN JR. * Jon M. Huntsman Jr. CHARLES W. MOORMAN * Charles W. Moorman DAMBISA F. MOYO * Dambisa F. Moyo DEBRA REED-KLAGES * Debra Reed-Klages D. JAMES UMPLEBY III * D. James Umpleby III CYNTHIA J. WARNER * Cynthia J. Warner 121\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": 0.042163, "explanation": "The actual 21-day forward return for EWJ starting 2025-02-24 was +4.22%, which classifies as 'positive'.", "metadata": {"future_return": 0.042163, "horizon_days": 21, "hist_return": 0.025566, "annualized_vol": 0.161739, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250714_0499", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2025-07-14", "context_summary": "MTUM over past 60 days: cumulative return +19.0%, annualized vol 17.7%. Market regime: bull.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=197.31, end=234.84, cumulative_return=+19.0%, annualized_volatility=17.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.53, 't10y3m_spread': 0.02, 'breakeven_10y': 2.37, 'hy_oas': 2.97, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.72, 'vix': 16.399999618530273}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-11] [\"As X loses its CEO, daily usage is down and competition is growing With the departure of X CEO Linda Yaccarino, which was announced Wednesday, the company that defined text-first social networking faces renewed competition. Year-over-year, the Elon Musk-owned social network has seen its daily active user base decline by roughly 10% as of the second quarter of 2025, according to new data provided by app intelligence firm Sensor Tower. While X\\u2019s user base is still 65% larger than Meta\\u2019s Threads and 10 times larger than its next-biggest rival, Bluesky, X\\u2019s lasting victory in this space is not guaranteed. On mobile devices, there\\u2019s already some indication that Threads is catching up. New data from market intelligence provider Similarweb released this week indicates Threads is nearing X\\u2019s daily app users on mobile. In June 2025, Threads\\u2019 mobile app for iOS and Android saw 115.1 million daily active users, representing 127.8% year-over-year growth; X reached 132 million daily actives, as its year-over-year growth declined by 15.2%. Overall, X is still larger than Threads thanks to its more prominent web presence. X also has other advantages, which could make for an interesting fight between the tech giants. On X, user engagement and loyalty remain strong, despite the increased competition from Meta as well as open source social networking movements like Bluesky and Mastodon, and other startups. According to Sensor Tower\\u2019s data, X users spent an average of 31 minutes per day on the platform in the second quarter of 2025, which was nearly quadruple that of Threads, at 8 minutes per day. Plus, nearly half (48%) of X\\u2019s global monthly app users in the quarter interacted with the platform on a daily basis, compared with 33% for Threads, the firm said. But Threads can\\u2019t be counted out yet, simply because X is larger. Though Threads may have fewer daily active users than X, it\\u2019s been seeing stronger growth. Over the past year, Threads\\u2019 global app daily active users were up 160% year-over-year, the Sensor Tower\\u2019s data shows, driven in part by the rollout of new features and functions, as well as by its ties to Meta\\u2019s other apps, like Facebook and Instagram, which serve as funnels. Threads is also laser-focused on growing its ads ecosystem, which is the app\\u2019s only means of monetization for the time being. In April, Meta opened up Threads ads to its global advertisers, and the following month announced tests for video ads, as well. The app has the advantage of being a part of Meta\\u2019s larger ads business, where its tools are already familiar to marketers and where it has the ability to tap into Meta\\u2019s nearly two decades of experience in maximizing ad revenues. Under Yaccarino, X\\u2019s ad ecosystem recovered, but it\\u2019s been a volatile ride. Advertisers in the media and entertainment, shopping, and gaming verticals through 2025 year-to-date represent 25%, 22%, and 7% of total U.S. \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": 0.036161, "explanation": "The actual 21-day forward return for MTUM starting 2025-07-14 was +3.62%, which classifies as 'positive'.", "metadata": {"future_return": 0.036161, "horizon_days": 21, "hist_return": 0.190217, "annualized_vol": 0.177003, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251203_0502", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-12-03", "context_summary": "VTI over past 60 days: cumulative return +4.7%, annualized vol 12.8%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=318.19, end=333.07, cumulative_return=+4.7%, annualized_volatility=12.8%\nMacro context: {'fed_funds_rate': 3.89, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.58, 't10y3m_spread': 0.32, 'breakeven_10y': 2.24, 'hy_oas': 2.92, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.23, 'vix': 16.59000015258789}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2025-11-19] nvda-20251026 0001045810 1/25 2026 Q3 FALSE 478 469 278 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:investment nvda:segment 0001045810 2025-01-27 2025-10-26 0001045810 2025-11-14 0001045810 2025-07-28 2025-10-26 0001045810 2024-07-29 2024-10-27 0001045810 2024-01-29 2024-10-27 0001045810 2025-10-26 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 2025-07-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-27 0001045810 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2025-10-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:CustomerOneMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerTwoMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerThreeMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerFourMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:Cust [...TRUNCATED...] President, Operations Adoption 9/9/2025 309,840 12/31/2026 Donald Robertson Vice President and Chief Accounting Officer Adoption 9/18/2025 138,042 * 12/31/2026 Ajay Puri Executive Vice President, Worldwide Field Operations Adoption 9/19/2025 1,000,000 6/24/2026 * Includes 38,042 shares from future vests of equity awards, and the actual number of shares to be sold will be net of shares withheld by the Company for taxes. 42 Item 6. Exhibits Exhibit No.  Exhibit Description 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 43 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 19, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 44\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 2025-12-03 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.046767, "annualized_vol": 0.12817, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20250612_0505", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2025-06-12", "context_summary": "^VIX over past 60 days: cumulative return -20.5%, annualized vol 143.6%. Market regime: sideways.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=21.70, end=17.26, cumulative_return=-20.5%, annualized_volatility=143.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.47, 't10y3m_spread': -0.04, 'breakeven_10y': 2.27, 'hy_oas': 3.12, 'ig_oas': 0.87, 'ted_spread': 0.09, 'mortgage_30y': 6.85, 'vix': 17.260000228881836}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-11] [\"Snap CEO Evan Spiegel promises new lightweight \\u2018Specs\\u2019 smart glasses next year, in race to beat Meta and Google to market Snapchat, long-known as a featherweight in the league of Big Tech giants, is hoping to best opponents Meta, Google and Apple by releasing its new augmented reality AI-enabled smart glasses months, maybe even years, before the big guys. Speaking at a conference on Tuesday, Snap CEO Evan Spiegel said the company would release a new version of its camera-equipped glasses next year that will incorporate an interactive, AI-enhanced digital screen within the lens. The 2026 release date would be ahead of Meta, which plans to release its AR \\u201cOrion\\u201d glasses in 2027, while Google has not attached a date to its Android XR glasses. \\u201cThe tiny smartphone limited our imagination,\\u201d Spiegel said in his keynote at the Augmented World Expo conference in Long Beach, Calif. \\u201cIt\\u2019s clear that today\\u2019s devices and user interfaces are woefully inadequate to realize the full potential of AI.\\u201d The new \\u201cSnapchat Specs\\u201d will be lightweight and AI-enhanced, Snap said. They will allow users to look at objects in the real world and leverage AI to access information, such as translating ingredients on a label from foreign languages. The glasses will also allow users to interact with the objects on the lens, Snap said, citing examples like playing video games with their eyeballs. The company did not share photos of the Specs frames or provide information on pricing. As part of the Specs announcement, Snapchat shared that operating system partnerships with OpenAI and Google Gemini will extend into experiences for the glasses. If Snap follows through on the promise of 2026 launch, it would be the first Big Tech company to market with augmented reality glasses for mainstream consumers, claiming an early lead in the race to create the successor to the smartphone\\u2014a competition involving everyone from Meta, Google, and Apple, to ChatGPT maker OpenAI, which recently announced a partnership with former Apple design boss Jony Ive. A pioneer in the glasses form factor, Snap made waves with the release of its \\u201cSpectacles\\u201d in 2016. The funky looking glasses were equipped with a camera that allowed users to post photos and short video clips directly to their Snapchat feed. But in recent years, Snap\\u2019s Spectacles have been eclipsed by Meta, which partnered with EssilorLuxottica to release Ray-Ban smart glasses. Though Meta hasn\\u2019t shared financials around its Ray-Ban glasses, EssilorLuxottica noted that the companies have sold over 2 billion glasses since their 2023 debut. Luxottica plans to increase products of the co-branded glasses to 10 million units by 2026, suggesting that the companies are pleased with the results and potential of the glasses. That said, Meta\\u2019s glasses do not have AR capabilities; rather, the glasses have audio-based AI features as well as photo and video capabil\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": -0.0899, "explanation": "The actual 21-day forward return for ^VIX starting 2025-06-12 was -8.99%, which classifies as 'negative'.", "metadata": {"future_return": -0.0899, "horizon_days": 21, "hist_return": -0.204608, "annualized_vol": 1.435744, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250814_0507", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2025-08-14", "context_summary": "SCHP over past 60 days: cumulative return +2.7%, annualized vol 4.0%. Market regime: bull.", "question": "Asset: SCHP\nHistorical prices (past 60 trading days): start=25.51, end=26.21, cumulative_return=+2.7%, annualized_volatility=4.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.57, 't10y3m_spread': -0.05, 'breakeven_10y': 2.37, 'hy_oas': 2.9, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 14.489999771118164}\nMarket regime: bull\n\nPredict whether the return of SCHP over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.017689, "explanation": "The actual 21-day forward return for SCHP starting 2025-08-14 was +1.77%, which classifies as 'positive'.", "metadata": {"future_return": 0.017689, "horizon_days": 21, "hist_return": 0.027369, "annualized_vol": 0.039532, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250618_0509", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2025-06-18", "context_summary": "ACWI over past 60 days: cumulative return +4.6%, annualized vol 19.0%. Market regime: sideways.", "question": "Asset: ACWI\nHistorical prices (past 60 trading days): start=117.76, end=123.17, cumulative_return=+4.6%, annualized_volatility=19.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.45, 't10y3m_spread': -0.03, 'breakeven_10y': 2.31, 'hy_oas': 3.17, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 6.84, 'vix': 21.600000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-17] [\"Life360 Stock Rises On Upbeat Report For Family Tracker Service Life360 stock rose Monday after a Wall Street analyst raised his price target on the family connection and safety company.\", \"Herbal Medicine Stock With No Sales Rallies 64,000% (Bloomberg) \\u2014 A biotech stock focused on herbal medicine has surged by more than 46,000% so far this year and yet, the company itself has made zero revenue \\u2014 much less turned a profit. Most Read from Bloomberg As Part of a $45 Billion Push, ICE Prepares for a Vast Expansion of Detention Space As American Architects Gather in Boston, Retrofits Are All the Rage The unbelievable rally has transformed Regencell Bioscience Holdings Limited, a penny stock as recently as April, to one worth nearly $30 billion in market value. A year ago, the stock had a market capitalization of just $53 million. This is despite the company having a net loss of $4.4 million for its fiscal year that ended June 2024, a 28% decrease from the previous year. Earlier this month the company said its board approved a 38-for-1 stock split. When the split took effect Monday, shares rose 283% \\u2014 their biggest one-day jump in nearly a year on a closing basis \\u2014 to a record high, triggering more than 10 volatility halts. Shares of the company have been on a bizarre, 460-fold tear in 2025, with little to no news from the firm. The Hong Kong-based firm, which debuted on the Nasdaq Capital Market in 2021, is in the research and development stage and has not generated any revenue since inception, according to its most-recent annual filing with the US Securities and Exchange Commission. A representative for Regencell didn\\u2019t respond to a Bloomberg News request for comment. Incorporated in the Cayman Islands, the firm aims to treat neurological disorders like ADHD and autism spectrum disorder through traditional herb-based medicines, according to its website. Its traditional Chinese medicine (TCM) formula, which forms the basis of its product candidates, \\u201ccontains only natural ingredients without any synthetic components.\\u201d \\u201cWe have not generated revenue from any TCM formulae candidates or applied for any regulatory approvals, nor have distribution capabilities or experience or any granted patents or pending patent applications and may never be profitable,\\u201d the company said in an October filing. The company also made its foray into treatments for Covid-19, conducting trials in 2022 for an \\u201cholistic approach\\u201d with its experimental therapy. Regencell said data from a 2022 trial showed the treatment was effective in reducing and eliminating Covid symptoms within six days, although the results were yet to be peer-reviewed. The firm has funded its operations so far, primarily from shareholder loans and proceeds from its initial public offering, the SEC filing showed. It said its gross proceeds from its IPO were $21.85 million, with additional net proceeds of $2.85 million from the issue of the over allotm\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": 0.04401, "explanation": "The actual 21-day forward return for ACWI starting 2025-06-18 was +4.40%, which classifies as 'positive'.", "metadata": {"future_return": 0.04401, "horizon_days": 21, "hist_return": 0.045941, "annualized_vol": 0.190389, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250513_0512", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHH"], "decision_date": "2025-05-13", "context_summary": "SCHH over past 60 days: cumulative return -0.8%, annualized vol 20.9%. Market regime: sideways.", "question": "Asset: SCHH\nHistorical prices (past 60 trading days): start=20.77, end=20.61, cumulative_return=-0.8%, annualized_volatility=20.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.47, 't10y3m_spread': 0.03, 'breakeven_10y': 2.29, 'hy_oas': 3.15, 'ig_oas': 0.97, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 18.38999938964844}\nMarket regime: sideways\n\nPredict whether the return of SCHH over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.023821, "explanation": "The actual 21-day forward return for SCHH starting 2025-05-13 was +2.38%, which classifies as 'positive'.", "metadata": {"future_return": 0.023821, "horizon_days": 21, "hist_return": -0.00794, "annualized_vol": 0.20852, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250429_0515", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-04-29", "context_summary": "SOL-USD over past 60 days: cumulative return -0.1%, annualized vol 99.0%. Market regime: bear.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=148.03, end=147.81, cumulative_return=-0.1%, annualized_volatility=99.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.56, 't10y3m_spread': -0.09, 'breakeven_10y': 2.25, 'hy_oas': 3.73, 'ig_oas': 1.04, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 25.14999961853028}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.150626, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-04-29 was +15.06%, which classifies as 'positive'.", "metadata": {"future_return": 0.150626, "horizon_days": 21, "hist_return": -0.001487, "annualized_vol": 0.989721, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250822_0518", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IYR"], "decision_date": "2025-08-22", "context_summary": "IYR over past 60 days: cumulative return +3.1%, annualized vol 12.9%. Market regime: bull.", "question": "Asset: IYR\nHistorical prices (past 60 trading days): start=91.45, end=94.26, cumulative_return=+3.1%, annualized_volatility=12.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.54, 't10y3m_spread': 0.01, 'breakeven_10y': 2.39, 'hy_oas': 2.95, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.58, 'vix': 16.600000381469727}\nMarket regime: bull\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": -0.009739, "explanation": "The actual 21-day forward return for IYR starting 2025-08-22 was -0.97%, which classifies as 'flat'.", "metadata": {"future_return": -0.009739, "horizon_days": 21, "hist_return": 0.030682, "annualized_vol": 0.128924, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250922_0521", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-09-22", "context_summary": "AVAX-USD over past 60 days: cumulative return +39.7%, annualized vol 71.3%. Market regime: bull.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=23.65, end=33.05, cumulative_return=+39.7%, annualized_volatility=71.3%\nMacro context: {'fed_funds_rate': 4.08, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.57, 't10y3m_spread': 0.11, 'breakeven_10y': 2.39, 'hy_oas': 2.72, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.26, 'vix': 15.449999809265137}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.293239, "explanation": "The actual 21-day forward return for AVAX-USD starting 2025-09-22 was -29.32%, which classifies as 'negative'.", "metadata": {"future_return": -0.293239, "horizon_days": 21, "hist_return": 0.397122, "annualized_vol": 0.712982, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251208_0524", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-12-08", "context_summary": "DOT-USD over past 60 days: cumulative return -13.1%, annualized vol 88.1%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=4.08, end=3.54, cumulative_return=-13.1%, annualized_volatility=88.1%\nMacro context: {'fed_funds_rate': 3.89, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.58, 't10y3m_spread': 0.43, 'breakeven_10y': 2.26, 'hy_oas': 2.85, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.19, 'vix': 15.40999984741211}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for DOT-USD starting 2025-12-08 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": -0.131373, "annualized_vol": 0.880885, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250912_0527", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-09-12", "context_summary": "AVAX-USD over past 60 days: cumulative return +37.1%, annualized vol 70.0%. Market regime: bull.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=21.28, end=29.18, cumulative_return=+37.1%, annualized_volatility=70.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.49, 't10y3m_spread': -0.07, 'breakeven_10y': 2.34, 'hy_oas': 2.78, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.35, 'vix': 14.710000038146973}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.082221, "explanation": "The actual 21-day forward return for AVAX-USD starting 2025-09-12 was +8.22%, which classifies as 'positive'.", "metadata": {"future_return": 0.082221, "horizon_days": 21, "hist_return": 0.370962, "annualized_vol": 0.699875, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250923_0530", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-09-23", "context_summary": "EEM over past 60 days: cumulative return +10.8%, annualized vol 10.6%. Market regime: bull.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=47.41, end=52.52, cumulative_return=+10.8%, annualized_volatility=10.6%\nMacro context: {'fed_funds_rate': 4.09, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.54, 't10y3m_spread': 0.15, 'breakeven_10y': 2.37, 'hy_oas': 2.69, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.26, 'vix': 16.100000381469727}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": 0.018011, "explanation": "The actual 21-day forward return for EEM starting 2025-09-23 was +1.80%, which classifies as 'positive'.", "metadata": {"future_return": 0.018011, "horizon_days": 21, "hist_return": 0.107715, "annualized_vol": 0.105765, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250114_0533", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-01-14", "context_summary": "SOL-USD over past 60 days: cumulative return -11.4%, annualized vol 63.4%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=206.25, end=182.84, cumulative_return=-11.4%, annualized_volatility=63.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.39, 't10y3m_spread': 0.42, 'breakeven_10y': 2.45, 'hy_oas': 2.85, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.93, 'vix': 19.190000534057617}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.100024, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-01-14 was +10.00%, which classifies as 'positive'.", "metadata": {"future_return": 0.100024, "horizon_days": 21, "hist_return": -0.113538, "annualized_vol": 0.63412, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250911_0536", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2025-09-11", "context_summary": "XLRE over past 60 days: cumulative return +0.7%, annualized vol 13.9%. Market regime: bull.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=40.52, end=40.82, cumulative_return=+0.7%, annualized_volatility=13.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.5, 't10y3m_spread': -0.05, 'breakeven_10y': 2.35, 'hy_oas': 2.84, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.5, 'vix': 15.350000381469728}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": -0.036425, "explanation": "The actual 21-day forward return for XLRE starting 2025-09-11 was -3.64%, which classifies as 'negative'.", "metadata": {"future_return": -0.036425, "horizon_days": 21, "hist_return": 0.007361, "annualized_vol": 0.139087, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250605_0539", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-06-05", "context_summary": "XLB over past 60 days: cumulative return +3.7%, annualized vol 22.4%. Market regime: sideways.", "question": "Asset: XLB\nHistorical prices (past 60 trading days): start=41.65, end=43.19, cumulative_return=+3.7%, annualized_volatility=22.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.5, 't10y3m_spread': -0.07, 'breakeven_10y': 2.31, 'hy_oas': 3.23, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 6.89, 'vix': 17.610000610351562}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-04] [\"Qualcomm CEO: We're diversifying beyond declining Apple business Listen and subscribe to Opening Bid on Apple Podcasts, Spotify, Amazon Music, YouTube or wherever you find your favorite podcasts. Qualcomm's (QCOM) next 40 years will look different than its past four decades as it seeks to diversify into data centers and cash in on the AI gold rush. But that also likely means going at things other than its lucrative business with Apple's (AAPL) iPhone. Qualcomm has been Apple's largest cellular modem provider, but the tech giant is transitioning to its own in-house C1 modem in a bid to boost margins. \\\"That's our contract, you know, and if we don't get a new contract, that's what it is,\\\" Qualcomm CEO Cristiano Amon said on Yahoo Finance's Opening Bid podcast (see video above; listen below). \\\"And there's so much drama and association about the Apple relationship, which I think it's not warranted, to be honest.\\\" The tech duo's licensing agreement ends in 2027. Research firm Futurum estimates that Qualcomm's annual modem revenue from Apple is between $5.7 billion and $5.9 billion. Analysts estimate Qualcomm will pull in about $43.5 billion in sales this year. Qualcomm has said publicly it expects to have a 70% share in iPhones launching this fall. That will drop to 20% for iPhones next fall, and then stand to be zero for iPhones debuting in fall 2027. Yahoo Finance caught up with the globe-trotting Amon \\u2014 fresh off a visit to Saudi Arabia with other top execs and the Trump administration \\u2014 at the Nasdaq. Amon began his career at Qualcomm as an engineer in 1995. \\\"We're planning our business assuming that they [Apple] are going to use their own modem,\\\" Amon said. \\\"And what's exciting about the company is all of this growth that we're creating, all of those other markets, including on Android. Like, if you look at our Android business, it has continued to grow.\\\" To offset the lost Apple sales, Qualcomm continues to invest in the connected car cockpit and the internet of things domain. The company thinks it can grow its business from these two segments to $22 billion by 2030, up from $8.3 billion in fiscal year 2024. \\\"Qualcomm's diversified growth across these specific verticals is credibly expected to significantly exceed the revenue scale of modem-only handset customers well into the era of 6G,\\\" Futurum researchers wrote in a note. The company also announced in mid-May that it plans to launch processors designed for data centers to power artificial intelligence, which will connect to Nvidia (NVDA) chips. Qualcomm failed to successfully expand into data centers years ago and returns to the field with formidable rivals in AMD (AMD), Intel (INTC), and soon ARM (ARM). \\\"It's a massive TAM [total addressable market] and will continue to grow at very high growth rates for decades. If we can build something unique and disruptive, there's room for Qualcomm,\\\" Amon said of the data center push. The Street has taken a wait-and-see approach t\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": 0.048949, "explanation": "The actual 21-day forward return for XLB starting 2025-06-05 was +4.89%, which classifies as 'positive'.", "metadata": {"future_return": 0.048949, "horizon_days": 21, "hist_return": 0.037031, "annualized_vol": 0.224319, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250902_0542", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-09-02", "context_summary": "EFA over past 60 days: cumulative return +4.1%, annualized vol 12.4%. Market regime: bull.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=86.33, end=89.85, cumulative_return=+4.1%, annualized_volatility=12.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.64, 't10y3m_spread': 0.0, 'breakeven_10y': 2.41, 'hy_oas': 2.84, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.56, 'vix': 15.359999656677246}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q WMT 2025-08-29] wmt-20250731 0000104169 1/31 2026 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-07-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-07-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-07-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-07-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-07-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-07-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-07-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-07-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-07-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-07-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-07-31 0000104169 2025-08-27 0000104169 2025-05-01 2025-07-31 0000104169 2024-05-01 2024-07-31 0000104169 2024-02-01 2024-07-31 0000104169 2025-07-31 0000104169 2025-01-31 0000104169 2024-07-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-30 0000104169 us-gaap:ParentMember 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-04-30 0000104169 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-05-01 2025-07-31 0000104169 us-gaap:ParentMember 2025-05-01 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-05-01 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-05-01 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-31 0000104169 us-gaap:ParentMember 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2025-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2025-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2025-05-01 2025-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-05-01 2025-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2025-07-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-07-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-31 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTran [...TRUNCATED...] ers, including changes in facts, assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 34 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid -R elated Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended July 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 35 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: August 29, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: August 29, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: August 29, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 36\n\nPredict whether the return of EFA over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.039302, "explanation": "The actual 21-day forward return for EFA starting 2025-09-02 was +3.93%, which classifies as 'positive'.", "metadata": {"future_return": 0.039302, "horizon_days": 21, "hist_return": 0.040755, "annualized_vol": 0.12433, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250829_0545", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SHY"], "decision_date": "2025-08-29", "context_summary": "SHY over past 60 days: cumulative return +1.5%, annualized vol 1.4%. Market regime: bull.", "question": "Asset: SHY\nHistorical prices (past 60 trading days): start=79.73, end=80.93, cumulative_return=+1.5%, annualized_volatility=1.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.6, 't10y3m_spread': -0.04, 'breakeven_10y': 2.41, 'hy_oas': 2.75, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.56, 'vix': 14.43000030517578}\nMarket regime: bull\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": 0.002031, "explanation": "The actual 21-day forward return for SHY starting 2025-08-29 was +0.20%, which classifies as 'flat'.", "metadata": {"future_return": 0.002031, "horizon_days": 21, "hist_return": 0.01506, "annualized_vol": 0.013688, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250116_0548", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-01-16", "context_summary": "XLU over past 60 days: cumulative return -5.5%, annualized vol 16.3%. Market regime: sideways.", "question": "Asset: XLU\nHistorical prices (past 60 trading days): start=39.24, end=37.07, cumulative_return=-5.5%, annualized_volatility=16.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.39, 't10y3m_spread': 0.31, 'breakeven_10y': 2.42, 'hy_oas': 2.72, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.93, 'vix': 16.1200008392334}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 2024-12-04 0000104169 2024-08-01 2024-10-31 0000104169 2023-08-01 2023-10-31 0000104169 2023-02-01 2023-10-31 0000104169 2024-10-31 0000104169 2024-01-31 0000104169 2023-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 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us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nPredict whether the return of XLU over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0047, "explanation": "The actual 21-day forward return for XLU starting 2025-01-16 was +0.47%, which classifies as 'flat'.", "metadata": {"future_return": 0.0047, "horizon_days": 21, "hist_return": -0.055202, "annualized_vol": 0.16332, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250117_0551", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-01-17", "context_summary": "SOL-USD over past 60 days: cumulative return +0.0%, annualized vol 63.1%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=206.25, end=206.25, cumulative_return=+0.0%, annualized_volatility=63.1%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.38, 't10y3m_spread': 0.27, 'breakeven_10y': 2.42, 'hy_oas': 2.73, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 7.04, 'vix': 16.600000381469727}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.068112, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-01-17 was -6.81%, which classifies as 'negative'.", "metadata": {"future_return": -0.068112, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.630632, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251212_0554", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-12-12", "context_summary": "EFA over past 60 days: cumulative return +2.1%, annualized vol 11.3%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=91.70, end=93.60, cumulative_return=+2.1%, annualized_volatility=11.3%\nMacro context: {'fed_funds_rate': 3.64, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.62, 't10y3m_spread': 0.48, 'breakeven_10y': 2.25, 'hy_oas': 2.88, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.22, 'vix': 14.850000381469728}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-10-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-10-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-10-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-10-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-10-31 0000104169 2025-12-02 0000104169 2025-08-01 2025-10-31 0000104169 2024-08-01 2024-10-31 0000104169 2024-02-01 2024-10-31 0000104169 2025-10-31 0000104169 2025-01-31 0000104169 2024-10-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-30 0000104169 us-gaap:ParentMember 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-04-30 0000104169 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-05-01 2025-07-31 0000104169 us-gaap:ParentMember 2025-05-01 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-05-01 2025-07-31 0000104169 2025-05-01 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-05-01 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-31 0000104169 us-gaap:ParentMember 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-08-01 2025-10-31 0000104169 us-gaap:ParentMember 2025-08-01 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-08-01 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-08-01 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\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": 0.0, "explanation": "The actual 21-day forward return for EFA starting 2025-12-12 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.02078, "annualized_vol": 0.113298, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250331_0557", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2025-03-31", "context_summary": "^VIX over past 60 days: cumulative return +24.8%, annualized vol 121.9%. Market regime: bear.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=17.35, end=21.65, cumulative_return=+24.8%, annualized_volatility=121.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.38, 't10y3m_spread': -0.06, 'breakeven_10y': 2.37, 'hy_oas': 3.47, 'ig_oas': 0.94, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 21.64999961853028}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-03-28] AMD downgraded, Roku reinstated: Wall Street\u2019s top analyst calls The most talked about and market moving research calls around Wall Street are now in one place. Here are today\u2019s research calls that investors need to know, as compiled by The Fly. Discover the latest stocks recommended by top Wall Street analysts, all in one place with Analyst Top Stocks. Make smarter investments with weekly expert stock picks from the Smart Investor Newsletter. Top 5 Upgrades: BofA upgraded Check Point (CHKP) to Buy from Neutral with a price target of $260, up from $230. The firm believes new CEO Nadav Zafrir is taking steps to \u201cfundamentally change the outlook,\u201d citing two factors for its upgrade, namely \u201cencouraging\u201d signs of new go-to-market and product initiatives as well as the background and pedigree of Zafrir RBC Capital upgraded Northrop Grumman (NOC) to Outperform from Sector Perform with a price target of $575, up from $500. The firm believes the positive shift in Northrop sentiment has \u201csignificant room to run\u201d as the company is well positioned relative to shifting Department of Defense priorities, execution on the B-21 remains strong, which could support an improved funding outlook, and the perception of the company relative to defense peers has improved. Wolfe Research upgraded Equinix (EQIX) to Outperform from Peer Perform with a $978 price target. Reduced job/GDP growth estimates may place many REITs at risks, but Equinix\u2019s strong balance sheet, low dividend payout, and large cash balance offer relative support in a downturn, the firm says. Goldman Sachs upgraded Par Pacific (PARR) to Buy from Neutral with a price target of $19, up from $18, implying 34% upside. The firm sees a \u201ccompelling risk/reward set-up\u201d at current share levels. Morgan Stanley upgraded Liberty Energy (LBRT) to Overweight from Equal Weight with a price target of $25, up from $20. Against a muted macro backdrop for North American shale completions markets, the firm favors \u201cpremium players\u201d like Liberty. Top 5 Downgrades: Jefferies downgraded AMD (AMD) to Hold from Buy with a price target of $120, down from $135. The firm cites the company\u2019s \u201climited traction\u201d in artificial intelligence, its belief Street estimates are too high, and expectations of mounting competition from Intel (INTC) for the downgrade. RBC Capital downgraded Lockheed Martin (LMT) to Sector Perform from Outperform with a price target of $480, down from $550. The firm believes the F-35 faces greater headline risk for international sales and increased U.S. budget pressure. Argus downgraded McCormick (MCK) to Hold from Buy. The company\u2019s Flavor Solutions segment is expected to be hurt by weak foot traffic at some restaurants in the EMEA and U.S segments, while cost headwinds in the form of higher input prices and management\u2019s plans to increase brand marketing spending at a high-single pace are likely to limit earnings growth in 2025 and beyond, the firm tells investors in a research note. JPMorgan downgraded TrueCa\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": 0.108618, "explanation": "The actual 21-day forward return for ^VIX starting 2025-03-31 was +10.86%, which classifies as 'positive'.", "metadata": {"future_return": 0.108618, "horizon_days": 21, "hist_return": 0.247839, "annualized_vol": 1.218976, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250925_0559", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2025-09-25", "context_summary": "CSHI over past 60 days: cumulative return +0.8%, annualized vol 0.8%. Market regime: bull.", "question": "Asset: CSHI\nHistorical prices (past 60 trading days): start=47.94, end=48.31, cumulative_return=+0.8%, annualized_volatility=0.8%\nMacro context: {'fed_funds_rate': 4.09, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.59, 't10y3m_spread': 0.14, 'breakeven_10y': 2.38, 'hy_oas': 2.7, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.26, 'vix': 16.18000030517578}\nMarket regime: bull\n\nPredict whether the return of CSHI over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002013, "explanation": "The actual 21-day forward return for CSHI starting 2025-09-25 was +0.20%, which classifies as 'flat'.", "metadata": {"future_return": 0.002013, "horizon_days": 21, "hist_return": 0.007743, "annualized_vol": 0.008145, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250403_0562", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["HYG"], "decision_date": "2025-04-03", "context_summary": "HYG over past 60 days: cumulative return +1.3%, annualized vol 4.2%. Market regime: bear.", "question": "Asset: HYG\nHistorical prices (past 60 trading days): start=73.44, end=74.39, cumulative_return=+1.3%, annualized_volatility=4.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.29, 't10y3m_spread': -0.12, 'breakeven_10y': 2.32, 'hy_oas': 3.42, 'ig_oas': 0.96, 'ted_spread': 0.09, 'mortgage_30y': 6.65, 'vix': 21.51000022888184}\nMarket regime: bear\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": 0.013776, "explanation": "The actual 21-day forward return for HYG starting 2025-04-03 was +1.38%, which classifies as 'positive'.", "metadata": {"future_return": 0.013776, "horizon_days": 21, "hist_return": 0.013002, "annualized_vol": 0.042123, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250217_0565", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2025-02-17", "context_summary": "^VIX over past 60 days: cumulative return -5.2%, annualized vol 123.8%. Market regime: sideways.", "question": "Asset: ^VIX\nHistorical prices (past 60 trading days): start=15.58, end=14.77, cumulative_return=-5.2%, annualized_volatility=123.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.21, 't10y3m_spread': 0.13, 'breakeven_10y': 2.43, 'hy_oas': 2.66, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.87, 'vix': 14.770000457763672}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K CAT 2025-02-14] cat-20241231 0000018230 FALSE 2024 FY 50 33.33 33.33 33.33 33.33 33.33 33.33 http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligationsCurrent http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligationsCurrent http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligations http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligations http://fasb.org/us-gaap/2024#AccountsPayableCurrent http://fasb.org/us-gaap/2024#AccountsPayableCurrent 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_________________________________________ *Management contracts and compensatory plans and arrangements required to be filed as exhibits pursuant to Item 15(b) of this report. The agreements and other documents filed as exhibits to this report are not intended to provide factual information or other disclosure other than with respect to the terms of the agreements or other documents themselves, and you should not rely on them for that purpose. In particular, any representations and warranties made by us in these agreements or other documents were made solely within the specific context of the relevant agreement or document and may not describe the actual state of affairs as of the date they were made or at any other time. Item 16.  Form 10-K Summary. None. 129 Table of Contents Form 10-K   SIGNATURES   Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.     CATERPILLAR INC.   Registrant     February 14, 2025 By: /s/ Derek Owens     Derek Owens Chief Legal Officer and General Counsel   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities and on the dates indicated.       Chairman of the Board  and Chief Executive Officer February 14, 2025 /s/ D. James Umpleby III   D. James Umpleby III       February 14, 2025 /s/ Andrew R.J. Bonfield Chief Financial Officer Andrew R.J. Bonfield     February 14, 2025 /s/ William E. Schaupp Vice President and Chief Accounting Officer   William E. Schaupp             February 14, 2025 /s/ Daniel M. Dickinson Director   Daniel M. Dickinson   February 14, 2025 /s/ James C. Fish, Jr. Director James C. Fish, Jr.       130 Table of Contents February 14, 2025 /s/ Gerald Johnson Director   Gerald Johnson   February 14, 2025 /s/ Nazzic S. Keene Director Nazzic S. Keene       February 14, 2025 /s/ David W. MacLennan Director   David W. MacLennan   February 14, 2025 /s/ Judith F. Marks Director Judith F. Marks February 14, 2025 /s/ Debra L. Reed-Klages Presiding Director Debra L. Reed-Klages       February 14, 2025 /s/ Susan C. Schwab Director   Susan C. Schwab             February 14, 2025 /s/ Rayford Wilkins, Jr. Director   Rayford Wilkins, Jr.   131\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": 0.296417, "explanation": "The actual 21-day forward return for ^VIX starting 2025-02-17 was +29.64%, which classifies as 'positive'.", "metadata": {"future_return": 0.296417, "horizon_days": 21, "hist_return": -0.05199, "annualized_vol": 1.237992, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20251103_0568", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2025-11-03", "context_summary": "XLRE over past 60 days: cumulative return -0.1%, annualized vol 13.6%. Market regime: bull.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=40.22, end=40.19, cumulative_return=-0.1%, annualized_volatility=13.6%\nMacro context: {'fed_funds_rate': 3.86, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.51, 't10y3m_spread': 0.22, 'breakeven_10y': 2.3, 'hy_oas': 2.94, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.17, 'vix': 17.440000534057617}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-K AAPL 2025-10-31] aapl-20250927 false 2025 FY 0000320193 P1Y P1Y P1Y P1Y http://fasb.org/us-gaap/2025#LongTermDebtNoncurrent http://fasb.org/us-gaap/2025#LongTermDebtNoncurrent http://fasb.org/us-gaap/2025#OtherAssetsNoncurrent http://fasb.org/us-gaap/2025#OtherAssetsNoncurrent http://fasb.org/us-gaap/2025#PropertyPlantAndEquipmentNet http://fasb.org/us-gaap/2025#PropertyPlantAndEquipmentNet http://fasb.org/us-gaap/2025#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2025#OtherLiabilitiesCurrent 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of this Annual Report on Form 10-K, included in the Exhibit 101 Inline XBRL Document Set. * Indicates management contract or compensatory plan or arrangement. ** Filed herewith. *** Furnished herewith. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Registrant hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. Item 16.    Form 10-K Summary None. Apple Inc. | 2025 Form 10-K | 57 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Date: October 31, 2025 Apple Inc. By: /s/ Kevan Parekh Kevan Parekh 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 Kevan Parekh, 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 31, 2025 TIMOTHY D. COOK /s/ Kevan Parekh Senior Vice President, Chief Financial Officer (Principal Financial Officer) October 31, 2025 KEVAN PAREKH /s/ Chris Kondo Senior Director of Corporate Accounting (Principal Accounting Officer) October 31, 2025 CHRIS KONDO /s/ Wanda Austin Director October 31, 2025 WANDA AUSTIN /s/ Alex Gorsky Director October 31, 2025 ALEX GORSKY /s/ Andrea Jung Director October 31, 2025 ANDREA JUNG /s/ Arthur D. Levinson Director and Chair of the Board October 31, 2025 ARTHUR D. LEVINSON /s/ Monica Lozano Director October 31, 2025 MONICA LOZANO /s/ Ronald D. Sugar Director October 31, 2025 RONALD D. SUGAR /s/ Susan L. Wagner Director October 31, 2025 SUSAN L. WAGNER Apple Inc. | 2025 Form 10-K | 58\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": 0.005878, "explanation": "The actual 21-day forward return for XLRE starting 2025-11-03 was +0.59%, which classifies as 'flat'.", "metadata": {"future_return": 0.005878, "horizon_days": 21, "hist_return": -0.000917, "annualized_vol": 0.135509, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20250310_0570", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-03-10", "context_summary": "BNB-USD over past 60 days: cumulative return -19.1%, annualized vol 46.9%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=685.12, end=554.58, cumulative_return=-19.1%, annualized_volatility=46.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.33, 't10y3m_spread': -0.02, 'breakeven_10y': 2.33, 'hy_oas': 2.97, 'ig_oas': 0.89, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 23.3700008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.137094, "explanation": "The actual 21-day forward return for BNB-USD starting 2025-03-10 was +13.71%, which classifies as 'positive'.", "metadata": {"future_return": 0.137094, "horizon_days": 21, "hist_return": -0.190536, "annualized_vol": 0.469479, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250619_0573", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2025-06-19", "context_summary": "MTUM over past 60 days: cumulative return +9.3%, annualized vol 23.8%. Market regime: sideways.", "question": "Asset: MTUM\nHistorical prices (past 60 trading days): start=209.36, end=228.90, cumulative_return=+9.3%, annualized_volatility=23.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.44, 't10y3m_spread': -0.04, 'breakeven_10y': 2.31, 'hy_oas': 3.16, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 20.13999938964844}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-18] [\"AI Could Create the First $10 Trillion Company. This Stock Pro Lays Out How. A conversation with Ulrike Hoffmann-Burchardi of UBS Global Wealth Management. Where she sees the next \\u201ctransformational innovations.\\u201d\", \"Streaming Finally Outpaces Traditional TV. The Leading Platform Might Surprise You. YouTube represented 12.5% of all television viewing in May\\u2014the highest share of TV for any streamer to date.\", \"Texas Instruments plans to invest more than $60 billion to manufacture billions of foundational semiconductors in the U.S. Leading U.S. companies Apple, Ford, Medtronic, NVIDIA and SpaceX strengthen partnerships with TI to unleash the next era of American innovation NEWS HIGHLIGHTS: More than $60 billion investment includes seven U.S. semiconductor fabs across three manufacturing mega-sites in Texas and Utah supporting more than 60,000 new U.S. jobs Largest investment in foundational semiconductor manufacturing in U.S. history, building on TI's almost-100-year legacy TI's largest mega-site in Sherman, Texas includes investment of up to $40 billion dollars for four fabs: SM1 and SM2 \\u2013 already underway \\u2013 and two additional fabs, SM3 and SM4 Leverages TI's strengths as a global technology and manufacturing leader to advance critical innovations from vehicles to smartphones to data centers DALLAS, June 18, 2025 /PRNewswire/ -- Texas Instruments (TI) (Nasdaq: TXN) today announced its plans to invest more than $60 billion across seven U.S. semiconductor fabs, making this the largest investment in foundational semiconductor manufacturing in U.S. history. Working with the Trump administration and building on the company's nearly 100-year legacy, TI is expanding its U.S. manufacturing capacity to supply the growing need for semiconductors that will advance critical innovations from vehicles to smartphones to data centers. Combined, TI's new manufacturing mega-sites in Texas and Utah will support more than 60,000 U.S. jobs. \\\"TI is building dependable, low-cost 300mm capacity at scale to deliver the analog and embedded processing chips that are vital for nearly every type of electronic system,\\\" said Haviv Ilan, president and CEO of Texas Instruments. \\\"Leading U.S. companies such as Apple, Ford, Medtronic, NVIDIA and SpaceX rely on TI's world-class technology and manufacturing expertise, and we are honored to work alongside them and the U.S. government to unleash what's next in American innovation.\\\" \\\"For nearly a century, Texas Instruments has been a bedrock American company driving innovation in technology and manufacturing,\\\" said U.S. Secretary of Commerce, Howard Lutnick. \\\"President Trump has made it a priority to increase semiconductor manufacturing in America \\u2013 including these foundational semiconductors that go into the electronics that people use every day. Our partnership with TI will support U.S. chip manufacturing for decades to come.\\\" Unleashing what's next in American innovation Today, TI is the largest \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": 0.038081, "explanation": "The actual 21-day forward return for MTUM starting 2025-06-19 was +3.81%, which classifies as 'positive'.", "metadata": {"future_return": 0.038081, "horizon_days": 21, "hist_return": 0.093305, "annualized_vol": 0.23771, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250620_0575", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2025-06-20", "context_summary": "BIL over past 60 days: cumulative return +0.7%, annualized vol 0.2%. Market regime: sideways.", "question": "Asset: BIL\nHistorical prices (past 60 trading days): start=88.09, end=88.68, cumulative_return=+0.7%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.44, 't10y3m_spread': -0.04, 'breakeven_10y': 2.31, 'hy_oas': 3.16, 'ig_oas': 0.88, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 20.13999938964844}\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": 0.002471, "explanation": "The actual 21-day forward return for BIL starting 2025-06-20 was +0.25%, which classifies as 'flat'.", "metadata": {"future_return": 0.002471, "horizon_days": 21, "hist_return": 0.006662, "annualized_vol": 0.002492, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20251110_0578", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["WEAT"], "decision_date": "2025-11-10", "context_summary": "WEAT over past 60 days: cumulative return +0.0%, annualized vol 16.3%. Market regime: sideways.", "question": "Asset: WEAT\nHistorical prices (past 60 trading days): start=20.95, end=20.95, cumulative_return=+0.0%, annualized_volatility=16.3%\nMacro context: {'fed_funds_rate': 3.87, 'cpi_yoy': 325.063, 'unemployment': 4.5, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.56, 't10y3m_spread': 0.19, 'breakeven_10y': 2.28, 'hy_oas': 3.15, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.22, 'vix': 19.07999992370605}\nMarket regime: sideways\n\nPredict whether the return of WEAT over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.028169, "explanation": "The actual 21-day forward return for WEAT starting 2025-11-10 was -2.82%, which classifies as 'negative'.", "metadata": {"future_return": -0.028169, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.16267, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250519_0581", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-05-19", "context_summary": "VTI over past 60 days: cumulative return -0.8%, annualized vol 23.6%. Market regime: sideways.", "question": "Asset: VTI\nHistorical prices (past 60 trading days): start=291.44, end=289.16, cumulative_return=-0.8%, annualized_volatility=23.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.45, 't10y3m_spread': 0.06, 'breakeven_10y': 2.34, 'hy_oas': 3.16, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 17.239999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-16] [\"Elite CEOs Don\\u2019t Need Earnings Guidance Avoiding the short-termism of Wall Street\\u2019s expectations game might be a good thing for more companies.\", \"How Apple, Consumer Tech Companies Got Ahead Of The Trump Tariffs The Trump tariffs may have surprised the general public but makers of consumer electronics and computer hardware had prepared for them.\", \"Trump Trade: Trump asks Apple to stop building iPhone plants in India Catch up on the top industries and stocks that were impacted, or were predicted to be impacted, by the comments, actions and policies of President Donald Trump with this daily recap compiled by The Fly: Quickly and easily unpack a company's performance with TipRanks' new KPI Data for smart investment decisions Receive undervalued, market resilient stocks straight to you inbox with TipRanks' Smart Value Newsletter IPHONE PLANTS: President Donald Trump is asking Apple (AAPL) CEO Tim Cook to stop building plants in India to make devices for the U.S., and is pushing for the iPhone maker to add domestic production, Bloomberg\\u2019s Jordan Fabian and Sankalp Phartiyal report. Apple plans to import most of the iPhones it sells in the U.S. from India by the end of next year, as Apple currently makes most of its iPhones in China. \\u201cI had a little problem with Tim Cook yesterday,\\u201d Trump said of his conversation with the Apple CEO in Qatar, where he\\u2019s on a state visit. \\u201cHe is building all over India. I don\\u2019t want you building in India.\\u201d As a result of their discussion, Trump said Apple will be \\u201cupping their production in the United States.\\u201d CHINESE PARTS: Tesla (TSLA) plans to resume shipping components from China to the U.S. for the production of Cybercab and Semi trucks at the end of May after the U.S. and China reached a truce over tariffs, Reuters\\u2019 reports, citing a person with direct knowledge of the matter. Tesla previously suspended plans to ship the components after U.S. President Donald Trump raised tariffs on Chinese goods to 145%, potentially disrupting Tesla\\u2019s plan to start mass production of the much-anticipated models. NUCLEAR DEAL: President Donald Trump said the U.S. may be getting closer to an agreement with Iran to curb the Islamic Republic\\u2019s nuclear program, Bloomberg\\u2019s Patrick Sykes reports. Trump referred to an NBC interview with Ali Shamkhani, an adviser to Iran\\u2019s Supreme Leader Ali Khamenei, in which Shamkhani reiterated Tehran\\u2019s position that it\\u2019s willing to limit uranium enrichment in exchange for sanctions relief. The U.S. and Iran have held four rounds of talks about the Islamic Republic\\u2019s atomic activities, mediated by Oman, with Trump seeking a deal that would prevent Iran from potentially building a nuclear weapon, and Tehran seeking a reprieve from U.S. sanctions. LAWSUIT SETTLEMENT: Paramount Global (PARA) executive George Cheeks is helping negotiate a settlement of President Trump\\u2019s $20B lawsuit against Paramount\\u20\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": 0.00444, "explanation": "The actual 21-day forward return for VTI starting 2025-05-19 was +0.44%, which classifies as 'flat'.", "metadata": {"future_return": 0.00444, "horizon_days": 21, "hist_return": -0.007811, "annualized_vol": 0.23588, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250505_0584", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNDX"], "decision_date": "2025-05-05", "context_summary": "BNDX over past 60 days: cumulative return +0.5%, annualized vol 4.1%. Market regime: sideways.", "question": "Asset: BNDX\nHistorical prices (past 60 trading days): start=47.01, end=47.22, cumulative_return=+0.5%, annualized_volatility=4.1%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.5, 't10y3m_spread': 0.0, 'breakeven_10y': 2.27, 'hy_oas': 3.6, 'ig_oas': 1.06, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 22.68000030517578}\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": 0.003593, "explanation": "The actual 21-day forward return for BNDX starting 2025-05-05 was +0.36%, which classifies as 'flat'.", "metadata": {"future_return": 0.003593, "horizon_days": 21, "hist_return": 0.004624, "annualized_vol": 0.04099, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250113_0587", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2025-01-13", "context_summary": "XLRE over past 60 days: cumulative return -10.6%, annualized vol 18.1%. Market regime: sideways.", "question": "Asset: XLRE\nHistorical prices (past 60 trading days): start=42.07, end=37.62, cumulative_return=-10.6%, annualized_volatility=18.1%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.37, 't10y3m_spread': 0.41, 'breakeven_10y': 2.43, 'hy_oas': 2.81, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.93, 'vix': 19.540000915527344}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 2024-12-04 0000104169 2024-08-01 2024-10-31 0000104169 2023-08-01 2023-10-31 0000104169 2023-02-01 2023-10-31 0000104169 2024-10-31 0000104169 2024-01-31 0000104169 2023-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-08-01 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\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": 0.055948, "explanation": "The actual 21-day forward return for XLRE starting 2025-01-13 was +5.59%, which classifies as 'positive'.", "metadata": {"future_return": 0.055948, "horizon_days": 21, "hist_return": -0.105661, "annualized_vol": 0.180894, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250415_0590", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-04-15", "context_summary": "BNB-USD over past 60 days: cumulative return -11.2%, annualized vol 44.4%. Market regime: bear.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=658.04, end=584.34, cumulative_return=-11.2%, annualized_volatility=44.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.54, 't10y3m_spread': 0.05, 'breakeven_10y': 2.23, 'hy_oas': 4.14, 'ig_oas': 1.15, 'ted_spread': 0.09, 'mortgage_30y': 6.62, 'vix': 30.88999938964844}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.039311, "explanation": "The actual 21-day forward return for BNB-USD starting 2025-04-15 was +3.93%, which classifies as 'positive'.", "metadata": {"future_return": 0.039311, "horizon_days": 21, "hist_return": -0.112011, "annualized_vol": 0.444281, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251022_0593", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-10-22", "context_summary": "LINK-USD over past 60 days: cumulative return -32.9%, annualized vol 74.3%. Market regime: bull.", "question": "Asset: LINK-USD\nHistorical prices (past 60 trading days): start=26.28, end=17.63, cumulative_return=-32.9%, annualized_volatility=74.3%\nMacro context: {'fed_funds_rate': 4.11, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.53, 't10y3m_spread': 0.02, 'breakeven_10y': 2.28, 'hy_oas': 2.97, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.27, 'vix': 17.8700008392334}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of LINK-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.120037, "explanation": "The actual 21-day forward return for LINK-USD starting 2025-10-22 was -12.00%, which classifies as 'negative'.", "metadata": {"future_return": -0.120037, "horizon_days": 21, "hist_return": -0.329157, "annualized_vol": 0.742696, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250813_0596", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IEF"], "decision_date": "2025-08-13", "context_summary": "IEF over past 60 days: cumulative return +3.0%, annualized vol 5.5%. Market regime: bull.", "question": "Asset: IEF\nHistorical prices (past 60 trading days): start=90.30, end=93.02, cumulative_return=+3.0%, annualized_volatility=5.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.57, 't10y3m_spread': -0.04, 'breakeven_10y': 2.38, 'hy_oas': 2.93, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 14.729999542236328}\nMarket regime: bull\n\nPredict whether the return of IEF over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.017739, "explanation": "The actual 21-day forward return for IEF starting 2025-08-13 was +1.77%, which classifies as 'positive'.", "metadata": {"future_return": 0.017739, "horizon_days": 21, "hist_return": 0.030172, "annualized_vol": 0.055466, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250207_0599", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-02-07", "context_summary": "SOL-USD over past 60 days: cumulative return -8.0%, annualized vol 77.4%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=206.25, end=189.77, cumulative_return=-8.0%, annualized_volatility=77.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.24, 't10y3m_spread': 0.11, 'breakeven_10y': 2.42, 'hy_oas': 2.66, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.89, 'vix': 15.5}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.229831, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-02-07 was -22.98%, which classifies as 'negative'.", "metadata": {"future_return": -0.229831, "horizon_days": 21, "hist_return": -0.079904, "annualized_vol": 0.773619, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250423_0602", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLP"], "decision_date": "2025-04-23", "context_summary": "XLP over past 60 days: cumulative return +3.3%, annualized vol 17.7%. Market regime: bear.", "question": "Asset: XLP\nHistorical prices (past 60 trading days): start=77.45, end=80.03, cumulative_return=+3.3%, annualized_volatility=17.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.65, 't10y3m_spread': 0.08, 'breakeven_10y': 2.27, 'hy_oas': 3.99, 'ig_oas': 1.11, 'ted_spread': 0.09, 'mortgage_30y': 6.83, 'vix': 30.56999969482422}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-22] Is This Fast-Growing Chain the Next Costco? You might not be familiar with BBB Foods (NYSE: TBBB). And that's OK. Most stateside investors aren't familiar with the rapidly expanding chain providing deeply discounted groceries and other household essentials to a widening audience with 2,772 locations at the start of this year. It's North America's fastest growing player in its space, but you have to travel to Mexico to see it in action. BBB is the parent company of Tiendas 3B, a small-box supermarket concept with big-time aspirations. The three Bs stand for Bueno, Bonito, and Barato in Spanish, translating to \"good, pretty, and cheap.\" The concept is a cross between Aldi and Costco, wedged into a smaller convenience store frame. Where to invest $1,000 right now? Our analyst team just revealed what they believe are the 10 best stocks to buy right now. Continue \u00bb It's not a household name, but that's more an opportunity than a problem. With a business model far removed from the intersection of headwinds holding back most retail concepts, it's a good time to look at BBB before it begins pinging on more growth investors' radars. Let's travel south to see why this stock could be headed north. When BBB went public 14 months ago, it became the first Mexican company to go public on a U.S. exchange in six years. It's fair to say that it's been a hit. Underwriters priced the offering at $17.50, and the hard discounter is currently trading nearly 50% higher. It's no broken IPO. BBB is earnings its upticks. Revenue soared 30% last year to reach the U.S. equivalent of nearly $2.8 billion, accelerating in its latest quarter with a 33% jump. Expansion is a big part of the growth story. BBB opened 484 net new stores last year. However, momentum is building at the store level. Comps climbed 13.3% last year, and that's stacked on top of a 17.6% same-store sales surge in 2023. It just turned profitable last year, breaking through with operating free cash the year before that. It's still cranking out negative working capital given the current opportunity for rapid expansion, but that deficit narrowed substantially last year. Supermarket chains historically crank out low net margins. They're in the business of providing modest markups to their goods, making that back by turning over its inventory as much as possible. Costco is a rock star in this realm, but its net margin has failed to break the 3% ceiling in any single year in more than three decades of public trading. Its annual membership fees account for 2% of the revenue mix, and -- like most grocers -- Tiendas 3B does not require paid memberships. BBB pales in comparison with its 0.6% net margin last year, but give it time. It just became profitable last year, and the benefits of scalability should fine the bottom line outpacing the still impressive forecast for top-line jumps. If you think Costco's selling a lot of its own Kirkland products, consider that private label sales account for just a little more than \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": -0.005748, "explanation": "The actual 21-day forward return for XLP starting 2025-04-23 was -0.57%, which classifies as 'flat'.", "metadata": {"future_return": -0.005748, "horizon_days": 21, "hist_return": 0.033316, "annualized_vol": 0.177477, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250408_0604", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-04-08", "context_summary": "EEM over past 60 days: cumulative return -4.9%, annualized vol 19.8%. Market regime: bear.", "question": "Asset: EEM\nHistorical prices (past 60 trading days): start=40.12, end=38.15, cumulative_return=-4.9%, annualized_volatility=19.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.42, 't10y3m_spread': -0.14, 'breakeven_10y': 2.19, 'hy_oas': 4.61, 'ig_oas': 1.2, 'ted_spread': 0.09, 'mortgage_30y': 6.64, 'vix': 43.34999847412109}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-07] The Zacks Analyst Blog Highlights: Broadcom, UnitedHealth, Toyota Motor and Perma-Pipe International Chicago, IL \u2013 April 7, 2025 \u2013 Zacks.com announces the list of stocks featured in the Analyst Blog. Every day the Zacks Equity Research analysts discuss the latest news and events impacting stocks and the financial markets. Stocks recently featured in the blog include: Broadcom Inc. AVGO, UnitedHealth Group Inc. UNH, Toyota Motor Corp. TM and Perma-Pipe International Holdings, Inc. PPIH. 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 Broadcom Inc. (AVGO), UnitedHealth Group Inc. (UNH) and Toyota Motor Corp. (TM), as well as a micro-cap stock Perma-Pipe International Holdings, Inc. (PPIH). The Zacks microcap research is unique as our research content on these small and under-the-radar companies is the only research of its type in the country. 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 >>> Ahead of Wall Street The daily 'Ahead of Wall Street' article is a must-read for all investors who would like to be ready for that day's trading action. The article comes out before the market opens and attempts to make sense of that morning's economic releases and how they will affect that day's market action. You can read this article for free on our home page and can actually sign up there to get an email notification as this article comes out each morning. You can read today's AWS here >>> Pre-Markets Down Another -2% on Good Jobs Report Today's Featured Research Reports Broadcom\u2019s shares have outperformed the Zacks Electronics - Semiconductors industry over the past year (+15.9% vs. -8.4%). The company is benefiting from strong demand for its networking products and custom AI accelerators (XPUs) as witnessed in its first-quarter fiscal 2025 report. Strong demand for Broadcom\u2019s application-specific integrated chips (ASICs), designed to support AI and machine learning, aids top-line growth. Broadcom expects second-quarter fiscal 2025 AI revenues to jump 44% year over year to $4.4 billion. The acquisition of VMware has benefited Infrastructure software solutions. As of Q1, roughly 70% of Broadcom\u2019s largest 10,000 customers have adopted VMware Cloud Foundation. Broadcom\u2019s expanding AI portfolio, along with a rich partner base, reflects solid top-line growth potential. However, gross margin in its fiscal Q2 is expected to contract sequentially on unfavorable revenue and product mix. High debt level is a headwind. (You can read the full research report on Broadcom here >>>) Shares of UnitedHealth have outperformed the Zacks Medical - HMOs industry over the past year (+20.5% vs. +12.3%). The company\u2019s top line remains poised for growth on the back of a strong market position, new deals, renewed agreements and expansion of service offerings\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": 0.1581, "explanation": "The actual 21-day forward return for EEM starting 2025-04-08 was +15.81%, which classifies as 'positive'.", "metadata": {"future_return": 0.1581, "horizon_days": 21, "hist_return": -0.04916, "annualized_vol": 0.197609, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250204_0607", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-02-04", "context_summary": "DOT-USD over past 60 days: cumulative return -51.6%, annualized vol 83.8%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=10.71, end=5.19, cumulative_return=-51.6%, annualized_volatility=83.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.28, 't10y3m_spread': 0.2, 'breakeven_10y': 2.45, 'hy_oas': 2.73, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 18.6200008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.024483, "explanation": "The actual 21-day forward return for DOT-USD starting 2025-02-04 was -2.45%, which classifies as 'negative'.", "metadata": {"future_return": -0.024483, "horizon_days": 21, "hist_return": -0.515582, "annualized_vol": 0.838368, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250730_0610", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2025-07-30", "context_summary": "EWJ over past 60 days: cumulative return +3.6%, annualized vol 16.3%. Market regime: bull.", "question": "Asset: EWJ\nHistorical prices (past 60 trading days): start=68.74, end=71.22, cumulative_return=+3.6%, annualized_volatility=16.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.48, 't10y3m_spread': -0.06, 'breakeven_10y': 2.43, 'hy_oas': 2.86, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.74, 'vix': 15.979999542236328}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BA 2025-07-29] ba-20250630 FALSE 2025 Q2 0000012927 --12-31 P1Y http://fasb.org/us-gaap/2025#OtherAssetsCurrent http://fasb.org/us-gaap/2025#OtherAssetsCurrent http://fasb.org/us-gaap/2025#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2025#AccruedLiabilitiesCurrent xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure ba:extension_period ba:aircraft ba:tanker ba:lot ba:simulator ba:segment 0000012927 2025-01-01 2025-06-30 0000012927 us-gaap:CommonStockMember 2025-01-01 2025-06-30 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us-gaap:ConvertiblePreferredStockMember us-gaap:PreferredStockMember 2023-12-31 0000012927 us-gaap:CommonStockMember 2023-12-31 0000012927 us-gaap:AdditionalPaidInCapitalMember 2023-12-31 0000012927 us-gaap:TreasuryStockCommonMember 2023-12-31 0000012927 us-gaap:RetainedEarningsMember 2023-12-31 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-12-31 0000012927 us-gaap:NoncontrollingInterestMember 2023-12-31 0000012927 us-gaap:RetainedEarningsMember 2024-01-01 2024-06-30 0000012927 us-gaap:NoncontrollingInterestMember 2024-01-01 2024-06-30 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-01 2024-06-30 0000012927 us-gaap:AdditionalPaidInCapitalMember 2024-01-01 2024-06-30 0000012927 us-gaap:TreasuryStockCommonMember 2024-01-01 2024-06-30 0000012927 us-gaap:ConvertiblePreferredStockMember us-gaap:PreferredStockMember 2024-06-30 0000012927 us-gaap:CommonStockMember 2024-06-30 0000012927 us-gaap:AdditionalPaidInCapitalMember 2024-06-30 0000012927 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2025-01-01 2025-06-30 0000012927 us-gaap:ConvertiblePreferredStockMember us-gaap:PreferredStockMember 2025-06-30 0000012927 us-gaap:CommonStockMember 2025-06-30 0000012927 us-gaap:AdditionalPaidInCapitalMember 2025-06-30 0000012927 us-gaap:TreasuryStockCommonMember 2025-06-30 0000012927 us-gaap:RetainedEarningsMember 2025-06-30 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-06-30 0000012927 us-gaap:NoncontrollingInterestMember 2025-06-30 0000012927 us-gaap:ConvertiblePreferredStockMember us-gaap:PreferredStockMember 2024-03-31 0000012927 us-gaap:CommonStockMember 2024-03-31 0000012927 us-gaap:AdditionalPaidInCapitalMember 2024-03-31 0000012927 us-gaap:TreasuryStockCommonMember 2024-03-31 0000012927 us-gaap:RetainedEarningsMember 2024-03-31 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-03-31 0000012927 us-gaap:NoncontrollingInterestMember 2024-03-31 0000012927 2024-03-31 0000012927 us-gaap:RetainedEarningsMember 2024-04-01 2024-06-30 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-01 2024-06-30 0000012927 us-gaap:AdditionalPaidInCapitalMember 2024-04-01 2024-06-30 0000012927 us-gaap:TreasuryStockCommonMember 2024-04-01 2024-06-30 0000012927 us-gaap:NoncontrollingInterestMember 2024-04-01 2024-06-30 0000012927 us-gaap:ConvertiblePreferredStockMember us-gaap:PreferredStockMember 2025-03-31 0000012927 us-gaap:CommonStockMember 2025-03-31 0000012927 us-gaap:AdditionalPaidInCapitalMember 2025-03-31 0000012927 us-gaap:TreasuryStockCommonMember 2025-03-31 0000012927 us-gaap:RetainedEarningsMember 2025-03-31 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-03-31 0000012927 us-gaap:NoncontrollingInterestMember 2025-03-31 0000012927 2025-03-31 0000012927 us-gaap:RetainedEarningsMember 2025-04-01 2025-06-30 0000012927 us-gaap:NoncontrollingInterestMember 2025-04-01 2025-06-30 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-01 2025-06-30 0000012927 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Mine Safety Disclosures Not applicable. Item 5. Other Information During the three months ended June 30, 2025, none of our directors or officers adopted , modified or terminated a “Rule 10b5-1 trading arrangement” or a “non-Rule 10b5-1 trading arrangement” as such terms are defined under Item 408 of Regulation S-K. 57 Table of Contents Item 6. Exhibits 2.1 Membership Interest Purchase Agreement, dated as of April 22, 2025, among The Boeing Company, JNPR Aero, LLC and Project Maroon, LLC (Exhibit 2.1 to the Company’s Current Report on Form 8-K, dated April 22, 2025) 10.1 Non-Prosecution Agreement, dated May 29, 2025 (Exhibit 10.1 to the Company’s Current Report on Form 8-K, dated May 29, 2025) 10.2 Form of U.S. Notice of Terms of Cash-Based Award (Exhibit 10.1 to the Company's Current Report on Form 8-K, dated June 27, 2025)* 10.3 Form of U.S. Notice of Terms of Supplemental Restricted Stock Units (Exhibit 10.5 to the Company's Form 10-Q for the quarter ended March 31, 2025)* 10.4 Form of U.S. Notice of Terms of Supplemental Non-Qualified Premium-Priced Stock Options (Exhibit 10.3 to the Company's Current Report on Form 8-K, dated June 27, 2025)* 10.5 Letter Agreement with Jesus Malave* † 15 Letter from Independent Registered Public Accounting Firm regarding unaudited interim financial information 31.1 Certification of Chief Executive Officer pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certification of Chief Executive Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 32.2 Certification of Chief Financial Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File (formatted as inline XBRL and contained in Exhibit 101) * Management contract or compensatory plan † Certain portions of this exhibit have been redacted pursuant to Item 601(b)(10)(iv) of Regulation S-K. The Company agrees to furnish supplementally an unredacted copy of the exhibit to the SEC upon request. 58 Table of Contents Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. THE BOEING COMPANY (Registrant) July 29, 2025 /s/ Michael J. Cleary (Date) Michael J. Cleary Senior Vice President and Controller 59\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": 0.071776, "explanation": "The actual 21-day forward return for EWJ starting 2025-07-30 was +7.18%, which classifies as 'positive'.", "metadata": {"future_return": 0.071776, "horizon_days": 21, "hist_return": 0.036, "annualized_vol": 0.163003, "has_text": true, "text_chars": 9044}} +{"id": "T1_all_20250124_0613", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-01-24", "context_summary": "ETH-USD over past 60 days: cumulative return -2.3%, annualized vol 55.9%. Market regime: sideways.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=3413.54, end=3334.71, cumulative_return=-2.3%, annualized_volatility=55.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.36, 't10y3m_spread': 0.29, 'breakeven_10y': 2.42, 'hy_oas': 2.66, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.96, 'vix': 15.020000457763672}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.176297, "explanation": "The actual 21-day forward return for ETH-USD starting 2025-01-24 was -17.63%, which classifies as 'negative'.", "metadata": {"future_return": -0.176297, "horizon_days": 21, "hist_return": -0.023093, "annualized_vol": 0.558704, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250702_0615", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-07-02", "context_summary": "VLUE over past 60 days: cumulative return +20.7%, annualized vol 20.0%. Market regime: sideways.", "question": "Asset: VLUE\nHistorical prices (past 60 trading days): start=93.72, end=113.09, cumulative_return=+20.7%, annualized_volatility=20.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.48, 't10y3m_spread': -0.14, 'breakeven_10y': 2.29, 'hy_oas': 2.91, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.77, 'vix': 16.829999923706055}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-07-01] [\"Peter Thiel sold 20 million shares of Facebook just months after its IPO\\u2014but they\\u2019d be worth nearly $15 billion more if he had held on Billionaire Peter Thiel was Facebook\\u2019s first outside investor, but he may now have regrets for how soon he cashed out. Just months after the tech company\\u2019s IPO, he sold millions of shares for $20 each for a sum of $400 million; with the stock now worth 37 times more, he could have been $15 billion richer today. Investing is a game of risk and reward. Get it right, and you could build a billion-dollar fortune. Get it wrong, and it might all go up in smoke. For PayPal cofounder Peter Thiel, being the first outside Facebook investor was hardly a bust\\u2014but there may be some seller\\u2019s remorse. The tech entrepreneur first coughed up $500,000 in 2004 for a 10% stake in the company, just months into its creation\\u2014giving it a value of about $4.9 million. Nearly a decade later, following the company\\u2019s May 2012 IPO, Thiel decided it was time to cash out. Thiel sold about 20.1 million shares in the company\\u2014a majority of his stake\\u2014for $19.27 to $20.69 each, netting him about $400 million at the time. Had he held his shares until today, they would be worth about $14.76 billion (Meta\\u2019s stock price is $736 at the time of writing), a decision that may haunt even one of Silicon Valley\\u2019s savviest investors. What led him to invest in the first place? He believed the college market\\u2014which was Facebook\\u2019s original audience\\u2014had been underestimated. \\u201cI think investors always have a bias to invest in things they themselves use and they undervalue things they don\\u2019t use so there aren\\u2019t many investors who are in college,\\u201d he said to This Week in Startups in 2015. Fortune reached out to Thiel for comment. Despite selling a majority of his stake in the company, the 57-year-old remained heavily involved for many years, serving on the board until 2022. \\u201cPeter has been a valuable member of our board and I\\u2019m deeply grateful for everything he has done for our company\\u2014from believing in us when few others would, to teaching me so many lessons about business, economics, and the world,\\u201d Facebook cofounder and CEO Mark Zuckerberg said at the time of Thiel\\u2019s stepping down. Today, Thiel\\u2019s net worth sits at about $21.7 billion, according to Bloomberg, thanks in part to the billions he made from being the cofounder of PayPal and Palantir. And he\\u2019s not the only investor to have thrived off the success of Facebook; the social network\\u2019s growth has created countless millionaires\\u2014and multiple billionaires. Of course, no one has benefited more financially than Zuckerberg, who is currently the second-richest person in the world, according to Bloomberg, with an estimated net worth of $260 billion. In fact, his worth has increased more than any other billionaire this year, with a year-to-date growth of $52.8 billion. But the compan\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": -0.031516, "explanation": "The actual 21-day forward return for VLUE starting 2025-07-02 was -3.15%, which classifies as 'negative'.", "metadata": {"future_return": -0.031516, "horizon_days": 21, "hist_return": 0.206651, "annualized_vol": 0.200385, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250210_0617", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2025-02-10", "context_summary": "FXI over past 60 days: cumulative return +5.6%, annualized vol 25.8%. Market regime: sideways.", "question": "Asset: FXI\nHistorical prices (past 60 trading days): start=30.25, end=31.93, cumulative_return=+5.6%, annualized_volatility=25.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.2, 't10y3m_spread': 0.14, 'breakeven_10y': 2.42, 'hy_oas': 2.67, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.89, 'vix': 16.540000915527344}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K AMZN 2025-02-07] amzn-20241231 false 2024 FY 0001018724 P3Y P1Y P1Y http://fasb.org/us-gaap/2024#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2024#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 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0001018724 us-gaap:ShareBasedCompensationAwardTrancheOneMember 2024-01-01 2024-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2022-01-01 2022-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2023-01-01 2023-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2024-01-01 2024-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2024-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsoli [...TRUNCATED...] Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy (incorporated by reference to the Company's Annual Report on Form 10-K for the Year ended December 31, 2023). 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2024, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2024, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 76 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 6, 2025.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 6, 2025.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Andrew Y. Ng Andrew Y. Ng Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 77\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": 0.081202, "explanation": "The actual 21-day forward return for FXI starting 2025-02-10 was +8.12%, which classifies as 'positive'.", "metadata": {"future_return": 0.081202, "horizon_days": 21, "hist_return": 0.055601, "annualized_vol": 0.258133, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20251215_0620", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-12-15", "context_summary": "DOT-USD over past 60 days: cumulative return +0.0%, annualized vol 78.8%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=3.54, end=3.54, cumulative_return=+0.0%, annualized_volatility=78.8%\nMacro context: {'fed_funds_rate': 3.64, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.67, 't10y3m_spread': 0.56, 'breakeven_10y': 2.26, 'hy_oas': 2.91, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.22, 'vix': 15.739999771118164}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for DOT-USD starting 2025-12-15 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.788269, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250811_0623", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["HAUZ"], "decision_date": "2025-08-11", "context_summary": "HAUZ over past 60 days: cumulative return +10.3%, annualized vol 10.6%. Market regime: bull.", "question": "Asset: HAUZ\nHistorical prices (past 60 trading days): start=20.60, end=22.72, cumulative_return=+10.3%, annualized_volatility=10.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.51, 't10y3m_spread': -0.05, 'breakeven_10y': 2.39, 'hy_oas': 2.94, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.63, 'vix': 15.149999618530272}\nMarket regime: bull\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": 0.022385, "explanation": "The actual 21-day forward return for HAUZ starting 2025-08-11 was +2.24%, which classifies as 'positive'.", "metadata": {"future_return": 0.022385, "horizon_days": 21, "hist_return": 0.103095, "annualized_vol": 0.105865, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250411_0625", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2025-04-11", "context_summary": "QQQ over past 60 days: cumulative return -13.5%, annualized vol 26.9%. Market regime: bear.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=513.45, end=444.03, cumulative_return=-13.5%, annualized_volatility=26.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.56, 't10y3m_spread': 0.06, 'breakeven_10y': 2.19, 'hy_oas': 4.42, 'ig_oas': 1.18, 'ted_spread': 0.09, 'mortgage_30y': 6.62, 'vix': 40.720001220703125}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-10] [\"Alnylam (ALNY) Moves 8.5% Higher: Will This Strength Last? Alnylam Pharmaceuticals (ALNY) shares rallied 8.5% in the last trading session to close at $243.27. This move can be attributable to notable volume with a higher number of shares being traded than in a typical session. This compares to the stock's 6% loss over the past four weeks. The rise in share price came after President Trump announced a 90-day pause on his sweeping tariffs against non-retaliating countries. This RNA interference drug developer is expected to post quarterly loss of $0.55 per share in its upcoming report, which represents a year-over-year change of -243.8%. Revenues are expected to be $587.45 million, up 18.8% from the year-ago quarter. While earnings and revenue growth expectations are important in evaluating the potential strength in a stock, empirical research shows a strong correlation between trends in earnings estimate revisions and near-term stock price movements. For Alnylam, the consensus EPS estimate for the quarter has been revised 1.5% lower over the last 30 days to the current level. And a negative trend in earnings estimate revisions doesn't usually translate into price appreciation. So, make sure to keep an eye on ALNY going forward to see if this recent jump can turn into more strength down the road. The stock currently carries a Zacks Rank #3 (Hold). You can see the complete list of today's Zacks Rank #1 (Strong Buy) stocks here >>>> Alnylam is a member of the Zacks Medical - Biomedical and Genetics industry. One other stock in the same industry, Immunome, Inc. (IMNM), finished the last trading session 11.7% higher at $6.21. IMNM has returned -36.3% over the past month. Immunome's consensus EPS estimate for the upcoming report has changed +18.3% over the past month to -$0.67. Compared to the company's year-ago EPS, this represents a change of -97.1%. Immunome currently boasts a Zacks Rank of #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 Alnylam Pharmaceuticals, Inc. (ALNY) : Free Stock Analysis Report Immunome, Inc. (IMNM) : Free Stock Analysis Report This article originally published on Zacks Investment Research (zacks.com). Zacks Investment Research\", \"Seeking Recession-Proof Stocks? RBC Suggests 2 Healthcare Stocks to Buy President Trump\\u2019s newly announced tariff policy has done more than just push the stock markets deeper into correction territory \\u2014 the sudden panic on Wall Street has increased worries about a full-blown recession hitting in the near future. According to USA Today, several big banks are putting the chance of a recession at 40% or higher. Discover outperforming stocks and invest smarter with Top Smart Score Stocks. Filter, analyze, and streamline your search for investment opportunities using Tipranks' Stock Screener. Only time will tell if we dip into recession. For now, worried investors are seeking \\u\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": 0.117628, "explanation": "The actual 21-day forward return for QQQ starting 2025-04-11 was +11.76%, which classifies as 'positive'.", "metadata": {"future_return": 0.117628, "horizon_days": 21, "hist_return": -0.135194, "annualized_vol": 0.269342, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251029_0628", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-10-29", "context_summary": "BTC-USD over past 60 days: cumulative return +0.0%, annualized vol 28.5%. Market regime: bull.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=103998.57, end=103998.57, cumulative_return=+0.0%, annualized_volatility=28.5%\nMacro context: {'fed_funds_rate': 4.12, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.52, 't10y3m_spread': 0.1, 'breakeven_10y': 2.28, 'hy_oas': 2.82, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.19, 'vix': 16.420000076293945}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.120507, "explanation": "The actual 21-day forward return for BTC-USD starting 2025-10-29 was -12.05%, which classifies as 'negative'.", "metadata": {"future_return": -0.120507, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.284556, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250501_0631", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2025-05-01", "context_summary": "SGOV over past 60 days: cumulative return +0.7%, annualized vol 0.2%. Market regime: bear.", "question": "Asset: SGOV\nHistorical prices (past 60 trading days): start=96.12, end=96.79, cumulative_return=+0.7%, annualized_volatility=0.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.57, 't10y3m_spread': -0.14, 'breakeven_10y': 2.23, 'hy_oas': 3.94, 'ig_oas': 1.09, 'ted_spread': 0.09, 'mortgage_30y': 6.81, 'vix': 24.700000762939453}\nMarket regime: bear\n\nPredict whether the return of SGOV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.002391, "explanation": "The actual 21-day forward return for SGOV starting 2025-05-01 was +0.24%, which classifies as 'flat'.", "metadata": {"future_return": 0.002391, "horizon_days": 21, "hist_return": 0.006979, "annualized_vol": 0.002281, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250127_0633", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-01-27", "context_summary": "EFA over past 60 days: cumulative return -0.3%, annualized vol 12.6%. Market regime: sideways.", "question": "Asset: EFA\nHistorical prices (past 60 trading days): start=76.70, end=76.50, cumulative_return=-0.3%, annualized_volatility=12.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.36, 't10y3m_spread': 0.28, 'breakeven_10y': 2.43, 'hy_oas': 2.66, 'ig_oas': 0.8, 'ted_spread': 0.09, 'mortgage_30y': 6.96, 'vix': 14.850000381469728}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q PG 2025-01-22] pg-20241231 0000080424 6/30 2025 Q2 false http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 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Purchases may be made in the open market and/or private transactions and purchases may be increased, decreased or discontinued at any time without prior notice. The share repurchases are authorized pursuant to a resolution issued by the Company's Board of Directors and are expected to be financed by a combination of operating cash flows and issuance of debt.      Item 5. Other Information During the three months ended December 31, 2024, none of our directors or officers adopted or terminated a \"Rule 10b5-1 trading arrangement\" or \"non-Rule 10b5-1 trading arrangement\" as defined in Item 408 of Regulation S-K. 30 The Procter & Gamble Company Item 6. Exhibits 3.1 Amended Articles of Incorporation (as amended by shareholders at the annual meeting on October 11, 2011 and consolidated by the Board of Directors on April 8, 2016) (Incorporated by reference to Exhibit (3-1) of the Company's Form 10-K for the year ended June 30, 2016) 3.2 Regulations (as approved by the Board of Directors on December 13, 2022, pursuant to authority granted by shareholders at the annual meeting on October 13, 2009) (Incorporated by reference to Exhibit (3-2) of the Company’s Current Report on Form 8-K filed December 13, 2022) 4.1 Indenture, dated as of September 3, 2009, between the Company and Deutsche Bank Trust Company Americas, as Trustee (Incorporated by reference to Exhibit (4-1) of the Company's Annual Report on Form 10-K for the year ended June 30, 2015) 31.1 Rule 13a-14(a)/15d-14(a) Certification – Chief Executive Officer + 31.2 Rule 13a-14(a)/15d-14(a) Certification – Chief Financial Officer + 32.1 Section 1350 Certifications – Chief Executive Officer + 32.2 Section 1350 Certifications – Chief Financial Officer + 101.SCH (1) Inline XBRL Taxonomy Extension Schema Document 101.CAL (1) Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF (1) Inline XBRL Taxonomy Definition Linkbase Document 101.LAB (1) Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE (1) Inline XBRL Taxonomy Extension Presentation Linkbase Document 104  Cover Page Interactive Data File (formatted in Inline XBRL and contained in Exhibit 101) + Filed herewith (1) Pursuant to Rule 406T of Regulation S-T, this information is furnished and not filed for purposes of Sections 11 or 12 of the Securities Act of 1933 and Section 18 of the Securities Exchange Act of 1934, and otherwise is not subject to liability under these sections. Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this Report to be signed on its behalf by the undersigned thereunto duly authorized. THE PROCTER & GAMBLE COMPANY January 22, 2025 /s/ MATTHEW W. JANZARUK Date (Matthew W. Janzaruk) Senior Vice President - Chief Accounting Officer (Principal Accounting Officer)\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": 0.039253, "explanation": "The actual 21-day forward return for EFA starting 2025-01-27 was +3.93%, which classifies as 'positive'.", "metadata": {"future_return": 0.039253, "horizon_days": 21, "hist_return": -0.002613, "annualized_vol": 0.126433, "has_text": true, "text_chars": 9044}} +{"id": "T1_all_20250508_0636", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-05-08", "context_summary": "AVAX-USD over past 60 days: cumulative return +8.8%, annualized vol 79.9%. Market regime: sideways.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=17.96, end=19.53, cumulative_return=+8.8%, annualized_volatility=79.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.48, 't10y3m_spread': -0.08, 'breakeven_10y': 2.25, 'hy_oas': 3.67, 'ig_oas': 1.05, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 23.549999237060547}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.006199, "explanation": "The actual 21-day forward return for AVAX-USD starting 2025-05-08 was +0.62%, which classifies as 'flat'.", "metadata": {"future_return": 0.006199, "horizon_days": 21, "hist_return": 0.087515, "annualized_vol": 0.799215, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250428_0639", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-04-28", "context_summary": "XLV over past 60 days: cumulative return -5.9%, annualized vol 16.8%. 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The repurchase program does not have an expiration date. For additional information related to share repurchases, see Note 11 of the Notes to Consolidated Financial Statements included in Part I, Item 1 of this Quarterly Report on Form 10-Q. (2)      Average price paid per share includes costs associated with the repurchases. ITEM 5. OTHER INFORMATION 10b5-1 Trading Plans During the quarter ended March 31, 2025, no Section 16 director or officer adopted , modified, or terminated a “Rule 10b5-1 trading arrangement” (as defined in Item 408 of Regulation S-K of the Exchange Act). There were no “non-Rule 10b5-1 trading arrangements” (as defined in Item 408 of Regulation S-K of the Exchange Act) adopted, modified, or terminated during the quarter ended March 31, 2025 by our directors and Section 16 officers. 47 ITEM 6. EXHIBITS Exhibit Number    Description Incorporated by reference herein Form Date 31.01 * Certification of Chief Executive Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.02 * Certification of Chief Financial Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.01 ‡ Certifications of Chief Executive Officer and Chief Financial Officer pursuant to 18 U.S.C. Section 1350, as adopted pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS * Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH * Inline XBRL Taxonomy Extension Schema Document 101.CAL * Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF * Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB * Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE * Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 * Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) __________________________  * Filed herewith. ‡ Furnished herewith. 48 SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. ALPHABET INC. April 24, 2025 By: /s/ ANAT ASHKENAZI Anat Ashkenazi Senior Vice President, Chief Financial Officer ALPHABET INC. April 24, 2025 By: /s/    AMIE THUENER O'TOOLE         Amie Thuener O'Toole Vice President, Corporate Controller and Principal Accounting Officer 49\n\nPredict whether the return of XLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.051371, "explanation": "The actual 21-day forward return for XLV starting 2025-04-28 was -5.14%, which classifies as 'negative'.", "metadata": {"future_return": -0.051371, "horizon_days": 21, "hist_return": -0.059426, "annualized_vol": 0.168285, "has_text": true, "text_chars": 9047}} +{"id": "T1_all_20250828_0641", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-28", "context_summary": "SPY over past 60 days: cumulative return +8.8%, annualized vol 9.7%. Market regime: bull.", "question": "Asset: SPY\nHistorical prices (past 60 trading days): start=589.33, end=641.19, cumulative_return=+8.8%, annualized_volatility=9.7%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.65, 't10y3m_spread': -0.02, 'breakeven_10y': 2.43, 'hy_oas': 2.78, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.58, 'vix': 14.850000381469728}\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q NVDA 2025-08-27] nvda-20250727 0001045810 1/25 2026 Q2 FALSE http://fasb.org/us-gaap/2025#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2025#AccruedLiabilitiesCurrent xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:investment nvda:segment 0001045810 2025-01-27 2025-07-27 0001045810 2025-08-22 0001045810 2025-04-28 2025-07-27 0001045810 2024-04-29 2024-07-28 0001045810 2024-01-29 2024-07-28 0001045810 2025-07-27 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 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Exhibits Exhibit No.  Exhibit Description 10.1+* Amended and Restated 2007 Equity Incentive Plan - Non-Employee Director Deferred Restricted Stock Unit Grant Notice and Deferred Restricted Stock Unit Agreement (2025) 10.2+* Amended and Restated 2007 Equity Incentive Plan - Non-Employee Director Restricted Stock Unit Grant Notice and Restricted Stock Unit Agreement (2025) 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. + Management contract or compensatory plan or arrangement. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 39 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: August 27, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 40\n\nPredict whether the return of SPY over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.022707, "explanation": "The actual 21-day forward return for SPY starting 2025-08-28 was +2.27%, which classifies as 'positive'.", "metadata": {"future_return": 0.022707, "horizon_days": 21, "hist_return": 0.087993, "annualized_vol": 0.096726, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20251210_0644", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-12-10", "context_summary": "SOL-USD over past 60 days: cumulative return -22.6%, annualized vol 67.0%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=178.05, end=137.90, cumulative_return=-22.6%, annualized_volatility=67.0%\nMacro context: {'fed_funds_rate': 3.89, 'cpi_yoy': 326.031, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.57, 't10y3m_spread': 0.45, 'breakeven_10y': 2.26, 'hy_oas': 2.89, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.19, 'vix': 16.93000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.087819, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-12-10 was -8.78%, which classifies as 'negative'.", "metadata": {"future_return": -0.087819, "horizon_days": 21, "hist_return": -0.225508, "annualized_vol": 0.669551, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20251002_0646", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ITB"], "decision_date": "2025-10-02", "context_summary": "ITB over past 60 days: cumulative return +9.1%, annualized vol 29.3%. Market regime: bull.", "question": "Asset: ITB\nHistorical prices (past 60 trading days): start=98.74, end=107.74, cumulative_return=+9.1%, annualized_volatility=29.3%\nMacro context: {'fed_funds_rate': 4.09, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.57, 't10y3m_spread': 0.11, 'breakeven_10y': 2.35, 'hy_oas': 2.81, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.3, 'vix': 16.290000915527344}\nMarket regime: bull\n\nPredict whether the return of ITB over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.072418, "explanation": "The actual 21-day forward return for ITB starting 2025-10-02 was -7.24%, which classifies as 'negative'.", "metadata": {"future_return": -0.072418, "horizon_days": 21, "hist_return": 0.091214, "annualized_vol": 0.292862, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250526_0649", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-05-26", "context_summary": "BNB-USD over past 60 days: cumulative return +5.1%, annualized vol 33.4%. Market regime: sideways.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=637.21, end=669.92, cumulative_return=+5.1%, annualized_volatility=33.4%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.51, 't10y3m_spread': 0.15, 'breakeven_10y': 2.33, 'hy_oas': 3.4, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.86, 'vix': 22.290000915527344}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.034744, "explanation": "The actual 21-day forward return for BNB-USD starting 2025-05-26 was -3.47%, which classifies as 'negative'.", "metadata": {"future_return": -0.034744, "horizon_days": 21, "hist_return": 0.051333, "annualized_vol": 0.334279, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250731_0652", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-07-31", "context_summary": "VLUE over past 60 days: cumulative return +10.6%, annualized vol 13.6%. 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FORM 10-K SUMMARY None. 100   SIGNAT URES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned; thereunto duly authorized, in the City of Redmond, State of Washington, on July 30, 2025.   M ICROSOFT  C ORPORATION   /s/ A LICE  L. J OLLA Alice L. Jolla Corporate Vice President and Chief Accounting Officer (Principal Accounting Officer)   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of Registrant and in the capacities indicated on July 30, 2025.   Signature Title   /s/ S ATYA  N ADELLA Chairman and Chief Executive Officer (Principal Executive Officer) Satya Nadella     /s/ R EID  G. H OFFMAN   Director Reid G. Hoffman     /s/ H UGH  F. J OHNSTON Director Hugh F. Johnston     /s/ T ERI L. L IST Director Teri L. List     /s/ C ATHERINE  M AC G REGOR   Director Catherine MacGregor         /s/ M ARK  A. L. M ASON   Director Mark A. L. Mason         /s/ S ANDRA  E. P ETERSON Lead Independent Director Sandra E. Peterson       /s/ P ENNY S. P RITZKER   Director Penny S. Pritzker       /s/ C ARLOS A. R ODRIGUEZ   Director Carlos A. Rodriguez       /s/ C HARLES  W. S CHARF Director Charles W. Scharf     /s/ J OHN  W. S TANTON Director John W. Stanton       /s/ E MMA  N. W ALMSLEY   Director Emma N. Walmsley     /s/ A MY  E. H OOD Executive Vice President and Chief Financial Officer (Principal Financial Officer) Amy E. Hood     /s/ A LICE  L. J OLLA Corporate Vice President and Chief Accounting Officer (Principal Accounting Officer) Alice L. Jolla     101\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": 0.059584, "explanation": "The actual 21-day forward return for VLUE starting 2025-07-31 was +5.96%, which classifies as 'positive'.", "metadata": {"future_return": 0.059584, "horizon_days": 21, "hist_return": 0.105945, "annualized_vol": 0.136109, "has_text": true, "text_chars": 9046}} +{"id": "T1_all_20250515_0655", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2025-05-15", "context_summary": "FXI over past 60 days: cumulative return +3.6%, annualized vol 32.2%. Market regime: sideways.", "question": "Asset: FXI\nHistorical prices (past 60 trading days): start=34.19, end=35.42, cumulative_return=+3.6%, annualized_volatility=32.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.48, 't10y3m_spread': 0.12, 'breakeven_10y': 2.37, 'hy_oas': 3.1, 'ig_oas': 0.93, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 18.6200008392334}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-14] 1 Surging Stock on Our Buy List and 2 to Brush Off Exciting developments are taking place for the stocks in this article. They\u2019ve all surged ahead of the broader market over the last month as catalysts such as new products and positive media coverage have propelled their returns. But not every company with momentum is a long-term winner, and plenty of investors have lost money betting on short-term fads. Keeping that in mind, here is one stock we think lives up to the hype and two that may correct. One-Month Return: +13.8% Headquartered in NYC, Genco (NYSE:GNK) is a shipping company that transports dry bulk cargo along worldwide maritime routes. Why Do We Steer Clear of GNK? Sluggish trends in its owned vessels suggest customers aren\u2019t adopting its solutions as quickly as the company hoped Earnings per share have contracted by 45.6% annually over the last two years, a headwind for returns as stock prices often echo long-term EPS performance Capital intensity has ramped up over the last five years as its free cash flow margin decreased by 6.5 percentage points Genco\u2019s stock price of $14.56 implies a valuation ratio of 22.2x forward P/E. Read our free research report to see why you should think twice about including GNK in your portfolio, it\u2019s free. One-Month Return: +30.4% Established in 2006, SolarEdge (NASDAQ: SEDG) creates advanced systems to improve the efficiency of solar panels. Why Should You Sell SEDG? Demand for its offerings was relatively low as its number of megawatts shipped has underwhelmed Eroding returns on capital from an already low base indicate that management\u2019s recent investments are destroying value Limited cash reserves may force the company to seek unfavorable financing terms that could dilute shareholders SolarEdge is trading at $18.15 per share, or 0.9x forward price-to-sales. Dive into our free research report to see why there are better opportunities than SEDG. One-Month Return: +21.7% Founded by Brian Chesky and Joe Gebbia in their San Francisco apartment, Airbnb (NASDAQ:ABNB) is the world\u2019s largest online marketplace for lodging, primarily homestays. Why Will ABNB Beat the Market? Has the opportunity to boost monetization through new features and premium offerings as its nights and experiences booked have grown by 10.4% annually over the last two years Earnings per share have massively outperformed its peers over the last three years, increasing by 49.4% annually Strong free cash flow margin of 39.7% enables it to reinvest or return capital consistently At $137.83 per share, Airbnb trades at 20.5x forward EV/EBITDA. Is now the time to initiate a position? See for yourself in our in-depth research report, it\u2019s free. Donald Trump\u2019s victory in the 2024 U.S. Presidential Election sent major indices to all-time highs, but stocks have retraced as investors debate the health of the economy and the potential impact of tariffs. While this leaves much uncertainty around 2025, a few companies are poised for long-term gains regar\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": 0.023217, "explanation": "The actual 21-day forward return for FXI starting 2025-05-15 was +2.32%, which classifies as 'positive'.", "metadata": {"future_return": 0.023217, "horizon_days": 21, "hist_return": 0.035949, "annualized_vol": 0.321516, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250815_0658", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["JNK"], "decision_date": "2025-08-15", "context_summary": "JNK over past 60 days: cumulative return +3.6%, annualized vol 3.0%. Market regime: bull.", "question": "Asset: JNK\nHistorical prices (past 60 trading days): start=89.55, end=92.76, cumulative_return=+3.6%, annualized_volatility=3.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 323.291, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.55, 't10y3m_spread': -0.01, 'breakeven_10y': 2.39, 'hy_oas': 2.89, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.58, 'vix': 14.829999923706056}\nMarket regime: bull\n\nPredict whether the return of JNK over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.013443, "explanation": "The actual 21-day forward return for JNK starting 2025-08-15 was +1.34%, which classifies as 'positive'.", "metadata": {"future_return": 0.013443, "horizon_days": 21, "hist_return": 0.035813, "annualized_vol": 0.029911, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250905_0661", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-09-05", "context_summary": "USMV over past 60 days: cumulative return +1.4%, annualized vol 8.8%. Market regime: bull.", "question": "Asset: USMV\nHistorical prices (past 60 trading days): start=91.82, end=93.08, cumulative_return=+1.4%, annualized_volatility=8.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.58, 't10y3m_spread': 0.01, 'breakeven_10y': 2.38, 'hy_oas': 2.84, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.5, 'vix': 15.300000190734863}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-04] [\"Should You Buy MP Materials Corp Stock Right Now? Shares of MP Materials are being carried higher on a wave of optimism. Yet, risks and uncertainties lie ahead for this rare-earth minerals producer. 10 stocks we like better than MP Materials \\u203a The narrative surrounding MP Materials (NYSE: MP) is wonderful right now. Following two transformative deals with the U.S. government and Apple, the rare-earth minerals company is receiving heavy investment and commitments to purchase materials and magnets (with pricing floor commitments running for a decade). At the same time, the company is expanding its existing magnet-producing facility in Texas while setting out to build a brand-new magnet production facility. So, is this a good time to buy the stock? The positive news is not lost on investors, and the stock is up an incredible 356% this year as of the time of writing. In a nutshell, investors are buying into the idea that MP Materials can solve the problem of sourcing rare earth materials and magnets domestically, thereby reducing dependence on China -- the country that has a practical monopoly on global rare earth magnets. That's the good news, but before you hit the buy button, consider that this could prove the apex of optimism over the stock. Execution risk remains around the manufacturing plant expansion and new construction projects. The company remains loss-making and may require additional capital, which would dilute the interests of existing shareholders. The involvement of the government in a public-private partnership introduces additional political risk, particularly since the U.S. government is likely to hold a significant amount of stock in MP Materials. In addition, it's incredibly difficult to predict where rare earth product prices will be over an extended period. The risks outlined above are significant, but it's also worth noting that there's an upside risk from other companies seeking to secure a domestic supply of rare earth materials and magnets. MP Materials certainly has a bright future, but investors might be overlooking several risks ahead, and the upside is too uncertain to predict accurately. On that basis, this is a stock most investors will want to avoid for now. Before you buy stock in MP Materials, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now\\u2026 and MP Materials wasn\\u2019t one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you\\u2019d have $654,759!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you\\u2019d have $1,046,799!* Now, it\\u2019s worth noting Stock Advisor\\u2019s total average return is 1,042% \\u2014 a market-crushing outperformance compared to 183% for the S&P 500. Don\\u2019t miss out\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": 0.010601, "explanation": "The actual 21-day forward return for USMV starting 2025-09-05 was +1.06%, which classifies as 'positive'.", "metadata": {"future_return": 0.010601, "horizon_days": 21, "hist_return": 0.013729, "annualized_vol": 0.087849, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250418_0664", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-04-18", "context_summary": "ETH-USD over past 60 days: cumulative return -42.3%, annualized vol 79.1%. Market regime: bear.", "question": "Asset: ETH-USD\nHistorical prices (past 60 trading days): start=2743.20, end=1582.55, cumulative_return=-42.3%, annualized_volatility=79.1%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.302, 'unemployment': 4.2, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.53, 't10y3m_spread': 0.0, 'breakeven_10y': 2.23, 'hy_oas': 4.02, 'ig_oas': 1.11, 'ted_spread': 0.09, 'mortgage_30y': 6.83, 'vix': 29.64999961853028}\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of ETH-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.47616, "explanation": "The actual 21-day forward return for ETH-USD starting 2025-04-18 was +47.62%, which classifies as 'positive'.", "metadata": {"future_return": 0.47616, "horizon_days": 21, "hist_return": -0.423101, "annualized_vol": 0.79066, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250904_0667", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-09-04", "context_summary": "BNB-USD over past 60 days: cumulative return +7.7%, annualized vol 35.6%. Market regime: bull.", "question": "Asset: BNB-USD\nHistorical prices (past 60 trading days): start=663.09, end=714.32, cumulative_return=+7.7%, annualized_volatility=35.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.61, 't10y3m_spread': 0.04, 'breakeven_10y': 2.4, 'hy_oas': 2.88, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.56, 'vix': 16.350000381469727}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BNB-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for BNB-USD starting 2025-09-04 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.077264, "annualized_vol": 0.356386, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250703_0670", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-07-03", "context_summary": "SOL-USD over past 60 days: cumulative return +5.7%, annualized vol 58.0%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=143.98, end=152.23, cumulative_return=+5.7%, annualized_volatility=58.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.52, 't10y3m_spread': -0.11, 'breakeven_10y': 2.3, 'hy_oas': 2.88, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.77, 'vix': 16.639999389648438}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.198188, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-07-03 was +19.82%, which classifies as 'positive'.", "metadata": {"future_return": 0.198188, "horizon_days": 21, "hist_return": 0.057261, "annualized_vol": 0.580254, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250226_0675", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-02-26", "context_summary": "XLV over past 60 days: cumulative return +1.8%, annualized vol 12.8%. 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us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealized [...TRUNCATED...] Power of Attorney for certain directors of Chevron Corporation, authorizing the signing of the Annual Report on Form 10-K on their behalf. 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer (page E-3). 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer (page E-4).   32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer (page E-5).   32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer (page E-6). 97.1+ Chevron Corporation Dodd-Frank Clawback Policy , filed as Exh i bit 97.1 to Ch ev ron Corporation ’ s Annual Report on Form 10-K for the year ended December 31, 2023, and incorporated herein by r eference . 99.1* Definitions of Selected Energy and Financial Terms (pages E-7 through E-10). 101* Interactive data files (formatted as Inline XBRL). 104* Cover Page Interactive Data File (contained in Exhibit 101).   ___________________________________________ + Indicates a management contract or compensatory plan or arrangement. *      Filed herewith. **      Furnished herewith. Pursuant to Item 601(b)(4) of Regulation S-K, certain instruments with respect to the company’s long-term debt are not filed with this Annual Report on Form 10-K. A copy of any such instrument will be furnished to the Securities and Exchange Commission upon request. 120 Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on the 21st day of February, 2025.  Chevron Corporation   By: /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities indicated on the 21st day of February, 2025.   Principal Executive Officer (and Director) /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer Principal Financial Officer /s/ EIMEAR P. BONNER Eimear P. Bonner, Vice President and Chief Financial Officer Principal Accounting Officer /s/ ALANA K. KNOWLES Alana K. Knowles, Vice President and Controller * By:  /s/ MARY A. FRANCIS Mary A. Francis, Attorney-in-Fact Directors WANDA M. AUSTIN * Wanda M. Austin JOHN B. FRANK * John B. Frank ALICE P. GAST * Alice P. Gast ENRIQUE HERNANDEZ, JR. * Enrique Hernandez, Jr. MARILLYN A. HEWSON * Marillyn A. Hewson JON M. HUNTSMAN JR. * Jon M. Huntsman Jr. CHARLES W. MOORMAN * Charles W. Moorman DAMBISA F. MOYO * Dambisa F. Moyo DEBRA REED-KLAGES * Debra Reed-Klages D. JAMES UMPLEBY III * D. James Umpleby III CYNTHIA J. WARNER * Cynthia J. Warner 121\n\nPredict whether the return of XLV over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.015486, "explanation": "The actual 21-day forward return for XLV starting 2025-02-26 was -1.55%, which classifies as 'negative'.", "metadata": {"future_return": -0.015486, "horizon_days": 21, "hist_return": 0.017789, "annualized_vol": 0.127647, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250205_0678", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2025-02-05", "context_summary": "QQQ over past 60 days: cumulative return +3.9%, annualized vol 19.0%. Market regime: sideways.", "question": "Asset: QQQ\nHistorical prices (past 60 trading days): start=501.59, end=521.17, cumulative_return=+3.9%, annualized_volatility=19.0%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.31, 't10y3m_spread': 0.19, 'breakeven_10y': 2.44, 'hy_oas': 2.71, 'ig_oas': 0.82, 'ted_spread': 0.09, 'mortgage_30y': 6.95, 'vix': 17.209999084472656}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K BA 2025-02-03] ba-20241231 FALSE 2024 FY BOEING CO 0000012927 http://fasb.org/us-gaap/2024#Revenues http://fasb.org/us-gaap/2024#Revenues http://fasb.org/us-gaap/2024#Revenues http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligations http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligations http://fasb.org/us-gaap/2024#LiabilitiesCurrent http://fasb.org/us-gaap/2024#LiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent 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us-gaap:OperatingSegmentsMember ba:BoeingDefenseSpaceSecuritySegmentMember 2023-01-01 2023-12-31 0000012927 us-gaap:OperatingSegmentsMember ba:BoeingDefenseSpaceSecuritySegmentMember 2022-01-01 2022-12-31 0000012927 us-gaap:OperatingSegmentsMember ba:GlobalServicesMember 2024-01-01 2024-12-31 0000012927 us-gaap:OperatingSegmentsMember ba:GlobalServicesMember 2023-01-01 2023-12-31 0000012927 us-gaap:OperatingSegmentsMember ba:GlobalServicesMember 2022-01-01 2022-12-31 0000012927 ba:CorporateReconcilingItemsAndEliminationsMember 2024-01-01 2024-12-31 0000012927 ba:CorporateReconcilingItemsAndEliminationsMember 2023-01-01 2 [...TRUNCATED...] ation of Chief Financial Officer pursuant to Section 906 of Sarbanes-Oxley Act of 2002 135 Table of Contents 97 The Boeing Company Clawback Policy (Exhibit 97 to the Company ’ s Form 1 0-K for the year ended December 31, 2023) 99.1 Commercial Program Method of Accounting (Exhibit (99)(i) to the Company’s Form 10-K for the year ended December 31, 1997) 101.SCH XBRL Taxonomy Extension Schema Document 101.CAL XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF XBRL Taxonomy Extension Definition Linkbase Document 101.LAB XBRL Taxonomy Extension Label Linkbase Document 101.PRE XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page XBRL tags are embedded within the Inline XBRL document contained in Exhibit 101      † Certain schedules have been omitted pursuant to Item 601(a)(5) of Regulation S-K. The Company will provide a copy of omitted schedule to the SEC upon request. * Management contract or compensatory plan In accordance with Item 601(b)(4)(iii)(A) of Regulation S-K, copies of certain instruments defining the rights of holders of long-term debt of the Company are not filed herewith. Pursuant to this regulation, we hereby agree to furnish a copy of any such instrument to the SEC upon request. Item 16. Form 10-K Summary None. 136 Table of Contents Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Date: February 3, 2025 THE BOEING COMPANY (Registrant) By:   /s/ Michael J. Cleary   Michael J. Cleary – Senior Vice President and Controller 137 Table of Contents Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities indicated on February 3, 2025. /s/ Robert K. Ortberg /s/ Lynn J. Good Robert K. Ortberg – President and Chief Executive Officer and Director Lynn J. Good – Director (Principal Executive Officer) /s/ Brian J. West /s/ Stayce D. Harris Brian J. West – Executive Vice President and Chief Financial Officer Stayce D. Harris – Director (Principal Financial Officer) /s/ Michael J. Cleary /s/ Akhil Johri Michael J. Cleary – Senior Vice President and Controller Akhil Johri – Director (Principal Accounting Officer) /s/ Robert A. Bradway /s/ David L. Joyce Robert A. Bradway – Director David L. Joyce – Director /s/ Mortimer J. Buckley III /s/ Steven M. Mollenkopf Mortimer J. Buckley – Director Steven M. Mollenkopf – Chair of the Board /s/ Lynne M. Doughtie /s/ John M. Richardson Lynne M. Doughtie – Director John M. Richardson – Director /s/ David L. Gitlin /s/ Sabrina Soussan David L. Gitlin – Director Sabrina Soussan – Director 138\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": -0.066546, "explanation": "The actual 21-day forward return for QQQ starting 2025-02-05 was -6.65%, which classifies as 'negative'.", "metadata": {"future_return": -0.066546, "horizon_days": 21, "hist_return": 0.039036, "annualized_vol": 0.189709, "has_text": true, "text_chars": 9044}} +{"id": "T1_all_20250103_0680", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-01-03", "context_summary": "SOL-USD over past 60 days: cumulative return +30.7%, annualized vol 68.2%. Market regime: sideways.", "question": "Asset: SOL-USD\nHistorical prices (past 60 trading days): start=157.75, end=206.25, cumulative_return=+30.7%, annualized_volatility=68.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.32, 't10y3m_spread': 0.21, 'breakeven_10y': 2.34, 'hy_oas': 2.88, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.91, 'vix': 17.93000030517578}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of SOL-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for SOL-USD starting 2025-01-03 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.307491, "annualized_vol": 0.68243, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250723_0683", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-07-23", "context_summary": "BTC-USD over past 60 days: cumulative return +0.0%, annualized vol 24.5%. Market regime: bull.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=103998.57, end=103998.57, cumulative_return=+0.0%, annualized_volatility=24.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.52, 't10y3m_spread': -0.06, 'breakeven_10y': 2.39, 'hy_oas': 2.9, 'ig_oas': 0.81, 'ted_spread': 0.09, 'mortgage_30y': 6.75, 'vix': 16.5}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for BTC-USD starting 2025-07-23 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.245489, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250211_0686", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-02-11", "context_summary": "XRP-USD over past 60 days: cumulative return +0.1%, annualized vol 75.8%. Market regime: sideways.", "question": "Asset: XRP-USD\nHistorical prices (past 60 trading days): start=2.42, end=2.42, cumulative_return=+0.1%, annualized_volatility=75.8%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.679, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.23, 't10y3m_spread': 0.16, 'breakeven_10y': 2.44, 'hy_oas': 2.66, 'ig_oas': 0.84, 'ted_spread': 0.09, 'mortgage_30y': 6.89, 'vix': 15.8100004196167}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of XRP-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.010562, "explanation": "The actual 21-day forward return for XRP-USD starting 2025-02-11 was +1.06%, which classifies as 'positive'.", "metadata": {"future_return": 0.010562, "horizon_days": 21, "hist_return": 0.000569, "annualized_vol": 0.758032, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250321_0689", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-03-21", "context_summary": "XLF over past 60 days: cumulative return +2.8%, annualized vol 17.1%. Market regime: sideways.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=47.40, end=48.71, cumulative_return=+2.8%, annualized_volatility=17.1%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.29, 't10y3m_spread': -0.09, 'breakeven_10y': 2.31, 'hy_oas': 3.17, 'ig_oas': 0.91, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 19.799999237060547}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-03-20] Asset Management & Auction Services Stocks Q4 Highlights: OPENLANE (NYSE:KAR) As the Q4 earnings season wraps, let\u2019s dig into this quarter\u2019s best and worst performers in the asset management & auction services industry, including OPENLANE (NYSE:KAR) and its peers. Like in other industries, the shift to online platforms can lower transaction costs and improve liquidity for sellers. Increasing digitization, AI-driven pricing analytics, and automation in logistics can enhance efficiency for operators who invest in technology and software. On the other hand, challenges include potential regulatory scrutiny on auction transparency, data privacy concerns with AI-driven valuation models, and shifting environmental policies that could impact the resale market for internal combustion vehicles. Additionally, supply chain volatility in new car production may create unpredictable swings in used vehicle supply, impacting auction volumes. The 4 asset management & auction services stocks we track reported an exceptional Q4. As a group, revenues beat analysts\u2019 consensus estimates by 9.1%. While some asset management & auction services stocks have fared somewhat better than others, they have collectively declined. On average, share prices are down 1.4% since the latest earnings results. Facilitating the sale of approximately 1.3 million used vehicles in 2023, OPENLANE (NYSE:KAR) operates digital marketplaces that connect sellers and buyers of used vehicles across North America and Europe, facilitating wholesale transactions. OPENLANE reported revenues of $455 million, up 12% year on year. This print exceeded analysts\u2019 expectations by 8.2%. Overall, it was a satisfactory quarter for the company with a decent beat of analysts\u2019 EPS estimates but a slight miss of analysts\u2019 full-year EPS guidance estimates. The stock is up 6% since reporting and currently trades at $21.25. Is now the time to buy OPENLANE? Access our full analysis of the earnings results here, it\u2019s free. Powering what it calls the \"circular economy\" with over 5.5 million registered buyers across its platforms, Liquidity Services (NASDAQ:LQDT) operates online marketplaces that connect buyers and sellers of surplus assets, from consumer returns to industrial equipment to government property. Liquidity Services reported revenues of $122.3 million, up 71.5% year on year, outperforming analysts\u2019 expectations by 16.1%. The business had an incredible quarter with an impressive beat of analysts\u2019 EPS estimates. Liquidity Services scored the biggest analyst estimates beat and fastest revenue growth among its peers. Although it had a fine quarter compared its peers, the market seems unhappy with the results as the stock is down 7% since reporting. It currently trades at $30.47. Is now the time to buy Liquidity Services? Access our full analysis of the earnings results here, it\u2019s free. Starting as a single salvage yard in California in 1982, Copart (NASDAQ:CPRT) operates an online auction platform that connects se\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": -0.07368, "explanation": "The actual 21-day forward return for XLF starting 2025-03-21 was -7.37%, which classifies as 'negative'.", "metadata": {"future_return": -0.07368, "horizon_days": 21, "hist_return": 0.027658, "annualized_vol": 0.171427, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250110_0691", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-01-10", "context_summary": "XLV over past 60 days: cumulative return -8.8%, annualized vol 11.9%. Market regime: sideways.", "question": "Asset: XLV\nHistorical prices (past 60 trading days): start=150.76, end=137.44, cumulative_return=-8.8%, annualized_volatility=11.9%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 318.961, 'unemployment': 4.0, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.41, 't10y3m_spread': 0.33, 'breakeven_10y': 2.39, 'hy_oas': 2.82, 'ig_oas': 0.83, 'ted_spread': 0.09, 'mortgage_30y': 6.93, 'vix': 17.700000762939453}\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 2024-12-04 0000104169 2024-08-01 2024-10-31 0000104169 2023-08-01 2023-10-31 0000104169 2023-02-01 2023-10-31 0000104169 2024-10-31 0000104169 2024-01-31 0000104169 2023-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-08-01 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\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": 0.047694, "explanation": "The actual 21-day forward return for XLV starting 2025-01-10 was +4.77%, which classifies as 'positive'.", "metadata": {"future_return": 0.047694, "horizon_days": 21, "hist_return": -0.088369, "annualized_vol": 0.119205, "has_text": true, "text_chars": 9045}} +{"id": "T1_all_20250728_0694", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-07-28", "context_summary": "BTC-USD over past 60 days: cumulative return +0.0%, annualized vol 24.6%. Market regime: bull.", "question": "Asset: BTC-USD\nHistorical prices (past 60 trading days): start=103998.57, end=103998.57, cumulative_return=+0.0%, annualized_volatility=24.6%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 322.169, 'unemployment': 4.3, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.49, 't10y3m_spread': -0.02, 'breakeven_10y': 2.44, 'hy_oas': 2.84, 'ig_oas': 0.78, 'ted_spread': 0.09, 'mortgage_30y': 6.74, 'vix': 14.93000030517578}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of BTC-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "flat", "answer_numeric": 0.0, "explanation": "The actual 21-day forward return for BTC-USD starting 2025-07-28 was +0.00%, which classifies as 'flat'.", "metadata": {"future_return": 0.0, "horizon_days": 21, "hist_return": 0.0, "annualized_vol": 0.245967, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250611_0697", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-06-11", "context_summary": "DOT-USD over past 60 days: cumulative return +15.5%, annualized vol 60.5%. Market regime: sideways.", "question": "Asset: DOT-USD\nHistorical prices (past 60 trading days): start=3.71, end=4.29, cumulative_return=+15.5%, annualized_volatility=60.5%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 321.435, 'unemployment': 4.1, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.46, 't10y3m_spread': 0.02, 'breakeven_10y': 2.29, 'hy_oas': 3.12, 'ig_oas': 0.87, 'ted_spread': 0.09, 'mortgage_30y': 6.85, 'vix': 16.950000762939453}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of DOT-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.15508, "explanation": "The actual 21-day forward return for DOT-USD starting 2025-06-11 was -15.51%, which classifies as 'negative'.", "metadata": {"future_return": -0.15508, "horizon_days": 21, "hist_return": 0.154567, "annualized_vol": 0.604515, "has_text": true, "text_chars": 20}} +{"id": "T1_all_20250930_0700", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LQD"], "decision_date": "2025-09-30", "context_summary": "LQD over past 60 days: cumulative return +3.4%, annualized vol 5.4%. Market regime: bull.", "question": "Asset: LQD\nHistorical prices (past 60 trading days): start=105.11, end=108.70, cumulative_return=+3.4%, annualized_volatility=5.4%\nMacro context: {'fed_funds_rate': 4.09, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24026.834, 't10y2y_spread': 0.52, 't10y3m_spread': 0.11, 'breakeven_10y': 2.35, 'hy_oas': 2.74, 'ig_oas': 0.77, 'ted_spread': 0.09, 'mortgage_30y': 6.3, 'vix': 16.1200008392334}\nMarket regime: bull\n\nPredict whether the return of LQD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "positive", "answer_numeric": 0.010949, "explanation": "The actual 21-day forward return for LQD starting 2025-09-30 was +1.09%, which classifies as 'positive'.", "metadata": {"future_return": 0.010949, "horizon_days": 21, "hist_return": 0.034116, "annualized_vol": 0.054287, "has_text": false, "text_chars": 0}} +{"id": "T1_all_20250507_0703", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2025-05-07", "context_summary": "XLE over past 60 days: cumulative return -10.3%, annualized vol 29.2%. Market regime: sideways.", "question": "Asset: XLE\nHistorical prices (past 60 trading days): start=43.51, end=39.01, cumulative_return=-10.3%, annualized_volatility=29.2%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 320.62, 'unemployment': 4.3, 'gdp_growth_qoq': 23770.976, 't10y2y_spread': 0.52, 't10y3m_spread': -0.03, 'breakeven_10y': 2.26, 'hy_oas': 3.66, 'ig_oas': 1.05, 'ted_spread': 0.09, 'mortgage_30y': 6.76, 'vix': 24.76000022888184}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-06] [\"ADP Announces Pricing of its Senior Notes Due 2032 ROSELAND, N.J., May 6, 2025 /PRNewswire/ -- ADP (Nasdaq: ADP), a leading global technology company providing comprehensive cloud-based human capital management (HCM) solutions, yesterday announced the pricing of a public offering of $1.0 billion aggregate principal amount of its 4.750% senior notes due 2032. ADP expects to receive the net offering proceeds upon closing on or about May 8, 2025. The intended use of proceeds from the offering is to refinance existing debt, and any remainder for general corporate purposes. ADP has filed a registration statement (including a prospectus and preliminary prospectus supplement) with the Securities and Exchange Commission (\\\"SEC\\\") for the offering to which this communication relates. Before you invest, you should read the base prospectus in that registration statement, the applicable preliminary prospectus supplement and the other documents ADP has filed with the SEC for more complete information about ADP and this offering. You may get these documents for free by visiting EDGAR on the SEC website at www.sec.gov. Alternatively, ADP, any underwriter or any dealer participating in the offering will arrange to send investors the prospectus and preliminary prospectus supplement upon request by contacting BofA Securities, Inc. by telephone at 1-800-294-1322 or by email at dg.prospectus_requests@bofa.com, J.P. Morgan Securities LLC by telephone (collect) at (212) 834-4533 or Morgan Stanley & Co. LLC by telephone at (866) 718-1649. This press release does not constitute an offer to sell or a solicitation of an offer to buy the debt securities or any other securities, nor shall there be any sale of these securities in any jurisdiction in which such an offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of any such jurisdiction. The offering of these securities may be made only by means of the prospectus supplement and the accompanying prospectus. This press release also does not constitute an offer to purchase, a solicitation of an offer to sell, or notice of redemption with respect to any securities of ADP. About ADP (NASDAQ \\u2013 ADP)Designing better ways to work through cutting-edge products, premium services and exceptional experiences that enable people to reach their full potential. HR, Talent, Time Management, Benefits and Payroll. Informed by data and designed for people. Forward-Looking Statements This document and other written or oral statements made from time to time by ADP may contain \\\"forward-looking statements\\\" within the meaning of the Private Securities Litigation Reform Act of 1995. Statements that are not historical in nature and which may be identified by the use of words like \\\"outlook,\\\" \\\"expects,\\\" \\\"assumes,\\\" \\\"projects,\\\" \\\"anticipates,\\\" \\\"estimates,\\\" \\\"we believe,\\\" \\\"could,\\\" \\\"is designed to\\\" and other words of similar meaning, are forward-looking statements. These st\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": 0.035506, "explanation": "The actual 21-day forward return for XLE starting 2025-05-07 was +3.55%, which classifies as 'positive'.", "metadata": {"future_return": 0.035506, "horizon_days": 21, "hist_return": -0.103436, "annualized_vol": 0.292485, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20250325_0706", "template": "T1", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-03-25", "context_summary": "XLF over past 60 days: cumulative return +2.7%, annualized vol 17.3%. Market regime: sideways.", "question": "Asset: XLF\nHistorical prices (past 60 trading days): start=48.07, end=49.39, cumulative_return=+2.7%, annualized_volatility=17.3%\nMacro context: {'fed_funds_rate': 4.33, 'cpi_yoy': 319.785, 'unemployment': 4.2, 'gdp_growth_qoq': 23548.21, 't10y2y_spread': 0.3, 't10y3m_spread': 0.01, 'breakeven_10y': 2.36, 'hy_oas': 3.05, 'ig_oas': 0.9, 'ted_spread': 0.09, 'mortgage_30y': 6.67, 'vix': 17.479999542236328}\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-03-24] [\"Nvidia\\u2019s Support Boosts Stereotaxis (STXS) in Advancing Robotic Surgery We recently compiled a list of the Top 8 AI News Updates Investors Shouldn\\u2019t Miss. In this article, we are going to take a look at where Stereotaxis, Inc. (NYSEAMERICAN:STXS) stands against the other AI stocks. On March 19th, the stock market bounced back after the US Federal Reserve kept interest rates unchanged at 4.25% to 4.5%. The Fed also anticipated two rate cuts this year despite elevated inflation. The S&P 500 index was up over 1%, while the Nasdaq Composite jumped by well over 200 points. The rally was led by the magnificent seven stocks after weeks of market declines amid trade wars and disappointing economic data. Elsewhere, AI continues to transform industries and individual lives, from AI nurses reshaping hospital care to schools reporting that students are learning faster and more effectively with AI. Furthermore, AngelList CEO Avlok Kohli claimed that all software companies are AI companies now. Meanwhile, security risks surrounding AI continue to loom. Computer scientist and AI pioneer Fei-Fei Li co-authored a report suggesting that lawmakers should consider AI risks that \\u201chave not yet been observed in the world\\u201d when devising AI regulations. The report highlighted that the novel risks posed by AI could require legislation that compels AI developers to publicly report their safety tests and security protocols. We selected AI stocks by reviewing news articles, stock analysis, and press releases. We listed the stocks in ascending order of their hedge fund sentiment taken from Insider Monkey\\u2019s Q4 2024 database of over 1000 hedge funds. Why are we interested in the stocks that hedge funds pile into? The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter\\u2019s strategy selects 14 small-cap and large-cap stocks every quarter and has returned 373.4% since May 2014, beating its benchmark by 218 percentage points (see more details here). A robotic arm assembling delicate surgical tools in a clean room environment. Stereotaxis, Inc. (NYSEAMERICAN:STXS) engages in discovering, designing, and delivering innovative surgical robotic systems, instruments, and information systems for minimally invasive endovascular surgeries. Its robotic systems help physicians operate with precision and safety, boosting productivity and connectivity in the operating room. The company is focusing on enhancing its robotic systems and the operating room environments using AI, automation, and data integration. On March 19th, Stereotaxis (NYSEAMERICAN:STXS) announced that Nvidia Corp. (NASDAQ:NVDA) accepted the company into the Nvidia Connect program. The program assists members with Nvidia\\u2019s software development resources and frameworks. Overall, STXS ranks 8th on our list of top AI news updates investors shouldn\\u2019t miss. While we acknowledge the potenti\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": -0.043228, "explanation": "The actual 21-day forward return for XLF starting 2025-03-25 was -4.32%, which classifies as 'negative'.", "metadata": {"future_return": -0.043228, "horizon_days": 21, "hist_return": 0.027397, "annualized_vol": 0.172668, "has_text": true, "text_chars": 3020}} +{"id": "T1_all_20251021_0709", "template": "T1", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-10-21", "context_summary": "AVAX-USD over past 60 days: cumulative return -19.3%, annualized vol 80.6%. Market regime: bull.", "question": "Asset: AVAX-USD\nHistorical prices (past 60 trading days): start=25.24, end=20.36, cumulative_return=-19.3%, annualized_volatility=80.6%\nMacro context: {'fed_funds_rate': 4.11, 'cpi_yoy': 324.245, 'unemployment': 4.4, 'gdp_growth_qoq': 24055.749, 't10y2y_spread': 0.54, 't10y3m_spread': 0.03, 'breakeven_10y': 2.26, 'hy_oas': 2.99, 'ig_oas': 0.79, 'ted_spread': 0.09, 'mortgage_30y': 6.27, 'vix': 18.229999542236328}\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nPredict whether the return of AVAX-USD over the next 21 trading days will be: positive (>+1%), negative (<-1%), or flat (within \u00b11%).", "answer": "negative", "answer_numeric": -0.130055, "explanation": "The actual 21-day forward return for AVAX-USD starting 2025-10-21 was -13.01%, which classifies as 'negative'.", "metadata": {"future_return": -0.130055, "horizon_days": 21, "hist_return": -0.193442, "annualized_vol": 0.805861, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251226_0002", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-12-26", "context_summary": "SOL-USD: 60-day return history, mean=-0.0078, std=0.0370.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0078, std=0.0370, min=-0.1157, max=0.0944\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0538", "answer_numeric": -0.053758, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0538 (i.e., on a bad day with 5% probability, the loss exceeds 5.38%). CVaR(95%) = -0.0855.", "metadata": {"var": -0.053758, "cvar": -0.085513, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251027_0003", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["HAUZ"], "decision_date": "2025-10-27", "context_summary": "HAUZ: 60-day return history, mean=0.0011, std=0.0069.", "question": "Asset: HAUZ\nDaily returns (past 60 days): mean=0.0011, std=0.0069, min=-0.0153, max=0.0167\nMarket regime: bull\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": "-0.0108", "answer_numeric": -0.0108, "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%) = -0.0126.", "metadata": {"var": -0.0108, "cvar": -0.012587, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251209_0006", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-12-09", "context_summary": "EFA: 60-day return history, mean=0.0004, std=0.0070.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0004, std=0.0070, min=-0.0186, max=0.0153\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-10-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-10-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-10-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-10-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-10-31 0000104169 2025-12-02 0000104169 2025-08-01 2025-10-31 0000104169 2024-08-01 2024-10-31 0000104169 2024-02-01 2024-10-31 0000104169 2025-10-31 0000104169 2025-01-31 0000104169 2024-10-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-30 0000104169 us-gaap:ParentMember 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-04-30 0000104169 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-05-01 2025-07-31 0000104169 us-gaap:ParentMember 2025-05-01 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-05-01 2025-07-31 0000104169 2025-05-01 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-05-01 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-31 0000104169 us-gaap:ParentMember 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-08-01 2025-10-31 0000104169 us-gaap:ParentMember 2025-08-01 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-08-01 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-08-01 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EFA. Express as a decimal (e.g., -0.02).", "answer": "-0.0131", "answer_numeric": -0.013063, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0131 (i.e., on a bad day with 5% probability, the loss exceeds 1.31%). CVaR(95%) = -0.0152.", "metadata": {"var": -0.013063, "cvar": -0.015205, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250716_0009", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-07-16", "context_summary": "SOL-USD: 60-day return history, mean=0.0002, std=0.0319.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0002, std=0.0319, min=-0.0622, max=0.1005\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0505", "answer_numeric": -0.050508, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0505 (i.e., on a bad day with 5% probability, the loss exceeds 5.05%). CVaR(95%) = -0.0570.", "metadata": {"var": -0.050508, "cvar": -0.056988, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250424_0012", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2025-04-24", "context_summary": "MATIC-USD: 60-day return history, mean=-0.0097, std=0.0451.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0097, std=0.0451, min=-0.1586, max=0.0741\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0998", "answer_numeric": -0.099792, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0998 (i.e., on a bad day with 5% probability, the loss exceeds 9.98%). CVaR(95%) = -0.1253.", "metadata": {"var": -0.099792, "cvar": -0.125321, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250711_0015", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2025-07-11", "context_summary": "ACWI: 60-day return history, mean=0.0027, std=0.0081.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0027, std=0.0081, min=-0.0163, max=0.0241\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-07-10] [\"Photos: Tim Cook, Sam Altman and Silicon Valley\\u2019s elite arrive at the \\u2018summer camp for billionaires\\u2019 Within the resort town of Sun Valley, Idaho, a small group of the world\\u2019s richest people are beginning to gather for Allen & Company\\u2019s annual Sun Valley Conference. The four-day retreat, known informally as \\u201csummer camp for billionaires,\\u201d is full of opportunities for powerful figures to schmooze, network, and make deals. Among this year\\u2019s cohort are tech tycoons Tim Cook of Apple, Sam Altman of OpenAI, and Andy Jassy of Amazon. Bob Iger and Michael Eisner, the current and former CEOs of Disney, respectively, are also in attendance, as well as General Motors CEO Mary Barra. The conference has no shortage of political presence, too: Ivanka Trump and Jared Kushner are both present at the conference this year. Some of the camp\\u2019s usual suspects, including Meta\\u2019s Mark Zuckerberg, Microsoft\\u2019s Bill Gates, and Amazon\\u2019s Jeff Bezos (who had his Venetian \\u201cWedding of the Century\\u201d not too long ago) have not yet been spotted, though they were reported to have been invited to this year\\u2019s conference, according to Variety. Additionally, Tesla\\u2019s Elon Musk wasn\\u2019t on the invite list, and Berkshire Hathaway\\u2019s Warren Buffett, who announced his retirement earlier this year, won\\u2019t be in attendance. This story was originally featured on Fortune.com\", \"The world\\u2019s 10 richest people: The wealthiest have $100 billion or more The world\\u2019s wealthiest people have several things in common, but one of the most prominent is that the 10 richest have more than $100 billion to their name. The very top have $200 billion or more. These amounts don\\u2019t consist of cash sitting in a bank but are mainly investments, often of some of the largest publicly traded companies, which even the general public can invest in. These billionaires reached their lofty heights through hard work, great ideas, serendipity and plenty of careful planning along the way. Here are the world\\u2019s 10 richest people and some of their key investments, according to the Bloomberg Billionaires Index, as of July 9, 2025. Elon Musk is one of the most controversial business figures, but what\\u2019s not under dispute is his wealth. Born in South Africa, Musk built Tesla into a leading player in the electric vehicle market, and is pushing space travel with his SpaceX venture. Musk made a small fortune as an early shareholder of PayPal, and more recently purchased Twitter, which he renamed X. Musk has courted controversy in recent years, becoming politically aligned with President Donald Trump during the 2024 presidential election before becoming the face of the Department of Government Efficiency (DOGE), as well as using drugs during a broadcast interview with top podcaster Joe Rogan. Get started: Match with an advisor who can help you achieve your financial goals Mark Zuckerberg is the founder of Meta Platforms, th\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": "-0.0116", "answer_numeric": -0.011621, "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%) = -0.0149.", "metadata": {"var": -0.011621, "cvar": -0.014922, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250421_0018", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["CORN"], "decision_date": "2025-04-21", "context_summary": "CORN: 60-day return history, mean=-0.0004, std=0.0099.", "question": "Asset: CORN\nDaily returns (past 60 days): mean=-0.0004, std=0.0099, min=-0.0221, max=0.0209\nMarket regime: bear\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": "-0.0185", "answer_numeric": -0.018528, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0185 (i.e., on a bad day with 5% probability, the loss exceeds 1.85%). CVaR(95%) = -0.0199.", "metadata": {"var": -0.018528, "cvar": -0.019913, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250425_0021", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["IEF"], "decision_date": "2025-04-25", "context_summary": "IEF: 60-day return history, mean=0.0006, std=0.0044.", "question": "Asset: IEF\nDaily returns (past 60 days): mean=0.0006, std=0.0044, min=-0.0103, max=0.0103\nMarket regime: bear\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": "-0.0058", "answer_numeric": -0.00581, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0058 (i.e., on a bad day with 5% probability, the loss exceeds 0.58%). CVaR(95%) = -0.0078.", "metadata": {"var": -0.00581, "cvar": -0.007819, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250521_0024", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-05-21", "context_summary": "ETH-USD: 60-day return history, mean=0.0043, std=0.0456.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0043, std=0.0456, min=-0.1269, max=0.1560\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0536", "answer_numeric": -0.053587, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0536 (i.e., on a bad day with 5% probability, the loss exceeds 5.36%). CVaR(95%) = -0.0907.", "metadata": {"var": -0.053587, "cvar": -0.090667, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250131_0027", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-01-31", "context_summary": "LINK-USD: 60-day return history, mean=0.0037, std=0.0615.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0037, std=0.0615, min=-0.1453, max=0.1799\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0814", "answer_numeric": -0.081371, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0814 (i.e., on a bad day with 5% probability, the loss exceeds 8.14%). CVaR(95%) = -0.1175.", "metadata": {"var": -0.081371, "cvar": -0.117491, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250228_0030", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-02-28", "context_summary": "DOT-USD: 60-day return history, mean=-0.0044, std=0.0461.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0044, std=0.0461, min=-0.1306, max=0.0874\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0974", "answer_numeric": -0.097416, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0974 (i.e., on a bad day with 5% probability, the loss exceeds 9.74%). CVaR(95%) = -0.1186.", "metadata": {"var": -0.097416, "cvar": -0.1186, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250327_0032", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-03-27", "context_summary": "DOT-USD: 60-day return history, mean=-0.0039, std=0.0458.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0039, std=0.0458, min=-0.1391, max=0.1146\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0853", "answer_numeric": -0.085308, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0853 (i.e., on a bad day with 5% probability, the loss exceeds 8.53%). CVaR(95%) = -0.1266.", "metadata": {"var": -0.085308, "cvar": -0.126573, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250225_0035", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2025-02-25", "context_summary": "XLP: 59-day return history, mean=0.0001, std=0.0071.", "question": "Asset: XLP\nDaily returns (past 59 days): mean=0.0001, std=0.0071, min=-0.0157, max=0.0211\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K CVX 2025-02-21] cvx-20241231 0000093410 false 2024 FY 367 http://fasb.org/us-gaap/2024#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2024#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 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us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealized [...TRUNCATED...] Power of Attorney for certain directors of Chevron Corporation, authorizing the signing of the Annual Report on Form 10-K on their behalf. 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer (page E-3). 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer (page E-4).   32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer (page E-5).   32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer (page E-6). 97.1+ Chevron Corporation Dodd-Frank Clawback Policy , filed as Exh i bit 97.1 to Ch ev ron Corporation ’ s Annual Report on Form 10-K for the year ended December 31, 2023, and incorporated herein by r eference . 99.1* Definitions of Selected Energy and Financial Terms (pages E-7 through E-10). 101* Interactive data files (formatted as Inline XBRL). 104* Cover Page Interactive Data File (contained in Exhibit 101).   ___________________________________________ + Indicates a management contract or compensatory plan or arrangement. *      Filed herewith. **      Furnished herewith. Pursuant to Item 601(b)(4) of Regulation S-K, certain instruments with respect to the company’s long-term debt are not filed with this Annual Report on Form 10-K. A copy of any such instrument will be furnished to the Securities and Exchange Commission upon request. 120 Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on the 21st day of February, 2025.  Chevron Corporation   By: /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities indicated on the 21st day of February, 2025.   Principal Executive Officer (and Director) /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer Principal Financial Officer /s/ EIMEAR P. BONNER Eimear P. Bonner, Vice President and Chief Financial Officer Principal Accounting Officer /s/ ALANA K. KNOWLES Alana K. Knowles, Vice President and Controller * By:  /s/ MARY A. FRANCIS Mary A. Francis, Attorney-in-Fact Directors WANDA M. AUSTIN * Wanda M. Austin JOHN B. FRANK * John B. Frank ALICE P. GAST * Alice P. Gast ENRIQUE HERNANDEZ, JR. * Enrique Hernandez, Jr. MARILLYN A. HEWSON * Marillyn A. Hewson JON M. HUNTSMAN JR. * Jon M. Huntsman Jr. CHARLES W. MOORMAN * Charles W. Moorman DAMBISA F. MOYO * Dambisa F. Moyo DEBRA REED-KLAGES * Debra Reed-Klages D. JAMES UMPLEBY III * D. James Umpleby III CYNTHIA J. WARNER * Cynthia J. Warner 121\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": "-0.0120", "answer_numeric": -0.01197, "explanation": "Historical simulation VaR at 95%: sort the 59 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%) = -0.0149.", "metadata": {"var": -0.01197, "cvar": -0.014872, "confidence": 0.95, "n_returns": 59, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250520_0038", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-05-20", "context_summary": "VTI: 60-day return history, mean=-0.0005, std=0.0147.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=-0.0005, std=0.0147, min=-0.0335, max=0.0264\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-19] [\"Zacks Investment Ideas feature highlights: Arista Networks, Apple and Applied Industrial Technologies Chicago, IL \\u2013 May 19, 2025\\u2013 Today, Zacks Investment Ideas feature highlights Arista Networks ANET, Apple AAPL and Applied Industrial Technologies AIT. There are many ways that companies can keep shareholders happy, whether that be through robust financial performance or consistent dividend payouts, just for a few simple examples. Companies can also demonstrate a shareholder-friendly nature through share repurchase programs, also commonly known as stock buybacks. Several companies, including Arista Networks, Apple and Applied Industrial Technologies, recently unveiled fresh buybacks. Let's take a closer look at the benefits and the announcements of each. Stock buybacks, also known as share repurchase programs, are commonly deployed by companies to boost shareholder value. A stock buyback occurs when a company purchases outstanding shares of its stock. In its simplest form, buybacks represent companies essentially re-investing in themselves. Reducing the number of outstanding shares can boost earnings per share (EPS), also helping to put a floor under shares, reflective of consistent buying pressure. Still, it's worth mentioning that buybacks can sometimes bring out critics, as some believe the cash could be better deployed elsewhere, such as R&D. Nonetheless, buybacks are generally a net positive for shareholders, particularly those of mature companies with a much smaller growth runway. Arista Networks' latest set of quarterly results beat our consensus EPS and sales estimates handily, with revenue of $2.0 billion showing nearly 30% growth year-over-year. The company's sales growth has been fueled by the AI frenzy, as the company is an industry leader in data-driven, client-to-cloud networking for large AI, data center, campus, and routing environments. The stock also sports a favorable Zacks Rank #2 (Buy), with EPS expectations increasing across the board. Arista Networks unveiled an additional $1.5 billion repurchase program in the release. Down 15% year-to-date, Apple shares have struggled in 2025, underperforming relative to the S&P 500 in a big way and driven lower by initial tariff headlines. Shares faced pressure as a result, but the recent de-escalation announcement between the US and China has brought back positivity. Apple unveiled a massive $100 billion additional repurchase program in its latest quarterly report, putting some of its cash to work. The earnings outlook for the tech titan remains under pressure, with analysts taking their EPS expectations lower across the board over recent months. The evolving EPS outlook of Apple is certainly going to be interesting, particularly so amid all the back-and-forth news we've received concerning tariffs and other economic developments. It's worth remembering that the company is no longer the growth machine it used to be, with EPS forecasted to climb 6% on 3% higher sales in its cu\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": "-0.0279", "answer_numeric": -0.027916, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0279 (i.e., on a bad day with 5% probability, the loss exceeds 2.79%). CVaR(95%) = -0.0335.", "metadata": {"var": -0.027916, "cvar": -0.033457, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250725_0040", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-07-25", "context_summary": "AVAX-USD: 60-day return history, mean=0.0009, std=0.0383.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0009, std=0.0383, min=-0.0760, max=0.0970\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0578", "answer_numeric": -0.057793, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0578 (i.e., on a bad day with 5% probability, the loss exceeds 5.78%). CVaR(95%) = -0.0723.", "metadata": {"var": -0.057793, "cvar": -0.072331, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250917_0043", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-09-17", "context_summary": "ETH-USD: 60-day return history, mean=0.0047, std=0.0377.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0047, std=0.0377, min=-0.0851, max=0.1440\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0443", "answer_numeric": -0.044338, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0443 (i.e., on a bad day with 5% probability, the loss exceeds 4.43%). CVaR(95%) = -0.0656.", "metadata": {"var": -0.044338, "cvar": -0.065623, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250221_0046", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-02-21", "context_summary": "DOT-USD: 60-day return history, mean=-0.0040, std=0.0457.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0040, std=0.0457, min=-0.1306, max=0.0874\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0846", "answer_numeric": -0.084645, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0846 (i.e., on a bad day with 5% probability, the loss exceeds 8.46%). CVaR(95%) = -0.1142.", "metadata": {"var": -0.084645, "cvar": -0.11418, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250317_0049", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-03-17", "context_summary": "ADA-USD: 60-day return history, mean=-0.0095, std=0.0602.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0095, std=0.0602, min=-0.1761, max=0.2212\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.1052", "answer_numeric": -0.105166, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1052 (i.e., on a bad day with 5% probability, the loss exceeds 10.52%). CVaR(95%) = -0.1324.", "metadata": {"var": -0.105166, "cvar": -0.132443, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250324_0052", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-03-24", "context_summary": "USMV: 60-day return history, mean=0.0006, std=0.0066.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0006, std=0.0066, min=-0.0149, max=0.0136\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-03-21] [\"Top Research Reports for Apple, Meta Platforms & Chevron Thursday, March 20, 2025 The Zacks Research Daily presents the best research output of our analyst team. Today's Research Daily features new research reports on 16 major stocks, including Apple Inc. (AAPL), Meta Platforms, Inc. (META) and Chevron Corp. (CVX), as well as two micro-cap stocks Taylor Devices, Inc. (TAYD) and GSI Technology, Inc. (GSIT). The Zacks microcap research is unique as our research content on these small and under-the-radar companies is the only research of its type in the country. 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 >>> Ahead of Wall Street The daily 'Ahead of Wall Street' article is a must-read for all investors who would like to be ready for that day's trading action. The article comes out before the market opens and attempts to make sense of that morning's economic releases and how they will affect that day's market action. You can read this article for free on our home page and can actually sign up there to get an email notification as this article comes out each morning. You can read today's AWS here >>> Pre-Markets Lower; Economic News Decent Today's Featured Research Reports Apple\\u2019s shares have outperformed the Zacks Computer - Micro Computers industry over the past year (+26.7% vs. +24.8%). The company is benefiting from strong growth in Services revenues. It now has more than 1 billion paid subscribers across its Services portfolio, more than double what it had four years ago. The expanding content portfolio of Apple TV+ and Apple Arcade helped in driving subscriber growth. Apple expects the March quarter\\u2019s (second-quarter fiscal 2025) revenues to grow low to mid-single digits on a year-over-year basis. For the Services segment, It expects a low double-digit growth rate. Introduction of Apple Intelligence, an advanced personal intelligence system seamlessly integrated into iOS 18, iPadOS 18 and macOS Sequoia will help Apple shares to push higher. However, weakness in iPhone sales particularly in China is a concern. Increasing regulatory headwinds is a headwind. (You can read the full research report on Apple here >>>) Shares of Meta Platforms have outperformed the Zacks Internet - Software industry over the past year (+20.1% vs. +3.8%). The company is benefiting from steady user growth across all regions, particularly Asia Pacific. Increased engagement for its offerings like Instagram, WhatsApp, Messenger and Facebook has been a major growth driver. META has been leveraging AI to improve the potency of its platform offerings. These services currently reach more than 3.35 billion people daily. Meta\\u2019s growing footprint among young adults, driven by improving recommendations, boosts its competitive prowess. AI usage is making it a popular name among advertisers. This is expected to drive top-line growth. Meta now expect\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": "-0.0107", "answer_numeric": -0.010699, "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%) = -0.0135.", "metadata": {"var": -0.010699, "cvar": -0.013536, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250206_0055", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USO"], "decision_date": "2025-02-06", "context_summary": "USO: 60-day return history, mean=0.0011, std=0.0146.", "question": "Asset: USO\nDaily returns (past 60 days): mean=0.0011, std=0.0146, min=-0.0290, max=0.0432\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": "-0.0185", "answer_numeric": -0.018453, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0185 (i.e., on a bad day with 5% probability, the loss exceeds 1.85%). CVaR(95%) = -0.0238.", "metadata": {"var": -0.018453, "cvar": -0.023846, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251111_0058", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["HYG"], "decision_date": "2025-11-11", "context_summary": "HYG: 60-day return history, mean=0.0002, std=0.0024.", "question": "Asset: HYG\nDaily returns (past 60 days): mean=0.0002, std=0.0024, min=-0.0058, max=0.0081\nMarket regime: bull\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": "-0.0031", "answer_numeric": -0.00308, "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%) = -0.0042.", "metadata": {"var": -0.00308, "cvar": -0.004181, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250203_0060", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2025-02-03", "context_summary": "FXI: 60-day return history, mean=0.0001, std=0.0185.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0001, std=0.0185, min=-0.0438, max=0.0476\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q AAPL 2025-01-31] aapl-20241228 false 2025 Q1 0000320193 --09-27 P1Y P1Y P1Y P1Y P421D P342D xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure aapl:Customer aapl:Vendor 0000320193 2024-09-29 2024-12-28 0000320193 us-gaap:CommonStockMember 2024-09-29 2024-12-28 0000320193 aapl:A0.000Notesdue2025Member 2024-09-29 2024-12-28 0000320193 aapl:A0.875NotesDue2025Member 2024-09-29 2024-12-28 0000320193 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0000320193 us-gaap:FairValueInputsLevel1Member 2024-09-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasurySecuritiesMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:ForeignGovernmentDebtSecuritiesMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:BankTimeDepositsMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:CommercialPaperMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:CorporateDebtSecuritiesMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:USStatesAndPoliticalSubdivisionsMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:AssetBackedSecuritiesMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel2Member 2024-09-28 0000320193 aapl:UnfavorableInvestigationOutcomeEUStateAidRulesMember 2024-12-28 0000320193 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Item 4.    Mine Safety Disclosures Not applicable. Item 5.    Other Information Insider Trading Arrangements On November 6, 2024 , Luca Maestri , the Company’s former Senior Vice President and Chief Financial Officer, and current Vice President, Corporate Services , entered into a trading plan intended to satisfy the affirmative defense conditions of Rule 10b5-1(c) under the Exchange Act. The plan provides for the sale, subject to certain price limits, of shares vesting between April 1, 2025 and October 15, 2025, pursuant to certain equity awards granted to Mr. Maestri, excluding any shares withheld by the Company to satisfy income tax withholding and remittance obligations. Mr. Maestri’s plan will expire on December 31, 2025 , subject to early termination in accordance with the terms of the plan. On November 25, 2024 , Kate Adams , the Company’s Senior Vice President, General Counsel and Secretary , entered into a trading plan intended to satisfy the affirmative defense conditions of Rule 10b5-1(c) under the Exchange Act. The plan provides for the sale of shares vesting between April 1, 2025 and October 1, 2025, pursuant to certain equity awards granted to Ms. Adams, excluding any shares withheld by the Company to satisfy income tax withholding and remittance obligations. Ms. Adam’s plan will expire on November 1, 2025 , subject to early termination in accordance with the terms of the plan. Item 6.    Exhibits Incorporated by Reference Exhibit Number Exhibit Description Form Exhibit Filing Date/ Period End Date 10.1*, ** A pple Inc. Employee Sto ck Purchase Plan, as am ended as of November 6, 2024. 10.2*, ** A pple Inc. Non-Employee Director Stock Plan, as amended Novembe r 6, 2024. 31.1** Rule 13a-14(a) / 15d-14(a) Certification of Chief Executive Officer. 31.2** Rule 13a-14(a) / 15d-14(a) Certification of Chief Financial Officer. 32.1*** Section 1350 Certifications of Chief Executive Officer and Chief Financial Officer. 101** Inline XBRL Document Set for the condensed consolidated financial statements and accompanying notes in Part I, Item 1, “Financial Statements” of this Quarterly Report on Form 10-Q. 104** Inline XBRL for the cover page of this Quarterly Report on Form 10-Q, included in the Exhibit 101 Inline XBRL Document Set. *    Indicates management contract or compensatory plan or arrangement. **    Filed herewith. ***    Furnished herewith. Apple Inc. | Q1 2025 Form 10-Q | 21 SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: January 31, 2025 Apple Inc. By: /s/ Kevan Parekh Kevan Parekh Senior Vice President, Chief Financial Officer Apple Inc. | Q1 2025 Form 10-Q | 22\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": "-0.0302", "answer_numeric": -0.030238, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0302 (i.e., on a bad day with 5% probability, the loss exceeds 3.02%). CVaR(95%) = -0.0417.", "metadata": {"var": -0.030238, "cvar": -0.041745, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20251008_0063", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-10-08", "context_summary": "XLF: 60-day return history, mean=0.0004, std=0.0075.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0004, std=0.0075, min=-0.0187, max=0.0164\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": "-0.0115", "answer_numeric": -0.01153, "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%) = -0.0182.", "metadata": {"var": -0.01153, "cvar": -0.018151, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250108_0066", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-01-08", "context_summary": "AVAX-USD: 60-day return history, mean=0.0071, std=0.0624.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0071, std=0.0624, min=-0.1614, max=0.2028\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0917", "answer_numeric": -0.091665, "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%) = -0.1254.", "metadata": {"var": -0.091665, "cvar": -0.12539, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250212_0069", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNO"], "decision_date": "2025-02-12", "context_summary": "BNO: 60-day return history, mean=0.0012, std=0.0128.", "question": "Asset: BNO\nDaily returns (past 60 days): mean=0.0012, std=0.0128, min=-0.0252, max=0.0461\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": "-0.0163", "answer_numeric": -0.016264, "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%) = -0.0198.", "metadata": {"var": -0.016264, "cvar": -0.019838, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251106_0073", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2025-11-06", "context_summary": "FXI: 60-day return history, mean=0.0010, std=0.0135.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0010, std=0.0135, min=-0.0438, max=0.0308\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q JPM 2025-11-04] jpm-20250930 0000019617 FALSE 2025 Q3 12/31 true false http://fasb.org/us-gaap/2025#NoninterestIncomeOther http://fasb.org/us-gaap/2025#NoninterestIncomeOther http://fasb.org/us-gaap/2025#NoninterestIncomeOther http://fasb.org/us-gaap/2025#NoninterestIncomeOther March 31, 2026 235 March 31, 2026 237 March 31, 2026 235 March 31, 2026 242 March 31, 2026 229 March 31, 2026 230 March 31, 2026 235 March 31, 2026 232 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Exhibit No. Description of Exhibit 3.1 Restate d Certificat e of Incorporation of JPMorgan Chase & Co., effective September 16, 202 5 . (a) 3.2 B y-laws of J P Morgan Chase & Co., as amended, effec tive Sept ember 12 , 202 5 ( incor porated by re ference to Exhibit 3. 2 to the Current Report on Form 8-K of J PM organ Ch a se & Co. (File No. 1-5805) filed S eptember 1 2, 202 5 ). 15 Letter re: Unaudited Interim Financial Information. (a) 22 Subsidiary Guarantors and Issuers of Guaranteed Securities . (a) 31.1 Certification. (a) 31.2 Certification. (a) 32 Certification Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002. (b) 101.INS The instance document does not appear in the interactive data file because its XBRL tags are embedded within the Inline XBRL document. (c) 101.SCH XBRL Taxonomy Extension Schema Document. (a) 101.CAL XBRL Taxonomy Extension Calculation Linkbase Document. (a) 101.DEF XBRL Taxonomy Extension Definition Linkbase Document. (a) 101.LAB XBRL Taxonomy Extension Label Linkbase Document. (a) 101.PRE XBRL Taxonomy Extension Presentation Linkbase Document. (a) 104 Cover Page Interactive Data File (embedded within the Inline XBRL document and included in Exhibit 101). (a) Filed herewith. (b) Furnished herewith. This exhibit shall not be deemed “filed” for purposes of Section 18 of the Securities Exchange Act of 1934, or otherwise subject to the liability of that Section. Such exhibit shall not be deemed incorporated into any filing under the Securities Act of 1933 or the Securities Exchange Act of 1934. (c) Pursuant to Rule 405 of Regulation S-T, includes the following financial information included in the Firm’s Quarterly Report on Form 10-Q for the quarterly period ended September 30, 2025, formatted in XBRL (eXtensible Business Reporting Language) interactive data files: (i) the Consolidated statements of income (unaudited) for the three and nine months ended September 30, 2025 and 2024, (ii) the Consolidated statements of comprehensive income (unaudited) for the three and nine months ended September 30, 2025 and 2024, (iii) the Consolidated balance sheets (unaudited) as of September 30, 2025 and December 31, 2024, (iv) the Consolidated statements of changes in stockholders’ equity (unaudited) for the three and nine months ended September 30, 2025 and 2024, (v) the Consolidated statements of cash flows (unaudited) for the nine months ended September 30, 2025 and 2024, and (vi) the Notes to Consolidated Financial Statements (unaudited). 206 SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. JPMorgan Chase & Co. (Registrant) By: /s/ Elena Korablina Elena Korablina Managing Director and Firmwide Controller (Principal Accounting Officer) Date: November 4, 2025 207\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": "-0.0194", "answer_numeric": -0.019415, "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%) = -0.0300.", "metadata": {"var": -0.019415, "cvar": -0.029961, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250318_0076", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-03-18", "context_summary": "SOL-USD: 60-day return history, mean=-0.0063, std=0.0648.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0063, std=0.0648, min=-0.2043, max=0.2423\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0767", "answer_numeric": -0.076741, "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%) = -0.1455.", "metadata": {"var": -0.076741, "cvar": -0.145477, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251121_0079", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SLV"], "decision_date": "2025-11-21", "context_summary": "SLV: 60-day return history, mean=0.0050, std=0.0195.", "question": "Asset: SLV\nDaily returns (past 60 days): mean=0.0050, std=0.0195, min=-0.0452, max=0.0426\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": "-0.0311", "answer_numeric": -0.031056, "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%) = -0.0419.", "metadata": {"var": -0.031056, "cvar": -0.041904, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250326_0082", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2025-03-26", "context_summary": "IYR: 60-day return history, mean=0.0003, std=0.0108.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=0.0003, std=0.0108, min=-0.0267, max=0.0231\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": "-0.0173", "answer_numeric": -0.01734, "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%) = -0.0233.", "metadata": {"var": -0.01734, "cvar": -0.023342, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250529_0085", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-05-29", "context_summary": "AVAX-USD: 60-day return history, mean=0.0042, std=0.0494.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0042, std=0.0494, min=-0.1060, max=0.1441\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0634", "answer_numeric": -0.063424, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0634 (i.e., on a bad day with 5% probability, the loss exceeds 6.34%). CVaR(95%) = -0.0945.", "metadata": {"var": -0.063424, "cvar": -0.094498, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251205_0088", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2025-12-05", "context_summary": "ICSH: 60-day return history, mean=0.0002, std=0.0002.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0002, std=0.0002, min=-0.0004, 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": "-0.0000", "answer_numeric": -2.2e-05, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = -0.0002.", "metadata": {"var": -2.2e-05, "cvar": -0.000217, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251020_0091", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BIL"], "decision_date": "2025-10-20", "context_summary": "BIL: 60-day return history, mean=0.0002, std=0.0001.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=0.0002, std=0.0001, min=0.0000, max=0.0004\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BIL. Express as a decimal (e.g., -0.02).", "answer": "0.0000", "answer_numeric": 0.0, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). 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There were no “non-Rule 10b5-1 trading arrangements” (as defined in Item 408 of Regulation S-K of the Exchange Act) adopted , modified, or terminated during the quarter ended September 30, 2025 by our directors and Section 16 officers. Required Disclosure Pursuant to Section 13(r) of the Exchange Act During the quarter ended September 30, 2025, Google LLC, a subsidiary of Alphabet, filed a notification with the Russian Federal Security Service (FSB) pursuant to Russian encryption control requirements, which must be complied with prior to the import of covered items. Neither we nor our subsidiaries generated any gross revenues or 52 net profits directly from such activity and neither we nor our subsidiaries sell to the FSB. In the ordinary course of its business, Alphabet expects that Google LLC will continue to file these notifications as required under Russian law. 53 ITEM 6. EXHIBITS Exhibit Number    Description Incorporated by reference herein Form Date 31.01 * Certification of Chief Executive Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.02 * Certification of Chief Financial Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.01 ‡ Certifications of Chief Executive Officer and Chief Financial Officer pursuant to 18 U.S.C. Section 1350, as adopted pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS * Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH * Inline XBRL Taxonomy Extension Schema Document 101.CAL * Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF * Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB * Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE * Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 * Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) __________________________  * Filed herewith. ‡ Furnished herewith. 54 SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. ALPHABET INC. October 29, 2025 By: /s/ ANAT ASHKENAZI Anat Ashkenazi Senior Vice President, Chief Financial Officer ALPHABET INC. October 29, 2025 By: /s/    AMIE THUENER O'TOOLE         Amie Thuener O'Toole Vice President, Corporate Controller and Principal Accounting Officer 55\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": "-0.0106", "answer_numeric": -0.010603, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0106 (i.e., on a bad day with 5% probability, the loss exceeds 1.06%). CVaR(95%) = -0.0175.", "metadata": {"var": -0.010603, "cvar": -0.017547, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9047}} +{"id": "T2_all_20250422_0097", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-04-22", "context_summary": "SOL-USD: 60-day return history, mean=-0.0021, std=0.0655.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0021, std=0.0655, min=-0.2043, max=0.2423\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0789", "answer_numeric": -0.078935, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0789 (i.e., on a bad day with 5% probability, the loss exceeds 7.89%). CVaR(95%) = -0.1601.", "metadata": {"var": -0.078935, "cvar": -0.160108, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250603_0100", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2025-06-03", "context_summary": "IWM: 60-day return history, mean=0.0000, std=0.0165.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0000, std=0.0165, min=-0.0371, max=0.0349\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-02] [\"2 Profitable Stocks to Target This Week and 1 to Ignore A company with profits isn\\u2019t always a great investment. Some struggle to maintain growth, face looming threats, or fail to reinvest wisely, limiting their future potential. Not all profitable companies are created equal, and that\\u2019s why we built StockStory - to help you find the ones that truly shine bright. That said, here are two profitable companies that balance growth and profitability and one best left off your watchlist. Trailing 12-Month GAAP Operating Margin: 5.2% Founded in 1983 in California, Mission Produce (NASDAQ:AVO) grows, packages, and distributes avocados. Why Is AVO Risky? At $11.19 per share, Mission Produce trades at 9.9x forward EV-to-EBITDA. Check out our free in-depth research report to learn more about why AVO doesn\\u2019t pass our bar. Trailing 12-Month GAAP Operating Margin: 9.6% Founded in 1969 by a group of former Fairchild semiconductor executives led by Jerry Sanders, Advanced Micro Devices (NASDAQ:AMD) is one of the leading designers of computer processors and graphics chips used in PCs and data centers. Why Are We Positive On AMD? AMD\\u2019s stock price of $110.51 implies a valuation ratio of 24.1x forward P/E. Is now the time to initiate a position? Find out in our full research report, it\\u2019s free. Trailing 12-Month GAAP Operating Margin: 25.2% Sporting a global footprint of facilities, Photronics (NASDAQ:PLAB) is a manufacturer of photomasks, templates used to transfer patterns onto semiconductor wafers. Why Do We Like PLAB? Photronics is trading at $16.75 per share, or 8.1x forward P/E. Is now the right time to buy? See for yourself in our in-depth research report, it\\u2019s free. Donald Trump\\u2019s victory in the 2024 U.S. Presidential Election sent major indices to all-time highs, but stocks have retraced as investors debate the health of the economy and the potential impact of tariffs. While this leaves much uncertainty around 2025, a few companies are poised for long-term gains regardless of the political or macroeconomic climate, like our Top 5 Strong Momentum Stocks for this week. This is a curated list of our High Quality stocks that have generated a market-beating return of 183% over the last five years (as of March 31st 2025). Stocks that made our list in 2020 include now familiar names such as Nvidia (+1,545% between March 2020 and March 2025) as well as under-the-radar businesses like the once-small-cap company Exlservice (+354% five-year return). Find your next big winner with StockStory today for free.\", \"Nvidia rival Groq makes a bold prediction on what's next for AI Listen and subscribe to Opening Bid on Apple Podcasts, Spotify, Amazon Music, YouTube or wherever you find your favorite podcasts. The next big breakthrough in AI could be one that channels the spirit of famed scientist Albert Einstein. \\\"The problem is that large language models [LLMs] make mistakes. And they're always going to make mistakes, but they're going to \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": "-0.0289", "answer_numeric": -0.028906, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0289 (i.e., on a bad day with 5% probability, the loss exceeds 2.89%). CVaR(95%) = -0.0371.", "metadata": {"var": -0.028906, "cvar": -0.037067, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250430_0103", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-04-30", "context_summary": "ADA-USD: 60-day return history, mean=-0.0009, std=0.0594.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0009, std=0.0594, min=-0.1761, max=0.2212\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.1002", "answer_numeric": -0.10025, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1002 (i.e., on a bad day with 5% probability, the loss exceeds 10.02%). CVaR(95%) = -0.1354.", "metadata": {"var": -0.10025, "cvar": -0.135417, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251218_0106", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-12-18", "context_summary": "BNB-USD: 60-day return history, mean=-0.0040, std=0.0271.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0040, std=0.0271, min=-0.0847, max=0.0600\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0425", "answer_numeric": -0.04252, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0425 (i.e., on a bad day with 5% probability, the loss exceeds 4.25%). CVaR(95%) = -0.0656.", "metadata": {"var": -0.04252, "cvar": -0.065635, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250303_0109", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-03-03", "context_summary": "VTI: 60-day return history, mean=-0.0003, std=0.0088.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=-0.0003, std=0.0088, min=-0.0314, max=0.0182\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K PFE 2025-02-27] pfe-20241231 0000078003 2024 FY false P4Y Consolidated Statements of Operations Consolidated Statements of Operations Consolidated Statements of Operations http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesCurrent 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ITEM 16. FORM 10-K SUMMARY None. SIGNATURES Under the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, this report was signed on behalf of the Registrant by the authorized person named below. Pfizer Inc. Dated: February 27, 2025 By: /S/    MARGARET M. MADDEN Margaret M. Madden Senior Vice President and Corporate Secretary Chief Governance Counsel We, the undersigned directors and officers of Pfizer Inc., hereby severally constitute Douglas M. Lankler and Margaret M. Madden, and each of them singly, our true and lawful attorneys with full power to them and each of them to sign for us, in our names in the capacities indicated below, any and all amendments to this Annual Report on Form 10-K filed with the Securities and Exchange Commission. Under the requirements of the Securities Exchange Act of 1934, this report was signed by the following persons on behalf of the Registrant and in the capacities and on the date indicated . Pfizer Inc. 2024 Form 10-K 113 Signature Title Date /S/    ALBERT BOURLA Albert Bourla Chairman, Chief Executive Officer and Director (Principal Executive Officer) February 27, 2025 /S/    DAVID M. DENTON David M. Denton Chief Financial Officer, Executive Vice President (Principal Financial Officer) February 27, 2025 /S/    JENNIFER B. DAMICO Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer) February 27, 2025 /S/    RONALD E. BLAYLOCK Ronald E. Blaylock Director February 27, 2025 /S/    MORTIMER J. BUCKLEY Mortimer J. Buckley Director February 27, 2025 /S/    SUSAN DESMOND-HELLMANN Susan Desmond-Hellmann Director February 27, 2025 /S/    JOSEPH J. ECHEVARRIA Joseph J. Echevarria Director February 27, 2025 /S/    SCOTT GOTTLIEB Scott Gottlieb Director February 27, 2025 /S/    HELEN H. HOBBS Helen H. Hobbs Director February 27, 2025 /S/    SUSAN HOCKFIELD Susan Hockfield Director February 27, 2025 /S/    DAN R. LITTMAN Dan R. Littman Director February 27, 2025 /S/    SHANTANU NARAYEN Shantanu Narayen Director February 27, 2025 /S/    SUZANNE NORA JOHNSON Suzanne Nora Johnson Director February 27, 2025 /S/    JAMES QUINCEY James Quincey Director February 27, 2025 /S/    JAMES C. SMITH James C. Smith Director February 27, 2025 /S/    CYRUS TARAPOREVALA Cyrus Taraporevala Director February 27, 2025 Pfizer Inc. 2024 Form 10-K 114\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": "-0.0152", "answer_numeric": -0.015154, "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%) = -0.0219.", "metadata": {"var": -0.015154, "cvar": -0.021895, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20251017_0112", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-10-17", "context_summary": "XRP-USD: 60-day return history, mean=-0.0040, std=0.0358.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0040, std=0.0358, min=-0.1591, max=0.0790\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0548", "answer_numeric": -0.054848, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0548 (i.e., on a bad day with 5% probability, the loss exceeds 5.48%). CVaR(95%) = -0.0969.", "metadata": {"var": -0.054848, "cvar": -0.09689, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251009_0115", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-10-09", "context_summary": "XLV: 60-day return history, mean=0.0014, std=0.0102.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0014, std=0.0102, min=-0.0284, max=0.0244\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": -0.014399, "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%) = -0.0201.", "metadata": {"var": -0.014399, "cvar": -0.020087, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250602_0118", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-06-02", "context_summary": "EEM: 60-day return history, mean=0.0002, std=0.0129.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0002, std=0.0129, min=-0.0341, max=0.0317\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-30] 4 Dividend-Paying Dow Jones Growth Stocks to Buy in June and Hold for Decades Apple could be heavily impacted by tariffs, but the long-term investment thesis is sound. Microsoft continues to fire on all cylinders and deserves to be near an all-time high. Visa and American Express benefit from network effects that help them steadily grow over time. 10 stocks we like better than Apple \u203a The modern-day Dow Jones Industrial Average contains a variety of industry-leading companies across stock market sectors -- making it an excellent way to discover blue chip companies to build a portfolio around. Here's why Apple (NASDAQ: AAPL), Microsoft (NASDAQ: MSFT), Visa (NYSE: V), and American Express (NYSE: AXP) are particularly compelling Dow stocks to buy in June and hold for decades to come. Apple used to be the most valuable company in the world, but it has taken a back seat behind Microsoft and Nvidia as Apple is down 22% year to date at the time of this writing, while Microsoft is up nearly 7%. Microsoft has given investors everything they could have asked for amid tariff tensions. The company continues to grow at an impressive rate while maintaining high operating margins. Microsoft is investing in artificial intelligence (AI) and cloud computing at a breakneck pace while buying back a significant amount of stock, raising its dividend by around 10% per year, and maintaining an exceptional balance sheet. The company's business model is relatively insulated from trade risks, so it's no wonder why the stock is knocking on the door of a new all-time high. But the same can't be said of Apple. It assembles the vast majority of key products, like iPhones, in China -- making it extremely vulnerable to tariffs. Apple stock has been on a roller coaster in 2025 as investors try to digest policies that seem to change overnight. President Trump has cast Apple onto the front lines of the trade war with China, with the latest decision being a 25% tariff on iPhones not made in the U.S. While Apple can adjust its supply chain to offset some tariff risk, it would be extremely difficult for Apple to make iPhones as cost-effectively outside of China. So, in the near term, Apple may just have to absorb the tariff hit and hope resolutions come soon or pass along a portion of the costs to consumers. The good news is that Apple has highly anticipated products with AI features coming this fall which may be enough to pique consumer interest and justify higher price tags. Investors can catch a glimpse of Apple's latest technology updates and features by tuning into its Worldwide Developers Conference from June 9 to June 13. Given tariff risks, some folks may want to take a wait-and-see approach to Apple. But the stock is fairly beaten down, and folks who think Apple has the brand power and innovation to justify price hikes may want to consider buying the stock in June. Apple's valuation is at reasonable levels with a price-to-earnings (P/E) ratio of 30.4 and a forward P/E of 27.2\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": "-0.0215", "answer_numeric": -0.021549, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0215 (i.e., on a bad day with 5% probability, the loss exceeds 2.15%). CVaR(95%) = -0.0308.", "metadata": {"var": -0.021549, "cvar": -0.030793, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250523_0120", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-05-23", "context_summary": "ETH-USD: 60-day return history, mean=0.0049, std=0.0459.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0049, std=0.0459, min=-0.1269, max=0.1560\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0536", "answer_numeric": -0.053587, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0536 (i.e., on a bad day with 5% probability, the loss exceeds 5.36%). CVaR(95%) = -0.0907.", "metadata": {"var": -0.053587, "cvar": -0.090667, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251216_0122", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2025-12-16", "context_summary": "^VIX: 60-day return history, mean=0.0009, std=0.0800.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=0.0009, std=0.0800, min=-0.1825, max=0.2508\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-10-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-10-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-10-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-10-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-10-31 0000104169 2025-12-02 0000104169 2025-08-01 2025-10-31 0000104169 2024-08-01 2024-10-31 0000104169 2024-02-01 2024-10-31 0000104169 2025-10-31 0000104169 2025-01-31 0000104169 2024-10-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-30 0000104169 us-gaap:ParentMember 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-04-30 0000104169 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-05-01 2025-07-31 0000104169 us-gaap:ParentMember 2025-05-01 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-05-01 2025-07-31 0000104169 2025-05-01 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-05-01 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-31 0000104169 us-gaap:ParentMember 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-08-01 2025-10-31 0000104169 us-gaap:ParentMember 2025-08-01 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-08-01 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-08-01 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ^VIX. Express as a decimal (e.g., -0.02).", "answer": "-0.1295", "answer_numeric": -0.129524, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1295 (i.e., on a bad day with 5% probability, the loss exceeds 12.95%). CVaR(95%) = -0.1487.", "metadata": {"var": -0.129524, "cvar": -0.14867, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250109_0125", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ITB"], "decision_date": "2025-01-09", "context_summary": "ITB: 60-day return history, mean=-0.0030, std=0.0156.", "question": "Asset: ITB\nDaily returns (past 60 days): mean=-0.0030, std=0.0156, min=-0.0409, 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": "-0.0288", "answer_numeric": -0.028772, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0288 (i.e., on a bad day with 5% probability, the loss exceeds 2.88%). CVaR(95%) = -0.0363.", "metadata": {"var": -0.028772, "cvar": -0.036321, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251223_0128", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2025-12-23", "context_summary": "^VIX: 60-day return history, mean=-0.0016, std=0.0812.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0016, std=0.0812, min=-0.1825, max=0.2508\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-10-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-10-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-10-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-10-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-10-31 0000104169 2025-12-02 0000104169 2025-08-01 2025-10-31 0000104169 2024-08-01 2024-10-31 0000104169 2024-02-01 2024-10-31 0000104169 2025-10-31 0000104169 2025-01-31 0000104169 2024-10-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-30 0000104169 us-gaap:ParentMember 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-04-30 0000104169 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-05-01 2025-07-31 0000104169 us-gaap:ParentMember 2025-05-01 2025-07-31 0000104169 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0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ^VIX. Express as a decimal (e.g., -0.02).", "answer": "-0.1295", "answer_numeric": -0.129524, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1295 (i.e., on a bad day with 5% probability, the loss exceeds 12.95%). CVaR(95%) = -0.1487.", "metadata": {"var": -0.129524, "cvar": -0.14867, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250924_0131", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["FXI"], "decision_date": "2025-09-24", "context_summary": "FXI: 60-day return history, mean=0.0014, std=0.0115.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0014, std=0.0115, min=-0.0258, max=0.0299\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": "-0.0151", "answer_numeric": -0.015089, "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%) = -0.0205.", "metadata": {"var": -0.015089, "cvar": -0.020543, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250721_0134", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-07-21", "context_summary": "XLF: 60-day return history, mean=0.0019, std=0.0087.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0019, std=0.0087, min=-0.0207, max=0.0205\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-18] [\"MP Materials (MP) Completes US$650 Million Equity Offering MP Materials has made significant announcements recently, including the completion of a follow-on equity offering of nearly $650 million and new high-profile partnerships with Apple and the Department of Defense. These developments coincide with a remarkable share price increase of 122% over the last quarter. The equity offering indicates strong market confidence, while the strategic partnerships bolster MP's long-term prospects in the rare earth sector. The broader market, with major indexes reaching record highs, provides a favorable backdrop, further enhancing MP's upward momentum. Such positive corporate maneuvers align well with the ongoing bullish trends in stock markets. Every company has risks, and we've spotted 1 warning sign for MP Materials you should know about. AI is about to change healthcare. These 27 stocks are working on everything from early diagnostics to drug discovery. The best part - they are all under $10b in market cap - there's still time to get in early. The recent announcements of MP Materials' successful equity offering and strategic partnerships with Apple and the Department of Defense could significantly impact its long-term narrative as it positions itself strongly within the rare earths sector. These developments are expected to enhance production capabilities and revenue opportunities, aligning with the company's strategy to expand into ex-China markets. Potential advancements in efficiency and sales volumes could positively influence future earnings and revenue forecasts, which analysts anticipate to grow robustly over the next three years. Over a five-year period, MP Materials has achieved a total return of 293.48%, which underscores its substantial growth trajectory. Notably, over the past year, its performance surpassed the US Metals and Mining industry, which returned 6.1%. However, despite recent impressive share price gains, the current price of US$58.55 contrasts with the consensus price target of US$38. This discrepancy highlights a potential overvaluation according to analysts, suggesting investors might benefit from tempering expectations in light of market factors and the company's execution of future growth plans. The strategic moves could help mitigate risks associated with heavy reliance on NdPr pricing and variable Chinese policies. However, executing its growth strategy without significant revenue or margin interruptions remains crucial. Although the company's long-term viability appears promising, as evidenced by planned expansions in the Upstream and Midstream segments, immediate financial forecasts also depend on external factors and successful integration of new processes. Thus, MP Materials' future prospects will largely depend on its ability to navigate these challenges effectively while aligning with analyst earnings forecasts and market expectations. Explore historical data to track MP Materials' performance over time in our past\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": "-0.0108", "answer_numeric": -0.010829, "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%) = -0.0195.", "metadata": {"var": -0.010829, "cvar": -0.019514, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250319_0136", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ITB"], "decision_date": "2025-03-19", "context_summary": "ITB: 60-day return history, mean=-0.0023, std=0.0162.", "question": "Asset: ITB\nDaily returns (past 60 days): mean=-0.0023, std=0.0162, min=-0.0409, max=0.0322\nMarket regime: bear\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": "-0.0260", "answer_numeric": -0.025985, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0260 (i.e., on a bad day with 5% probability, the loss exceeds 2.60%). CVaR(95%) = -0.0327.", "metadata": {"var": -0.025985, "cvar": -0.03266, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250804_0139", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-08-04", "context_summary": "XLU: 60-day return history, mean=0.0012, std=0.0086.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0012, std=0.0086, min=-0.0184, max=0.0211\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q AAPL 2025-08-01] aapl-20250628 false 2025 Q3 0000320193 --09-27 P1Y P1Y P1Y P1Y xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure aapl:Customer aapl:Vendor 0000320193 2024-09-29 2025-06-28 0000320193 us-gaap:CommonStockMember 2024-09-29 2025-06-28 0000320193 aapl:A0.000Notesdue2025Member 2024-09-29 2025-06-28 0000320193 aapl:A1.625NotesDue2026Member 2024-09-29 2025-06-28 0000320193 aapl:A2.000NotesDue2027Member 2024-09-29 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aapl:WearablesHomeandAccessoriesMember 2024-09-29 2025-06-28 0000320193 aapl:WearablesHomeandAccessoriesMember 2023-10-01 2024-06-29 0000320193 2025-06-29 2025-06-28 0000320193 2026-06-28 2025-06-28 0000320193 2027-06-27 2025-06-28 0000320193 2028-07-02 2025-06-28 0000320193 us-gaap:CashMember 2025-06-28 0000320193 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2025-06-28 0000320193 us-gaap:FairValueInputsLevel1Member us-gaap:MutualFundMember 2025-06-28 0000320193 us-gaap:FairValueInputsLevel1Member 2025-06-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:USTreasurySecuritiesMember 2025-06-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-06-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:ForeignGovernmentDebtSecuritiesMember 2025-06-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:BankTimeDepositsMember 2025-06-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:CommercialPaperMember 2025-06-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:CorporateDebtSecuritiesMember 2025-06-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:USStatesAndPoliticalSubdivisionsMember 2025-06-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:AssetBackedSecuritiesMember 2025-06-28 0000320193 us-gaap:FairValueInputsLevel2Member 2025-06-28 0000320193 us-gaap:CashMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel1Member us-gaap:MutualFundMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel1Member 2024-09-28 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap [...TRUNCATED...] ns, except number of shares, which are reflected in thousands, and per-share amounts): Periods Total Number of Shares Purchased Average Price Paid Per Share Total Number of Shares Purchased as Part of Publicly Announced Plans or Programs Approximate Dollar Value of Shares That May Yet Be Purchased Under the Plans or Programs (1) March 30, 2025 to May 3, 2025: Open market and privately negotiated purchases 43,161  $ 200.79  43,161  May 4, 2025 to May 31, 2025: Open market and privately negotiated purchases 28,223  $ 203.17  28,223  June 1, 2025 to June 28, 2025: Open market and privately negotiated purchases 32,880  $ 200.73  32,880  Total 104,264  $ 119,779  (1) On May 2, 2024, the Company announced a program to repurchase up to $110 billion of the Company’s common stock. As of June 28, 2025, remaining availability under the May 2024 program was $19.8 billion. On May 1, 2025, the Company announced an additional program to repurchase up to $100 billion of the Company’s common stock. The programs do not obligate the Company to acquire a minimum amount of shares. Under the programs, shares may be repurchased in privately negotiated or open market transactions, including under plans complying with Rule 10b5-1 under the Exchange Act. Item 3.    Defaults Upon Senior Securities None. Item 4.    Mine Safety Disclosures Not applicable. Item 5.    Other Information Insider Trading Arrangements None. Apple Inc. | Q3 2025 Form 10-Q | 21 Item 6.    Exhibits Incorporated by Reference Exhibit Number Exhibit Description Form Exhibit Filing Date/ Period End Date 4.1 Officer’s Certificate of the Registrant, dated as of May 12, 2025, including forms of global notes representing the 4.000% Notes due 2028, 4.200% Notes due 2030, 4.500% Notes due 2032 and 4.750% Notes due 2035. 8-K 4.1 5/12/25 31.1* Rule 13a-14(a) / 15d-14(a) Certification of Chief Executive Officer. 31.2* Rule 13a-14(a) / 15d-14(a) Certification of Chief Financial Officer. 32.1** Section 1350 Certifications of Chief Executive Officer and Chief Financial Officer. 101* Inline XBRL Document Set for the condensed consolidated financial statements and accompanying notes in Part I, Item 1, “Financial Statements” of this Quarterly Report on Form 10-Q. 104* Inline XBRL for the cover page of this Quarterly Report on Form 10-Q, included in the Exhibit 101 Inline XBRL Document Set. *    Filed herewith. **    Furnished herewith. Apple Inc. | Q3 2025 Form 10-Q | 22 SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: August 1, 2025 Apple Inc. By: /s/ Kevan Parekh Kevan Parekh Senior Vice President, Chief Financial Officer Apple Inc. | Q3 2025 Form 10-Q | 23\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": "-0.0141", "answer_numeric": -0.014073, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0141 (i.e., on a bad day with 5% probability, the loss exceeds 1.41%). CVaR(95%) = -0.0168.", "metadata": {"var": -0.014073, "cvar": -0.016807, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20250826_0142", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2025-08-26", "context_summary": "MTUM: 60-day return history, mean=0.0009, std=0.0072.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0009, std=0.0072, min=-0.0147, max=0.0169\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-08-25] Who\u2019s the Next Apple? 3 Breakout Stocks That Point the Way Editor\u2019s Note: Every investing era has its defining moment. In the 1980s, Apple squared off against IBM. In the 1990s, Amazon reshaped retail. And now, it\u2019s AI transforming industries at a breakneck pace. It\u2019s a force that\u2019s fundamentally changing how fast companies can grow, scale, and generate profits. It is therefore producing an unusual class of stock breakouts. InvestorPlace Senior Analyst Luke Lango calls these \u201cAI Income Events\u201d \u2013 moments when hype flips into adoption-driven growth. InvestorPlace - Stock Market News, Stock Advice & Trading Tips A few recent AI Income Events include\u2026 Super Micro Computer (SMCI) \u2013 233% in just 2 months SoundHound AI Inc. (SOUN) \u2013 300% in a few months BigBear.ai Holdings, Inc. (BBAI) \u2013 100% in weeks Palantir Technologies Inc. (PLTR) \u2013 290% in 5 months AppLovin Corporation (APP) \u2013 500% in 5 months But what history shows us is clear\u2026 The biggest breakthroughs \u2013 and the biggest stock market winners \u2013 almost never come from the incumbents. They come from the upstarts. So, Luke is joining us today to share how three little-known companies triggered \u201cAI Income Events\u201d\u2026 and how you can turn a $5,000 stake into $30,000 within six months by capturing a series of these events. Take it away, Luke\u2026 One August morning in 1981, Steve Jobs sat at Apple Inc.\u2019s (AAPL) headquarters with a Wall Street Journal folded under his arm. The headline: IBM Corp. (IBM) was entering the personal computer market. Apple, barely 5 years old, suddenly found itself up against Big Blue. With trademark audacity, Jobs turned the moment into theater. Apple ran a cheeky full-page WSJ ad: \u201cWelcome, IBM. Seriously.\u201d Later, in a 1983 speech, Jobs cast Apple as the rebel, warning \u201cIBM wants it all.\u201d That spirit paid off. The Macintosh, launched in 1984 with its iconic Super Bowl ad, made Apple the symbol of insurgent tech. Since then, Apple stock has soared nearly 175,000%, while IBM is up just about 2,500%. Apple isn\u2019t alone in this story. History shows transformational breakthroughs usually come from upstarts, not incumbents. Each innovation cycle produces Davids that topple Goliaths. Now that we\u2019re in the AI innovation cycle, let\u2019s look at three Davids whose \u201cAI Income Events\u201d rewarded investors with huge gains. Their biggest moves are likely largely past \u2014 so I\u2019ll also show you how my team is spotting the next round\u2026 AI has become the great equalizer. Any small firm can now harness it to leap ahead of giants. The challenge is spotting when hype (Phase 1) flips to adoption-driven growth (Phase 2). That\u2019s where my Nexus system comes in. I\u2019ll tell you more about Nexus in a minute, but first let\u2019s take a look at three AI Income Events it uncovered\u2026 Case Study #1: Back in October 2023, most investors had never heard of our first case study. It was a Microsoft partner in cloud software \u2014 a solid business, sure, but hardly front-page material. Then on October 10, this company unveiled an AI-power\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MTUM. Express as a decimal (e.g., -0.02).", "answer": "-0.0100", "answer_numeric": -0.009959, "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%) = -0.0121.", "metadata": {"var": -0.009959, "cvar": -0.012128, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20251030_0145", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-10-30", "context_summary": "XLF: 60-day return history, mean=0.0002, std=0.0086.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0002, std=0.0086, min=-0.0282, max=0.0164\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BA 2025-10-29] ba-20250930 FALSE 2025 Q3 0000012927 --12-31 P1Y http://fasb.org/us-gaap/2025#OtherAssetsCurrent http://fasb.org/us-gaap/2025#OtherAssetsCurrent http://fasb.org/us-gaap/2025#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2025#AccruedLiabilitiesCurrent xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure ba:extension_period ba:aircraft ba:tanker ba:lot ba:simulator ba:segment 0000012927 2025-01-01 2025-09-30 0000012927 us-gaap:CommonStockMember 2025-01-01 2025-09-30 0000012927 ba:DepositarySharesMember 2025-01-01 2025-09-30 0000012927 2025-10-22 0000012927 us-gaap:ProductMember 2025-01-01 2025-09-30 0000012927 us-gaap:ProductMember 2024-01-01 2024-09-30 0000012927 us-gaap:ProductMember 2025-07-01 2025-09-30 0000012927 us-gaap:ProductMember 2024-07-01 2024-09-30 0000012927 us-gaap:ServiceMember 2025-01-01 2025-09-30 0000012927 us-gaap:ServiceMember 2024-01-01 2024-09-30 0000012927 us-gaap:ServiceMember 2025-07-01 2025-09-30 0000012927 us-gaap:ServiceMember 2024-07-01 2024-09-30 0000012927 2024-01-01 2024-09-30 0000012927 2025-07-01 2025-09-30 0000012927 2024-07-01 2024-09-30 0000012927 2025-09-30 0000012927 2024-12-31 0000012927 us-gaap:ConvertiblePreferredStockMember 2024-01-01 2024-12-31 0000012927 us-gaap:ConvertiblePreferredStockMember 2025-01-01 2025-09-30 0000012927 us-gaap:ConvertiblePreferredStockMember 2024-12-31 0000012927 us-gaap:ConvertiblePreferredStockMember 2025-09-30 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2025-07-01 2025-09-30 0000012927 us-gaap:AdditionalPaidInCapitalMember 2025-07-01 2025-09-30 0000012927 us-gaap:TreasuryStockCommonMember 2025-07-01 2025-09-30 0000012927 us-gaap:OperatingSegmentsMember ba:CommercialAirplanesSegmentMember 2025-01-01 2025-09-30 0000012927 us-gaap:OperatingSegmentsMember ba:CommercialAirplanesSegmentMember 2024-01-01 2024-09-30 0000012927 us-gaap:OperatingSegmentsMember ba:CommercialAirplanesSegmentMember 2025-07-01 2025-09-30 0000012927 us-gaap:OperatingSegmentsMember ba:CommercialAirplanesSegmentMember 2024-07-01 2024-09-30 0000012927 us-gaap:OperatingSegmentsMem [...TRUNCATED...] #160;of Shares That May Yet be Purchased Under the Plans or Programs 7/1/2025 thru 7/31/2025 28,866  $232.93  8/1/2025 thru 8/31/2025 6,963  229.15  9/1/2025 thru 9/30/2025 3,728  235.24  Total 39,557  $232.48  (1) A total of 39,557 shares were transferred to us from employees in satisfaction of minimum tax withholding obligations associated with the vesting of restricted stock units during the period. We did not purchase any shares of our common stock in the open market pursuant to a repurchase program. Item 3. Defaults Upon Senior Securities Not applicable. Item 4. Mine Safety Disclosures Not applicable. 57 Table of Contents Item 5. Other Information During the three months ended September 30, 2025, none of our directors or officers adopted , modified or terminated a “Rule 10b5-1 trading arrangement” or a “non-Rule 10b5-1 trading arrangement” as such terms are defined under Item 408 of Regulation S-K. 58 Table of Contents Item 6. Exhibits 10.1 364-Day Credit Agreement, dated as of August 25, 2025, among The Boeing Company for itself and on behalf of its Subsidiaries, as a Borrower, the Lenders party hereto, Citibank, N.A., as Administrative Agent, JPMorgan Chase Bank, N.A. as Syndication Agent and Citibank, N.A. and JPMorgan Chase Bank N.A., as Joint Lead Arrangers and Joint Book Managers (Exhibit 10.1 to the Company’s Current Report on Form 8-K, dated August 25, 2025) 15 Letter from Independent Registered Public Accounting Firm regarding unaudited interim financial information 31.1 Certification of Chief Executive Officer pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certification of Chief Executive Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 32.2 Certification of Chief Financial Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File (formatted as inline XBRL and contained in Exhibit 101) 59 Table of Contents Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. THE BOEING COMPANY (Registrant) October 29, 2025 /s/ Michael J. Cleary (Date) Michael J. Cleary Senior Vice President and Controller 60\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": "-0.0172", "answer_numeric": -0.017198, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0172 (i.e., on a bad day with 5% probability, the loss exceeds 1.72%). CVaR(95%) = -0.0229.", "metadata": {"var": -0.017198, "cvar": -0.02289, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9044}} +{"id": "T2_all_20250709_0147", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-07-09", "context_summary": "VTI: 60-day return history, mean=0.0022, std=0.0107.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0022, std=0.0107, min=-0.0335, max=0.0264\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-07-08] [\"Analysis: 'Trump Effect' website takes credit for US investment made under Biden By Jarrett Renshaw (Reuters) -Within hours of taking office in January, President Donald Trump boasted about attracting $3 trillion in new corporate investments to the United States. Since then, Trump has said the investments have swelled to $14 trillion, or roughly half of the nation's annual gross domestic product. The White House calls it \\\"The Trump Effect\\\" and features a rolling list on its website of more than 70 projects it says Trump's economic policies spurred, from a new bakery plant in Texas to a LEGO facility in Virginia and a microchip plant in Arizona. As of July 2, the website listed more than $2.6 trillion in U.S. investments, well short of the $14 trillion Trump boasts about. But a Reuters review found that just under half of the claimed spending on the website - totaling more than $1.3 trillion - originated under former President Joe Biden or represented routine spending repackaged to promote domestic investments. At least eight of the projects touted by the White House had sought or secured critical local incentive packages before Trump took office while at least a half dozen other projects had already been announced by local officials or the companies themselves, Reuters found. Two of the Trump Effect projects were aided by Biden's legislative efforts to boost domestic manufacturing, the review found. One company on the list, Swiss-based Roche, warned that Trump's plans to equalize U.S. and international drug prices now threatens its promised $50 billion in U.S. investments. Asked about taking credit for projects already underway before Trump came into office, the White House said the final investment decisions were announced under his watch and prove his economic policies are triggering U.S. investment. \\u201cPresident Trump is the greatest closer in modern history, and his leadership and policies are a critical catalyst converting hypothetical discussions into firm investment commitments and ground being broken for new plants and offices,\\\" White House spokesman Kush Desai said. The Reuters review included interviewing local officials and reviewing public records and corporate statements. It was not clear in many cases what role, if any, Trump or his policies played in getting the deals across the line. Mark Zandi, the chief economist at Moody's Analytics, said his economic forecast - along with the consensus estimates - for investment in the economy has remained relatively unchanged despite the White House's claims of new historic investments. \\\"I think despite all the announcements it hasn't translated into any change in expectations,\\\" Zandi said. \\\"The fundamentals that ultimately drive investment spending, broadly, if anything, appear to have weakened since the start of the year.\\\" Trump's push to impose sweeping tariffs on dozens of trading partners has injected uncertainty into global markets, lowering economic projections and freezing\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": "-0.0177", "answer_numeric": -0.017732, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0177 (i.e., on a bad day with 5% probability, the loss exceeds 1.77%). CVaR(95%) = -0.0262.", "metadata": {"var": -0.017732, "cvar": -0.026171, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250120_0150", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2025-01-20", "context_summary": "ACWI: 60-day return history, mean=0.0001, std=0.0075.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0001, std=0.0075, min=-0.0302, max=0.0162\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 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0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ACWI. Express as a decimal (e.g., -0.02).", "answer": "-0.0105", "answer_numeric": -0.010545, "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%) = -0.0202.", "metadata": {"var": -0.010545, "cvar": -0.020233, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20251229_0153", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-12-29", "context_summary": "XLF: 60-day return history, mean=0.0007, std=0.0089.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0007, std=0.0089, min=-0.0282, max=0.0180\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLF. Express as a decimal (e.g., -0.02).", "answer": "-0.0172", "answer_numeric": -0.017236, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0172 (i.e., on a bad day with 5% probability, the loss exceeds 1.72%). CVaR(95%) = -0.0231.", "metadata": {"var": -0.017236, "cvar": -0.023146, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250812_0156", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-08-12", "context_summary": "XLY: 60-day return history, mean=0.0007, std=0.0107.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0007, std=0.0107, min=-0.0255, max=0.0291\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q UNH 2025-08-11] unh-20250630 false 2025 Q2 0000731766 12/31 50 xbrli:shares iso4217:USD iso4217:USD xbrli:shares utr:Rate xbrli:pure unh:reportableSegments 0000731766 2025-01-01 2025-06-30 0000731766 2025-07-31 0000731766 2025-06-30 0000731766 2024-12-31 0000731766 2025-04-01 2025-06-30 0000731766 2024-04-01 2024-06-30 0000731766 2024-01-01 2024-06-30 0000731766 us-gaap:ProductMember 2025-04-01 2025-06-30 0000731766 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Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) * 10. 1 Employment Agreeme nt, effective as of May 12, 2025, between United HealthC are Services, Inc. and Stephen Hemsely 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Denotes management contracts and compensation plans in which certain directors and named executive officers participate and which are being filed pursuant to Item 601(b)(10)(iii)(A) of Regulation S-K. ** Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ S TEPHEN H EMSLEY Chair and Chief Executive Officer (principal executive officer) Dated: August 11, 2025 Stephen Hemsley    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 11, 2025 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 11, 2025 Thomas Roos    28\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": -0.017546, "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": -0.017546, "cvar": -0.023481, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250915_0159", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-09-15", "context_summary": "ADA-USD: 60-day return history, mean=0.0033, std=0.0391.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0033, std=0.0391, min=-0.0960, max=0.0927\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0509", "answer_numeric": -0.050904, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0509 (i.e., on a bad day with 5% probability, the loss exceeds 5.09%). CVaR(95%) = -0.0866.", "metadata": {"var": -0.050904, "cvar": -0.086626, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250819_0161", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-08-19", "context_summary": "BTC-USD: 60-day return history, mean=0.0019, std=0.0151.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0019, std=0.0151, min=-0.0404, max=0.0455\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0173", "answer_numeric": -0.017308, "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%) = -0.0264.", "metadata": {"var": -0.017308, "cvar": -0.026355, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250130_0164", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-01-30", "context_summary": "XLV: 60-day return history, mean=-0.0002, std=0.0086.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=-0.0002, std=0.0086, min=-0.0187, max=0.0222\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q MSFT 2025-01-29] 10-Q Q2 --06-30 false 0000789019 2025 http://fasb.org/us-gaap/2024#DerivativeAssets http://fasb.org/us-gaap/2024#DerivativeAssets http://fasb.org/us-gaap/2024#DerivativeLiabilities http://fasb.org/us-gaap/2024#DerivativeLiabilities http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsCurrent 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E XHIBITS               Incorporated by Reference Exhibit Number   Exhibit Description   Filed Herewith   Form   Period Ending   Exhibit   Filing Date                                                     15.1 Letter regarding unaudited interim financial information   X                                           31.1 Certification of Chief Executive Officer Pursuant to Section 302 of the Sarbanes-Oxley Act of 2002   X                                       31.2 Certification of Chief Financial Officer Pursuant to Section 302 of the Sarbanes-Oxley Act of 2002   X                                       32.1* Certification of Chief Executive Officer Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002   X                                       32.2* Certification of Chief Financial Officer Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002   X                                       101.INS Inline XBRL Instance Document–the instance document does not appear in the Interactive Data File as its XBRL tags are embedded within the Inline XBRL document   X                                       101.SCH Inline XBRL Taxonomy Extension Schema with Embedded Linkbase Documents   X                                       104 Cover page formatted as Inline XBRL and contained in Exhibit 101   X                   * Furnished, not filed.   Items 3 and 4 are not applicable and have been omitted. 66   SIGNAT URE Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned; thereunto duly authorized.   M ICROSOFT  C ORPORATION /s/ A LICE  L. J OLLA Alice L. Jolla Corporate Vice President and Chief Accounting Officer (Duly Authorized Officer) January 29, 2025   67\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": "-0.0137", "answer_numeric": -0.013712, "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%) = -0.0162.", "metadata": {"var": -0.013712, "cvar": -0.016202, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20250630_0167", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-06-30", "context_summary": "EFA: 60-day return history, mean=0.0016, std=0.0107.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0016, std=0.0107, min=-0.0289, max=0.0259\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-27] [\"Alibaba Just Released New AI Models for Apple. Does That Make AAPL Stock a Buy? For Apple (AAPL), artificial intelligence is the key to future-proofing its robust devices and services ecosystem. Yet in China, Apple\\u2019s second-largest market, the company\\u2019s AI ambitions have hit a wall. Between trade tensions, strict regulations, Beijing\\u2019s data-localization demands, fierce competition for device sales, Apple\\u2019s Intelligence suite remained locked out of the mainland. Alibaba Group (BABA) has just handed Apple a potential key. Its Qwen3 AI models have been fine-tuned for Apple\\u2019s MLX framework, enabling them to run natively on iPhones, iPads, and Macs. Tesla\\u2019s Robotaxis Reportedly Sped and Veered Into the Wrong Lanes. Does This Crush the Bull Case for TSLA Stock? 1 Dividend Stock to Buy Yielding Over 7% Ditch Big Tech and Buy These 3 Popular Stocks in 2025 Instead Get exclusive insights with the FREE Barchart Brief newsletter. Subscribe now for quick, incisive midday market analysis you won't find anywhere else. It is a strategic play. Apple needs a domestic AI partner to navigate China\\u2019s tight controls, and Alibaba\\u2019s open-source route gives it both flexibility and local legitimacy. This could finally pave the road for Apple Intelligence to launch in China - a much-needed boost for iPhone sales. Nearly six months into 2025, and Apple bulls are still bruised, with shares 23% off their peak. So, will this Alibaba alliance reignite the rally or trigger more turbulence? Apple (AAPL), the $3 trillion global tech titan from Cupertino, redefined technology with the iPhone, Mac, and iPad. But its real power play now is the services segment. With over a billion paid subscribers and high-margin offerings like iCloud, Apple Music, and the App Store, it is weathering global headwinds while tightening its grip on the digital ecosystem. Despite being big on innovation, AAPL\\u2019s stock has slumped 19.5% in 2025, making Apple the worst YTD performer among the Magnificent Seven. Regulatory headwinds and mounting competition have eroded investor confidence. While large-cap tech rebounded in May, Apple missed the rally and dropped 6% that month alone. The decline deepened with rising tariff tensions, especially fears of a 25% hit if Apple doesn\\u2019t shift manufacturing to the U.S. Yet the core issue extends beyond geopolitics and trade friction. \\u201cApple Intelligence\\u201d debuted at WWDC 2024, failed to generate lasting enthusiasm, hindered by limited device compatibility and the postponement of key features like the enhanced Siri. Legal pressures and underwhelming developments at WWDC 2025, where cosmetic updates overshadowed bold innovation, further reinforced perceptions that Apple is trailing AI leaders such as Google (GOOGL). While the company\\u2019s ecosystem remains robust, its current AI narrative lacks the momentum to inspire market confidence. Apple\\u2019s fiscal Q2 2025 arrived on May 1 with both flash and fricti\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": "-0.0200", "answer_numeric": -0.019983, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0200 (i.e., on a bad day with 5% probability, the loss exceeds 2.00%). CVaR(95%) = -0.0248.", "metadata": {"var": -0.019983, "cvar": -0.024837, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250307_0170", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-03-07", "context_summary": "ADA-USD: 60-day return history, mean=-0.0056, std=0.0592.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0056, std=0.0592, min=-0.1761, max=0.2212\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.1009", "answer_numeric": -0.100938, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1009 (i.e., on a bad day with 5% probability, the loss exceeds 10.09%). CVaR(95%) = -0.1324.", "metadata": {"var": -0.100938, "cvar": -0.132443, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250512_0172", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2025-05-12", "context_summary": "SCHP: 60-day return history, mean=0.0004, std=0.0034.", "question": "Asset: SCHP\nDaily returns (past 60 days): mean=0.0004, std=0.0034, min=-0.0090, max=0.0064\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": "-0.0056", "answer_numeric": -0.00564, "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%) = -0.0080.", "metadata": {"var": -0.00564, "cvar": -0.008015, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250530_0174", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2025-05-30", "context_summary": "CSHI: 60-day return history, mean=-0.0001, std=0.0032.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=-0.0001, std=0.0032, min=-0.0115, max=0.0123\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for CSHI. Express as a decimal (e.g., -0.02).", "answer": "-0.0031", "answer_numeric": -0.003096, "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%) = -0.0115.", "metadata": {"var": -0.003096, "cvar": -0.011497, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250129_0177", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-01-29", "context_summary": "ADA-USD: 60-day return history, mean=-0.0014, std=0.0502.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0014, std=0.0502, min=-0.1578, max=0.1342\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0860", "answer_numeric": -0.086007, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0860 (i.e., on a bad day with 5% probability, the loss exceeds 8.60%). CVaR(95%) = -0.1172.", "metadata": {"var": -0.086007, "cvar": -0.117238, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250402_0180", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["IVV"], "decision_date": "2025-04-02", "context_summary": "IVV: 60-day return history, mean=-0.0006, std=0.0103.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=-0.0006, std=0.0103, min=-0.0264, max=0.0205\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-01] I&M is Future Ready with Plans to Enhance Diverse Energy Mix FORT WAYNE, Ind., April 1, 2025 /PRNewswire/ -- Indiana Michigan Power (I&M), an American Electric Power (Nasdaq: AEP) company, recently submitted its 2024 Integrated Resource Plan (IRP) to the Indiana Utility Regulatory Commission (IURC). I&M's plan outlines the transformation the company is undergoing to meet the evolving energy needs of customers while maintaining reliable and consistent power. The Future Ready Plan supports a resilient grid using a diverse portfolio of generation resources, energy efficiency and demand response programs to provide reliable, affordable energy for I&M customers today and into the future. The plan, which is specific to the state of Indiana, provides a detailed breakdown of future energy needs and how the company will meet customer demand through the 2044 IRP planning period. I&M is required to submit this 20-year IRP every three years to the IURC. I&M will conduct a similar process next year for the company's Michigan service area. The foundation of this plan is based on the evolving energy needs of existing customers. It also takes into account how I&M will serve future customers in a reliable, cost-effective manner. Additional input was considered throughout the IRP process through a Public Advisory Process, which provided opportunities for stakeholders to engage in the process through a series of five workshops. These workshops began in June 2024 and concluded in March 2025. \"I&M has an opportunity to make a significant impact on the communities we serve by adapting to meet customers' evolving energy needs now and into the future,\" said Steve Baker, I&M president and chief operating officer. \"By diversifying our generation mix with a portfolio of resources that can be available around the clock, our customers can trust that we are Future Ready to serve their homes, businesses and factories 24/7.\" Enhancing Generation Diversity I&M currently supports a diverse mix of generation resources to power customers' homes and businesses. This mix includes solar, wind, nuclear, coal and hydroelectric resources. As the trend for energy and demand continues to increase within I&M's territory, identifying resources to support future need is critical. The Indiana IRP targets additional renewable and natural gas resources to meet projected energy needs. These include the incorporation of solar, storage, wind and natural gas combined cycle and combustion turbine resources, as well as relicensing the Elkhart and Mottville hydroelectric facilities in 2030 and 2033, respectively. The resources identified in the IRP are in addition to the solar, wind and natural gas capacity resources recently approved by the IURC as the company prepares for the planned retirement of the coal-fueled Rockport Plant by the end of 2028. Focus on Nuclear Resources The 2024 Indiana IRP recommends the relicensing for both units at the D.C. Cook Nuclear Plant, located in Bridgman, Mich. The cu\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": "-0.0174", "answer_numeric": -0.017449, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0174 (i.e., on a bad day with 5% probability, the loss exceeds 1.74%). CVaR(95%) = -0.0216.", "metadata": {"var": -0.017449, "cvar": -0.021635, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20251118_0183", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-11-18", "context_summary": "EFA: 60-day return history, mean=0.0001, std=0.0067.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0001, std=0.0067, min=-0.0186, max=0.0106\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CVX 2025-11-06] cvx-20250930 0000093410 12/31 2025 Q3 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cvx:segment cvx:lawsuit cvx:state cvx:tribe cvx:parish 0000093410 2025-01-01 2025-09-30 0000093410 2025-09-30 0000093410 2025-07-01 2025-09-30 0000093410 2024-07-01 2024-09-30 0000093410 2024-01-01 2024-09-30 0000093410 2024-12-31 0000093410 2023-12-31 0000093410 2024-09-30 0000093410 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(2) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections During the three months ended September 30, 2025, none of our directors or executive officers adopted, modified or terminated a Rule 10b5-1 trading arrangement or a non-Rule 10b5-1 trading arrangement, as such terms are defined in Item 408 of Regulation S-K. 47 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 4.1 Fourth Supplemental Indenture, dated as of August 13, 2025, among Chevron U.S.A. Inc., Chevron Corporation, as guarantor, and Deutsche Bank Trust Company Americas, as trustee, filed as Exhibit 4. 2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 4.2 Forms of 3.950% Notes Due 2027, 4.050% Notes Due 2028, Floating Rate Notes Due 2028-B, 4.300% Notes Due 2030, Floating Rate Notes due 2030, 4.500% Notes Due 2032 and 4.850% Notes Due 2035, contained in Exhibit 4.2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 10.1+* Aircraft Time-Sharing Agreement, dated as of February 24, 2015, between Hess Corporation and John B. Hess. 10.2* Transition Services Agreement, dated as of July 14, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.3* Amendment One to Transition Services Agreement, dated as of August 27, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.4* Membership Interest Purchase Agreement, dated as of September 10, 2025, between Hess Corporation and JBH Ventures, LLC . 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ + Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 48 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 6, 2025 49\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": "-0.0108", "answer_numeric": -0.010843, "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%) = -0.0150.", "metadata": {"var": -0.010843, "cvar": -0.014988, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250609_0186", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2025-06-09", "context_summary": "VNQ: 60-day return history, mean=-0.0001, std=0.0136.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=-0.0001, std=0.0136, min=-0.0339, max=0.0322\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VNQ. Express as a decimal (e.g., -0.02).", "answer": "-0.0266", "answer_numeric": -0.026628, "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%) = -0.0315.", "metadata": {"var": -0.026628, "cvar": -0.031522, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250909_0188", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-09-09", "context_summary": "BTC-USD: 60-day return history, mean=-0.0005, std=0.0151.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0005, std=0.0151, min=-0.0404, max=0.0396\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0294", "answer_numeric": -0.029388, "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%) = -0.0355.", "metadata": {"var": -0.029388, "cvar": -0.035524, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251231_0191", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["REZ"], "decision_date": "2025-12-31", "context_summary": "REZ: 60-day return history, mean=0.0000, std=0.0084.", "question": "Asset: REZ\nDaily returns (past 60 days): mean=0.0000, std=0.0084, min=-0.0246, max=0.0166\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": "-0.0116", "answer_numeric": -0.011577, "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%) = -0.0209.", "metadata": {"var": -0.011577, "cvar": -0.020858, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251024_0194", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLE"], "decision_date": "2025-10-24", "context_summary": "XLE: 60-day return history, mean=0.0004, std=0.0105.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0004, std=0.0105, min=-0.0294, max=0.0202\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q KO 2025-10-23] ko-20250926 false 12/31 Q3 2025 0000021344 http://fasb.org/us-gaap/2025#OtherAssetsNoncurrent http://fasb.org/us-gaap/2025#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2025#OtherAssetsNoncurrent http://fasb.org/us-gaap/2025#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2025#OtherAssetsNoncurrent http://fasb.org/us-gaap/2025#PrepaidExpenseAndOtherAssetsCurrent 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country:US 2025-06-28 2025-09-26 0000021344 ko:InternationalMember 2025-06-28 2025-09-26 0000021344 ko:ConcentrateOperationsMember country:US 2024-06-29 2024-09-27 0000021344 ko:ConcentrateOperationsMember ko:InternationalMember 2024-06-29 2024-09-27 0000021344 ko:ConcentrateOperationsMember 2024-06-29 2024-09-27 0000021344 ko:FinishedProductOperationsMember country:US 2024-06-29 2024-09-27 0000021344 ko:FinishedProductOperationsMember ko:InternationalMember 2024-06-29 2024-09-27 0000021344 ko:FinishedProductOperationsMember 2024-06-29 2024-09-27 0000021344 country:US 2024-06-29 2024-09-27 0000021344 ko:InternationalMember 2024-06-29 2024-09-27 0000021344 ko:Co [...TRUNCATED...] ;30, 1991, between Coca-Cola Refreshments USA, Inc. and Deutsche Bank Trust Company Americas, as trustee — incorporated herein by reference to Exhibit 4.01 to Coca-Cola Refreshments USA, Inc.’s Current Report on Form 8-K dated January 29, 1992. 4.49 Second Supplemental Indenture, dated as of June 22, 2017, to the Indenture, dated as of July 30, 1991, as amended, among Coca-Cola Refreshments USA, Inc., the Company and Deutsche Bank Trust Company Americas, as trustee — incorporated herein by reference to Exhibit 4.3 to the Company’s Current Report on Form 8-K filed on June 23, 2017. 4.50 Third Supplemental Indenture, dated as of July 5, 2017, to the Indenture, dated as of July 30, 1991, as amended, among Coca-Cola Refreshments USA, Inc., the Company and Deutsche Bank Trust Company Americas, as trustee — incorporated herein by reference to Exhibit 4.3 to the Company’s Current Report on Form 8-K filed on July 6, 2017. 10.1 Letter, dated July 17, 2025, from the Company to Luisa Ortega. 31.1 Rule 13a-14(a)/15d-14(a) Certification, executed by James Quincey, Chairman of the Board of Directors and Chief Executive Officer of The Coca-Cola Company. 31.2 Rule 13a-14(a)/15d-14(a) Certification, executed by John Murphy, President and Chief Financial Officer of The Coca-Cola Company. 32.1 Certifications required by Rule 13a-14(b) or Rule 15d-14(b) and Section 1350 of Chapter 63 of Title 18 of the United States Code (18 U.S.C. Section 1350), executed by James Quincey, Chairman of the Board of Directors and Chief Executive Officer of The Coca-Cola Company, and by John Murphy, President and Chief Financial Officer of The Coca-Cola Company. 101 The following financial information from The Coca-Cola Company’s Quarterly Report on Form 10-Q for the quarter ended September 26, 2025, formatted in iXBRL (Inline Extensible Business Reporting Language): (i) Consolidated Statements of Income for the three and nine months ended September 26, 2025 and September 27, 2024; (ii) Consolidated Statements of Comprehensive Income for the three and nine months ended September 26, 2025 and September 27, 2024; (iii) Consolidated Balance Sheets as of September 26, 2025 and December 31, 2024; (iv) Consolidated Statements of Cash Flows for the nine months ended September 26, 2025 and September 27, 2024; and (v) Notes to Consolidated Financial Statements. 104 Cover Page Interactive Data File (the cover page XBRL tags are embedded within the iXBRL document and included in Exhibit 101). 57 SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.     THE COCA-COLA COMPANY (Registrant) /s/ ERIN L. MAY Date: October 23, 2025 Erin L. May Senior Vice President, Controller and Chief Accounting Officer (Principal Accounting Officer) 58\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLE. Express as a decimal (e.g., -0.02).", "answer": "-0.0188", "answer_numeric": -0.018788, "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%) = -0.0238.", "metadata": {"var": -0.018788, "cvar": -0.023849, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9044}} +{"id": "T2_all_20251113_0196", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-11-13", "context_summary": "ADA-USD: 60-day return history, mean=-0.0069, std=0.0442.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0069, std=0.0442, min=-0.1761, max=0.1097\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0622", "answer_numeric": -0.062238, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0622 (i.e., on a bad day with 5% probability, the loss exceeds 6.22%). CVaR(95%) = -0.1130.", "metadata": {"var": -0.062238, "cvar": -0.113038, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250528_0199", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-05-28", "context_summary": "BNB-USD: 60-day return history, mean=0.0019, std=0.0205.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0019, std=0.0205, min=-0.0649, max=0.0608\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0266", "answer_numeric": -0.02659, "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%) = -0.0475.", "metadata": {"var": -0.02659, "cvar": -0.047488, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250101_0202", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VCIT"], "decision_date": "2025-01-01", "context_summary": "VCIT: 60-day return history, mean=-0.0002, std=0.0034.", "question": "Asset: VCIT\nDaily returns (past 60 days): mean=-0.0002, std=0.0034, min=-0.0100, max=0.0094\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": "-0.0059", "answer_numeric": -0.005946, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0059 (i.e., on a bad day with 5% probability, the loss exceeds 0.59%). CVaR(95%) = -0.0081.", "metadata": {"var": -0.005946, "cvar": -0.008083, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251124_0205", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-11-24", "context_summary": "DOT-USD: 60-day return history, mean=-0.0064, std=0.0541.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0064, std=0.0541, min=-0.1989, max=0.2170\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0675", "answer_numeric": -0.067545, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0675 (i.e., on a bad day with 5% probability, the loss exceeds 6.75%). CVaR(95%) = -0.1369.", "metadata": {"var": -0.067545, "cvar": -0.136933, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251015_0208", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IGOV"], "decision_date": "2025-10-15", "context_summary": "IGOV: 60-day return history, mean=-0.0002, std=0.0052.", "question": "Asset: IGOV\nDaily returns (past 60 days): mean=-0.0002, std=0.0052, min=-0.0100, max=0.0139\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IGOV. Express as a decimal (e.g., -0.02).", "answer": "-0.0085", "answer_numeric": -0.008529, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0085 (i.e., on a bad day with 5% probability, the loss exceeds 0.85%). CVaR(95%) = -0.0095.", "metadata": {"var": -0.008529, "cvar": -0.009541, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250227_0210", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2025-02-27", "context_summary": "QUAL: 59-day return history, mean=-0.0002, std=0.0073.", "question": "Asset: QUAL\nDaily returns (past 59 days): mean=-0.0002, std=0.0073, min=-0.0265, max=0.0158\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K NVDA 2025-02-26] nvda-20250126 0001045810 2025 FY false 491 358 P1Y P2Y P2Y P1Y P3Y http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent iso4217:USD xbrli:shares iso4217:USD xbrli:shares xbrli:pure nvda:period nvda:segment 0001045810 2024-01-29 2025-01-26 0001045810 2024-07-26 0001045810 2025-02-21 0001045810 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2024-01-29 2025-01-26 0001045810 nvda:ComputeAndNetworkingSegmentMember 2025-01-26 0001045810 nvda:GraphicsSegmentMember 2025-01-26 0001045810 nvda:ComputeAndNetworkingSegmentMember 2024-01-28 0001045810 nvda:GraphicsSegmentMember 2024-01-28 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-01-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2024-01-28 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2024-01-28 0001045810 us-gaap:CorporateDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:USTreasurySecuritiesMember 2025-01-26 0001045810 [...TRUNCATED...] written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051 Item 16. Form 10-K Summary Not Applicable. 85 Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on February 26, 2025. NVIDIA Corporation By: /s/ Jen-Hsun Huang    Jen-Hsun Huang   President and Chief Executive Officer Power of Attorney KNOW ALL PERSONS BY THESE PRESENTS, that each person whose signature appears below constitutes and appoints Jen-Hsun Huang and Colette M. Kress, and each or any one of them, his true and lawful attorney-in-fact and agent, with full power of substitution and resubstitution, for him and in his name, place and stead, in any and all capacities, to sign any and all amendments to this report, and to file the same, with all exhibits thereto, and other documents in connection therewith, with the Securities and Exchange Commission, granting unto said attorneys-in-facts and agents, and each of them, full power and authority to do and perform each and every act and thing requisite and necessary to be done in connection therewith, as fully to all intents and purposes as he might or could do in person, hereby ratifying and confirming all that said attorneys-in-fact and agents, or any of them, or their or his substitutes or substitutes, may lawfully do or cause to be done by virtue hereof. 86 Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated. Signature Title Date /s/ JEN-HSUN HUANG  President, Chief Executive Officer and Director (Principal Executive Officer) February 26, 2025 Jen-Hsun Huang   /s/ COLETTE M. KRESS  Executive Vice President and Chief Financial Officer (Principal Financial Officer) February 26, 2025 Colette M. Kress   /s/ DONALD ROBERTSON Vice President and Chief Accounting Officer (Principal Accounting Officer) February 26, 2025 Donald Robertson /s/ ROBERT K. BURGESS Director February 26, 2025 Robert K. Burgess /s/ TENCH COXE   Director February 26, 2025 Tench Coxe    /s/ JOHN O. DABIRI Director February 26, 2025 John O. Dabiri   /s/ PERSIS S. DRELL Director February 26, 2025 Persis S. Drell /s/ DAWN HUDSON Director February 26, 2025 Dawn Hudson /s/ HARVEY C. JONES  Director February 26, 2025 Harvey C. Jones   /s/ MELISSA B. LORA Director February 26, 2025 Melissa B. Lora /s/ STEPHEN C. NEAL Director February 26, 2025 Stephen C. Neal /s/ ELLEN OCHOA Director February 26, 2025 Ellen Ochoa /s/ A. BROOKE SEAWELL Director February 26, 2025 A. Brooke Seawell  /s/ AARTI SHAH Director February 26, 2025 Aarti Shah /s/ MARK A. STEVENS Director February 26, 2025 Mark A. Stevens    87\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": "-0.0112", "answer_numeric": -0.01121, "explanation": "Historical simulation VaR at 95%: sort the 59 daily returns and take the 5th percentile. VaR(95%) = -0.0112 (i.e., on a bad day with 5% probability, the loss exceeds 1.12%). CVaR(95%) = -0.0194.", "metadata": {"var": -0.01121, "cvar": -0.019383, "confidence": 0.95, "n_returns": 59, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20250613_0213", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-06-13", "context_summary": "ETH-USD: 60-day return history, mean=0.0083, std=0.0377.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0083, std=0.0377, min=-0.0737, max=0.1560\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0393", "answer_numeric": -0.039258, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0393 (i.e., on a bad day with 5% probability, the loss exceeds 3.93%). CVaR(95%) = -0.0564.", "metadata": {"var": -0.039258, "cvar": -0.056441, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250121_0216", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2025-01-21", "context_summary": "XLK: 60-day return history, mean=0.0002, std=0.0126.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0002, std=0.0126, min=-0.0328, max=0.0281\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLK. Express as a decimal (e.g., -0.02).", "answer": "-0.0222", "answer_numeric": -0.022201, "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%) = -0.0302.", "metadata": {"var": -0.022201, "cvar": -0.030179, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250926_0219", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-09-26", "context_summary": "AVAX-USD: 60-day return history, mean=0.0027, std=0.0473.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0027, std=0.0473, min=-0.1139, max=0.1346\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0585", "answer_numeric": -0.058522, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0585 (i.e., on a bad day with 5% probability, the loss exceeds 5.85%). CVaR(95%) = -0.0927.", "metadata": {"var": -0.058522, "cvar": -0.092677, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251204_0221", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-12-04", "context_summary": "BNB-USD: 60-day return history, mean=-0.0029, std=0.0402.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0029, std=0.0402, min=-0.1186, max=0.1459\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0638", "answer_numeric": -0.063759, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0638 (i.e., on a bad day with 5% probability, the loss exceeds 6.38%). CVaR(95%) = -0.0893.", "metadata": {"var": -0.063759, "cvar": -0.089259, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250417_0223", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-04-17", "context_summary": "LINK-USD: 60-day return history, mean=-0.0053, std=0.0603.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0053, std=0.0603, min=-0.1701, max=0.1774\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0982", "answer_numeric": -0.098244, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0982 (i.e., on a bad day with 5% probability, the loss exceeds 9.82%). CVaR(95%) = -0.1432.", "metadata": {"var": -0.098244, "cvar": -0.143241, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251104_0226", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-11-04", "context_summary": "XLV: 60-day return history, mean=0.0017, std=0.0081.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0017, std=0.0081, min=-0.0167, max=0.0244\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q CAT 2025-11-03] cat-20250930 0000018230 FALSE 12/31 2025 Q3 50 365 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cat:group_president cat:segment 0000018230 2025-01-01 2025-09-30 0000018230 us-gaap:CommonStockMember 2025-01-01 2025-09-30 0000018230 cat:A5.3DebenturesDueSeptember152035Member 2025-01-01 2025-09-30 0000018230 2025-09-30 0000018230 cat:MachineryEnergyTransportationMember 2025-07-01 2025-09-30 0000018230 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us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-12-31 0000018230 us-gaap:TreasuryStockCommonMember 2024-12-31 0000018230 us-gaap:RetainedEarningsMember 2024-12-31 0000018230 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-12-31 0000018230 us-gaap:NoncontrollingInterestMember 2024-12-31 0000018230 us-gaap:RetainedEarningsMember 2025-01-01 2025-09-30 0000018230 us-gaap:NoncontrollingInterestMember 2025-01-01 2025-09-30 0000018230 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-01 2025-09-30 0000018230 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-01-01 2025-09-30 0000018230 us-gaap:TreasuryStockCommonMember 2025-01-01 2025-09-30 0000018230 2025-10-01 2025-09-30 0000018230 us-gaap:EmployeeStockOptionMember 2025-01-01 2025-09-30 0000018230 us-gaap:EmployeeStockOptionMember 2024-01-01 2024-09-30 0000018230 us-gaap:RestrictedStockUnitsRSUMember 2025-01-01 2025-09-30 0000018230 us-gaap:RestrictedStockUnitsRSUMember 2024-01-01 2024-09-30 0000018230 us-gaap:PerformanceSharesMember 2025-01-01 2025-09-30 0000018230 us-gaap:PerformanceSharesMember 2024-01-01 2024-09-30 0000018230 us-gaap:ForeignExchangeContractMember us-gaap:DesignatedAsHedgingInstrumentMember 2025-09-30 0000018230 us-gaap:ForeignExchangeContractMember us-gaap:DesignatedAsHedgingInstrumentMember 2024-12-31 0000018230 us-gaap:InterestRateContractMember us-gaap:DesignatedAsHedgingInstrumentMember 2025-09-30 0000018230 us-gaap:InterestRateContractMember us-gaap:DesignatedAsHedgingInstrumentMember 2024-12-31 0000018230 us-gaap:DesignatedAsHedgingInstrumentMember 2025-09-30 0000018230 us-gaap:DesignatedAsHedgingInstrumentMe [...TRUNCATED...] rrent Report on Form 8-K filed September 3, 2025) 10.11 CIF LUX Local Currency Addendum to the Fourth Amended and Restated Credit Agreement (Five-Year Facility) (incorporated by reference from Exhibit 10.11 to the Company's Current Report on Form 8-K filed September 3, 2025) 10.12 Japan Local Currency Addendum to the Fourth Amended and Restated Credit Agreement (Five-Year Facility) (incorporated by reference from Exhibit 10.12 to the Company's Current Report on Form 8-K filed September 3, 2025) 31.1 Certification of Chief Executive Officer of Caterpillar Inc., as required pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer of Caterpillar Inc., as required pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32 Certification of Chief Executive Officer of Caterpillar Inc. and Chief Financial Officer of Caterpillar Inc., as required pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS Inline XBRL Instance Document (the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document) 101.SCH   Inline XBRL Taxonomy Extension Schema Document 101.CAL   Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF   Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB   Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE   Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive File (embedded within the Inline XBRL document and included in Exhibit 101) The agreements and other documents filed as exhibits to this report are not intended to provide factual information or other disclosure other than with respect to the terms of the agreements or other documents themselves, and you should not rely on them for that purpose. In particular, any representations and warranties made by us in these agreements or other documents 81 Table of Contents were made solely within the specific context of the relevant agreement or document and may not describe the actual state of affairs as of the date they were made or at any other time. 82 Table of Contents SIGNATURES   Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       CATERPILLAR INC.               November 3, 2025 /s/ Joseph E. Creed Chief Executive Officer   Joseph E. Creed         November 3, 2025 /s/ Andrew R.J. Bonfield Chief Financial Officer   Andrew R.J. Bonfield               November 3, 2025 /s/ Derek Owens Chief Legal Officer and General Counsel   Derek Owens             November 3, 2025 /s/ William E. Schaupp Vice President and Chief Accounting Officer   William E. Schaupp   83\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": "-0.0117", "answer_numeric": -0.011729, "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%) = -0.0152.", "metadata": {"var": -0.011729, "cvar": -0.0152, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250801_0229", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SHV"], "decision_date": "2025-08-01", "context_summary": "SHV: 60-day return history, mean=0.0002, std=0.0001.", "question": "Asset: SHV\nDaily returns (past 60 days): mean=0.0002, std=0.0001, min=-0.0001, max=0.0005\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SHV. Express as a decimal (e.g., -0.02).", "answer": "0.0000", "answer_numeric": 0.0, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = -0.0000.", "metadata": {"var": 0.0, "cvar": -1.3e-05, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251014_0232", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-10-14", "context_summary": "XLF: 60-day return history, mean=0.0001, std=0.0077.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0001, std=0.0077, min=-0.0220, max=0.0164\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": -0.01159, "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%) = -0.0197.", "metadata": {"var": -0.01159, "cvar": -0.019725, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250617_0235", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2025-06-17", "context_summary": "ICSH: 60-day return history, mean=0.0002, std=0.0003.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0002, std=0.0003, min=-0.0006, max=0.0008\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%) = -0.0005.", "metadata": {"var": -0.000198, "cvar": -0.000462, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250522_0237", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQI"], "decision_date": "2025-05-22", "context_summary": "VNQI: 60-day return history, mean=0.0009, std=0.0096.", "question": "Asset: VNQI\nDaily returns (past 60 days): mean=0.0009, std=0.0096, 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": "-0.0140", "answer_numeric": -0.013976, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0140 (i.e., on a bad day with 5% probability, the loss exceeds 1.40%). CVaR(95%) = -0.0218.", "metadata": {"var": -0.013976, "cvar": -0.021823, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250314_0240", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLP"], "decision_date": "2025-03-14", "context_summary": "XLP: 60-day return history, mean=-0.0006, std=0.0088.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0006, std=0.0088, min=-0.0220, max=0.0211\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-03-13] [\"iRobot stock dives on its 'substantial doubt' of surviving in 2025 iRobot (IRBT) stock is plummeting by nearly 35% ahead of Wednesday's market close after the Roomba-maker warned about the company's \\\"substantial doubt\\\" of its ability to continue. This comes over a year after its deal with Amazon (AMZN) fell through Julie Hyman and Josh Lipton report more on iRobot's negative stock moves. To watch more expert insights and analysis on the latest market action, check out more Market Domination here.\", \"Game On: Discord reportedly in talks for IPO in 2025 \\u201cGame On\\u201d is The Fly\\u2019s weekly recap of the stories powering up or beating down video game stocks. Easily identify stocks' risks and opportunities. Discover stocks' market position with detailed competitor analyses. NEW RELEASES: This week\\u2019s most notable new game release is Take-Two\\u2019s (TTWO) professional wrestling sim \\u201cWWE 2K25,\\u201d which launches March 14 for PlayStation 4 (SONY), PS5, PC, Xbox One (MSFT), and Xbox Series X/S. DISCORD IPO: Discord, a social media and messaging app loved by gamers, that \\u201callows users to chat via voice, video, or text,\\u201d has held discussions with bankers recently \\u201cto discuss preparations for an initial public offering,\\u201d possibly in 2025, Lauren Hirsch and Mike Isaac of The New York Times reported Monday. The device will look unmistakably \\u201cXbox,\\u201d including an official Xbox guide button and Xbox-related design sensibilities, the author said, noting he expects the handheld to likely run full Windows, alongside the ability to install Steam. Additionally, sources told Corden that the company\\u2019s internal successor to the Xbox Series X/S platform has been fully greenlit by CEO Satya Nadella, with a premium successor the Series X and the new gaming handheld as part of the next-generation plans, with the new devices slated for 2027. Click here to check out recent Media Buzz Sentiment on Microsoft as measured by TipRanks. LOOP ON BEST BUY: Loop Capital maintained a Buy rating and $90 price target on Best Buy (BBY) last week. The firm\\u2019s quarterly pricing study comparing Best Buy and Amazon\\u2019s (AMZN) prices on 50 items across five different product categories left it \\u201cencouraged\\u201d that Best Buy\\u2019s prices remain highly competitive with Amazon\\u2019s, the analyst tells investors in a research note. While the increasingly uncertain U.S. macroeconomic environment is likely to remain a near-term overhang, there are two significant upcoming fundamental catalysts this year \\u2013 the introduction of the Nintendo Switch 2 (NTDOY) and the debut of Take-Two\\u2019s \\u201cGrand Theft Auto VI,\\u201d the firm added. MORE VIDEO GAME NEWS: Electronic Arts\\u2019 (EA) \\u201cSplit Fiction\\u201d sold 1M units in its first 48 hours Activision said that \\u201cTony Hawk\\u2019s Pro Skater 3 + 4\\u201d will release July 11 for Xbox, PlayStation, PC, and Nintendo Switch Sony\\u2019s Visual Arts studio was hit with a f\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": "-0.0158", "answer_numeric": -0.015816, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0158 (i.e., on a bad day with 5% probability, the loss exceeds 1.58%). CVaR(95%) = -0.0195.", "metadata": {"var": -0.015816, "cvar": -0.019479, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250218_0243", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-02-18", "context_summary": "SOL-USD: 60-day return history, mean=-0.0005, std=0.0461.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0005, std=0.0461, min=-0.0771, max=0.1924\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0636", "answer_numeric": -0.063594, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0636 (i.e., on a bad day with 5% probability, the loss exceeds 6.36%). CVaR(95%) = -0.0730.", "metadata": {"var": -0.063594, "cvar": -0.072979, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250516_0246", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-05-16", "context_summary": "AVAX-USD: 60-day return history, mean=0.0053, std=0.0500.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0053, std=0.0500, min=-0.1060, max=0.1441\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0627", "answer_numeric": -0.062741, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0627 (i.e., on a bad day with 5% probability, the loss exceeds 6.27%). CVaR(95%) = -0.0899.", "metadata": {"var": -0.062741, "cvar": -0.089948, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250825_0249", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-08-25", "context_summary": "BNB-USD: 60-day return history, mean=0.0053, std=0.0214.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0053, std=0.0214, min=-0.0346, max=0.0712\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0272", "answer_numeric": -0.027178, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0272 (i.e., on a bad day with 5% probability, the loss exceeds 2.72%). CVaR(95%) = -0.0322.", "metadata": {"var": -0.027178, "cvar": -0.032176, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250328_0252", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2025-03-28", "context_summary": "CSHI: 60-day return history, mean=0.0002, std=0.0006.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0002, std=0.0006, min=-0.0017, max=0.0020\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for CSHI. Express as a decimal (e.g., -0.02).", "answer": "-0.0005", "answer_numeric": -0.000518, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0005 (i.e., on a bad day with 5% probability, the loss exceeds 0.05%). CVaR(95%) = -0.0013.", "metadata": {"var": -0.000518, "cvar": -0.001273, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250506_0258", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2025-05-06", "context_summary": "MATIC-USD: 52-day return history, mean=-0.0069, std=0.0431.", "question": "Asset: MATIC-USD\nDaily returns (past 52 days): mean=-0.0069, std=0.0431, min=-0.1586, max=0.0741\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0916", "answer_numeric": -0.091566, "explanation": "Historical simulation VaR at 95%: sort the 52 daily returns and take the 5th percentile. VaR(95%) = -0.0916 (i.e., on a bad day with 5% probability, the loss exceeds 9.16%). CVaR(95%) = -0.1202.", "metadata": {"var": -0.091566, "cvar": -0.120245, "confidence": 0.95, "n_returns": 52, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250107_0260", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-01-07", "context_summary": "BTC-USD: 60-day return history, mean=0.0053, std=0.0268.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0053, std=0.0268, min=-0.0575, max=0.1022\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0368", "answer_numeric": -0.036841, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0368 (i.e., on a bad day with 5% probability, the loss exceeds 3.68%). CVaR(95%) = -0.0484.", "metadata": {"var": -0.036841, "cvar": -0.04838, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250918_0262", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-09-18", "context_summary": "SOL-USD: 60-day return history, mean=0.0062, std=0.0413.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0062, std=0.0413, min=-0.0902, max=0.1130\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0452", "answer_numeric": -0.045202, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0452 (i.e., on a bad day with 5% probability, the loss exceeds 4.52%). CVaR(95%) = -0.0747.", "metadata": {"var": -0.045202, "cvar": -0.074716, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250306_0264", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-03-06", "context_summary": "ETH-USD: 60-day return history, mean=-0.0072, std=0.0431.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0072, std=0.0431, min=-0.1485, max=0.1367\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0802", "answer_numeric": -0.080214, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0802 (i.e., on a bad day with 5% probability, the loss exceeds 8.02%). CVaR(95%) = -0.1136.", "metadata": {"var": -0.080214, "cvar": -0.113568, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250401_0267", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2025-04-01", "context_summary": "CSHI: 60-day return history, mean=0.0002, std=0.0007.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0002, std=0.0007, min=-0.0017, max=0.0020\nMarket regime: bear\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for CSHI. Express as a decimal (e.g., -0.02).", "answer": "-0.0010", "answer_numeric": -0.001007, "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%) = -0.0012.", "metadata": {"var": -0.001007, "cvar": -0.001207, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250407_0269", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-04-07", "context_summary": "VLUE: 60-day return history, mean=-0.0010, std=0.0111.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0010, std=0.0111, min=-0.0356, max=0.0176\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-04] 3 Stocks Estimated To Be Undervalued By Up To 37.7% The United States stock market recently experienced significant volatility, with major indexes like the Dow Jones and S&P 500 facing their worst day since 2020 due to newly announced tariffs. In such turbulent times, identifying undervalued stocks can be a strategic move for investors seeking opportunities amidst broader market declines. Click here to see the full list of 189 stocks from our Undervalued US Stocks Based On Cash Flows screener. Let's explore several standout options from the results in the screener. Overview: AppLovin Corporation develops a software platform aimed at improving marketing and monetization for advertisers both in the United States and globally, with a market cap of approximately $98.72 billion. Operations: The company's revenue is primarily derived from its Apps segment, generating $1.49 billion, and its Advertising segment, contributing $3.22 billion. Estimated Discount To Fair Value: 24.3% AppLovin is trading 24.3% below its estimated fair value, with earnings expected to grow significantly at 23.19% annually, outpacing the US market's growth rate. Despite a high level of debt and recent legal challenges alleging unethical practices, the company reported strong financial results with Q4 sales reaching US$1.37 billion and net income at US$599.2 million. However, insider selling and share price volatility present potential risks for investors considering cash flow valuation metrics. Our earnings growth report unveils the potential for significant increases in AppLovin's future results. Navigate through the intricacies of AppLovin with our comprehensive financial health report here. Overview: Comstock Resources, Inc. is an independent energy company focused on the acquisition, exploration, development, and production of natural gas and oil properties in the United States with a market cap of $6.29 billion. Operations: The company's revenue primarily comes from its oil and gas exploration and production segment, which generated $1.25 billion. Estimated Discount To Fair Value: 21.3% Comstock Resources is trading 21.3% below its estimated fair value of US$26.1, with revenue expected to grow at 20.9% annually, surpassing the US market's growth rate. Despite a high debt level and recent quarterly losses of US$58.13 million amidst declining production, forecasts indicate the company will become profitable within three years with earnings growth projected at over 110% per year, suggesting potential for investors focused on cash flow valuation metrics. Our growth report here indicates Comstock Resources may be poised for an improving outlook. Dive into the specifics of Comstock Resources here with our thorough financial health report. Overview: BBB Foods Inc. operates a chain of grocery retail stores in Mexico and has a market cap of $3.11 billion. Operations: The company's revenue is primarily derived from the sale, acquisition, and distribution of various products and consu\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": "-0.0178", "answer_numeric": -0.017833, "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%) = -0.0311.", "metadata": {"var": -0.017833, "cvar": -0.031051, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250514_0272", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-05-14", "context_summary": "XLY: 60-day return history, mean=-0.0018, std=0.0189.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=-0.0018, std=0.0189, min=-0.0388, max=0.0338\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-13] Alnylam Pharmaceuticals (NasdaqGS:ALNY) To Present Pivotal TTR Franchise Data At Heart Failure Congress In May 2025, Alnylam Pharmaceuticals announced its plan to present new data from its transthyretin amyloidosis (TTR) franchise at the Heart Failure 2025 Congress, alongside securing broader international approvals for its therapeutic vutrisiran (AMVUTTRA). During the same month, the overall market rallied due to positive developments in U.S.-China trade relations, with major indexes experiencing substantial gains. Alnylam's 5.63% rise over the period likely reflects investor optimism towards its recent product announcements and earnings improvements, aligning with broader market upward trends driven by eased international trade tensions. Alnylam Pharmaceuticals has 1 warning sign we think you should know about. Find companies with promising cash flow potential yet trading below their fair value. The recent announcement by Alnylam Pharmaceuticals about presenting new data at Heart Failure 2025 Congress and gaining wider international approvals for vutrisiran could significantly bolster investor confidence in the company's growth trajectory. Given the expanded indication for AMVUTTRA in ATTR cardiomyopathy, the potential for increased revenue is substantial. This aligns with the company's aim to achieve sustainable profitability, despite current earnings being at US$269.7 million. Additionally, analysts forecast future earnings to improve, with expected revenue reaching several billion dollars, indicating growth prospects fueled by new product launches and expanding market share. Over the past three years, Alnylam's total shareholder return, including share price and dividends, was 101.13%. This robust performance compares favorably against the market's 8% return over the past year. Additionally, Alnylam outperformed the US Biotechs industry, which experienced a 15.3% decline in the same time frame. These figures underscore Alnylam's relative strength and investor optimism toward its pipeline and strategic initiatives. The enthusiasm generated by Alnylam's recent developments is also reflected in the stock's price movement. The shares currently trade at a discount to the consensus analyst price target of US$320.56, suggesting potential upside if future earnings and revenue growth materialize as expected. However, despite the positive sentiment, the stock's price-to-sales ratio remains above both industry and peer averages, indicating a premium valuation. As such, the price movement in conjunction with analyst forecasts highlights both potential growth opportunities and the inherent risks associated with Alnylam's current market positioning. Navigate through the intricacies of Alnylam Pharmaceuticals with our comprehensive balance sheet health report here. This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to \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": "-0.0365", "answer_numeric": -0.036464, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0365 (i.e., on a bad day with 5% probability, the loss exceeds 3.65%). CVaR(95%) = -0.0388.", "metadata": {"var": -0.036464, "cvar": -0.038816, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250527_0275", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-05-27", "context_summary": "ADA-USD: 60-day return history, mean=0.0014, std=0.0434.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0014, std=0.0434, min=-0.1251, max=0.1422\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0481", "answer_numeric": -0.048139, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0481 (i.e., on a bad day with 5% probability, the loss exceeds 4.81%). CVaR(95%) = -0.0849.", "metadata": {"var": -0.048139, "cvar": -0.084879, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251112_0278", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ITB"], "decision_date": "2025-11-12", "context_summary": "ITB: 60-day return history, mean=-0.0014, std=0.0154.", "question": "Asset: ITB\nDaily returns (past 60 days): mean=-0.0014, std=0.0154, min=-0.0318, max=0.0472\nMarket regime: bull\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": "-0.0268", "answer_numeric": -0.026802, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0268 (i.e., on a bad day with 5% probability, the loss exceeds 2.68%). CVaR(95%) = -0.0306.", "metadata": {"var": -0.026802, "cvar": -0.030637, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251028_0281", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-10-28", "context_summary": "SOL-USD: 60-day return history, mean=-0.0004, std=0.0423.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0004, std=0.0423, min=-0.1463, max=0.1093\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0568", "answer_numeric": -0.056822, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0568 (i.e., on a bad day with 5% probability, the loss exceeds 5.68%). CVaR(95%) = -0.1019.", "metadata": {"var": -0.056822, "cvar": -0.101916, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250414_0284", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["USO"], "decision_date": "2025-04-14", "context_summary": "USO: 60-day return history, mean=-0.0033, std=0.0203.", "question": "Asset: USO\nDaily returns (past 60 days): mean=-0.0033, std=0.0203, min=-0.0678, max=0.0557\nMarket regime: bear\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": "-0.0338", "answer_numeric": -0.03377, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0338 (i.e., on a bad day with 5% probability, the loss exceeds 3.38%). CVaR(95%) = -0.0559.", "metadata": {"var": -0.03377, "cvar": -0.055921, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250219_0287", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-02-19", "context_summary": "DOT-USD: 60-day return history, mean=-0.0061, std=0.0456.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0061, std=0.0456, min=-0.1306, max=0.0874\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0846", "answer_numeric": -0.084645, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0846 (i.e., on a bad day with 5% probability, the loss exceeds 8.46%). CVaR(95%) = -0.1142.", "metadata": {"var": -0.084645, "cvar": -0.11418, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250115_0290", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-01-15", "context_summary": "VLUE: 60-day return history, mean=-0.0006, std=0.0086.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0006, std=0.0086, min=-0.0279, max=0.0296\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 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0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VLUE. Express as a decimal (e.g., -0.02).", "answer": "-0.0116", "answer_numeric": -0.011614, "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%) = -0.0177.", "metadata": {"var": -0.011614, "cvar": -0.017675, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250827_0293", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-08-27", "context_summary": "USMV: 60-day return history, mean=0.0001, std=0.0057.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0001, std=0.0057, min=-0.0114, max=0.0111\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-08-26] [\"Apple\\u2019s August Stock Revival Gives Hope to Concerned Investors (Bloomberg) -- Apple Inc.\\u2019s stock is showing signs of life after struggling through most of 2025, as the tariff-related risks that have weighed on the company start to ease. Shares of the tech giant entered August down 17% for the year due in part to concerns about the impact of President Donald Trump\\u2019s sweeping levies, which cost the company $800 million in its fiscal third quarter alone. The US president has long criticized Apple for its reliance on overseas production partners, at one point even threatening to punish the company with tariffs if it didn\\u2019t make its iPhones in the US. Most Read from Bloomberg In Trump\\u2019s DC Crackdown, the National Park Service Leads Homeless Sweeps Germany Revives a Building Style With a Bleak History: Prefab Housing Chicago Schools\\u2019 Late Pension Payment Magnifies Fiscal Mess To Boost Housing, Chicago Kills Parking Minimums Central Glasgow Could Be Poised for a Revival Then, at an event in the Oval Office on Aug. 6, Apple Chief Executive Officer Tim Cook committed to spending an additional $100 billion on manufacturing in the US. Combined with the iPhone maker\\u2019s expansion of a long-standing deal with glass-supplier Corning Inc., the risk of additional Trump tariffs were seen as diminishing and the stock took off, soaring 8.7% in August, putting it on pace for its best month since June 2024. The stock fell 0.7% on Tuesday. \\u201cThe picture is a lot clearer from a tariff standpoint,\\u201d said George Cipolloni, a veteran portfolio manager. Apple \\u201cwas in Trump\\u2019s crosshairs, but Cook kissed the ring and now it no longer seems to be, which removes a headwind.\\u201d It\\u2019s been a strange stretch for Apple. The stock has been a reliable winner for years, soaring more than 240% from 2020 through 2024, putting it among the 20 best performers in the tech-heavy Nasdaq 100 Index. But this year has been different. Even with its August run, the shares are still down 10% in 2025, putting them among the worst performers in the benchmark. In addition to tariffs, the company is facing skepticism about its artificial intelligence plans and sluggish sales growth. The stock also remains relatively expensive. Even with this year\\u2019s selloff, it\\u2019s trading at 29 times projected earnings, a premium to its average over the past decade of 21 times and to the Nasdaq 100\\u2019s multiple of 27. However, sentiment is clearly improving. Late last month, Apple reported its fastest quarterly revenue growth in more than three years, supported by its iPhone business and strength in the China market. AI Strategy More importantly, the Cupertino, California-based company is working on a revamped AI strategy that will include robots, a lifelike version of its Siri digital assistant, and a smart speaker with a display, Bloomberg News reported two weeks ago. It\\u2019s also said to be in early discussions about using Google Gemini to po\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": "-0.0089", "answer_numeric": -0.00886, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0089 (i.e., on a bad day with 5% probability, the loss exceeds 0.89%). CVaR(95%) = -0.0100.", "metadata": {"var": -0.00886, "cvar": -0.010019, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250304_0295", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2025-03-04", "context_summary": "XLE: 60-day return history, mean=-0.0011, std=0.0131.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=-0.0011, std=0.0131, min=-0.0356, max=0.0218\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K PFE 2025-02-27] pfe-20241231 0000078003 2024 FY false P4Y Consolidated Statements of Operations Consolidated Statements of Operations Consolidated Statements of Operations http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#OtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesCurrent 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ITEM 16. FORM 10-K SUMMARY None. SIGNATURES Under the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, this report was signed on behalf of the Registrant by the authorized person named below. Pfizer Inc. Dated: February 27, 2025 By: /S/    MARGARET M. MADDEN Margaret M. Madden Senior Vice President and Corporate Secretary Chief Governance Counsel We, the undersigned directors and officers of Pfizer Inc., hereby severally constitute Douglas M. Lankler and Margaret M. Madden, and each of them singly, our true and lawful attorneys with full power to them and each of them to sign for us, in our names in the capacities indicated below, any and all amendments to this Annual Report on Form 10-K filed with the Securities and Exchange Commission. Under the requirements of the Securities Exchange Act of 1934, this report was signed by the following persons on behalf of the Registrant and in the capacities and on the date indicated . Pfizer Inc. 2024 Form 10-K 113 Signature Title Date /S/    ALBERT BOURLA Albert Bourla Chairman, Chief Executive Officer and Director (Principal Executive Officer) February 27, 2025 /S/    DAVID M. DENTON David M. Denton Chief Financial Officer, Executive Vice President (Principal Financial Officer) February 27, 2025 /S/    JENNIFER B. DAMICO Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer) February 27, 2025 /S/    RONALD E. BLAYLOCK Ronald E. Blaylock Director February 27, 2025 /S/    MORTIMER J. BUCKLEY Mortimer J. Buckley Director February 27, 2025 /S/    SUSAN DESMOND-HELLMANN Susan Desmond-Hellmann Director February 27, 2025 /S/    JOSEPH J. ECHEVARRIA Joseph J. Echevarria Director February 27, 2025 /S/    SCOTT GOTTLIEB Scott Gottlieb Director February 27, 2025 /S/    HELEN H. HOBBS Helen H. Hobbs Director February 27, 2025 /S/    SUSAN HOCKFIELD Susan Hockfield Director February 27, 2025 /S/    DAN R. LITTMAN Dan R. Littman Director February 27, 2025 /S/    SHANTANU NARAYEN Shantanu Narayen Director February 27, 2025 /S/    SUZANNE NORA JOHNSON Suzanne Nora Johnson Director February 27, 2025 /S/    JAMES QUINCEY James Quincey Director February 27, 2025 /S/    JAMES C. SMITH James C. Smith Director February 27, 2025 /S/    CYRUS TARAPOREVALA Cyrus Taraporevala Director February 27, 2025 Pfizer Inc. 2024 Form 10-K 114\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": "-0.0246", "answer_numeric": -0.024617, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0246 (i.e., on a bad day with 5% probability, the loss exceeds 2.46%). CVaR(95%) = -0.0313.", "metadata": {"var": -0.024617, "cvar": -0.031307, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20251126_0297", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2025-11-26", "context_summary": "IYR: 60-day return history, mean=0.0002, std=0.0082.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=0.0002, std=0.0082, min=-0.0253, max=0.0164\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": "-0.0118", "answer_numeric": -0.011833, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0118 (i.e., on a bad day with 5% probability, the loss exceeds 1.18%). CVaR(95%) = -0.0195.", "metadata": {"var": -0.011833, "cvar": -0.019509, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250818_0300", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-08-18", "context_summary": "XRP-USD: 60-day return history, mean=0.0067, std=0.0398.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0067, std=0.0398, min=-0.1033, max=0.1492\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0398", "answer_numeric": -0.039769, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0398 (i.e., on a bad day with 5% probability, the loss exceeds 3.98%). CVaR(95%) = -0.0767.", "metadata": {"var": -0.039769, "cvar": -0.076732, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250320_0303", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2025-03-20", "context_summary": "MATIC-USD: 60-day return history, mean=-0.0119, std=0.0453.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=-0.0119, std=0.0453, min=-0.1586, max=0.0741\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0998", "answer_numeric": -0.099792, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0998 (i.e., on a bad day with 5% probability, the loss exceeds 9.98%). CVaR(95%) = -0.1253.", "metadata": {"var": -0.099792, "cvar": -0.125321, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250616_0306", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-06-16", "context_summary": "BTC-USD: 60-day return history, mean=0.0040, std=0.0187.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0040, std=0.0187, min=-0.0393, max=0.0677\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0203", "answer_numeric": -0.020308, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0203 (i.e., on a bad day with 5% probability, the loss exceeds 2.03%). CVaR(95%) = -0.0316.", "metadata": {"var": -0.020308, "cvar": -0.031592, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250610_0309", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-06-10", "context_summary": "ADA-USD: 60-day return history, mean=0.0031, std=0.0364.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0031, std=0.0364, min=-0.0764, max=0.1422\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0458", "answer_numeric": -0.045814, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0458 (i.e., on a bad day with 5% probability, the loss exceeds 4.58%). CVaR(95%) = -0.0606.", "metadata": {"var": -0.045814, "cvar": -0.060612, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250704_0311", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-07-04", "context_summary": "DOT-USD: 60-day return history, mean=-0.0009, std=0.0408.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0009, std=0.0408, min=-0.0792, max=0.1197\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0517", "answer_numeric": -0.051663, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0517 (i.e., on a bad day with 5% probability, the loss exceeds 5.17%). CVaR(95%) = -0.0699.", "metadata": {"var": -0.051663, "cvar": -0.069868, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251225_0314", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-12-25", "context_summary": "ADA-USD: 60-day return history, mean=-0.0092, std=0.0421.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0092, std=0.0421, min=-0.0958, max=0.1251\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0631", "answer_numeric": -0.063096, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0631 (i.e., on a bad day with 5% probability, the loss exceeds 6.31%). CVaR(95%) = -0.0783.", "metadata": {"var": -0.063096, "cvar": -0.078293, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250701_0317", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-07-01", "context_summary": "BTC-USD: 60-day return history, mean=0.0019, std=0.0177.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0019, std=0.0177, min=-0.0393, max=0.0640\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0208", "answer_numeric": -0.0208, "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%) = -0.0316.", "metadata": {"var": -0.0208, "cvar": -0.031592, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250214_0320", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-02-14", "context_summary": "ETH-USD: 60-day return history, mean=-0.0059, std=0.0332.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0059, std=0.0332, min=-0.0832, max=0.0704\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0562", "answer_numeric": -0.056178, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0562 (i.e., on a bad day with 5% probability, the loss exceeds 5.62%). CVaR(95%) = -0.0774.", "metadata": {"var": -0.056178, "cvar": -0.077413, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250910_0323", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-09-10", "context_summary": "EEM: 60-day return history, mean=0.0013, std=0.0079.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0013, std=0.0079, min=-0.0160, max=0.0256\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": "-0.0124", "answer_numeric": -0.012396, "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%) = -0.0145.", "metadata": {"var": -0.012396, "cvar": -0.01449, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20251003_0326", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2025-10-03", "context_summary": "MTUM: 60-day return history, mean=0.0013, std=0.0069.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0013, std=0.0069, min=-0.0112, max=0.0236\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": "-0.0084", "answer_numeric": -0.008448, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0084 (i.e., on a bad day with 5% probability, the loss exceeds 0.84%). CVaR(95%) = -0.0107.", "metadata": {"var": -0.008448, "cvar": -0.010747, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250908_0329", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-09-08", "context_summary": "BTC-USD: 60-day return history, mean=0.0001, std=0.0160.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0001, std=0.0160, min=-0.0404, max=0.0419\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0294", "answer_numeric": -0.029388, "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%) = -0.0355.", "metadata": {"var": -0.029388, "cvar": -0.035524, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251201_0332", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-12-01", "context_summary": "SOL-USD: 60-day return history, mean=-0.0074, std=0.0443.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0074, std=0.0443, min=-0.1463, max=0.1093\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0650", "answer_numeric": -0.064954, "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%) = -0.1128.", "metadata": {"var": -0.064954, "cvar": -0.112825, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250606_0335", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-06-06", "context_summary": "BNB-USD: 60-day return history, mean=0.0024, std=0.0191.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0024, std=0.0191, min=-0.0447, max=0.0608\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0226", "answer_numeric": -0.022598, "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%) = -0.0392.", "metadata": {"var": -0.022598, "cvar": -0.039188, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250717_0338", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2025-07-17", "context_summary": "EWJ: 60-day return history, mean=0.0011, std=0.0097.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0011, std=0.0097, min=-0.0241, max=0.0260\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-16] [\"Tariffs Are Showing Up in Inflation. Why Trump Can\\u2019t Afford to Ditch Powell. House deals a blow to \\u201cCrypto Week,\\u201d ASML warns on 2026 growth, a promising Chinese weight-loss drug, and more news to start your day.\", \"Top Midday Gainers Longevity Health (XAGE) shares almost doubled amid heavy trading after the company said late Monday\", \"Why Is Jamf (JAMF) Stock Soaring Today Shares of apple device management company, Jamf (NASDAQ:JAMF) jumped 7.2% in the morning session after the company announced it expects to exceed the high end of its second-quarter 2025 guidance and revealed a new strategic reinvestment plan. The Apple device management company now anticipates both revenue and non-GAAP operating income to surpass its previous forecasts. The original guidance for the second quarter, which ended June 30, projected total revenue between $167.5 million and $169.5 million, with non-GAAP operating income of $29.5 million to $30.5 million. In a move to bolster long-term growth, Jamf also announced a strategic plan that includes reducing its workforce by about 6.4% and reallocating resources. The company will increase its focus on enterprise customers and accelerate investments in artificial intelligence. While the restructuring will result in one-time charges of $11.0 million to $12.5 million, investors appear to be focused on the positive outlook and the company's efforts to improve operational efficiency and drive future profitability. After the initial pop the shares cooled down to $8.30, up 1% from previous close. Is now the time to buy Jamf? Access our full analysis report here, it\\u2019s free. Jamf\\u2019s shares are somewhat volatile and have had 12 moves greater than 5% over the last year. In that context, today\\u2019s move indicates the market considers this news meaningful but not something that would fundamentally change its perception of the business. The previous big move we wrote about was 4 days ago when the stock dropped 3.9% after a broader market sell-off triggered by renewed trade tensions. U.S. stock indices fell after the Trump administration announced intentions to impose a 35% tariff on many goods imported from Canada. This move is far more than a typical trade dispute; it targets the United States' largest and most deeply integrated trading partner. Canada is not merely a neighbor but a critical component of North American supply chains, particularly in sectors like automotive, energy, and critical minerals. This move sparked concerns about potential retaliatory actions and a wider impact on the North American economy, leading to a risk-off sentiment among investors. The S&P 500, Dow Jones Industrial Average, and Nasdaq all opened lower, pulling back from recent record highs and heading for their first weekly loss in three weeks. Jamf is down 41.1% since the beginning of the year, and at $8.30 per share, it is trading 56.1% below its 52-week high of $18.91 from July 2024. Investors who bought $1,000 worth of Jam\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EWJ. Express as a decimal (e.g., -0.02).", "answer": "-0.0125", "answer_numeric": -0.012482, "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%) = -0.0200.", "metadata": {"var": -0.012482, "cvar": -0.020002, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250626_0341", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-06-26", "context_summary": "LINK-USD: 60-day return history, mean=-0.0012, std=0.0415.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0012, std=0.0415, min=-0.0759, max=0.1469\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0597", "answer_numeric": -0.059724, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0597 (i.e., on a bad day with 5% probability, the loss exceeds 5.97%). CVaR(95%) = -0.0718.", "metadata": {"var": -0.059724, "cvar": -0.071834, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250627_0344", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2025-06-27", "context_summary": "VEA: 60-day return history, mean=0.0017, std=0.0104.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0017, std=0.0104, min=-0.0276, max=0.0263\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-26] [\"Top Research Reports for Apple, AMD & Applied Materials Wednesday, June 25, 2025 The Zacks Research Daily presents the best research output of our analyst team. Today's Research Daily features new research reports on 16 major stocks, including Apple Inc. (AAPL), Advanced Micro Devices, Inc. (AMD) and Applied Materials, Inc. (AMAT), as well as two micro-cap stocks: Canterbury Park Holding Corp. (CPHC) and Where Food Comes From, Inc. (WFCF). Zacks microcap research is unique as our research content on these small and under-the-radar companies is the only research of its type in the country. 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 >>> Ahead of Wall Street The daily 'Ahead of Wall Street' article is a must-read for all investors who would like to be ready for that day's trading action. The article comes out before the market opens and attempts to make sense of that morning's economic releases and how they will affect that day's market action. You can read this article for free on our home page and can actually sign up there to get an email notification as this article comes out each morning. You can read today's AWS here >> Pre-Markets Flattish Ahead of Late-Week Economic News Today's Featured Research Reports Shares of Apple have declined -4.7% over the past year against the Zacks Computer - Micro Computers industry\\u2019s decline of -6.0%. The company is facing weakness in iPhone sales, particularly in China, which remains a concern. Increasing regulatory headwinds and tariffs are also a concern for investors. Nevertheless, Apple is benefiting from strong growth in Services revenues. It now has more than 1 billion paid subscribers across its Services portfolio, more than double what it had four years ago. The expanding content portfolio of Apple TV+ and Apple Arcade helped in driving subscriber growth. Apple expects the June quarter\\u2019s (third-quarter fiscal 2025) revenues to grow low to mid-single digits on a year-over-year basis. The introduction of Apple Intelligence, an advanced personal intelligence system integrated into iOS 18, iPadOS 18 and macOS Sequoia, is helping Apple sell more of its devices, including iPhone. (You can read the full research report on Apple here >>>) AMD\\u2019s shares have gained +17.5% over the year-to-date period against the Zacks Computer - Integrated Systems industry\\u2019s gain of +28%. The company is benefiting from robust Data Center and Client revenues that fully offset sluggishness in the Gaming and Embedded segments. Data centers are benefiting from solid adoption of fifth-gen EPYC Turin processors and expanding Instinct AI accelerator deployments across hyperscalers and enterprises. New product launches, such as the Ryzen 9 9950 X3D and Radeon 9070 series, have been major growth drivers. Gross margin expanded for the fifth consecutive quarter, driven by a more diverse Ryzen mix. AM\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": "-0.0200", "answer_numeric": -0.020028, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0200 (i.e., on a bad day with 5% probability, the loss exceeds 2.00%). CVaR(95%) = -0.0236.", "metadata": {"var": -0.020028, "cvar": -0.023589, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250313_0347", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-03-13", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0095, std=0.0573.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0095, std=0.0573, min=-0.1606, max=0.1404\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.1208", "answer_numeric": -0.12084, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1208 (i.e., on a bad day with 5% probability, the loss exceeds 12.08%). CVaR(95%) = -0.1421.", "metadata": {"var": -0.12084, "cvar": -0.14214, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250916_0350", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2025-09-16", "context_summary": "QQQ: 60-day return history, mean=0.0019, std=0.0072.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0019, std=0.0072, min=-0.0199, max=0.0183\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": "-0.0086", "answer_numeric": -0.008624, "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%) = -0.0151.", "metadata": {"var": -0.008624, "cvar": -0.015066, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250625_0353", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-06-25", "context_summary": "VTI: 60-day return history, mean=0.0008, std=0.0133.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0008, std=0.0133, min=-0.0335, max=0.0264\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-24] [\"Trump\\u2019s Chip Tariff Threat Sparks Pushback From Auto Industry to Tech (Bloomberg) -- Blowback to President Donald Trump\\u2019s idea of tariffs on imported semiconductors is proving to be broad and deep, stretching from auto companies and boat makers to the technology industry and crypto enthusiasts, according to a review of more than 150 public comments on the proposal. Most Read from Bloomberg Bezos Wedding Draws Protests, Soul-Searching Over Tourism in Venice US State Budget Wounds Intensify From Trump, DOGE Policy Shifts US Renters Face Storm of Rising Costs Commuters Are Caught in Johannesburg's Taxi Feuds as Transit Lags The possible levy of up to 25% has united rivals like Tesla Inc., General Motors Co. and Ford Motor Co. in voicing reservations. It\\u2019s brought together industry lobbies from the Crypto Council for Innovation to the National Marine Manufacturers Association. Even Taiwan and the People\\u2019s Republic of China are finding common cause, along with predictable parts of the tech sector including chipmakers and wireless providers. The reason is that chips are now in almost everything: refrigerators and microwaves, tire pressure sensors and navigation systems, electronic bidets and sonar equipment and, of course, smartphones and computers. Tariffs threaten to snarl supply lines and jack up costs for consumers. \\u201cThere\\u2019s a large mismatch between the amount of chips we use in this country in various products and the supply created here in the US,\\u201d JoAnne Feeney, a partner and portfolio manager at Advisors Capital Management, said in an interview. \\u201cPutting a tax on those imports will simply raise the cost, and that\\u2019s not a good thing for consumers.\\u201d Case in point is the marine association, which warns the impact would be felt by more than 1,300 manufacturers who face higher expenses for essentials like propulsion technology, engines and GPS systems. \\u201cThese systems are not optional luxuries \\u2014 they are fundamental to safety, function and performance,\\u201d the association said. \\u201cMany components have no US equivalent or are only available from highly concentrated suppliers overseas.\\u201d The boating sector\\u2019s concerns were among comments from 154 stakeholders submitted to a Commerce Department review of whether to slap tariffs on chips as part of Trump\\u2019s campaign to redraw global supply lines and boost domestic manufacturing. Predictable tech sources weighed in, including chipmakers Taiwan Semiconductor Manufacturing Co. and Intel Corp. But feedback also landed from a wide spectrum of sectors, along with trading partners like Japan and Brazil. The companies, trade groups and individuals who commented on the chips investigation largely signaled support for the president\\u2019s vision of deepening the US manufacturing base and expanding the American workforce. Yet most expressed concern over the potential consequences and urged making any levies that emerge as targeted as pos\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": "-0.0245", "answer_numeric": -0.024525, "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%) = -0.0335.", "metadata": {"var": -0.024525, "cvar": -0.033457, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250821_0356", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LQD"], "decision_date": "2025-08-21", "context_summary": "LQD: 60-day return history, mean=0.0006, std=0.0034.", "question": "Asset: LQD\nDaily returns (past 60 days): mean=0.0006, std=0.0034, min=-0.0061, max=0.0089\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LQD. Express as a decimal (e.g., -0.02).", "answer": "-0.0060", "answer_numeric": -0.005962, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0060 (i.e., on a bad day with 5% probability, the loss exceeds 0.60%). CVaR(95%) = -0.0060.", "metadata": {"var": -0.005962, "cvar": -0.006035, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250707_0358", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-07-07", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0001, std=0.0461.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0001, std=0.0461, min=-0.0876, max=0.1321\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0624", "answer_numeric": -0.062396, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0624 (i.e., on a bad day with 5% probability, the loss exceeds 6.24%). CVaR(95%) = -0.0769.", "metadata": {"var": -0.062396, "cvar": -0.076886, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250624_0361", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IYR"], "decision_date": "2025-06-24", "context_summary": "IYR: 60-day return history, mean=0.0000, std=0.0127.", "question": "Asset: IYR\nDaily returns (past 60 days): mean=0.0000, std=0.0127, 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": "-0.0270", "answer_numeric": -0.027045, "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%) = -0.0308.", "metadata": {"var": -0.027045, "cvar": -0.0308, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251016_0363", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-10-16", "context_summary": "XLV: 60-day return history, mean=0.0011, std=0.0098.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0011, std=0.0098, min=-0.0284, max=0.0244\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": "-0.0146", "answer_numeric": -0.014561, "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%) = -0.0201.", "metadata": {"var": -0.014561, "cvar": -0.020087, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20251211_0366", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2025-12-11", "context_summary": "MTUM: 60-day return history, mean=0.0002, std=0.0092.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0002, std=0.0092, min=-0.0240, max=0.0189\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-10-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-10-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-10-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-10-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-10-31 0000104169 2025-12-02 0000104169 2025-08-01 2025-10-31 0000104169 2024-08-01 2024-10-31 0000104169 2024-02-01 2024-10-31 0000104169 2025-10-31 0000104169 2025-01-31 0000104169 2024-10-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-30 0000104169 us-gaap:ParentMember 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-04-30 0000104169 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-05-01 2025-07-31 0000104169 us-gaap:ParentMember 2025-05-01 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-05-01 2025-07-31 0000104169 2025-05-01 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-05-01 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-31 0000104169 us-gaap:ParentMember 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-08-01 2025-10-31 0000104169 us-gaap:ParentMember 2025-08-01 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-08-01 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-08-01 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MTUM. Express as a decimal (e.g., -0.02).", "answer": "-0.0176", "answer_numeric": -0.01759, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0176 (i.e., on a bad day with 5% probability, the loss exceeds 1.76%). CVaR(95%) = -0.0226.", "metadata": {"var": -0.01759, "cvar": -0.022606, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250724_0369", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-07-24", "context_summary": "DOT-USD: 60-day return history, mean=-0.0011, std=0.0350.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0011, std=0.0350, min=-0.0949, max=0.0849\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0520", "answer_numeric": -0.052002, "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%) = -0.0751.", "metadata": {"var": -0.052002, "cvar": -0.075115, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250404_0372", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLI"], "decision_date": "2025-04-04", "context_summary": "XLI: 60-day return history, mean=-0.0004, std=0.0111.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=-0.0004, std=0.0111, min=-0.0336, max=0.0203\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-03] SMCI Stock Set to Transition from Micro to Mighty as Wall St. Analysts Eye 40% Upside Super Micro Computer (SMCI) might have the word \u201cmicro\u201d in its name, but make no mistake\u2014this Silicon Valley-based server and storage powerhouse has been delivering mighty growth over the past three years. With the boom in AI training, cloud data centers, and enterprise IT, Super Micro has surged 829%, alongside some of the hottest trends in technology. Discover the latest stocks recommended by top Wall Street analysts, all in one place with Analyst Top Stocks. Make smarter investments with weekly expert stock picks from the Smart Investor Newsletter. While the company\u2019s most explosive alpha years\u20142023 and 2024\u2014are now behind us, I believe the runway is far from finished. Based on projected earnings per share growth and only a slight expansion in the price-to-earnings ratio, I\u2019m targeting a 40% return from the stock over the next twelve months. Let\u2019s start with the obvious: Super Micro\u2019s growth has been anything but modest. The surge in artificial intelligence workloads and expansion in cloud infrastructure has created ideal conditions for the company to thrive. Management has been bold, too. They\u2019ve described the AI revolution as \u201cmuch more impactful than the Industrial Revolution,\u201d and they\u2019re positioning Super Micro accordingly. If that thesis holds true\u2014and I believe it does\u2014then the company is in a superb position to capitalize over the coming years. One specific area where Super Micro stands out is liquid-cooled server design. According to the company\u2019s CEO, roughly 30% of new data centers are expected to adopt direct liquid cooling over the next twelve months. That\u2019s significant\u2014and Super Micro is already a frontrunner in this space. According to Main Street Data, SMCI\u2019s revenues have grown as segment proportions have remained broadly consistent. Let\u2019s talk numbers. In FY2024, SMCI posted 110% year-over-year revenue growth. GAAP net income also surged, climbing 80% from the previous year. Looking further back, from FY2021 through FY2024, Super Micro pulled off a stunning 60% compound annual growth rate in revenue\u2014while only growing its operating expenses by 25%. The company is scaling with discipline and efficiency, an increasingly rare feat in today\u2019s hyper-growth tech landscape. We\u2019re already well into FY2025, with Q3 results expected in May. For the full year, management is guiding toward approximately $24 billion in revenue, representing about 60% year-over-year growth. They\u2019re also quite bullish about FY2026, setting expectations for $40 billion in annual revenue. That forecast may be optimistic, but the broader growth trajectory is undeniably strong\u2014and the valuation doesn\u2019t seem overstretched given the potential upside ahead. Currently, Super Micro stock is trading at ~$35 per share after a sharp pullback, meaning it\u2019s priced at less than its trailing twelve-month revenue\u2014a clear signal of value. But investor sentiment has understandably cooled. Th\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": "-0.0197", "answer_numeric": -0.019745, "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%) = -0.0255.", "metadata": {"var": -0.019745, "cvar": -0.025517, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20251001_0375", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-10-01", "context_summary": "USMV: 60-day return history, mean=0.0003, std=0.0052.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0003, std=0.0052, min=-0.0114, max=0.0124\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for USMV. Express as a decimal (e.g., -0.02).", "answer": "-0.0086", "answer_numeric": -0.008617, "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%) = -0.0098.", "metadata": {"var": -0.008617, "cvar": -0.009806, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20251128_0378", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-11-28", "context_summary": "XLY: 60-day return history, mean=0.0003, std=0.0124.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0003, std=0.0124, min=-0.0279, max=0.0261\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2025-11-19] nvda-20251026 0001045810 1/25 2026 Q3 FALSE 478 469 278 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:investment nvda:segment 0001045810 2025-01-27 2025-10-26 0001045810 2025-11-14 0001045810 2025-07-28 2025-10-26 0001045810 2024-07-29 2024-10-27 0001045810 2024-01-29 2024-10-27 0001045810 2025-10-26 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 2025-07-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-27 0001045810 us-gaap:RetainedEarningsMember 2025-07-27 0001045810 2025-07-27 0001045810 us-gaap:RetainedEarningsMember 2025-07-28 2025-10-26 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-28 2025-10-26 0001045810 us-gaap:CommonStockMember 2025-07-28 2025-10-26 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-28 2025-10-26 0001045810 us-gaap:CommonStockMember 2025-10-26 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-10-26 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-26 0001045810 us-gaap:RetainedEarningsMember 2025-10-26 0001045810 us-gaap:CommonStockMember 2024-07-28 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-07-28 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-28 0001045810 us-gaap:RetainedEarningsMember 2024-07-28 0001045810 2024-07-28 0001045810 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2025-01-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-10-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:CustomerOneMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerTwoMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerThreeMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerFourMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:Cust [...TRUNCATED...] President, Operations Adoption 9/9/2025 309,840 12/31/2026 Donald Robertson Vice President and Chief Accounting Officer Adoption 9/18/2025 138,042 * 12/31/2026 Ajay Puri Executive Vice President, Worldwide Field Operations Adoption 9/19/2025 1,000,000 6/24/2026 * Includes 38,042 shares from future vests of equity awards, and the actual number of shares to be sold will be net of shares withheld by the Company for taxes. 42 Item 6. Exhibits Exhibit No.  Exhibit Description 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 43 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 19, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 44\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": "-0.0229", "answer_numeric": -0.022866, "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%) = -0.0255.", "metadata": {"var": -0.022866, "cvar": -0.025517, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20250807_0381", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-08-07", "context_summary": "VLUE: 60-day return history, mean=0.0013, std=0.0089.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0013, std=0.0089, min=-0.0210, max=0.0281\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q CAT 2025-08-06] cat-20250630 0000018230 FALSE 12/31 2025 Q2 50 338 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cat:entity cat:group_president cat:segment 0000018230 2025-01-01 2025-06-30 0000018230 us-gaap:CommonStockMember 2025-01-01 2025-06-30 0000018230 cat:A5.3DebenturesDueSeptember152035Member 2025-01-01 2025-06-30 0000018230 2025-06-30 0000018230 cat:MachineryEnergyTransportationMember 2025-04-01 2025-06-30 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Exhibits 4.1 Form of 5.200% Senior Note due 2035 (incorporated by reference from Exhibit 4.1 to the Company’s Current Report on Form 8-K filed May 15, 2025) 4.2 Form of 5.500% Senior Note due 2055 (incorporated by reference from Exhibit 4.2 to the Company’s Current Report on Form 8-K filed May 15, 2025) 10.1 First Amended and Restated Aircraft Time Sharing Agreement, dated as of April 28, 2025. 10.2 Aircraft Time Sharing Agreement, dated as of May 7, 2025. 31.1 Certification of Chief Executive Officer of Caterpillar Inc., as required pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer of Caterpillar Inc., as required pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32 Certification of Chief Executive Officer of Caterpillar Inc. and Chief Financial Officer of Caterpillar Inc., as required pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS Inline XBRL Instance Document (the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document) 101.SCH   Inline XBRL Taxonomy Extension Schema Document 101.CAL   Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF   Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB   Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE   Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive File (embedded within the Inline XBRL document and included in Exhibit 101) The agreements and other documents filed as exhibits to this report are not intended to provide factual information or other disclosure other than with respect to the terms of the agreements or other documents themselves, and you should not rely on them for that purpose. In particular, any representations and warranties made by us in these agreements or other documents were made solely within the specific context of the relevant agreement or document and may not describe the actual state of affairs as of the date they were made or at any other time. 80 Table of Contents SIGNATURES   Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       CATERPILLAR INC.               August 6, 2025 /s/ Joseph E. Creed Chief Executive Officer   Joseph E. Creed         August 6, 2025 /s/ Andrew R.J. Bonfield Chief Financial Officer   Andrew R.J. Bonfield               August 6, 2025 /s/ Derek Owens Chief Legal Officer and General Counsel   Derek Owens             August 6, 2025 /s/ William E. Schaupp Vice President and Chief Accounting Officer   William E. Schaupp   81\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VLUE. Express as a decimal (e.g., -0.02).", "answer": "-0.0120", "answer_numeric": -0.012013, "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%). 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ITEM 16. FORM 10-K SUMMARY None. SIGNATURES Under the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, this report was signed on behalf of the Registrant by the authorized person named below. Pfizer Inc. Dated: February 27, 2025 By: /S/    MARGARET M. MADDEN Margaret M. Madden Senior Vice President and Corporate Secretary Chief Governance Counsel We, the undersigned directors and officers of Pfizer Inc., hereby severally constitute Douglas M. Lankler and Margaret M. Madden, and each of them singly, our true and lawful attorneys with full power to them and each of them to sign for us, in our names in the capacities indicated below, any and all amendments to this Annual Report on Form 10-K filed with the Securities and Exchange Commission. Under the requirements of the Securities Exchange Act of 1934, this report was signed by the following persons on behalf of the Registrant and in the capacities and on the date indicated . Pfizer Inc. 2024 Form 10-K 113 Signature Title Date /S/    ALBERT BOURLA Albert Bourla Chairman, Chief Executive Officer and Director (Principal Executive Officer) February 27, 2025 /S/    DAVID M. DENTON David M. Denton Chief Financial Officer, Executive Vice President (Principal Financial Officer) February 27, 2025 /S/    JENNIFER B. DAMICO Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer) February 27, 2025 /S/    RONALD E. BLAYLOCK Ronald E. Blaylock Director February 27, 2025 /S/    MORTIMER J. BUCKLEY Mortimer J. Buckley Director February 27, 2025 /S/    SUSAN DESMOND-HELLMANN Susan Desmond-Hellmann Director February 27, 2025 /S/    JOSEPH J. ECHEVARRIA Joseph J. Echevarria Director February 27, 2025 /S/    SCOTT GOTTLIEB Scott Gottlieb Director February 27, 2025 /S/    HELEN H. HOBBS Helen H. Hobbs Director February 27, 2025 /S/    SUSAN HOCKFIELD Susan Hockfield Director February 27, 2025 /S/    DAN R. LITTMAN Dan R. Littman Director February 27, 2025 /S/    SHANTANU NARAYEN Shantanu Narayen Director February 27, 2025 /S/    SUZANNE NORA JOHNSON Suzanne Nora Johnson Director February 27, 2025 /S/    JAMES QUINCEY James Quincey Director February 27, 2025 /S/    JAMES C. SMITH James C. Smith Director February 27, 2025 /S/    CYRUS TARAPOREVALA Cyrus Taraporevala Director February 27, 2025 Pfizer Inc. 2024 Form 10-K 114\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": "-0.0120", "answer_numeric": -0.011982, "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%) = -0.0213.", "metadata": {"var": -0.011982, "cvar": -0.021342, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250708_0386", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-07-08", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0025, std=0.0427.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0025, std=0.0427, min=-0.0876, max=0.1133\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0624", "answer_numeric": -0.062396, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0624 (i.e., on a bad day with 5% probability, the loss exceeds 6.24%). CVaR(95%) = -0.0769.", "metadata": {"var": -0.062396, "cvar": -0.076886, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250729_0388", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-07-29", "context_summary": "ADA-USD: 60-day return history, mean=0.0022, std=0.0367.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0022, std=0.0367, min=-0.0960, max=0.0853\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0496", "answer_numeric": -0.049567, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0496 (i.e., on a bad day with 5% probability, the loss exceeds 4.96%). CVaR(95%) = -0.0686.", "metadata": {"var": -0.049567, "cvar": -0.068649, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250409_0390", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-04-09", "context_summary": "BNB-USD: 60-day return history, mean=-0.0002, std=0.0311.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0002, std=0.0311, min=-0.0767, max=0.0863\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0649", "answer_numeric": -0.064917, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0649 (i.e., on a bad day with 5% probability, the loss exceeds 6.49%). CVaR(95%) = -0.0695.", "metadata": {"var": -0.064917, "cvar": -0.069471, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251007_0393", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BIL"], "decision_date": "2025-10-07", "context_summary": "BIL: 60-day return history, mean=0.0002, std=0.0001.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=0.0002, std=0.0001, min=0.0000, max=0.0004\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BIL. Express as a decimal (e.g., -0.02).", "answer": "0.0000", "answer_numeric": 0.0, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = 0.0000.", "metadata": {"var": 0.0, "cvar": 0.0, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251127_0396", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2025-11-27", "context_summary": "MTUM: 60-day return history, mean=0.0004, std=0.0096.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0004, std=0.0096, min=-0.0240, max=0.0236\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2025-11-19] nvda-20251026 0001045810 1/25 2026 Q3 FALSE 478 469 278 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:investment nvda:segment 0001045810 2025-01-27 2025-10-26 0001045810 2025-11-14 0001045810 2025-07-28 2025-10-26 0001045810 2024-07-29 2024-10-27 0001045810 2024-01-29 2024-10-27 0001045810 2025-10-26 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 2025-07-27 0001045810 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2025-01-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-10-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:CustomerOneMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerTwoMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerThreeMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerFourMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:Cust [...TRUNCATED...] President, Operations Adoption 9/9/2025 309,840 12/31/2026 Donald Robertson Vice President and Chief Accounting Officer Adoption 9/18/2025 138,042 * 12/31/2026 Ajay Puri Executive Vice President, Worldwide Field Operations Adoption 9/19/2025 1,000,000 6/24/2026 * Includes 38,042 shares from future vests of equity awards, and the actual number of shares to be sold will be net of shares withheld by the Company for taxes. 42 Item 6. Exhibits Exhibit No.  Exhibit Description 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 43 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 19, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 44\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": "-0.0176", "answer_numeric": -0.01759, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0176 (i.e., on a bad day with 5% probability, the loss exceeds 1.76%). CVaR(95%) = -0.0226.", "metadata": {"var": -0.01759, "cvar": -0.022606, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20250128_0398", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2025-01-28", "context_summary": "QQQ: 60-day return history, mean=0.0006, std=0.0124.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0006, std=0.0124, min=-0.0367, max=0.0268\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q PG 2025-01-22] pg-20241231 0000080424 6/30 2025 Q2 false http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent 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2024-12-31 0000080424 us-gaap:CommonStockMember 2024-06-30 0000080424 us-gaap:PreferredStockMember 2024-06-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2024-06-30 0000080424 pg:ReserveforESOPDebtRetirementMember 2024-06-30 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-06-30 0000080424 us-gaap:TreasuryStockCommonMember 2024-06-30 0000080424 us-gaap:RetainedEarningsMember 2024-06-30 0000080424 us-gaap:NoncontrollingInterestMember 2024-06-30 0000080424 us-gaap:RetainedEarningsMember 2024-07-01 2024-12-31 0000080424 us-gaap:NoncontrollingInterestMember 2024-07-01 2024-12-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-01 2024-12-31 0000080424 us-gaap:CommonStockMember 2024-07-01 2024-12-31 0000080424 us-gaap:TreasuryStockCommonMember 2024-07-01 2024-12-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2024-07-01 2024-12-31 0000080424 us-gaap:PreferredStockMember 2024-07-01 2024-12-31 0000080424 pg:ReserveforESOPDebtRetirementMember 2024-07-01 2024-12-31 0000080424 us-gaap:CommonStockMember 2023-09-30 0000080424 us-gaap:PreferredStockMember 2023-09-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-09-30 0000080424 pg:ReserveforESOPDebtRetirementMember 2023-09-30 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-09-30 0000080424 us-gaap:TreasuryStockCommonMember 2023-09-30 0000080424 us-gaap:RetainedEarningsMember 2023-09-30 0000080424 us-gaap:NoncontrollingInterestMember 2023-09-30 0000080424 2023-09-30 0000080424 us-gaap:RetainedEarningsMember 2023-10-01 2023-12-31 0000080424 us-gaap:NoncontrollingInterestMember 2023-10-01 2023-12-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-10-01 2023-12-31 0000080424 us-gaap:CommonStockMember 2023-10-01 2023-12-31 0000080424 us-gaap:TreasuryStockCommonMember 2023-10-01 2023-12-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-10-01 2023-12-31 0000080424 us-gaap:PreferredStockMember 2023-10-01 2023-12-31 0000080424 us-gaap:CommonStockMember 2023-12-31 0000080424 us-gaap:PreferredStockMember 2023-12-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-12-31 0000080424 pg:ReserveforESOPDebtRetirementMember 2023-12-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-12-31 0000080424 us-gaap:TreasuryStockCommonMember 2023-12-31 0000080424 us-gaap:RetainedEarningsMember 2023-12-31 0000080424 us-gaap:NoncontrollingInterestMember 2023-12-31 0000080424 2023-12-31 0000080424 us-gaap:CommonStockMember 2023-06-30 0000080424 us-gaap:PreferredStockMember 2023-06-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-06-30 0000080424 pg:R [...TRUNCATED...] 7 billion in fiscal year 2025, notwithstanding any purchases under the Company's compensation and benefit plans. Purchases may be made in the open market and/or private transactions and purchases may be increased, decreased or discontinued at any time without prior notice. The share repurchases are authorized pursuant to a resolution issued by the Company's Board of Directors and are expected to be financed by a combination of operating cash flows and issuance of debt.      Item 5. Other Information During the three months ended December 31, 2024, none of our directors or officers adopted or terminated a \"Rule 10b5-1 trading arrangement\" or \"non-Rule 10b5-1 trading arrangement\" as defined in Item 408 of Regulation S-K. 30 The Procter & Gamble Company Item 6. Exhibits 3.1 Amended Articles of Incorporation (as amended by shareholders at the annual meeting on October 11, 2011 and consolidated by the Board of Directors on April 8, 2016) (Incorporated by reference to Exhibit (3-1) of the Company's Form 10-K for the year ended June 30, 2016) 3.2 Regulations (as approved by the Board of Directors on December 13, 2022, pursuant to authority granted by shareholders at the annual meeting on October 13, 2009) (Incorporated by reference to Exhibit (3-2) of the Company’s Current Report on Form 8-K filed December 13, 2022) 4.1 Indenture, dated as of September 3, 2009, between the Company and Deutsche Bank Trust Company Americas, as Trustee (Incorporated by reference to Exhibit (4-1) of the Company's Annual Report on Form 10-K for the year ended June 30, 2015) 31.1 Rule 13a-14(a)/15d-14(a) Certification – Chief Executive Officer + 31.2 Rule 13a-14(a)/15d-14(a) Certification – Chief Financial Officer + 32.1 Section 1350 Certifications – Chief Executive Officer + 32.2 Section 1350 Certifications – Chief Financial Officer + 101.SCH (1) Inline XBRL Taxonomy Extension Schema Document 101.CAL (1) Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF (1) Inline XBRL Taxonomy Definition Linkbase Document 101.LAB (1) Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE (1) Inline XBRL Taxonomy Extension Presentation Linkbase Document 104  Cover Page Interactive Data File (formatted in Inline XBRL and contained in Exhibit 101) + Filed herewith (1) Pursuant to Rule 406T of Regulation S-T, this information is furnished and not filed for purposes of Sections 11 or 12 of the Securities Act of 1933 and Section 18 of the Securities Exchange Act of 1934, and otherwise is not subject to liability under these sections. Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this Report to be signed on its behalf by the undersigned thereunto duly authorized. THE PROCTER & GAMBLE COMPANY January 22, 2025 /s/ MATTHEW W. JANZARUK Date (Matthew W. Janzaruk) Senior Vice President - Chief Accounting Officer (Principal Accounting Officer)\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for QQQ. Express as a decimal (e.g., -0.02).", "answer": "-0.0242", "answer_numeric": -0.024187, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0242 (i.e., on a bad day with 5% probability, the loss exceeds 2.42%). CVaR(95%) = -0.0306.", "metadata": {"var": -0.024187, "cvar": -0.030619, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9044}} +{"id": "T2_all_20251107_0401", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2025-11-07", "context_summary": "EWJ: 60-day return history, mean=0.0009, std=0.0099.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0009, std=0.0099, min=-0.0325, max=0.0222\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CVX 2025-11-06] cvx-20250930 0000093410 12/31 2025 Q3 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cvx:segment cvx:lawsuit cvx:state cvx:tribe cvx:parish 0000093410 2025-01-01 2025-09-30 0000093410 2025-09-30 0000093410 2025-07-01 2025-09-30 0000093410 2024-07-01 2024-09-30 0000093410 2024-01-01 2024-09-30 0000093410 2024-12-31 0000093410 2023-12-31 0000093410 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-06-30 0000093410 us-gaap:RetainedEarningsMember 2024-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-06-30 0000093410 us-gaap:ParentMember 2024-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-06-30 0000093410 2024-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-07-01 2024-09-30 0000093410 us-gaap:ParentMember 2024-07-01 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 2024-07-01 2024-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-07-01 2024-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-01 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-07-01 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 2024-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-09-30 0000093410 us-gaap:ParentMember 2024-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-06-30 0000093410 us-gaap:RetainedEarningsMember 2025-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-06-30 0000093410 us-gaap:ParentMember 2025-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-06-30 0000093410 2025-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-07-01 2025-09-30 0000093410 us-gaap:ParentMember 2025-07-01 2025-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-07-01 2025-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-07-01 2025-09-30 0000093410 us-gaap:RetainedEarningsMember 2025-07-01 2025-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-01 2025-09-30 0000093410 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0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-01 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-01-01 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-12-31 0000093410 us-gaap:RetainedEarningsMember 2024-12-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-12-31 0000093410 us-gaap:TreasuryStockCommonMember 2024-12-31 0000093410 us-gaap:ParentMember 2024-12-31 0000093410 us-gaap:NoncontrollingInterestMember 2024-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-01-01 2025-09-30 0000093410 us-gaap:ParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-01-01 2025-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-01-01 2025-09-30 0000093410 us-gaap:RetainedEarningsMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-09-30 0000093410 [...TRUNCATED...] 160; $154.38 16,620,000   (1) Includes common shares repurchased from participants in the company’s executive compensation plans for personal income tax withholdings. (2) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections During the three months ended September 30, 2025, none of our directors or executive officers adopted, modified or terminated a Rule 10b5-1 trading arrangement or a non-Rule 10b5-1 trading arrangement, as such terms are defined in Item 408 of Regulation S-K. 47 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 4.1 Fourth Supplemental Indenture, dated as of August 13, 2025, among Chevron U.S.A. Inc., Chevron Corporation, as guarantor, and Deutsche Bank Trust Company Americas, as trustee, filed as Exhibit 4. 2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 4.2 Forms of 3.950% Notes Due 2027, 4.050% Notes Due 2028, Floating Rate Notes Due 2028-B, 4.300% Notes Due 2030, Floating Rate Notes due 2030, 4.500% Notes Due 2032 and 4.850% Notes Due 2035, contained in Exhibit 4.2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 10.1+* Aircraft Time-Sharing Agreement, dated as of February 24, 2015, between Hess Corporation and John B. Hess. 10.2* Transition Services Agreement, dated as of July 14, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.3* Amendment One to Transition Services Agreement, dated as of August 27, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.4* Membership Interest Purchase Agreement, dated as of September 10, 2025, between Hess Corporation and JBH Ventures, LLC . 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ + Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 48 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 6, 2025 49\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": "-0.0122", "answer_numeric": -0.012227, "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%) = -0.0204.", "metadata": {"var": -0.012227, "cvar": -0.020395, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250123_0404", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQI"], "decision_date": "2025-01-23", "context_summary": "VNQI: 60-day return history, mean=-0.0010, std=0.0084.", "question": "Asset: VNQI\nDaily returns (past 60 days): mean=-0.0010, std=0.0084, min=-0.0241, max=0.0161\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": "-0.0153", "answer_numeric": -0.015325, "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%) = -0.0201.", "metadata": {"var": -0.015325, "cvar": -0.020069, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250416_0406", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2025-04-16", "context_summary": "XLRE: 60-day return history, mean=-0.0007, std=0.0135.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=-0.0007, std=0.0135, min=-0.0375, max=0.0314\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-15] Will PRGS' AI-Powered Upgrades to Sitefinity Drive the Stock Upward? Progress Software PRGS unveiled AI-powered upgrades to its Sitefinity content management platform, aimed at accelerating content creation and enhancing digital customer engagement. The new Sitefinity 15.3 release integrates embedded Generative AI (Gen AI) services, enabling marketers to summarize content, personalize messages, and generate tags within the platform. PRGS features AI-enhanced media search, allowing users to find visuals using natural language, and built-in Azure AI translation for efficient multilingual content management. Sitefinity now offers in-line AI-based content optimization and advanced BI system integration, empowering organizations to streamline workflows, refine digital assets, and apply custom AI models for deeper insights and improved marketing performance. PRGS\u2019 Strong Portfolio Boosts Prospects PRGS shares have plunged 11.8% year to date, outperforming the broader Zacks Computer & Technology sector\u2019s decline of 14.5%. However, since reporting first-quarter fiscal 2025 earnings results on March 31, Progress Software shares jumped 11.5%. Progress Software Corporation price-consensus-chart | Progress Software Corporation Quote In the fiscal first quarter, annualized recurring revenues (ARR) of $836 million surged 48% year over year on a constant currency basis. Growth was driven by strong performance in ShareFile, alongside consistent contributions from core products, including OpenEdge, Sitefinity, DevTools, Kemp LoadMaster, and WhatsUp Gold. Revenues for the reported quarter totaled $238 million, landing at the high end of guidance and up 29% year over year. AI remains a core strategic focus. Progress Software is embedding AI across its product portfolio to streamline workflows, automate experiences, and enhance customer value. Early this month, Progress Software announced purpose-built AI in ShareFile to enhance efficiency and strengthen data security, driving existing document-centric workflows. AI Arms Race: PRGS Faces Stiff Competition Progress Software\u2019s AI push is aligned with broader industry trends, as peers aggressively expand their agentic AI ecosystems. PRGS has also outperformed its industry peers that are accelerating AI adoption, including Oracle ORCL and Adobe ADBE. Year to date, shares of Oracle and Adobe have plunged 19.5% and 21.3%, respectively. Oracle recently deepened its strategic collaboration with NVIDIA to accelerate agentic AI deployment. Through native integration of NVIDIA AI Enterprise software and NIM microservices into Oracle Cloud Infrastructure (\u201cOCI\u201d), users can access over 160 AI tools and deploy advanced reasoning models, such as Llama Nemotron, directly from the OCI Console. This initiative positions Oracle as a full-stack AI provider, offering flexible, scalable infrastructure for enterprise-grade AI workloads. Adobe, in partnership with Microsoft MSFT, is enhancing AI accessibility through Microsoft 365 Copilot.\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": "-0.0252", "answer_numeric": -0.025172, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0252 (i.e., on a bad day with 5% probability, the loss exceeds 2.52%). CVaR(95%) = -0.0319.", "metadata": {"var": -0.025172, "cvar": -0.031906, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250102_0409", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-01-02", "context_summary": "VTI: 60-day return history, mean=0.0004, std=0.0083.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0004, std=0.0083, min=-0.0314, max=0.0264\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 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The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VTI. Express as a decimal (e.g., -0.02).", "answer": "-0.0112", "answer_numeric": -0.011196, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0112 (i.e., on a bad day with 5% probability, the loss exceeds 1.12%). CVaR(95%) = -0.0210.", "metadata": {"var": -0.011196, "cvar": -0.021004, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250305_0412", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2025-03-05", "context_summary": "EMB: 60-day return history, mean=0.0002, std=0.0041.", "question": "Asset: EMB\nDaily returns (past 60 days): mean=0.0002, std=0.0041, min=-0.0150, max=0.0115\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": "-0.0051", "answer_numeric": -0.005137, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0051 (i.e., on a bad day with 5% probability, the loss exceeds 0.51%). CVaR(95%) = -0.0085.", "metadata": {"var": -0.005137, "cvar": -0.008533, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250220_0415", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-02-20", "context_summary": "SOL-USD: 60-day return history, mean=-0.0002, std=0.0457.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0002, std=0.0457, min=-0.0771, max=0.1924\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0595", "answer_numeric": -0.059526, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0595 (i.e., on a bad day with 5% probability, the loss exceeds 5.95%). CVaR(95%) = -0.0720.", "metadata": {"var": -0.059526, "cvar": -0.071974, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250213_0417", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MORT"], "decision_date": "2025-02-13", "context_summary": "MORT: 60-day return history, mean=0.0008, std=0.0104.", "question": "Asset: MORT\nDaily returns (past 60 days): mean=0.0008, std=0.0104, min=-0.0330, max=0.0203\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": "-0.0132", "answer_numeric": -0.013232, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0132 (i.e., on a bad day with 5% probability, the loss exceeds 1.32%). CVaR(95%) = -0.0229.", "metadata": {"var": -0.013232, "cvar": -0.022897, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251023_0419", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-10-23", "context_summary": "BNB-USD: 60-day return history, mean=0.0041, std=0.0399.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0041, std=0.0399, min=-0.1186, max=0.1459\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0638", "answer_numeric": -0.063759, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0638 (i.e., on a bad day with 5% probability, the loss exceeds 6.38%). CVaR(95%) = -0.0850.", "metadata": {"var": -0.063759, "cvar": -0.084959, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251013_0422", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-10-13", "context_summary": "SOL-USD: 60-day return history, mean=0.0008, std=0.0470.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0008, std=0.0470, min=-0.1463, max=0.1130\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0691", "answer_numeric": -0.069079, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0691 (i.e., on a bad day with 5% probability, the loss exceeds 6.91%). CVaR(95%) = -0.1093.", "metadata": {"var": -0.069079, "cvar": -0.109337, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250604_0425", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2025-06-04", "context_summary": "FXI: 60-day return history, mean=0.0003, std=0.0181.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0003, std=0.0181, min=-0.0438, max=0.0476\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-03] [\"Nvidia\\u2019s $1 Trillion Rally Has Traders Primed to Ramp Back Up (Bloomberg) -- Nvidia Corp. shares have staged a $1 trillion rebound in two months \\u2014 and investors are betting the rally has further to go as fears about the chipmaker give way to optimism. Most Read from Bloomberg Where the Wild Children\\u2019s Museums Are Billionaire Steve Cohen Wants NY to Expand Taxpayer-Backed Ferry At London\\u2019s New Design Museum, Visitors Get Hands-On Access LA City Council Passes Budget That Trims Police, Fire Spending The Global Struggle to Build Safer Cars Last week\\u2019s earnings report assuaged some key investor concerns: particularly whether US restrictions on the sales of advanced semiconductors in China would derail Nvidia\\u2019s rapid revenue growth as well as the outlook for artificial intelligence spending, and the firm\\u2019s ability to expand supply of its newest Blackwell chips. \\u201cThose questions have been answered in the positive for Nvidia,\\u201d said Thomas Martin, senior portfolio manager at Globalt Investments. \\u201cIt\\u2019s time to ramp back up your ownership.\\u201d After soaring for two and a half years amid insatiable demand for its chips used in AI computing, Nvidia shares tumbled in the first few months of 2025 on concerns about President Donald Trump\\u2019s trade policies and a potential pullback in spending by its biggest customers. Nvidia rose 0.9% on Tuesday, and since an April low, the stock has rallied more than 45%, pushing Nvidia\\u2019s market value to $3.4 trillion. That\\u2019s just shy of Microsoft Corp., the world\\u2019s most valuable company. Nvidia shares remain 7% below a record high in January. Despite the big advance, Nvidia trades at roughly 29 times profits projected over the next 12 months, well below the average over the past decade at 34 times. By contrast, the Nasdaq 100 is priced at 26 times despite Wall Street estimates calling for revenue growth this year that\\u2019s a fraction of Nvidia\\u2019s. The stock\\u2019s PEG ratio \\u2014 a measure of valuation relative to growth \\u2014 is under 0.9, by far the lowest among the Magnificent Seven, which also includes Apple Inc., Amazon.com Inc., Alphabet Inc., Tesla Inc. and Meta Platforms Inc. Of course, Nvidia is still exposed to US tariffs given its chips are manufactured overseas and could be hurt by a deterioration in trade relations with China, a country that accounted for 13% of revenue in the first quarter. However, purchase agreements with governments in the Middle East are seen as offsetting some lost sales and Nvidia\\u2019s product pipeline is expected to keep competitors at bay. Microsoft, Meta, Alphabet, and Amazon, which together comprise more than 40% of Nvidia\\u2019s revenue, continue to invest aggressively in AI infrastructure. Capital expenditures for the four companies are projected to reach roughly $330 billion in 2026, up 6% from estimated spending this year, according to the average of analyst estimates compiled by Bloomberg. Amazo\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": "-0.0272", "answer_numeric": -0.027249, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0272 (i.e., on a bad day with 5% probability, the loss exceeds 2.72%). CVaR(95%) = -0.0389.", "metadata": {"var": -0.027249, "cvar": -0.038932, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250122_0428", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-01-22", "context_summary": "BTC-USD: 60-day return history, mean=0.0015, std=0.0245.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0015, std=0.0245, min=-0.0575, max=0.0472\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0382", "answer_numeric": -0.038196, "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%) = -0.0527.", "metadata": {"var": -0.038196, "cvar": -0.052692, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250806_0431", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["FXI"], "decision_date": "2025-08-06", "context_summary": "FXI: 60-day return history, mean=0.0014, std=0.0115.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0014, std=0.0115, min=-0.0184, max=0.0342\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q JPM 2025-08-05] jpm-20250630 0000019617 FALSE 2025 Q2 12/31 true false http://fasb.org/us-gaap/2025#NoninterestIncomeOther http://fasb.org/us-gaap/2025#NoninterestIncomeOther http://fasb.org/us-gaap/2025#NoninterestIncomeOther http://fasb.org/us-gaap/2025#NoninterestIncomeOther xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:USD utr:bbl iso4217:USD utr:MMBTU jpm:loan_segment jpm:loan_payment jpm:fund jpm:segment 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The Firm did not charge a fee for these transactions. The payments were for the renewal of travel documentation for the client’s three minor children and were therefore exempt transactions pursuant to 31 C.F.R. 560.219(d). The Firm does not intend to engage in such transactions in the future. 202 Item 6.    Exhibits. Exhibit No. Description of Exhibit 15 Letter re: Unaudited Interim Financial Information. (a) 22 Subsidiary Guarantors and Issuers of Guaranteed Securities . (a) 31.1 Certification. (a) 31.2 Certification. (a) 32 Certification Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002. (b) 101.INS The instance document does not appear in the interactive data file because its XBRL tags are embedded within the Inline XBRL document. (c) 101.SCH XBRL Taxonomy Extension Schema Document. (a) 101.CAL XBRL Taxonomy Extension Calculation Linkbase Document. (a) 101.DEF XBRL Taxonomy Extension Definition Linkbase Document. (a) 101.LAB XBRL Taxonomy Extension Label Linkbase Document. (a) 101.PRE XBRL Taxonomy Extension Presentation Linkbase Document. (a) 104 Cover Page Interactive Data File (embedded within the Inline XBRL document and included in Exhibit 101). (a) Filed herewith. (b) Furnished herewith. This exhibit shall not be deemed “filed” for purposes of Section 18 of the Securities Exchange Act of 1934, or otherwise subject to the liability of that Section. Such exhibit shall not be deemed incorporated into any filing under the Securities Act of 1933 or the Securities Exchange Act of 1934. (c) Pursuant to Rule 405 of Regulation S-T, includes the following financial information included in the Firm’s Quarterly Report on Form 10-Q for the quarterly period ended June 30, 2025, formatted in XBRL (eXtensible Business Reporting Language) interactive data files: (i) the Consolidated statements of income (unaudited) for the three and six months ended June 30, 2025 and 2024, (ii) the Consolidated statements of comprehensive income (unaudited) for the three and six months ended June 30, 2025 and 2024, (iii) the Consolidated balance sheets (unaudited) as of June 30, 2025 and December 31, 2024, (iv) the Consolidated statements of changes in stockholders’ equity (unaudited) for the three and six months ended June 30, 2025 and 2024, (v) the Consolidated statements of cash flows (unaudited) for the six months ended June 30, 2025 and 2024, and (vi) the Notes to Consolidated Financial Statements (unaudited). 203 SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. JPMorgan Chase & Co. (Registrant) By: /s/ Elena Korablina Elena Korablina Managing Director and Firmwide Controller (Principal Accounting Officer) Date: August 5, 2025 204\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": "-0.0156", "answer_numeric": -0.015587, "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%) = -0.0175.", "metadata": {"var": -0.015587, "cvar": -0.017468, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250901_0434", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-09-01", "context_summary": "BTC-USD: 60-day return history, mean=0.0000, std=0.0162.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0000, std=0.0162, min=-0.0404, max=0.0419\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0294", "answer_numeric": -0.029388, "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%) = -0.0355.", "metadata": {"var": -0.029388, "cvar": -0.035524, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250929_0437", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-09-29", "context_summary": "ETH-USD: 60-day return history, mean=0.0021, std=0.0393.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0021, std=0.0393, min=-0.0851, max=0.1440\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0558", "answer_numeric": -0.055842, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0558 (i.e., on a bad day with 5% probability, the loss exceeds 5.58%). CVaR(95%) = -0.0700.", "metadata": {"var": -0.055842, "cvar": -0.07003, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250502_0438", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-05-02", "context_summary": "DOT-USD: 60-day return history, mean=-0.0029, std=0.0387.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0029, std=0.0387, min=-0.1391, max=0.0793\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0640", "answer_numeric": -0.063973, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0640 (i.e., on a bad day with 5% probability, the loss exceeds 6.40%). CVaR(95%) = -0.0950.", "metadata": {"var": -0.063973, "cvar": -0.095047, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250509_0441", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-05-09", "context_summary": "XRP-USD: 60-day return history, mean=0.0022, std=0.0411.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0022, std=0.0411, min=-0.1053, max=0.1433\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0544", "answer_numeric": -0.054378, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0544 (i.e., on a bad day with 5% probability, the loss exceeds 5.44%). CVaR(95%) = -0.0724.", "metadata": {"var": -0.054378, "cvar": -0.072396, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251114_0444", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-11-14", "context_summary": "BTC-USD: 60-day return history, mean=-0.0022, std=0.0208.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0022, std=0.0208, min=-0.0698, max=0.0403\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0370", "answer_numeric": -0.037025, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0370 (i.e., on a bad day with 5% probability, the loss exceeds 3.70%). CVaR(95%) = -0.0514.", "metadata": {"var": -0.037025, "cvar": -0.051351, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250312_0449", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DBA"], "decision_date": "2025-03-12", "context_summary": "DBA: 60-day return history, mean=-0.0000, std=0.0088.", "question": "Asset: DBA\nDaily returns (past 60 days): mean=-0.0000, std=0.0088, min=-0.0189, max=0.0162\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": "-0.0153", "answer_numeric": -0.015307, "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%) = -0.0178.", "metadata": {"var": -0.015307, "cvar": -0.017817, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250722_0452", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2025-07-22", "context_summary": "QQQ: 60-day return history, mean=0.0035, std=0.0091.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0035, std=0.0091, min=-0.0140, max=0.0340\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-21] [\"Crypto Whales Drive $4 Trillion Market Revival on Policy Optimism (Bloomberg) -- A relentless wave of optimism is sweeping the nearly $4 trillion crypto market, driven by a frenzy of Washington policy moves accelerating its assimilation into regulated finance. The passage of a landmark stablecoin law and broader legislative momentum have injected new legitimacy into the sector, lifting prices and rekindling risk appetite across digital assets. Most Read from Bloomberg Why the Federal Reserve\\u2019s Building Renovation Costs $2.5 Billion Milan Corruption Probe Casts Shadow Over Property Boom How San Jose\\u2019s Mayor Is Working to Build an AI Capital Signs of retail re-engagement are resurfacing. Coinbase\\u2019s app surged to fifth place in Apple\\u2019s Finance category, up from 25th a month earlier, according to data tracker Sensor Tower. Google searches for \\u201cBitcoin\\u201d are climbing. Telegram groups and Discord forums saw spirited activity during Washington\\u2019s \\u201cCrypto Week,\\u201d a highly choreographed policy blitz that culminated in President Donald Trump signing the first major US stablecoin framework into law. That spike in visibility, however, belies a more complex picture of who\\u2019s actually driving flows. While consumer interest is returning, the rally\\u2019s architecture is distinctly institutional. Large private holders \\u2014 those controlling 10,000 Bitcoin or more \\u2014 acquired roughly 47,000 tokens ahead of Bitcoin\\u2019s all-time high of about $123,000 on July 14, 10x Research data show. Since then, these substantial holders have begun to unwind positions, contributing to a pullback to around $118,600. Much of the re-engagement started about a month ago, after stablecoin issuer Circle Internet Group Inc.\\u2019s blockbuster June initial public offering, according to Chris Rhine, head of liquid active strategies at Galaxy Digital. \\u201cIt\\u2019s encouraged all investors to get re-engaged\\u2014 small retail to large institutions,\\u201d Rhine said. \\u201cWe have institutions calling us now, asking how to position around stablecoins. The sense of urgency is there.\\u201d That urgency, however, is not translating into core retail metrics yet \\u2014 at least as it comes to quarterly results. Coinbase Global Inc., which reports on July 31, likely saw its second-quarter trading volumes fall 44% from the previous quarter and 3% year-on-year, according to Oppenheimer & Co. Wallet app downloads for the exchange\\u2019s recently re-named other main app, Coinbase Wallet, dropped 51% quarter-on-quarter, with similar declines observed across other major exchanges, according to Sensor Tower. Much of the speculative attention once directed at tokens has shifted elsewhere. Analysts note retail investors have pivoted towards AI-linked equities and crypto-adjacent names such as Strategy, where volatility and narrative appeal remain high. Some retail participants have exited the market entirely, citing macroeconomic concerns and \\u2\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": "-0.0094", "answer_numeric": -0.009368, "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%) = -0.0121.", "metadata": {"var": -0.009368, "cvar": -0.012143, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20251125_0455", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-11-25", "context_summary": "XRP-USD: 60-day return history, mean=-0.0026, std=0.0409.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0026, std=0.0409, min=-0.1591, max=0.0878\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0535", "answer_numeric": -0.053495, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0535 (i.e., on a bad day with 5% probability, the loss exceeds 5.35%). CVaR(95%) = -0.1011.", "metadata": {"var": -0.053495, "cvar": -0.101097, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251119_0458", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2025-11-19", "context_summary": "QQQ: 60-day return history, mean=0.0008, std=0.0101.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0008, std=0.0101, min=-0.0353, max=0.0219\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CVX 2025-11-06] cvx-20250930 0000093410 12/31 2025 Q3 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cvx:segment cvx:lawsuit cvx:state cvx:tribe cvx:parish 0000093410 2025-01-01 2025-09-30 0000093410 2025-09-30 0000093410 2025-07-01 2025-09-30 0000093410 2024-07-01 2024-09-30 0000093410 2024-01-01 2024-09-30 0000093410 2024-12-31 0000093410 2023-12-31 0000093410 2024-09-30 0000093410 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2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-09-30 0000093410 [...TRUNCATED...] 160; $154.38 16,620,000   (1) Includes common shares repurchased from participants in the company’s executive compensation plans for personal income tax withholdings. (2) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections During the three months ended September 30, 2025, none of our directors or executive officers adopted, modified or terminated a Rule 10b5-1 trading arrangement or a non-Rule 10b5-1 trading arrangement, as such terms are defined in Item 408 of Regulation S-K. 47 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 4.1 Fourth Supplemental Indenture, dated as of August 13, 2025, among Chevron U.S.A. Inc., Chevron Corporation, as guarantor, and Deutsche Bank Trust Company Americas, as trustee, filed as Exhibit 4. 2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 4.2 Forms of 3.950% Notes Due 2027, 4.050% Notes Due 2028, Floating Rate Notes Due 2028-B, 4.300% Notes Due 2030, Floating Rate Notes due 2030, 4.500% Notes Due 2032 and 4.850% Notes Due 2035, contained in Exhibit 4.2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 10.1+* Aircraft Time-Sharing Agreement, dated as of February 24, 2015, between Hess Corporation and John B. Hess. 10.2* Transition Services Agreement, dated as of July 14, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.3* Amendment One to Transition Services Agreement, dated as of August 27, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.4* Membership Interest Purchase Agreement, dated as of September 10, 2025, between Hess Corporation and JBH Ventures, LLC . 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ + Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 48 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 6, 2025 49\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": "-0.0189", "answer_numeric": -0.018888, "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%) = -0.0255.", "metadata": {"var": -0.018888, "cvar": -0.025488, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250715_0461", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-07-15", "context_summary": "BTC-USD: 60-day return history, mean=0.0025, std=0.0168.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0025, std=0.0168, min=-0.0393, max=0.0455\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0208", "answer_numeric": -0.0208, "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%) = -0.0316.", "metadata": {"var": -0.0208, "cvar": -0.031592, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250718_0463", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IEF"], "decision_date": "2025-07-18", "context_summary": "IEF: 60-day return history, mean=0.0000, std=0.0037.", "question": "Asset: IEF\nDaily returns (past 60 days): mean=0.0000, std=0.0037, min=-0.0080, max=0.0074\nMarket regime: bull\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": "-0.0067", "answer_numeric": -0.006724, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0067 (i.e., on a bad day with 5% probability, the loss exceeds 0.67%). CVaR(95%) = -0.0076.", "metadata": {"var": -0.006724, "cvar": -0.007558, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250820_0466", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["PDBC"], "decision_date": "2025-08-20", "context_summary": "PDBC: 60-day return history, mean=0.0003, std=0.0096.", "question": "Asset: PDBC\nDaily returns (past 60 days): mean=0.0003, std=0.0096, min=-0.0309, max=0.0278\nMarket regime: bull\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": "-0.0100", "answer_numeric": -0.010036, "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%) = -0.0240.", "metadata": {"var": -0.010036, "cvar": -0.023972, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250805_0469", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2025-08-05", "context_summary": "SGOV: 60-day return history, mean=0.0002, std=0.0001.", "question": "Asset: SGOV\nDaily returns (past 60 days): mean=0.0002, std=0.0001, min=-0.0001, max=0.0005\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SGOV. Express as a decimal (e.g., -0.02).", "answer": "0.0000", "answer_numeric": 0.0, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = -0.0000.", "metadata": {"var": 0.0, "cvar": -1.7e-05, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251224_0472", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-12-24", "context_summary": "DOT-USD: 60-day return history, mean=-0.0081, std=0.0493.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0081, std=0.0493, min=-0.1354, max=0.2170\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0675", "answer_numeric": -0.067545, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0675 (i.e., on a bad day with 5% probability, the loss exceeds 6.75%). CVaR(95%) = -0.0970.", "metadata": {"var": -0.067545, "cvar": -0.097014, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250106_0475", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2025-01-06", "context_summary": "VEA: 60-day return history, mean=-0.0010, std=0.0071.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=-0.0010, std=0.0071, min=-0.0251, max=0.0150\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 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0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VEA. Express as a decimal (e.g., -0.02).", "answer": "-0.0133", "answer_numeric": -0.013298, "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": -0.013298, "cvar": -0.018617, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20251222_0478", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2025-12-22", "context_summary": "VNQ: 60-day return history, mean=-0.0003, std=0.0079.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=-0.0003, std=0.0079, min=-0.0258, max=0.0162\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for VNQ. Express as a decimal (e.g., -0.02).", "answer": "-0.0123", "answer_numeric": -0.012289, "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%) = -0.0194.", "metadata": {"var": -0.012289, "cvar": -0.019386, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251217_0480", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2025-12-17", "context_summary": "CSHI: 60-day return history, mean=0.0002, std=0.0006.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0002, std=0.0006, min=-0.0012, max=0.0020\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for CSHI. Express as a decimal (e.g., -0.02).", "answer": "-0.0006", "answer_numeric": -0.000602, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0006 (i.e., on a bad day with 5% probability, the loss exceeds 0.06%). CVaR(95%) = -0.0008.", "metadata": {"var": -0.000602, "cvar": -0.000754, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251117_0483", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2025-11-17", "context_summary": "IWM: 60-day return history, mean=0.0008, std=0.0123.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0008, std=0.0123, min=-0.0304, max=0.0349\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CVX 2025-11-06] cvx-20250930 0000093410 12/31 2025 Q3 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cvx:segment cvx:lawsuit cvx:state cvx:tribe cvx:parish 0000093410 2025-01-01 2025-09-30 0000093410 2025-09-30 0000093410 2025-07-01 2025-09-30 0000093410 2024-07-01 2024-09-30 0000093410 2024-01-01 2024-09-30 0000093410 2024-12-31 0000093410 2023-12-31 0000093410 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-06-30 0000093410 us-gaap:RetainedEarningsMember 2024-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-06-30 0000093410 us-gaap:ParentMember 2024-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-06-30 0000093410 2024-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-07-01 2024-09-30 0000093410 us-gaap:ParentMember 2024-07-01 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 2024-07-01 2024-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-07-01 2024-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-01 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-07-01 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 2024-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-09-30 0000093410 us-gaap:ParentMember 2024-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-06-30 0000093410 us-gaap:RetainedEarningsMember 2025-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-06-30 0000093410 us-gaap:ParentMember 2025-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-06-30 0000093410 2025-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-07-01 2025-09-30 0000093410 us-gaap:ParentMember 2025-07-01 2025-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-07-01 2025-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-07-01 2025-09-30 0000093410 us-gaap:RetainedEarningsMember 2025-07-01 2025-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-01 2025-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-09-30 0000093410 us-gaap:RetainedEarningsMember 2025-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-09-30 0000093410 us-gaap:ParentMember 2025-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2023-12-31 0000093410 us-gaap:RetainedEarningsMember 2023-12-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-12-31 0000093410 us-gaap:TreasuryStockCommonMember 2023-12-31 0000093410 us-gaap:ParentMember 2023-12-31 0000093410 us-gaap:NoncontrollingInterestMember 2023-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-01-01 2024-09-30 0000093410 us-gaap:ParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 2024-01-01 2024-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-01 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-01-01 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-12-31 0000093410 us-gaap:RetainedEarningsMember 2024-12-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-12-31 0000093410 us-gaap:TreasuryStockCommonMember 2024-12-31 0000093410 us-gaap:ParentMember 2024-12-31 0000093410 us-gaap:NoncontrollingInterestMember 2024-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-01-01 2025-09-30 0000093410 us-gaap:ParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-01-01 2025-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-01-01 2025-09-30 0000093410 us-gaap:RetainedEarningsMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-09-30 0000093410 [...TRUNCATED...] 160; $154.38 16,620,000   (1) Includes common shares repurchased from participants in the company’s executive compensation plans for personal income tax withholdings. (2) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections During the three months ended September 30, 2025, none of our directors or executive officers adopted, modified or terminated a Rule 10b5-1 trading arrangement or a non-Rule 10b5-1 trading arrangement, as such terms are defined in Item 408 of Regulation S-K. 47 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 4.1 Fourth Supplemental Indenture, dated as of August 13, 2025, among Chevron U.S.A. Inc., Chevron Corporation, as guarantor, and Deutsche Bank Trust Company Americas, as trustee, filed as Exhibit 4. 2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 4.2 Forms of 3.950% Notes Due 2027, 4.050% Notes Due 2028, Floating Rate Notes Due 2028-B, 4.300% Notes Due 2030, Floating Rate Notes due 2030, 4.500% Notes Due 2032 and 4.850% Notes Due 2035, contained in Exhibit 4.2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 10.1+* Aircraft Time-Sharing Agreement, dated as of February 24, 2015, between Hess Corporation and John B. Hess. 10.2* Transition Services Agreement, dated as of July 14, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.3* Amendment One to Transition Services Agreement, dated as of August 27, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.4* Membership Interest Purchase Agreement, dated as of September 10, 2025, between Hess Corporation and JBH Ventures, LLC . 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ + Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 48 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 6, 2025 49\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IWM. Express as a decimal (e.g., -0.02).", "answer": "-0.0180", "answer_numeric": -0.018026, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0180 (i.e., on a bad day with 5% probability, the loss exceeds 1.80%). CVaR(95%) = -0.0267.", "metadata": {"var": -0.018026, "cvar": -0.026732, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250410_0486", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-04-10", "context_summary": "BTC-USD: 60-day return history, mean=-0.0021, std=0.0319.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0021, std=0.0319, min=-0.0868, max=0.0955\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0511", "answer_numeric": -0.051083, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0511 (i.e., on a bad day with 5% probability, the loss exceeds 5.11%). CVaR(95%) = -0.0715.", "metadata": {"var": -0.051083, "cvar": -0.071545, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251010_0489", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-10-10", "context_summary": "LINK-USD: 60-day return history, mean=0.0010, std=0.0477.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0010, std=0.0477, min=-0.0939, max=0.1341\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0694", "answer_numeric": -0.069401, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0694 (i.e., on a bad day with 5% probability, the loss exceeds 6.94%). CVaR(95%) = -0.0836.", "metadata": {"var": -0.069401, "cvar": -0.08363, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250808_0492", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IVV"], "decision_date": "2025-08-08", "context_summary": "IVV: 60-day return history, mean=0.0014, std=0.0067.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0014, std=0.0067, min=-0.0168, max=0.0203\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q CVX 2025-08-07] cvx-20250630 0000093410 12/31 2025 Q2 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cvx:segment cvx:lawsuit cvx:state cvx:tribe cvx:parish 0000093410 2025-01-01 2025-06-30 0000093410 2025-06-30 0000093410 2025-04-01 2025-06-30 0000093410 2024-04-01 2024-06-30 0000093410 2024-01-01 2024-06-30 0000093410 2024-12-31 0000093410 2023-12-31 0000093410 2024-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-03-31 0000093410 us-gaap:RetainedEarningsMember 2024-03-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-03-31 0000093410 us-gaap:TreasuryStockCommonMember 2024-03-31 0000093410 us-gaap:ParentMember 2024-03-31 0000093410 us-gaap:NoncontrollingInterestMember 2024-03-31 0000093410 2024-03-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-04-01 2024-06-30 0000093410 us-gaap:ParentMember 2024-04-01 2024-06-30 0000093410 us-gaap:RetainedEarningsMember 2024-04-01 2024-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-04-01 2024-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-01 2024-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-04-01 2024-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-06-30 0000093410 us-gaap:RetainedEarningsMember 2024-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-06-30 0000093410 us-gaap:ParentMember 2024-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-03-31 0000093410 us-gaap:RetainedEarningsMember 2025-03-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-03-31 0000093410 us-gaap:TreasuryStockCommonMember 2025-03-31 0000093410 us-gaap:ParentMember 2025-03-31 0000093410 us-gaap:NoncontrollingInterestMember 2025-03-31 0000093410 2025-03-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-04-01 2025-06-30 0000093410 us-gaap:ParentMember 2025-04-01 2025-06-30 0000093410 us-gaap:RetainedEarningsMember 2025-04-01 2025-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-04-01 2025-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-01 2025-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-04-01 2025-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-06-30 0000093410 us-gaap:RetainedEarningsMember 2025-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-06-30 0000093410 us-gaap:ParentMember 2025-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2023-12-31 0000093410 us-gaap:RetainedEarningsMember 2023-12-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-12-31 0000093410 us-gaap:TreasuryStockCommonMember 2023-12-31 0000093410 us-gaap:ParentMember 2023-12-31 0000093410 us-gaap:NoncontrollingInterestMember 2023-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-01-01 2024-06-30 0000093410 us-gaap:ParentMember 2024-01-01 2024-06-30 0000093410 us-gaap:RetainedEarningsMember 2024-01-01 2024-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-01-01 2024-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-01 2024-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-01-01 2024-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-12-31 0000093410 us-gaap:RetainedEarningsMember 2024-12-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-12-31 0000093410 us-gaap:TreasuryStockCommonMember 2024-12-31 0000093410 us-gaap:ParentMember 2024-12-31 0000093410 us-gaap:NoncontrollingInterestMember 2024-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-01-01 2025-06-30 0000093410 us-gaap:ParentMember 2025-01-01 2025-06-30 0000093410 us-gaap:RetainedEarningsMember 2025-01-01 2025-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-01-01 2025-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-01 2025-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-01-01 2025-06-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-06-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-06-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-01 2024-06-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-01-01 2024-06-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-06-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-06-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-06-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-06-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-01-01 2025-06-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2025-01-01 2025-06-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-01-01 2025-06-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2025-01-01 2025-06-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-06-30 0000093410 [...TRUNCATED...] iculties in integrating Hess may result in a failure to realize anticipated synergies in the expected timeframe, in operational challenges, and in the diversion of management’s attention from ongoing business concerns as well as in unforeseen expenses associated with the acquisition, which may have an adverse impact on the company’s financial results. Item 2. Unregistered Sales of Equity Securities and Use of Proceeds CHEVRON CORPORATION ISSUER PURCHASES OF EQUITY SECURITIES   Period Total Number of Shares Purchased (1,2) Average Price Paid per Share Total Number of Shares Purchased as Part of Publicly Announced Program Approximate Dollar Value of Shares that May Yet Be Purchased Under the 2023 Program (2) (Billions of dollars) April 1 - April 30, 2025 11,783,184  $140.41 11,769,564  $43.0 May 1 - May 31, 2025 6,837,101  $137.88 6,836,812  $42.1 June 1 - June 30, 2025 635  $144.01 —  $42.1 Total 18,620,920   $139.48 18,606,376   (1) Includes common shares repurchased from participants in the company’s executive compensation plans for personal income tax withholdings. (2) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. 44 Table of Contents Item 5. Other Information Rule 10b5-1 Plan Elections During the three months ended June 30, 2025, none of our directors or executive officers adopted, modified or terminated a Rule 10b5-1 trading arrangement or a non-Rule 10b5-1 trading arrangement, as such terms are defined in Item 408 of Regulation S-K. Item 6. Exhibits Exhibit Index Exhibit Number Description 3.1 Restated Certificate of Incorporation of Chevron Corporation, dated May 28, 2025, filed as Exhibit 3.1 to Chevron Corporation’s Current Report on Form 8-K filed May 30, 2025, and incorporated herein by reference. 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ *    Filed herewith. **     Furnished herewith. 45 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: August 7, 2025 46\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": "-0.0085", "answer_numeric": -0.008457, "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%) = -0.0147.", "metadata": {"var": -0.008457, "cvar": -0.014727, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20251120_0495", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-11-20", "context_summary": "BTC-USD: 60-day return history, mean=-0.0037, std=0.0221.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0037, std=0.0221, min=-0.0698, max=0.0403\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0382", "answer_numeric": -0.038199, "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%) = -0.0565.", "metadata": {"var": -0.038199, "cvar": -0.056483, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250903_0498", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-09-03", "context_summary": "VTI: 60-day return history, mean=0.0014, std=0.0065.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0014, std=0.0065, min=-0.0167, max=0.0172\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-02] [\"Citi Initiates Lumentum With Buy Rating On AI Data Center Growth Citigroup initiated coverage of Lumentum with a buy rating on AI data center growth. Lumentum stock has surged 55% in 2025.\", \"Big Tech\\u2019s Market Dominance Stirs Debate on Concentration Risks (Bloomberg) \\u2014 The unprecedented level of concentration in a handful of tech stocks provokes strong feelings on Wall Street. Some investors fear the top-heaviness means the bull run is on quicksand, and will sink the minute an AI-frenzy-fueled Nvidia Corp. (NVDA) or Microsoft Corp. (MSFT) stumbles. The dominance also leads to portfolio risks, with diversification suffering. For others, the worries are overblown, gains have historically been powered by a small group of megacaps, and this is simply tech\\u2019s latest time to shine. Most Read from Bloomberg Sydney\\u2019s New Airport Will Take Travelers Into the Wild One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Amtrak Debuts New High-Speed Acela Trains After Years of Delays Trump Signs Order to \\u2018Make Federal Architecture Beautiful Again\\u2019 Parents Mobilize to Protect School Commutes Amid Trump Deployment in DC The debate is becoming more urgent as Nividia, Microsoft (MSFT), Apple Inc. (AAPL), Alphabet Inc. (GOOG, GOOGL), Amazon.com Inc. and Meta Platforms Inc. (META) account for more than 30% of the benchmark index, more than three times their weighting from a decade ago. Gains for Nividia, Microsoft and Meta alone account for about 270 points of the S&P 500\\u2019s (^GSPC) 579-point advance in 2025, or nearly half of this year\\u2019s 9.8% rally. For Scott Chronert, Citi Research\\u2019s managing director, the concentration is a badge of honor, well-deserved for a group that continues to deliver unparalleled growth in sales and earnings. The five biggest \\u2014 Nvidia, Microsoft, Apple, Alphabet and Amazon \\u2014 increased profits by 26% in the second quarter, compared with estimates for 15%, according to data compiled by Bloomberg Intelligence. The S&P 500 as a whole saw earnings rise by 11% from a year ago. The biggest tech companies have \\u201cearned\\u201d their weightings as a function of growth metrics, Chronert said. To him, valuations aren\\u2019t stretched based on the profit forecasts that they have consistently been able to meet. On a price/earnings to growth basis, no cause for alarm exists, he said. \\u201cThe PEG ratio for the Mag 7 is not materially different than for the rest of the market,\\u201d Chronert said. Valuation isn\\u2019t an issue, he adds, \\u201cso long as earnings growth expectations are met or beat\\u201d \\u2014 a bar he conceded could be getting harder to surpass as targets swell. Still, there are reasons why the tech megacap domination is likely to persist without incident. They generate vast amount of cash in good economic times and bad, making them growth and defensive plays at the same time. They also stand to get outsize benefits from recent Trump administration policy changes, \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": -0.007942, "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%) = -0.0123.", "metadata": {"var": -0.007942, "cvar": -0.012319, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250919_0501", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-09-19", "context_summary": "XLY: 60-day return history, mean=0.0018, std=0.0097.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0018, std=0.0097, min=-0.0244, max=0.0299\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": "-0.0129", "answer_numeric": -0.012866, "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%) = -0.0185.", "metadata": {"var": -0.012866, "cvar": -0.018505, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250623_0503", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-06-23", "context_summary": "USMV: 60-day return history, mean=-0.0000, std=0.0091.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=-0.0000, std=0.0091, min=-0.0253, max=0.0221\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-20] [\"Alibaba\\u2019s (BABA) New Qwen3 AI Models Now Compatible With Apple Devices Alibaba Group Holding Limited (NYSE:BABA) is one of the 10 AI Stocks Getting Wall Street\\u2019s Attention. On June 17, South China Morning Post reported that the company updated its Qwen3 family of artificial intelligence (AI) models that could signal the potential roll-out in China of machine-learning technology on a range of Apple devices, including iPhones, iPads, and MacBooks. Alibaba announced the launch of new Qwen3 artificial intelligence models for Apple\\u2019s MLX architecture, announcing in a post on Wechat that the models will be able to run on a range of Apple devices, including iPhone, iPad, MacBook, and Mac. A busy sidewalk filled with people using Apple devices like iPhones, iPads and Apple Watches. The MLX framework is designed to be user-friendly and efficient in training and deploying AI models on Apple\\u2019s silicon hardware. Through this development, Apple is aiming to expand the availability of its Apple Intelligence suite to China. Alibaba Group Holding Limited (NYSE:BABA) is an internet giant that offers e-commerce services in China and internationally. While we acknowledge the potential of BABA as an investment, we believe certain AI stocks offer greater upside potential and carry less downside risk. If you\\u2019re looking for an extremely undervalued AI stock that also stands to benefit significantly from Trump-era tariffs and the onshoring trend, see our free report on the best short-term AI stock. READ NEXT: 10 AI Stocks on Wall Street\\u2019s Radar and 15 AI Stocks Making Waves on Wall Street. Disclosure: None.\", \"Trump Hints He\\u2019ll Hold Off Iran Strike, Give Diplomacy Time (Bloomberg) -- US President Donald Trump signaled he would give diplomacy a chance before deciding whether to strike Iran, dialing back on recent comments that suggested military action could be imminent. Most Read from Bloomberg Security Concerns Hit Some of the World\\u2019s \\u2018Most Livable Cities\\u2019 One Architect\\u2019s Quest to Save Mumbai\\u2019s Heritage From Disappearing JFK AirTrain Cuts Fares 50% This Summer to Lure Riders Off Roads NYC Congestion Toll Cuts Manhattan Gridlock by 25%, RPA Reports Taser-Maker Axon Triggers a NIMBY Backlash in its Hometown \\u201cBased on the fact that there\\u2019s a substantial chance of negotiations that may or may not take place with Iran in the near future, I will make my decision whether or not to go within the next two weeks,\\u201d Trump said in a dictated message, according to White House spokeswoman Karoline Leavitt. Subscribe to the Bloomberg Daybreak Podcast on Apple, Spotify and other Podcast Platforms. Iran maintained Friday it won\\u2019t negotiate with the US while an Israeli assault continues. The only way to end the imposed war is to \\u201cunconditionally stop\\u201d the enemy\\u2019s aggression, Iranian President Masoud Pezeshkian said Friday in a post on X. Oil prices fell following a report from Reuters that Ir\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": "-0.0133", "answer_numeric": -0.013278, "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": -0.013278, "cvar": -0.019951, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20251230_0506", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-12-30", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0055, std=0.0412.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0055, std=0.0412, min=-0.1171, max=0.0995\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0654", "answer_numeric": -0.065376, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0654 (i.e., on a bad day with 5% probability, the loss exceeds 6.54%). CVaR(95%) = -0.0901.", "metadata": {"var": -0.065376, "cvar": -0.09011, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250224_0508", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ITB"], "decision_date": "2025-02-24", "context_summary": "ITB: 59-day return history, mean=-0.0033, std=0.0164.", "question": "Asset: ITB\nDaily returns (past 59 days): mean=-0.0033, std=0.0164, min=-0.0409, 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": "-0.0260", "answer_numeric": -0.025997, "explanation": "Historical simulation VaR at 95%: sort the 59 daily returns and take the 5th percentile. VaR(95%) = -0.0260 (i.e., on a bad day with 5% probability, the loss exceeds 2.60%). CVaR(95%) = -0.0327.", "metadata": {"var": -0.025997, "cvar": -0.03266, "confidence": 0.95, "n_returns": 59, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250714_0510", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-07-14", "context_summary": "EFA: 60-day return history, mean=0.0021, std=0.0074.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0021, std=0.0074, min=-0.0129, max=0.0205\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-11] [\"As X loses its CEO, daily usage is down and competition is growing With the departure of X CEO Linda Yaccarino, which was announced Wednesday, the company that defined text-first social networking faces renewed competition. Year-over-year, the Elon Musk-owned social network has seen its daily active user base decline by roughly 10% as of the second quarter of 2025, according to new data provided by app intelligence firm Sensor Tower. While X\\u2019s user base is still 65% larger than Meta\\u2019s Threads and 10 times larger than its next-biggest rival, Bluesky, X\\u2019s lasting victory in this space is not guaranteed. On mobile devices, there\\u2019s already some indication that Threads is catching up. New data from market intelligence provider Similarweb released this week indicates Threads is nearing X\\u2019s daily app users on mobile. In June 2025, Threads\\u2019 mobile app for iOS and Android saw 115.1 million daily active users, representing 127.8% year-over-year growth; X reached 132 million daily actives, as its year-over-year growth declined by 15.2%. Overall, X is still larger than Threads thanks to its more prominent web presence. X also has other advantages, which could make for an interesting fight between the tech giants. On X, user engagement and loyalty remain strong, despite the increased competition from Meta as well as open source social networking movements like Bluesky and Mastodon, and other startups. According to Sensor Tower\\u2019s data, X users spent an average of 31 minutes per day on the platform in the second quarter of 2025, which was nearly quadruple that of Threads, at 8 minutes per day. Plus, nearly half (48%) of X\\u2019s global monthly app users in the quarter interacted with the platform on a daily basis, compared with 33% for Threads, the firm said. But Threads can\\u2019t be counted out yet, simply because X is larger. Though Threads may have fewer daily active users than X, it\\u2019s been seeing stronger growth. Over the past year, Threads\\u2019 global app daily active users were up 160% year-over-year, the Sensor Tower\\u2019s data shows, driven in part by the rollout of new features and functions, as well as by its ties to Meta\\u2019s other apps, like Facebook and Instagram, which serve as funnels. Threads is also laser-focused on growing its ads ecosystem, which is the app\\u2019s only means of monetization for the time being. In April, Meta opened up Threads ads to its global advertisers, and the following month announced tests for video ads, as well. The app has the advantage of being a part of Meta\\u2019s larger ads business, where its tools are already familiar to marketers and where it has the ability to tap into Meta\\u2019s nearly two decades of experience in maximizing ad revenues. Under Yaccarino, X\\u2019s ad ecosystem recovered, but it\\u2019s been a volatile ride. Advertisers in the media and entertainment, shopping, and gaming verticals through 2025 year-to-date represent 25%, 22%, and 7% of total U.S. \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": "-0.0109", "answer_numeric": -0.01093, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0109 (i.e., on a bad day with 5% probability, the loss exceeds 1.09%). CVaR(95%) = -0.0123.", "metadata": {"var": -0.01093, "cvar": -0.012286, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20251203_0513", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-12-03", "context_summary": "USMV: 60-day return history, mean=0.0001, std=0.0055.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0001, std=0.0055, min=-0.0127, max=0.0124\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2025-11-19] nvda-20251026 0001045810 1/25 2026 Q3 FALSE 478 469 278 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:investment nvda:segment 0001045810 2025-01-27 2025-10-26 0001045810 2025-11-14 0001045810 2025-07-28 2025-10-26 0001045810 2024-07-29 2024-10-27 0001045810 2024-01-29 2024-10-27 0001045810 2025-10-26 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 2025-07-27 0001045810 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us-gaap:ResearchAndDevelopmentExpenseMember 2025-01-27 2025-10-26 0001045810 us-gaap:ResearchAndDevelopmentExpenseMember 2024-01-29 2024-10-27 0001045810 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2025-07-28 2025-10-26 0001045810 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2024-07-29 2024-10-27 0001045810 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2025-01-27 2025-10-26 0001045810 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2024-01-29 2024-10-27 0001045810 nvda:RSUsPSUsandMarketbasedPSUsMember 2025-01-26 0001045810 nvda:RSUsPSUsandMarketbasedPSUsMember 2025-01-27 2025-10-26 0001045810 nvda:RSUsPSUsandMarketbasedPSUsMember 2025-10-26 0001045810 us-gaap:EmployeeStockMember 2025-01-27 2025-10-26 0001045810 us-gaap:USTreasurySecuritiesMember 2025-10-26 0001045810 us-gaap:CorporateDebtSecuritiesMember 2025-10-26 0001045810 us-gaap:MoneyMarketFundsMember 2025-10-26 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-10-26 0001045810 us-gaap:CertificatesOfDepositMember 2025-10-26 0001045810 us-gaap:ForeignGovernmentDebtMember 2025-10-26 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2025-10-26 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2025-10-26 0001045810 2025-01-27 2025-04-27 0001045810 us-gaap:CorporateDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:USTreasurySecuritiesMember 2025-01-26 0001045810 us-gaap:MoneyMarketFundsMember 2025-01-26 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:ForeignGovernmentDebtMember 2025-01-26 0001045810 us-gaap:CertificatesOfDepositMember 2025-01-26 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2025-01-26 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2025-01-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-10-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-01-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-10-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:CustomerOneMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerTwoMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerThreeMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerFourMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:Cust [...TRUNCATED...] President, Operations Adoption 9/9/2025 309,840 12/31/2026 Donald Robertson Vice President and Chief Accounting Officer Adoption 9/18/2025 138,042 * 12/31/2026 Ajay Puri Executive Vice President, Worldwide Field Operations Adoption 9/19/2025 1,000,000 6/24/2026 * Includes 38,042 shares from future vests of equity awards, and the actual number of shares to be sold will be net of shares withheld by the Company for taxes. 42 Item 6. Exhibits Exhibit No.  Exhibit Description 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 43 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 19, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 44\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": "-0.0082", "answer_numeric": -0.00821, "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%) = -0.0106.", "metadata": {"var": -0.00821, "cvar": -0.010648, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20250612_0516", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IGOV"], "decision_date": "2025-06-12", "context_summary": "IGOV: 60-day return history, mean=0.0011, std=0.0067.", "question": "Asset: IGOV\nDaily returns (past 60 days): mean=0.0011, std=0.0067, min=-0.0138, max=0.0139\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IGOV. Express as a decimal (e.g., -0.02).", "answer": "-0.0096", "answer_numeric": -0.009555, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0096 (i.e., on a bad day with 5% probability, the loss exceeds 0.96%). CVaR(95%) = -0.0125.", "metadata": {"var": -0.009555, "cvar": -0.012527, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250814_0518", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IAU"], "decision_date": "2025-08-14", "context_summary": "IAU: 60-day return history, mean=0.0004, std=0.0099.", "question": "Asset: IAU\nDaily returns (past 60 days): mean=0.0004, std=0.0099, min=-0.0183, max=0.0238\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IAU. Express as a decimal (e.g., -0.02).", "answer": "-0.0156", "answer_numeric": -0.015616, "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%) = -0.0174.", "metadata": {"var": -0.015616, "cvar": -0.017421, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250618_0521", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["CPER"], "decision_date": "2025-06-18", "context_summary": "CPER: 60-day return history, mean=-0.0001, std=0.0191.", "question": "Asset: CPER\nDaily returns (past 60 days): mean=-0.0001, std=0.0191, min=-0.0392, max=0.0357\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for CPER. Express as a decimal (e.g., -0.02).", "answer": "-0.0361", "answer_numeric": -0.036142, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0361 (i.e., on a bad day with 5% probability, the loss exceeds 3.61%). CVaR(95%) = -0.0392.", "metadata": {"var": -0.036142, "cvar": -0.039186, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250513_0524", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-05-13", "context_summary": "BTC-USD: 60-day return history, mean=0.0043, std=0.0255.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0043, std=0.0255, min=-0.0634, max=0.0826\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0326", "answer_numeric": -0.032559, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0326 (i.e., on a bad day with 5% probability, the loss exceeds 3.26%). CVaR(95%) = -0.0455.", "metadata": {"var": -0.032559, "cvar": -0.045484, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250429_0527", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-04-29", "context_summary": "VLUE: 60-day return history, mean=-0.0013, std=0.0134.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0013, std=0.0134, min=-0.0356, max=0.0296\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-28] Earnings Preview: Axsome Therapeutics (AXSM) Q1 Earnings Expected to Decline The market expects Axsome Therapeutics (AXSM) to deliver a year-over-year decline in earnings on higher revenues when it reports results for the quarter ended March 2025. This widely-known consensus outlook is important in assessing the company's earnings picture, but a powerful factor that might influence its near-term stock price is how the actual results compare to these estimates. The earnings report, which is expected to be released on May 5, 2025, might help the stock move higher if these key numbers are better than expectations. On the other hand, if they miss, the stock may move lower. While management's discussion of business conditions on the earnings call will mostly determine the sustainability of the immediate price change and future earnings expectations, it's worth having a handicapping insight into the odds of a positive EPS surprise. This biopharmaceutical company is expected to post quarterly loss of $1.26 per share in its upcoming report, which represents a year-over-year change of -15.6%. Revenues are expected to be $119.49 million, up 59.3% from the year-ago quarter. The consensus EPS estimate for the quarter has been revised 2.36% higher over the last 30 days to the current level. This is essentially a reflection of how the covering analysts have collectively reassessed their initial estimates over this period. Investors should keep in mind that an aggregate change may not always reflect the direction of estimate revisions by each of the covering analysts. Estimate revisions ahead of a company's earnings release offer clues to the business conditions for the period whose results are coming out. This insight is at the core of our proprietary surprise prediction model -- the Zacks Earnings ESP (Expected Surprise Prediction). The Zacks Earnings ESP compares the Most Accurate Estimate to the Zacks Consensus Estimate for the quarter; the Most Accurate Estimate is a more recent version of the Zacks Consensus EPS estimate. The idea here is that analysts revising their estimates right before an earnings release have the latest information, which could potentially be more accurate than what they and others contributing to the consensus had predicted earlier. Thus, a positive or negative Earnings ESP reading theoretically indicates the likely deviation of the actual earnings from the consensus estimate. However, the model's predictive power is significant for positive ESP readings only. A positive Earnings ESP is a strong predictor of an earnings beat, particularly when combined with a Zacks Rank #1 (Strong Buy), 2 (Buy) or 3 (Hold). Our research shows that stocks with this combination produce a positive surprise nearly 70% of the time, and a solid Zacks Rank actually increases the predictive power of Earnings ESP. Please note that a negative Earnings ESP reading is not indicative of an earnings miss. Our research shows that it is difficult to predict an earn\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": "-0.0227", "answer_numeric": -0.022727, "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%) = -0.0356.", "metadata": {"var": -0.022727, "cvar": -0.035551, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250822_0529", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-08-22", "context_summary": "EFA: 60-day return history, mean=0.0008, std=0.0077.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0008, std=0.0077, min=-0.0162, max=0.0246\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-08-21] [\"Fox Launches Fox One Streaming Service Fox (FOX, FOXA) said Thursday it has launched Fox One, a new streaming service that offers the compa\", \"Nasdaq, S&P 500 close lower with tech stocks leading the sell-off The Nasdaq Composite (^IXIC) closed about 142 points lower on Wednesday, as Big Tech names like Apple (AAPL), Micron (MU), and Intel (INTC) weighed on the index. The S&P 500 (^GSPC) also closed in the red, while the Dow Jones Industrial Average (^DJI) posted a slight gain. Yahoo Finance Markets and Data Editor Jared Blikre recaps the action at the close. To watch more expert insights and analysis on the latest market action, check out more Market Domination Overtime.\", \"Sector Update: Tech Stocks Decline Late Afternoon Tech stocks fell late Wednesday afternoon with the Technology Select Sector SPDR Fund (XLK) shedding\", \"Heard on the Street Wednesday Recap: AI Trade Down Technology stocks sell off again. Two days don't make a trend, but investors seem to have second thoughts on the market's AI-fueled upswing. All eight tech companies with market values over $1 trillion closed another day in the red.\", \"GM Raided Silicon Valley to Build Its New AI Team. Here\\u2019s What It\\u2019s Doing. So far the team includes hires from Google, Meta, AWS and even a Pixar vet who is helping GM develop new factory \\u2018cobots.\\u2019\", \"AI Fatigue Hits Tech Biggies: Inverse ETFs in Focus Short sellers are wagering against top AI stocks currently, which has earned them billions. On Wednesday, the Nasdaq Composite fell 0.7%, capping a two-day decline of 1.5% as concerns about the sustainability of the AI boom made the rounds. According to data from S3 Partners, short sellers amassed $5.6 billion on wagers against AI-linked companies in just two trading sessions. Among the Magnificent Seven, Meta META has been the hardest hit, down 4% over the past five sessions. NVIDIA NVDA slipped 3.8%, while Microsoft MSFT and Apple AAPL fell nearly 3% each. Alphabet GOOG also fell about 1%. Short bets against these five giants alone led to $2.8 billion in profits for investors over the past two days. Beyond Big Tech, losses were steeper. Advanced Micro Devices AMD slid more than 10% in the last week, while Broadcom AVGO and Micron MU each fell over 5%. AI data center operator CoreWeave CRWV \\u2014 seen as an AI \\u201cpure play\\u201d \\u2014 nosedived 24% in the same period. Meta has made huge investments in AI. Despite this, short sellers increased positions worth $4.7 billion over the past week, reaping $1.1 billion in profits in just two days. Meanwhile, Palantir PLTR, which had surged more than 150% since April, has now fallen over 15% in its longest losing streak since March. Investors shorting Palantir have gained more than $1 billion. The recent downturn has been fueled by shifting sentiment. On Monday, researchers for MIT\\u2019s Project NANDA released a report saying 95% of companies it studied are getting no return on AI. The findings of the report were first detail\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": "-0.0116", "answer_numeric": -0.011636, "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%) = -0.0138.", "metadata": {"var": -0.011636, "cvar": -0.013826, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250922_0532", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["FXI"], "decision_date": "2025-09-22", "context_summary": "FXI: 60-day return history, mean=0.0017, std=0.0114.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=0.0017, std=0.0114, min=-0.0258, max=0.0299\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": "-0.0151", "answer_numeric": -0.015089, "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%) = -0.0205.", "metadata": {"var": -0.015089, "cvar": -0.020543, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20251208_0535", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2025-12-08", "context_summary": "SGOV: 60-day return history, mean=0.0002, std=0.0001.", "question": "Asset: SGOV\nDaily returns (past 60 days): mean=0.0002, std=0.0001, min=-0.0001, max=0.0005\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SGOV. Express as a decimal (e.g., -0.02).", "answer": "0.0001", "answer_numeric": 9.4e-05, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0001 (i.e., on a bad day with 5% probability, the loss exceeds 0.01%). CVaR(95%) = -0.0000.", "metadata": {"var": 9.4e-05, "cvar": -3.3e-05, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250912_0537", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IWM"], "decision_date": "2025-09-12", "context_summary": "IWM: 60-day return history, mean=0.0022, std=0.0113.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0022, std=0.0113, min=-0.0206, max=0.0349\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for IWM. Express as a decimal (e.g., -0.02).", "answer": "-0.0140", "answer_numeric": -0.013966, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0140 (i.e., on a bad day with 5% probability, the loss exceeds 1.40%). CVaR(95%) = -0.0185.", "metadata": {"var": -0.013966, "cvar": -0.018497, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250923_0540", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-09-23", "context_summary": "VLUE: 60-day return history, mean=0.0016, std=0.0079.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0016, std=0.0079, min=-0.0130, max=0.0225\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": "-0.0119", "answer_numeric": -0.011887, "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%) = -0.0125.", "metadata": {"var": -0.011887, "cvar": -0.012501, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250114_0543", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-01-14", "context_summary": "XRP-USD: 60-day return history, mean=0.0225, std=0.0741.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0225, std=0.0741, min=-0.1493, max=0.2545\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0678", "answer_numeric": -0.067823, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0678 (i.e., on a bad day with 5% probability, the loss exceeds 6.78%). CVaR(95%) = -0.1069.", "metadata": {"var": -0.067823, "cvar": -0.106918, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250911_0546", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["MORT"], "decision_date": "2025-09-11", "context_summary": "MORT: 60-day return history, mean=0.0017, std=0.0098.", "question": "Asset: MORT\nDaily returns (past 60 days): mean=0.0017, std=0.0098, min=-0.0167, max=0.0301\nMarket regime: bull\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": "-0.0131", "answer_numeric": -0.013116, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0131 (i.e., on a bad day with 5% probability, the loss exceeds 1.31%). CVaR(95%) = -0.0149.", "metadata": {"var": -0.013116, "cvar": -0.014935, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250605_0548", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-06-05", "context_summary": "XLY: 60-day return history, mean=0.0004, std=0.0178.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0004, std=0.0178, min=-0.0388, max=0.0338\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-04] [\"Qualcomm CEO: We're diversifying beyond declining Apple business Listen and subscribe to Opening Bid on Apple Podcasts, Spotify, Amazon Music, YouTube or wherever you find your favorite podcasts. Qualcomm's (QCOM) next 40 years will look different than its past four decades as it seeks to diversify into data centers and cash in on the AI gold rush. But that also likely means going at things other than its lucrative business with Apple's (AAPL) iPhone. Qualcomm has been Apple's largest cellular modem provider, but the tech giant is transitioning to its own in-house C1 modem in a bid to boost margins. \\\"That's our contract, you know, and if we don't get a new contract, that's what it is,\\\" Qualcomm CEO Cristiano Amon said on Yahoo Finance's Opening Bid podcast (see video above; listen below). \\\"And there's so much drama and association about the Apple relationship, which I think it's not warranted, to be honest.\\\" The tech duo's licensing agreement ends in 2027. Research firm Futurum estimates that Qualcomm's annual modem revenue from Apple is between $5.7 billion and $5.9 billion. Analysts estimate Qualcomm will pull in about $43.5 billion in sales this year. Qualcomm has said publicly it expects to have a 70% share in iPhones launching this fall. That will drop to 20% for iPhones next fall, and then stand to be zero for iPhones debuting in fall 2027. Yahoo Finance caught up with the globe-trotting Amon \\u2014 fresh off a visit to Saudi Arabia with other top execs and the Trump administration \\u2014 at the Nasdaq. Amon began his career at Qualcomm as an engineer in 1995. \\\"We're planning our business assuming that they [Apple] are going to use their own modem,\\\" Amon said. \\\"And what's exciting about the company is all of this growth that we're creating, all of those other markets, including on Android. Like, if you look at our Android business, it has continued to grow.\\\" To offset the lost Apple sales, Qualcomm continues to invest in the connected car cockpit and the internet of things domain. The company thinks it can grow its business from these two segments to $22 billion by 2030, up from $8.3 billion in fiscal year 2024. \\\"Qualcomm's diversified growth across these specific verticals is credibly expected to significantly exceed the revenue scale of modem-only handset customers well into the era of 6G,\\\" Futurum researchers wrote in a note. The company also announced in mid-May that it plans to launch processors designed for data centers to power artificial intelligence, which will connect to Nvidia (NVDA) chips. Qualcomm failed to successfully expand into data centers years ago and returns to the field with formidable rivals in AMD (AMD), Intel (INTC), and soon ARM (ARM). \\\"It's a massive TAM [total addressable market] and will continue to grow at very high growth rates for decades. If we can build something unique and disruptive, there's room for Qualcomm,\\\" Amon said of the data center push. The Street has taken a wait-and-see approach t\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": "-0.0319", "answer_numeric": -0.031933, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0319 (i.e., on a bad day with 5% probability, the loss exceeds 3.19%). CVaR(95%) = -0.0388.", "metadata": {"var": -0.031933, "cvar": -0.038816, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250902_0551", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2025-09-02", "context_summary": "CSHI: 60-day return history, mean=0.0002, std=0.0006.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0002, std=0.0006, min=-0.0010, max=0.0016\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for CSHI. Express as a decimal (e.g., -0.02).", "answer": "-0.0008", "answer_numeric": -0.000813, "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%) = -0.0010.", "metadata": {"var": -0.000813, "cvar": -0.001005, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250829_0554", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-08-29", "context_summary": "AVAX-USD: 60-day return history, mean=0.0056, std=0.0429.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0056, std=0.0429, min=-0.0912, max=0.1084\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0585", "answer_numeric": -0.058522, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0585 (i.e., on a bad day with 5% probability, the loss exceeds 5.85%). CVaR(95%) = -0.0793.", "metadata": {"var": -0.058522, "cvar": -0.079335, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250116_0557", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2025-01-16", "context_summary": "MATIC-USD: 60-day return history, mean=0.0038, std=0.0573.", "question": "Asset: MATIC-USD\nDaily returns (past 60 days): mean=0.0038, std=0.0573, min=-0.1702, max=0.1530\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0776", "answer_numeric": -0.077566, "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%) = -0.1191.", "metadata": {"var": -0.077566, "cvar": -0.119121, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250117_0560", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2025-01-17", "context_summary": "XLI: 60-day return history, mean=-0.0003, std=0.0092.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=-0.0003, std=0.0092, min=-0.0287, max=0.0303\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 2024-12-04 0000104169 2024-08-01 2024-10-31 0000104169 2023-08-01 2023-10-31 0000104169 2023-02-01 2023-10-31 0000104169 2024-10-31 0000104169 2024-01-31 0000104169 2023-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-08-01 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-08-01 2024-10-31 0000104169 us-gaap:CommonStockMember 2024-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-10-31 0000104169 us-gaap:RetainedEarningsMember 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-31 0000104169 us-gaap:ParentMember 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-10-31 0000104169 us-gaap:CommonStockMember 2023-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-01-31 0000104169 us-gaap:ParentMember 2023-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-01-31 0000104169 2023-01-31 0000104169 us-gaap:RetainedEarningsMember 2023-02-01 2023-04-30 0000104169 us-gaap:ParentMember 2023-02-01 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-02-01 2023-04-30 0000104169 2023-02-01 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-02-01 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-02-01 2023-04-30 0000104169 us-gaap:CommonStockMember 2023-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-04-30 0000104169 us-gaap:ParentMember 2023-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2023-04-30 0000104169 2023-04-30 0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLI. Express as a decimal (e.g., -0.02).", "answer": "-0.0122", "answer_numeric": -0.01218, "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%) = -0.0193.", "metadata": {"var": -0.01218, "cvar": -0.01929, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20251212_0563", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-12-12", "context_summary": "BTC-USD: 60-day return history, mean=-0.0034, std=0.0222.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0034, std=0.0222, min=-0.0532, max=0.0583\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0451", "answer_numeric": -0.045129, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0451 (i.e., on a bad day with 5% probability, the loss exceeds 4.51%). CVaR(95%) = -0.0508.", "metadata": {"var": -0.045129, "cvar": -0.050844, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250331_0566", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-03-31", "context_summary": "DOT-USD: 60-day return history, mean=-0.0048, std=0.0465.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0048, std=0.0465, min=-0.1391, max=0.1146\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0853", "answer_numeric": -0.085308, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0853 (i.e., on a bad day with 5% probability, the loss exceeds 8.53%). CVaR(95%) = -0.1266.", "metadata": {"var": -0.085308, "cvar": -0.126573, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250925_0569", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-09-25", "context_summary": "ADA-USD: 60-day return history, mean=0.0005, std=0.0372.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0005, std=0.0372, min=-0.0847, max=0.0927\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0503", "answer_numeric": -0.05031, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0503 (i.e., on a bad day with 5% probability, the loss exceeds 5.03%). CVaR(95%) = -0.0770.", "metadata": {"var": -0.05031, "cvar": -0.077027, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250403_0572", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-04-03", "context_summary": "VTI: 60-day return history, mean=-0.0008, std=0.0104.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=-0.0008, std=0.0104, min=-0.0276, max=0.0212\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-02] Rocket acquires Mr. Cooper, Musk\u2019s xAI acquires X: Morning Buzz The major averages were mostly lower near noon, with the Dow up fractionally but the Nasdaq down nearly 250 points amid mounting concerns about President Donald Trump\u2019s upcoming announcement of promised new tariffs. Meanwhile, the S&P 500\u2019s early losses brought the index to its lowest level since September. Discover the latest stocks recommended by top Wall Street analysts, all in one place with Analyst Top Stocks. Make smarter investments with weekly expert stock picks from the Smart Investor Newsletter. Looking to commodities, gold prices are sharply higher, continuing their rally to over $3,150, while oil prices are also up over 2.5%. Get caught up quickly on the top news and calls moving stocks with these five Top Five lists. 1. STOCK NEWS: Rocket Companies (RKT) agreed to acquire Mr. Cooper (COOP) in a $9.4B all-stock transaction Elon Musk said that xAI has acquired X, formerly Twitter, in an all-stock transaction that values xAI at $80B Meanwhile, Tesla (TSLA) sales in Canada are under scrutiny, NY Times reports GlobalFoundries (GFS) is exploring the possibility of merger with United Microelectronics (UMC), Nikkei reports Southern States (SSBK) and FB Financial (FBK) have entered into a definitive merger agreement 2. WALL STREET CALLS: KLA Corp. (KLAC) upgraded at Morgan Stanley, here\u2019s why RBC downgraded Sarepta (SRPT) citing a \u201cless bullish\u201d stance after doctor checks Truist upgraded Celsius Holdings (CELH) to Buy BMO Capital downgraded U.S. Steel (X) to Market Perform Stephens downgraded Comerica (CMA) to Equal Weight 3. AROUND THE WEB: Harley-Davidson (HOG) has said its products are afflicted by unfair trade policies and if the European Union implements a 50% retaliatory tariff on its motorcycles in April, prices could reach astounding heights in the company\u2019s second-largest market by sales, WSJ reports Thames Water announced that it chose U.S. private equity company KKR (KKR) as its preferred partner to lead its recapitalization, WSJ says Costco (COST) created store brand Kirkland Signature three decades ago and it is now a linchpin the company\u2019s success that accounts for roughly a third of its approximately $254.5B in annual revenue, WSJ reports France\u2019s competition regulator fined Apple (AAPL) EUR 150M due to concerns the company abused its dominant position through the privacy measures it imposes on app developers on its iPhone and iPads, WSJ says After Micron (MU), the world\u2019s third-largest DRAM manufacturer, recently announced a price increase, the other two major DRAM players Samsung (SSNLF) and SK Hynix (HXSCL) are also expected to raise prices, DigiTimes reports 4. MOVERS: Corcept Therapeutics (CORT) gains after announcing its ROSELLA trial met its primary endpoint Hut 8 (HUT) increases after launching American Bitcoin with Eric Trump Goodyear Tire (GT) higher after Deutsche Bank upgraded the stock to Buy Vaxcyte (PCVX) falls after reporting results from its Phase \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": "-0.0187", "answer_numeric": -0.018653, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0187 (i.e., on a bad day with 5% probability, the loss exceeds 1.87%). CVaR(95%) = -0.0222.", "metadata": {"var": -0.018653, "cvar": -0.022171, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250217_0575", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-17", "context_summary": "SPY: 60-day return history, mean=0.0008, std=0.0077.", "question": "Asset: SPY\nDaily returns (past 60 days): mean=0.0008, std=0.0077, min=-0.0274, max=0.0180\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K CAT 2025-02-14] cat-20241231 0000018230 FALSE 2024 FY 50 33.33 33.33 33.33 33.33 33.33 33.33 http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligationsCurrent http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligationsCurrent http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligations http://fasb.org/us-gaap/2024#LongTermDebtAndCapitalLeaseObligations http://fasb.org/us-gaap/2024#AccountsPayableCurrent 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_________________________________________ *Management contracts and compensatory plans and arrangements required to be filed as exhibits pursuant to Item 15(b) of this report. The agreements and other documents filed as exhibits to this report are not intended to provide factual information or other disclosure other than with respect to the terms of the agreements or other documents themselves, and you should not rely on them for that purpose. In particular, any representations and warranties made by us in these agreements or other documents were made solely within the specific context of the relevant agreement or document and may not describe the actual state of affairs as of the date they were made or at any other time. Item 16.  Form 10-K Summary. None. 129 Table of Contents Form 10-K   SIGNATURES   Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.     CATERPILLAR INC.   Registrant     February 14, 2025 By: /s/ Derek Owens     Derek Owens Chief Legal Officer and General Counsel   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities and on the dates indicated.       Chairman of the Board  and Chief Executive Officer February 14, 2025 /s/ D. James Umpleby III   D. James Umpleby III       February 14, 2025 /s/ Andrew R.J. Bonfield Chief Financial Officer Andrew R.J. Bonfield     February 14, 2025 /s/ William E. Schaupp Vice President and Chief Accounting Officer   William E. Schaupp             February 14, 2025 /s/ Daniel M. Dickinson Director   Daniel M. Dickinson   February 14, 2025 /s/ James C. Fish, Jr. Director James C. Fish, Jr.       130 Table of Contents February 14, 2025 /s/ Gerald Johnson Director   Gerald Johnson   February 14, 2025 /s/ Nazzic S. Keene Director Nazzic S. Keene       February 14, 2025 /s/ David W. MacLennan Director   David W. MacLennan   February 14, 2025 /s/ Judith F. Marks Director Judith F. Marks February 14, 2025 /s/ Debra L. Reed-Klages Presiding Director Debra L. Reed-Klages       February 14, 2025 /s/ Susan C. Schwab Director   Susan C. Schwab             February 14, 2025 /s/ Rayford Wilkins, Jr. Director   Rayford Wilkins, Jr.   131\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SPY. Express as a decimal (e.g., -0.02).", "answer": "-0.0116", "answer_numeric": -0.011616, "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%) = -0.0190.", "metadata": {"var": -0.011616, "cvar": -0.019011, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20251103_0578", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-11-03", "context_summary": "XLV: 60-day return history, mean=0.0018, std=0.0082.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0018, std=0.0082, min=-0.0167, max=0.0244\nMarket regime: bull\nRecent filing/news:\n[SEC 10-K AAPL 2025-10-31] aapl-20250927 false 2025 FY 0000320193 P1Y P1Y P1Y P1Y http://fasb.org/us-gaap/2025#LongTermDebtNoncurrent http://fasb.org/us-gaap/2025#LongTermDebtNoncurrent http://fasb.org/us-gaap/2025#OtherAssetsNoncurrent http://fasb.org/us-gaap/2025#OtherAssetsNoncurrent http://fasb.org/us-gaap/2025#PropertyPlantAndEquipmentNet http://fasb.org/us-gaap/2025#PropertyPlantAndEquipmentNet http://fasb.org/us-gaap/2025#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2025#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2025#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2025#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2025#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2025#OtherLiabilitiesCurrent http://fasb.org/us-gaap/2025#OtherLiabilitiesNoncurrent http://fasb.org/us-gaap/2025#OtherLiabilitiesNoncurrent iso4217:USD xbrli:shares iso4217:USD xbrli:shares xbrli:pure aapl:Customer aapl:Vendor aapl:Subsidiary 0000320193 2024-09-29 2025-09-27 0000320193 us-gaap:CommonStockMember 2024-09-29 2025-09-27 0000320193 aapl:A0.000Notesdue2025Member 2024-09-29 2025-09-27 0000320193 aapl:A1.625NotesDue2026Member 2024-09-29 2025-09-27 0000320193 aapl:A2.000NotesDue2027Member 2024-09-29 2025-09-27 0000320193 aapl:A1.375NotesDue2029Member 2024-09-29 2025-09-27 0000320193 aapl:A3.050NotesDue2029Member 2024-09-29 2025-09-27 0000320193 aapl:A0.500Notesdue2031Member 2024-09-29 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us-gaap:FairValueInputsLevel2Member 2025-09-27 0000320193 us-gaap:AssetBackedSecuritiesMember us-gaap:FairValueInputsLevel2Member 2025-09-27 0000320193 us-gaap:FairValueInputsLevel2Member 2025-09-27 0000320193 us-gaap:CashMember 2024-09-28 0000320193 us-gaap:MoneyMarketFundsMember us-gaap:FairValueInputsLevel1Member 2024-09-28 0000320193 us-gaap:MutualFundMember us-gaap:FairValueInputsLevel1Member 2024-09-28 0000320193 us-gaap:FairValueInputsLevel1Member 2024-09-28 0000320193 us-gaap:USTreasurySecuritiesMember us-gaap:FairValueInputsLevel2Member 2024-09-28 0000320193 us-gaap:USGovernmentAgenciesDebtSecuritiesMember us-gaap:FairValueInputsLevel2Member 2024-09-28 0000320193 us-gaap:ForeignGovernmentDebtSecurities [...TRUNCATED...] overy Policy 10-K 97.1 9/28/24 Apple Inc. | 2025 Form 10-K | 56 Incorporated by Reference Exhibit Number Exhibit Description Form Exhibit Filing Date/ Period End Date 101** Inline XBRL Document Set for the consolidated financial statements and accompanying notes in Part II, Item 8, “Financial Statements and Supplementary Data” of this Annual Report on Form 10-K. 104** Inline XBRL for the cover page of this Annual Report on Form 10-K, included in the Exhibit 101 Inline XBRL Document Set. * Indicates management contract or compensatory plan or arrangement. ** Filed herewith. *** Furnished herewith. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Registrant hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. Item 16.    Form 10-K Summary None. Apple Inc. | 2025 Form 10-K | 57 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Date: October 31, 2025 Apple Inc. By: /s/ Kevan Parekh Kevan Parekh 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 Kevan Parekh, 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 31, 2025 TIMOTHY D. COOK /s/ Kevan Parekh Senior Vice President, Chief Financial Officer (Principal Financial Officer) October 31, 2025 KEVAN PAREKH /s/ Chris Kondo Senior Director of Corporate Accounting (Principal Accounting Officer) October 31, 2025 CHRIS KONDO /s/ Wanda Austin Director October 31, 2025 WANDA AUSTIN /s/ Alex Gorsky Director October 31, 2025 ALEX GORSKY /s/ Andrea Jung Director October 31, 2025 ANDREA JUNG /s/ Arthur D. Levinson Director and Chair of the Board October 31, 2025 ARTHUR D. LEVINSON /s/ Monica Lozano Director October 31, 2025 MONICA LOZANO /s/ Ronald D. Sugar Director October 31, 2025 RONALD D. SUGAR /s/ Susan L. Wagner Director October 31, 2025 SUSAN L. WAGNER Apple Inc. | 2025 Form 10-K | 58\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": "-0.0117", "answer_numeric": -0.011729, "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%) = -0.0152.", "metadata": {"var": -0.011729, "cvar": -0.0152, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20250310_0581", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-03-10", "context_summary": "DOT-USD: 60-day return history, mean=-0.0074, std=0.0494.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0074, std=0.0494, min=-0.1391, max=0.1146\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.1103", "answer_numeric": -0.110271, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1103 (i.e., on a bad day with 5% probability, the loss exceeds 11.03%). CVaR(95%) = -0.1283.", "metadata": {"var": -0.110271, "cvar": -0.128295, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250619_0584", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-06-19", "context_summary": "SOL-USD: 60-day return history, mean=0.0013, std=0.0331.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0013, std=0.0331, min=-0.0622, max=0.1138\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0440", "answer_numeric": -0.043958, "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%) = -0.0570.", "metadata": {"var": -0.043958, "cvar": -0.056988, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250620_0587", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BIL"], "decision_date": "2025-06-20", "context_summary": "BIL: 60-day return history, mean=0.0002, std=0.0002.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=0.0002, std=0.0002, min=0.0000, max=0.0004\nMarket regime: sideways\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BIL. Express as a decimal (e.g., -0.02).", "answer": "0.0000", "answer_numeric": 0.0, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = 0.0000.", "metadata": {"var": 0.0, "cvar": 0.0, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251110_0590", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-11-10", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0054, std=0.0490.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0054, std=0.0490, min=-0.1912, max=0.1091\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0911", "answer_numeric": -0.091058, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0911 (i.e., on a bad day with 5% probability, the loss exceeds 9.11%). CVaR(95%) = -0.1407.", "metadata": {"var": -0.091058, "cvar": -0.140738, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250519_0592", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-05-19", "context_summary": "BTC-USD: 60-day return history, mean=0.0037, std=0.0244.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0037, std=0.0244, min=-0.0634, max=0.0826\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BTC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0326", "answer_numeric": -0.032559, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0326 (i.e., on a bad day with 5% probability, the loss exceeds 3.26%). CVaR(95%) = -0.0455.", "metadata": {"var": -0.032559, "cvar": -0.045484, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250505_0594", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2025-05-05", "context_summary": "QQQ: 60-day return history, mean=-0.0018, std=0.0180.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=-0.0018, std=0.0180, min=-0.0399, max=0.0340\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q AAPL 2025-05-02] aapl-20250329 false 2025 Q2 0000320193 --09-27 P1Y P1Y P1Y P1Y xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure aapl:Vendor 0000320193 2024-09-29 2025-03-29 0000320193 us-gaap:CommonStockMember 2024-09-29 2025-03-29 0000320193 aapl:A0.000Notesdue2025Member 2024-09-29 2025-03-29 0000320193 aapl:A0.875NotesDue2025Member 2024-09-29 2025-03-29 0000320193 aapl:A1.625NotesDue2026Member 2024-09-29 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us-gaap:CommercialPaperMember 2025-03-29 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:CorporateDebtSecuritiesMember 2025-03-29 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:USStatesAndPoliticalSubdivisionsMember 2025-03-29 0000320193 us-gaap:FairValueInputsLevel2Member us-gaap:AssetBackedSecuritiesMember 2025-03-29 0000320193 us-gaap:FairValueInputsLevel2Member 2025-03-29 0000320193 us-gaap:CashMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel1Member us-gaap:MoneyMarketFundsMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel1Member us-gaap:MutualFundMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel1Member 2024-09-28 00003 [...TRUNCATED...] f Proceeds Purchases of Equity Securities by the Issuer and Affiliated Purchasers Share repurchase activity during the three months ended March 29, 2025 was as follows (in millions, except number of shares, which are reflected in thousands, and per-share amounts): Periods Total Number of Shares Purchased Average Price Paid Per Share Total Number of Shares Purchased as Part of Publicly Announced Plans or Programs Approximate Dollar Value of Shares That May Yet Be Purchased Under the Plans or Programs (1) December 29, 2024 to February 1, 2025: Open market and privately negotiated purchases 36,809  $ 235.43  36,809  February 2, 2025 to March 1, 2025: Open market and privately negotiated purchases 31,856  $ 238.07  31,856  March 2, 2025 to March 29, 2025: Open market and privately negotiated purchases 39,455  $ 221.77  39,455  Total 108,120  $ 40,779  (1) As of March 29, 2025, the Company was authorized by the Board of Directors to purchase up to $110 billion of the Company’s common stock under a share repurchase program announced on May 2, 2024, of which $69.2 billion had been utilized. On May 1, 2025, the Company announced the Board of Directors had authorized an additional program to repurchase up to $100 billion of the Company’s common stock. The programs do not obligate the Company to acquire a minimum amount of shares. Under the programs, shares may be repurchased in privately negotiated or open market transactions, including under plans complying with Rule 10b5-1 under the Exchange Act. Item 3.    Defaults Upon Senior Securities None. Item 4.    Mine Safety Disclosures Not applicable. Item 5.    Other Information Insider Trading Arrangements None. Item 6.    Exhibits Incorporated by Reference Exhibit Number Exhibit Description Form Exhibit Filing Date/ Period End Date 31.1* Rule 13a-14(a) / 15d-14(a) Certification of Chief Executive Officer. 31.2* Rule 13a-14(a) / 15d-14(a) Certification of Chief Financial Officer. 32.1** Section 1350 Certifications of Chief Executive Officer and Chief Financial Officer. 101* Inline XBRL Document Set for the condensed consolidated financial statements and accompanying notes in Part I, Item 1, “Financial Statements” of this Quarterly Report on Form 10-Q. 104* Inline XBRL for the cover page of this Quarterly Report on Form 10-Q, included in the Exhibit 101 Inline XBRL Document Set. *    Filed herewith. **    Furnished herewith. Apple Inc. | Q2 2025 Form 10-Q | 22 SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: May 2, 2025 Apple Inc. By: /s/ Kevan Parekh Kevan Parekh Senior Vice President, Chief Financial Officer Apple Inc. | Q2 2025 Form 10-Q | 23\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": "-0.0395", "answer_numeric": -0.039547, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0395 (i.e., on a bad day with 5% probability, the loss exceeds 3.95%). CVaR(95%) = -0.0399.", "metadata": {"var": -0.039547, "cvar": -0.039913, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20250113_0596", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-01-13", "context_summary": "XLU: 60-day return history, mean=-0.0009, std=0.0103.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=-0.0009, std=0.0103, min=-0.0239, max=0.0197\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 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0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XLU. Express as a decimal (e.g., -0.02).", "answer": "-0.0216", "answer_numeric": -0.021592, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0216 (i.e., on a bad day with 5% probability, the loss exceeds 2.16%). CVaR(95%) = -0.0227.", "metadata": {"var": -0.021592, "cvar": -0.022702, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250415_0599", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-04-15", "context_summary": "XLY: 60-day return history, mean=-0.0035, std=0.0167.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=-0.0035, std=0.0167, min=-0.0388, max=0.0338\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-14] [\"Apple upgraded, Wayfair downgraded: Wall Street's top analyst calls The most talked about and market moving research calls around Wall Street are now in one place. Here are today's research calls that investors need to know, as compiled by The Fly.Top 5 Upgrades: KeyBanc upgraded Apple (AAPL) to Sector Weight from Underweight without a price target. Last Friday's announcement of exception from tariffs on smartphones is probably the best-case scenario for Apple, which makes it unlikely KeyBanc's prior downside call will be achieved, the firm tells investors in a research note. Baird upgraded Atlassian (TEAM) to Outperform from Neutral with a price target of $255, down from $320. The firm cites Atlassian's platform opportunity, positive receptivity to its generative artificial intelligence strategy, and a valuation at the lower end of the stock's historical range for the upgrade. Deutsche Bank upgraded Peloton (PTON) to Buy from Hold with a price target of $6.60, down from $8.60. The firm believes the shares have been \\\"unfairly punished\\\" since the fiscal Q2 report, down over 30%. KeyBanc upgraded DuPont (DD) to Overweight from Sector Weight with an $81 price target. The firm cites the selloff in the shares and the Trump administration's recent steps on deescalating the tariff uncertainty for the upgrade. Goldman Sachs double upgraded Choice Hotels (CHH) to Buy from Sell with a price target of $138, down from $141. With an increasingly uncertain demand backdrop, Choice Hotels is one of the most defensive names in the sector given its largely franchise revenue structure and \\\"solid\\\" balance sheet, the firm tells investors in a research note. Top 5 Downgrades: Deutsche Bank downgraded Wayfair (W) to Hold from Buy with a price target of $25, down from $54. Wayfair's business model is \\\"by far the most upended by the new tariff regime\\\" in the internet group, as evidenced by the shares declining 42% since earnings, the firm notes. Deutsche Bank downgraded General Motors (GM) to Hold from Buy with a $43 price target. While stating that the stock already trades at a low multiple, the firm worries GM \\\"may be an impaired asset for several years\\\" given structural uncertainty around U.S. industrial and tariff policy. Wells Fargo downgraded Comcast (CMCSA) to Underweight from Equal Weight with a price target of $31, down from $37. The firm says Comcast is being pulled into a convergence investment cycle with higher mobile costs to re-accelerate broadband, and says it is no longer defensive. Goldman Sachs downgraded Marriott (MAR) to Neutral from Buy with a price target of $245, down from $313. The firm expects the recent macro volatility and consumer pressures to be a headwind to the \\\"macro sensitive segments.\\\" Goldman also downgraded Hilton (HLT) and Hyatt (H) to Neutral from Buy. TD Cowen downgraded Medpace (MEDP) to Hold from Buy with a price target of $328, down from $370. The firm cites the challenging biotech funding and uncertain regulatory env\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": "-0.0365", "answer_numeric": -0.036464, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0365 (i.e., on a bad day with 5% probability, the loss exceeds 3.65%). CVaR(95%) = -0.0388.", "metadata": {"var": -0.036464, "cvar": -0.038816, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20251022_0602", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SCHH"], "decision_date": "2025-10-22", "context_summary": "SCHH: 60-day return history, mean=0.0005, std=0.0082.", "question": "Asset: SCHH\nDaily returns (past 60 days): mean=0.0005, std=0.0082, min=-0.0158, max=0.0182\nMarket regime: bull\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": "-0.0115", "answer_numeric": -0.011541, "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%) = -0.0154.", "metadata": {"var": -0.011541, "cvar": -0.015361, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250207_0606", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2025-02-07", "context_summary": "ICSH: 60-day return history, mean=0.0002, std=0.0003.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0002, std=0.0003, min=-0.0007, max=0.0008\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%) = -0.0003.", "metadata": {"var": -0.000198, "cvar": -0.000332, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250423_0608", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-04-23", "context_summary": "VLUE: 60-day return history, mean=-0.0019, std=0.0132.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0019, std=0.0132, min=-0.0356, max=0.0296\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-22] Is This Fast-Growing Chain the Next Costco? You might not be familiar with BBB Foods (NYSE: TBBB). And that's OK. Most stateside investors aren't familiar with the rapidly expanding chain providing deeply discounted groceries and other household essentials to a widening audience with 2,772 locations at the start of this year. It's North America's fastest growing player in its space, but you have to travel to Mexico to see it in action. BBB is the parent company of Tiendas 3B, a small-box supermarket concept with big-time aspirations. The three Bs stand for Bueno, Bonito, and Barato in Spanish, translating to \"good, pretty, and cheap.\" The concept is a cross between Aldi and Costco, wedged into a smaller convenience store frame. Where to invest $1,000 right now? Our analyst team just revealed what they believe are the 10 best stocks to buy right now. Continue \u00bb It's not a household name, but that's more an opportunity than a problem. With a business model far removed from the intersection of headwinds holding back most retail concepts, it's a good time to look at BBB before it begins pinging on more growth investors' radars. Let's travel south to see why this stock could be headed north. When BBB went public 14 months ago, it became the first Mexican company to go public on a U.S. exchange in six years. It's fair to say that it's been a hit. Underwriters priced the offering at $17.50, and the hard discounter is currently trading nearly 50% higher. It's no broken IPO. BBB is earnings its upticks. Revenue soared 30% last year to reach the U.S. equivalent of nearly $2.8 billion, accelerating in its latest quarter with a 33% jump. Expansion is a big part of the growth story. BBB opened 484 net new stores last year. However, momentum is building at the store level. Comps climbed 13.3% last year, and that's stacked on top of a 17.6% same-store sales surge in 2023. It just turned profitable last year, breaking through with operating free cash the year before that. It's still cranking out negative working capital given the current opportunity for rapid expansion, but that deficit narrowed substantially last year. Supermarket chains historically crank out low net margins. They're in the business of providing modest markups to their goods, making that back by turning over its inventory as much as possible. Costco is a rock star in this realm, but its net margin has failed to break the 3% ceiling in any single year in more than three decades of public trading. Its annual membership fees account for 2% of the revenue mix, and -- like most grocers -- Tiendas 3B does not require paid memberships. BBB pales in comparison with its 0.6% net margin last year, but give it time. It just became profitable last year, and the benefits of scalability should fine the bottom line outpacing the still impressive forecast for top-line jumps. If you think Costco's selling a lot of its own Kirkland products, consider that private label sales account for just a little more than \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": "-0.0227", "answer_numeric": -0.022727, "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%) = -0.0356.", "metadata": {"var": -0.022727, "cvar": -0.035551, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250408_0611", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-04-08", "context_summary": "ADA-USD: 60-day return history, mean=-0.0056, std=0.0598.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0056, std=0.0598, min=-0.1761, max=0.2212\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.1055", "answer_numeric": -0.105513, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1055 (i.e., on a bad day with 5% probability, the loss exceeds 10.55%). CVaR(95%) = -0.1384.", "metadata": {"var": -0.105513, "cvar": -0.138419, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250204_0614", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-02-04", "context_summary": "LINK-USD: 60-day return history, mean=-0.0000, std=0.0602.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0000, std=0.0602, min=-0.1453, max=0.1799\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.1020", "answer_numeric": -0.101983, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1020 (i.e., on a bad day with 5% probability, the loss exceeds 10.20%). CVaR(95%) = -0.1215.", "metadata": {"var": -0.101983, "cvar": -0.121458, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250124_0619", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-01-24", "context_summary": "EFA: 60-day return history, mean=-0.0001, std=0.0079.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=-0.0001, std=0.0079, min=-0.0248, max=0.0200\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q PG 2025-01-22] pg-20241231 0000080424 6/30 2025 Q2 false http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#OtherAssetsNoncurrent http://fasb.org/us-gaap/2024#PrepaidExpenseAndOtherAssetsCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#OtherLiabilitiesNoncurrent 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2024-07-01 2024-12-31 0000080424 us-gaap:CommonStockMember 2023-09-30 0000080424 us-gaap:PreferredStockMember 2023-09-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-09-30 0000080424 pg:ReserveforESOPDebtRetirementMember 2023-09-30 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-09-30 0000080424 us-gaap:TreasuryStockCommonMember 2023-09-30 0000080424 us-gaap:RetainedEarningsMember 2023-09-30 0000080424 us-gaap:NoncontrollingInterestMember 2023-09-30 0000080424 2023-09-30 0000080424 us-gaap:RetainedEarningsMember 2023-10-01 2023-12-31 0000080424 us-gaap:NoncontrollingInterestMember 2023-10-01 2023-12-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-10-01 2023-12-31 0000080424 us-gaap:CommonStockMember 2023-10-01 2023-12-31 0000080424 us-gaap:TreasuryStockCommonMember 2023-10-01 2023-12-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-10-01 2023-12-31 0000080424 us-gaap:PreferredStockMember 2023-10-01 2023-12-31 0000080424 us-gaap:CommonStockMember 2023-12-31 0000080424 us-gaap:PreferredStockMember 2023-12-31 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-12-31 0000080424 pg:ReserveforESOPDebtRetirementMember 2023-12-31 0000080424 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-12-31 0000080424 us-gaap:TreasuryStockCommonMember 2023-12-31 0000080424 us-gaap:RetainedEarningsMember 2023-12-31 0000080424 us-gaap:NoncontrollingInterestMember 2023-12-31 0000080424 2023-12-31 0000080424 us-gaap:CommonStockMember 2023-06-30 0000080424 us-gaap:PreferredStockMember 2023-06-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-06-30 0000080424 pg:R [...TRUNCATED...] 7 billion in fiscal year 2025, notwithstanding any purchases under the Company's compensation and benefit plans. Purchases may be made in the open market and/or private transactions and purchases may be increased, decreased or discontinued at any time without prior notice. The share repurchases are authorized pursuant to a resolution issued by the Company's Board of Directors and are expected to be financed by a combination of operating cash flows and issuance of debt.      Item 5. Other Information During the three months ended December 31, 2024, none of our directors or officers adopted or terminated a \"Rule 10b5-1 trading arrangement\" or \"non-Rule 10b5-1 trading arrangement\" as defined in Item 408 of Regulation S-K. 30 The Procter & Gamble Company Item 6. Exhibits 3.1 Amended Articles of Incorporation (as amended by shareholders at the annual meeting on October 11, 2011 and consolidated by the Board of Directors on April 8, 2016) (Incorporated by reference to Exhibit (3-1) of the Company's Form 10-K for the year ended June 30, 2016) 3.2 Regulations (as approved by the Board of Directors on December 13, 2022, pursuant to authority granted by shareholders at the annual meeting on October 13, 2009) (Incorporated by reference to Exhibit (3-2) of the Company’s Current Report on Form 8-K filed December 13, 2022) 4.1 Indenture, dated as of September 3, 2009, between the Company and Deutsche Bank Trust Company Americas, as Trustee (Incorporated by reference to Exhibit (4-1) of the Company's Annual Report on Form 10-K for the year ended June 30, 2015) 31.1 Rule 13a-14(a)/15d-14(a) Certification – Chief Executive Officer + 31.2 Rule 13a-14(a)/15d-14(a) Certification – Chief Financial Officer + 32.1 Section 1350 Certifications – Chief Executive Officer + 32.2 Section 1350 Certifications – Chief Financial Officer + 101.SCH (1) Inline XBRL Taxonomy Extension Schema Document 101.CAL (1) Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF (1) Inline XBRL Taxonomy Definition Linkbase Document 101.LAB (1) Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE (1) Inline XBRL Taxonomy Extension Presentation Linkbase Document 104  Cover Page Interactive Data File (formatted in Inline XBRL and contained in Exhibit 101) + Filed herewith (1) Pursuant to Rule 406T of Regulation S-T, this information is furnished and not filed for purposes of Sections 11 or 12 of the Securities Act of 1933 and Section 18 of the Securities Exchange Act of 1934, and otherwise is not subject to liability under these sections. Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this Report to be signed on its behalf by the undersigned thereunto duly authorized. THE PROCTER & GAMBLE COMPANY January 22, 2025 /s/ MATTHEW W. JANZARUK Date (Matthew W. Janzaruk) Senior Vice President - Chief Accounting Officer (Principal Accounting Officer)\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EFA. Express as a decimal (e.g., -0.02).", "answer": "-0.0146", "answer_numeric": -0.014603, "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%) = -0.0196.", "metadata": {"var": -0.014603, "cvar": -0.019638, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9044}} +{"id": "T2_all_20250702_0622", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2025-07-02", "context_summary": "IVV: 60-day return history, mean=0.0017, std=0.0121.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0017, std=0.0121, min=-0.0328, max=0.0261\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-07-01] [\"Peter Thiel sold 20 million shares of Facebook just months after its IPO\\u2014but they\\u2019d be worth nearly $15 billion more if he had held on Billionaire Peter Thiel was Facebook\\u2019s first outside investor, but he may now have regrets for how soon he cashed out. Just months after the tech company\\u2019s IPO, he sold millions of shares for $20 each for a sum of $400 million; with the stock now worth 37 times more, he could have been $15 billion richer today. Investing is a game of risk and reward. Get it right, and you could build a billion-dollar fortune. Get it wrong, and it might all go up in smoke. For PayPal cofounder Peter Thiel, being the first outside Facebook investor was hardly a bust\\u2014but there may be some seller\\u2019s remorse. The tech entrepreneur first coughed up $500,000 in 2004 for a 10% stake in the company, just months into its creation\\u2014giving it a value of about $4.9 million. Nearly a decade later, following the company\\u2019s May 2012 IPO, Thiel decided it was time to cash out. Thiel sold about 20.1 million shares in the company\\u2014a majority of his stake\\u2014for $19.27 to $20.69 each, netting him about $400 million at the time. Had he held his shares until today, they would be worth about $14.76 billion (Meta\\u2019s stock price is $736 at the time of writing), a decision that may haunt even one of Silicon Valley\\u2019s savviest investors. What led him to invest in the first place? He believed the college market\\u2014which was Facebook\\u2019s original audience\\u2014had been underestimated. \\u201cI think investors always have a bias to invest in things they themselves use and they undervalue things they don\\u2019t use so there aren\\u2019t many investors who are in college,\\u201d he said to This Week in Startups in 2015. Fortune reached out to Thiel for comment. Despite selling a majority of his stake in the company, the 57-year-old remained heavily involved for many years, serving on the board until 2022. \\u201cPeter has been a valuable member of our board and I\\u2019m deeply grateful for everything he has done for our company\\u2014from believing in us when few others would, to teaching me so many lessons about business, economics, and the world,\\u201d Facebook cofounder and CEO Mark Zuckerberg said at the time of Thiel\\u2019s stepping down. Today, Thiel\\u2019s net worth sits at about $21.7 billion, according to Bloomberg, thanks in part to the billions he made from being the cofounder of PayPal and Palantir. And he\\u2019s not the only investor to have thrived off the success of Facebook; the social network\\u2019s growth has created countless millionaires\\u2014and multiple billionaires. Of course, no one has benefited more financially than Zuckerberg, who is currently the second-richest person in the world, according to Bloomberg, with an estimated net worth of $260 billion. In fact, his worth has increased more than any other billionaire this year, with a year-to-date growth of $52.8 billion. But the compan\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": "-0.0226", "answer_numeric": -0.022608, "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%) = -0.0297.", "metadata": {"var": -0.022608, "cvar": -0.029697, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250210_0624", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-02-10", "context_summary": "EEM: 60-day return history, mean=-0.0003, std=0.0087.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=-0.0003, std=0.0087, min=-0.0236, max=0.0203\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K AMZN 2025-02-07] amzn-20241231 false 2024 FY 0001018724 P3Y P1Y P1Y http://fasb.org/us-gaap/2024#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2024#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 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us-gaap:SalesReturnsAndAllowancesMember 2023-01-01 2023-12-31 0001018724 us-gaap:SalesReturnsAndAllowancesMember 2024-01-01 2024-12-31 0001018724 us-gaap:ShareBasedCompensationAwardTrancheOneMember 2024-01-01 2024-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2022-01-01 2022-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2023-01-01 2023-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2024-01-01 2024-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2024-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsoli [...TRUNCATED...] Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy (incorporated by reference to the Company's Annual Report on Form 10-K for the Year ended December 31, 2023). 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2024, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2024, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 76 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 6, 2025.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 6, 2025.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Andrew Y. Ng Andrew Y. Ng Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 77\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": "-0.0172", "answer_numeric": -0.017191, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0172 (i.e., on a bad day with 5% probability, the loss exceeds 1.72%). CVaR(95%) = -0.0203.", "metadata": {"var": -0.017191, "cvar": -0.02034, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9046}} +{"id": "T2_all_20251215_0627", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-12-15", "context_summary": "LINK-USD: 60-day return history, mean=-0.0042, std=0.0426.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0042, std=0.0426, min=-0.1339, max=0.1179\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0642", "answer_numeric": -0.064245, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0642 (i.e., on a bad day with 5% probability, the loss exceeds 6.42%). CVaR(95%) = -0.0917.", "metadata": {"var": -0.064245, "cvar": -0.091665, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250811_0630", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-08-11", "context_summary": "SOL-USD: 60-day return history, mean=0.0027, std=0.0350.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0027, std=0.0350, min=-0.0785, max=0.1005\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0505", "answer_numeric": -0.050508, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0505 (i.e., on a bad day with 5% probability, the loss exceeds 5.05%). CVaR(95%) = -0.0617.", "metadata": {"var": -0.050508, "cvar": -0.061748, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250411_0633", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-04-11", "context_summary": "LINK-USD: 60-day return history, mean=-0.0051, std=0.0601.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0051, std=0.0601, min=-0.1701, max=0.1774\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0982", "answer_numeric": -0.098244, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0982 (i.e., on a bad day with 5% probability, the loss exceeds 9.82%). CVaR(95%) = -0.1432.", "metadata": {"var": -0.098244, "cvar": -0.143241, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251029_0636", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["GLD"], "decision_date": "2025-10-29", "context_summary": "GLD: 60-day return history, mean=0.0034, std=0.0110.", "question": "Asset: GLD\nDaily returns (past 60 days): mean=0.0034, std=0.0110, min=-0.0240, max=0.0243\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for GLD. Express as a decimal (e.g., -0.02).", "answer": "-0.0185", "answer_numeric": -0.018471, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0185 (i.e., on a bad day with 5% probability, the loss exceeds 1.85%). CVaR(95%) = -0.0223.", "metadata": {"var": -0.018471, "cvar": -0.022258, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250501_0639", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2025-05-01", "context_summary": "MATIC-USD: 57-day return history, mean=-0.0086, std=0.0454.", "question": "Asset: MATIC-USD\nDaily returns (past 57 days): mean=-0.0086, std=0.0454, min=-0.1586, max=0.0741\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for MATIC-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.1002", "answer_numeric": -0.100211, "explanation": "Historical simulation VaR at 95%: sort the 57 daily returns and take the 5th percentile. VaR(95%) = -0.1002 (i.e., on a bad day with 5% probability, the loss exceeds 10.02%). CVaR(95%) = -0.1253.", "metadata": {"var": -0.100211, "cvar": -0.125321, "confidence": 0.95, "n_returns": 57, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250127_0641", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-01-27", "context_summary": "DOT-USD: 60-day return history, mean=-0.0039, std=0.0512.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0039, std=0.0512, min=-0.1824, max=0.0807\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for DOT-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0943", "answer_numeric": -0.094275, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0943 (i.e., on a bad day with 5% probability, the loss exceeds 9.43%). CVaR(95%) = -0.1314.", "metadata": {"var": -0.094275, "cvar": -0.131448, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250508_0644", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-05-08", "context_summary": "EFA: 60-day return history, mean=0.0010, std=0.0117.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0010, std=0.0117, min=-0.0289, max=0.0259\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CAT 2025-05-07] cat-20250331 0000018230 FALSE 12/31 2025 Q1 50 http://fasb.org/us-gaap/2024#Revenues http://fasb.org/us-gaap/2024#Revenues xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cat:group_president cat:segment 0000018230 2025-01-01 2025-03-31 0000018230 us-gaap:CommonStockMember 2025-01-01 2025-03-31 0000018230 cat:A5.3DebenturesDueSeptember152035Member 2025-01-01 2025-03-31 0000018230 2025-03-31 0000018230 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us-gaap:FairValueHedgingMember us-gaap:DesignatedAsHedgingInstrumentMember 2025-01-01 2025-03-31 0000018230 us-gaap:InterestRateContractMember us-gaap:FairValueHedgingMember us-gaap:DesignatedAsHedgingInstrumentMember 2024-01-01 2024-03-31 0000018230 us-gaap:ForeignExchangeContractMember us-gaap:NondesignatedMember 2025-01-01 2025-03-31 0000018230 us-gaap:ForeignExchangeContractMember us-gaap:NondesignatedMember 2024-01-01 2024-03-31 0000018230 us-gaap:CommodityContractMember us-gaap:NondesignatedMember 2025-01-01 2025-03-31 0000018230 us-gaap:CommodityContractMember us-gaap:NondesignatedMember 2024-01-01 2024-03-31 0000018230 us-gaap [...TRUNCATED...] ately 50,000 shares of Caterpillar common stock were purchased by the EIP Plans pursuant to the terms of such plans. Item 5. Other Information During the three months ended March 31, 2025, none of the company’s directors or officers (as defined in Rule 16a-1(f) of the Securities Exchange Act of 1934) adopted , terminated or modified a Rule 10b5-1 trading arrangement or non-Rule 10b5-1 trading arrangement (as such terms are defined in Item 408 of Regulation S-K of the Securities Act of 1933). 67 Table of Contents Item 6. Exhibits 31.1 Certification of Chief Executive Officer of Caterpillar Inc., as required pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer of Caterpillar Inc., as required pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32 Certification of Chief Executive Officer of Caterpillar Inc. and Chief Financial Officer of Caterpillar Inc., as required pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS Inline XBRL Instance Document (the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document) 101.SCH   Inline XBRL Taxonomy Extension Schema Document 101.CAL   Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF   Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB   Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE   Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive File (embedded within the Inline XBRL document and included in Exhibit 101) The agreements and other documents filed as exhibits to this report are not intended to provide factual information or other disclosure other than with respect to the terms of the agreements or other documents themselves, and you should not rely on them for that purpose. In particular, any representations and warranties made by us in these agreements or other documents were made solely within the specific context of the relevant agreement or document and may not describe the actual state of affairs as of the date they were made or at any other time. 68 Table of Contents SIGNATURES   Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       CATERPILLAR INC.               May 7, 2025 /s/ Joseph E. Creed Chief Executive Officer   Joseph E. Creed         May 7, 2025 /s/ Andrew R.J. Bonfield Chief Financial Officer   Andrew R.J. Bonfield               May 7, 2025 /s/ Derek Owens Chief Legal Officer and General Counsel   Derek Owens             May 7, 2025 /s/ William E. Schaupp Vice President and Chief Accounting Officer   William E. Schaupp   69\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": "-0.0213", "answer_numeric": -0.021321, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0213 (i.e., on a bad day with 5% probability, the loss exceeds 2.13%). CVaR(95%) = -0.0257.", "metadata": {"var": -0.021321, "cvar": -0.025725, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250428_0647", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-04-28", "context_summary": "LINK-USD: 60-day return history, mean=0.0010, std=0.0585.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0010, std=0.0585, min=-0.1701, max=0.1774\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0822", "answer_numeric": -0.082212, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0822 (i.e., on a bad day with 5% probability, the loss exceeds 8.22%). CVaR(95%) = -0.1303.", "metadata": {"var": -0.082212, "cvar": -0.130344, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250828_0650", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-08-28", "context_summary": "ETH-USD: 60-day return history, mean=0.0111, std=0.0402.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0111, std=0.0402, min=-0.0851, max=0.1440\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ETH-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0443", "answer_numeric": -0.044338, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0443 (i.e., on a bad day with 5% probability, the loss exceeds 4.43%). CVaR(95%) = -0.0656.", "metadata": {"var": -0.044338, "cvar": -0.065623, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251210_0653", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-12-10", "context_summary": "EFA: 60-day return history, mean=0.0003, std=0.0070.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0003, std=0.0070, min=-0.0186, max=0.0153\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 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0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for EFA. Express as a decimal (e.g., -0.02).", "answer": "-0.0131", "answer_numeric": -0.013063, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0131 (i.e., on a bad day with 5% probability, the loss exceeds 1.31%). CVaR(95%) = -0.0152.", "metadata": {"var": -0.013063, "cvar": -0.015205, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20251002_0655", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2025-10-02", "context_summary": "ACWI: 60-day return history, mean=0.0013, std=0.0054.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0013, std=0.0054, min=-0.0127, max=0.0164\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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": "-0.0059", "answer_numeric": -0.005862, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0059 (i.e., on a bad day with 5% probability, the loss exceeds 0.59%). CVaR(95%) = -0.0088.", "metadata": {"var": -0.005862, "cvar": -0.008757, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250526_0658", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-05-26", "context_summary": "XRP-USD: 60-day return history, mean=0.0007, std=0.0388.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0007, std=0.0388, min=-0.1053, max=0.1433\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0558", "answer_numeric": -0.055836, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0558 (i.e., on a bad day with 5% probability, the loss exceeds 5.58%). CVaR(95%) = -0.0767.", "metadata": {"var": -0.055836, "cvar": -0.076741, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250731_0661", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-07-31", "context_summary": "LINK-USD: 60-day return history, mean=0.0046, std=0.0372.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0046, std=0.0372, min=-0.0752, max=0.1049\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0594", "answer_numeric": -0.05942, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0594 (i.e., on a bad day with 5% probability, the loss exceeds 5.94%). CVaR(95%) = -0.0682.", "metadata": {"var": -0.05942, "cvar": -0.068153, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250515_0664", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-05-15", "context_summary": "USMV: 60-day return history, mean=-0.0001, std=0.0094.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=-0.0001, std=0.0094, min=-0.0253, max=0.0221\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-14] 1 Surging Stock on Our Buy List and 2 to Brush Off Exciting developments are taking place for the stocks in this article. They\u2019ve all surged ahead of the broader market over the last month as catalysts such as new products and positive media coverage have propelled their returns. But not every company with momentum is a long-term winner, and plenty of investors have lost money betting on short-term fads. Keeping that in mind, here is one stock we think lives up to the hype and two that may correct. One-Month Return: +13.8% Headquartered in NYC, Genco (NYSE:GNK) is a shipping company that transports dry bulk cargo along worldwide maritime routes. Why Do We Steer Clear of GNK? Sluggish trends in its owned vessels suggest customers aren\u2019t adopting its solutions as quickly as the company hoped Earnings per share have contracted by 45.6% annually over the last two years, a headwind for returns as stock prices often echo long-term EPS performance Capital intensity has ramped up over the last five years as its free cash flow margin decreased by 6.5 percentage points Genco\u2019s stock price of $14.56 implies a valuation ratio of 22.2x forward P/E. Read our free research report to see why you should think twice about including GNK in your portfolio, it\u2019s free. One-Month Return: +30.4% Established in 2006, SolarEdge (NASDAQ: SEDG) creates advanced systems to improve the efficiency of solar panels. Why Should You Sell SEDG? Demand for its offerings was relatively low as its number of megawatts shipped has underwhelmed Eroding returns on capital from an already low base indicate that management\u2019s recent investments are destroying value Limited cash reserves may force the company to seek unfavorable financing terms that could dilute shareholders SolarEdge is trading at $18.15 per share, or 0.9x forward price-to-sales. Dive into our free research report to see why there are better opportunities than SEDG. One-Month Return: +21.7% Founded by Brian Chesky and Joe Gebbia in their San Francisco apartment, Airbnb (NASDAQ:ABNB) is the world\u2019s largest online marketplace for lodging, primarily homestays. Why Will ABNB Beat the Market? Has the opportunity to boost monetization through new features and premium offerings as its nights and experiences booked have grown by 10.4% annually over the last two years Earnings per share have massively outperformed its peers over the last three years, increasing by 49.4% annually Strong free cash flow margin of 39.7% enables it to reinvest or return capital consistently At $137.83 per share, Airbnb trades at 20.5x forward EV/EBITDA. Is now the time to initiate a position? See for yourself in our in-depth research report, it\u2019s free. Donald Trump\u2019s victory in the 2024 U.S. Presidential Election sent major indices to all-time highs, but stocks have retraced as investors debate the health of the economy and the potential impact of tariffs. While this leaves much uncertainty around 2025, a few companies are poised for long-term gains regar\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": "-0.0139", "answer_numeric": -0.013903, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0139 (i.e., on a bad day with 5% probability, the loss exceeds 1.39%). CVaR(95%) = -0.0200.", "metadata": {"var": -0.013903, "cvar": -0.020004, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250815_0667", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-08-15", "context_summary": "SOL-USD: 60-day return history, mean=0.0045, std=0.0368.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0045, std=0.0368, min=-0.0785, max=0.1005\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0471", "answer_numeric": -0.047112, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0471 (i.e., on a bad day with 5% probability, the loss exceeds 4.71%). CVaR(95%) = -0.0615.", "metadata": {"var": -0.047112, "cvar": -0.061462, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250905_0669", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-09-05", "context_summary": "LINK-USD: 60-day return history, mean=0.0098, std=0.0529.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0098, std=0.0529, min=-0.0939, max=0.1341\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0697", "answer_numeric": -0.069662, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0697 (i.e., on a bad day with 5% probability, the loss exceeds 6.97%). CVaR(95%) = -0.0854.", "metadata": {"var": -0.069662, "cvar": -0.085372, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250418_0671", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2025-04-18", "context_summary": "ACWI: 60-day return history, mean=-0.0017, std=0.0120.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=-0.0017, std=0.0120, min=-0.0309, max=0.0250\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-17] Trump Trade: Nvidia sees Q1 charges of $5.5B due to H20 restrictions Catch up on the top industries and stocks that were impacted, or were predicted to be impacted, by the comments, actions and policies of President Donald Trump with this daily recap compiled by The Fly: Discover outperforming stocks and invest smarter with Top Smart Score Stocks. Filter, analyze, and streamline your search for investment opportunities using Tipranks' Stock Screener. RESTRICTIONS: In a regulatory filing, Nvidia (NVDA) stated, \u201cOn April 9, 2025, the U.S. government, or USG, informed NVIDIA Corporation, or the company, that the USG requires a license for export to China (including Hong Kong and Macau) and D:5 countries, or to companies headquartered or with an ultimate parent therein, of the Company\u2019s H20 integrated circuits and any other circuits achieving the H20\u2019s memory bandwidth, interconnect bandwidth, or combination thereof. The USG indicated that the license requirement addresses the risk that the covered products may be used in, or diverted to, a supercomputer in China. On April 14, 2025, the USG informed the company that the license requirement will be in effect for the indefinite future. The company\u2019s first quarter of fiscal year 2026 ends on April 27, 2025. First quarter results are expected to include up to approximately $5.5 billion of charges associated with H20 products for inventory, purchase commitments, and related reserves.\u201d Wells Fargo notes that following Nvidia\u2019s 8K announcement last night, AMD (AMD) has filed an 8K this morning announcing that it too expects new U.S. Government license controls on GPU sales into China to impact the company\u2019s MI308X. AMD says that while it expects to apply for licenses, there are no assurances that licenses will be granted. Therefore, the company is announcing that it expects to take up to an $800M inventory, purchase commitment, and related reserve charge, likely in Q2, says Wells. The firm has an Overweight rating on AMD with a price target of $140. PARTS FROM CHINA: Tesla\u2019s (TSLA) plans to ship parts from China for the Cybercab and Semi electric trucks in the U.S. were suspended after President Donald Trump raised tariffs on Chinese goods, Reuters reports, citing a person with direct knowledge. The move may disrupt the company\u2019s plans to begin mass production of the models. Tesla was prepared to absorb the costs when Trump imposed the 34% tariff on Chinese goods but could not do so when the tariffs were increased, leaving shipping plans suspended, the person told Reuters. DELISTING: Officials in President Donald Trump\u2019s administration and the president\u2019s supporters are \u201cleaning further into the prospect of delisting the nearly 300 Chinese companies that trade on U.S. exchanges,\u201d according to a recap from Politico. On April 10, Fox Business Network\u2019s Charles Gasparino previously reported, citing sources, that the Trump administration was proceeding toward a possible delisting of Chinese public company share\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": "-0.0264", "answer_numeric": -0.026435, "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%) = -0.0309.", "metadata": {"var": -0.026435, "cvar": -0.030947, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250703_0675", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-07-03", "context_summary": "LINK-USD: 60-day return history, mean=0.0000, std=0.0419.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0000, std=0.0419, min=-0.0759, max=0.1469\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0597", "answer_numeric": -0.059724, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0597 (i.e., on a bad day with 5% probability, the loss exceeds 5.97%). CVaR(95%) = -0.0718.", "metadata": {"var": -0.059724, "cvar": -0.071834, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20251006_0677", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-10-06", "context_summary": "BNB-USD: 60-day return history, mean=0.0073, std=0.0285.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0073, std=0.0285, min=-0.0718, max=0.0910\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BNB-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0349", "answer_numeric": -0.034911, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0349 (i.e., on a bad day with 5% probability, the loss exceeds 3.49%). CVaR(95%) = -0.0553.", "metadata": {"var": -0.034911, "cvar": -0.055281, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250226_0680", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-02-26", "context_summary": "XLB: 59-day return history, mean=-0.0010, std=0.0091.", "question": "Asset: XLB\nDaily returns (past 59 days): mean=-0.0010, std=0.0091, min=-0.0288, max=0.0221\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-K CVX 2025-02-21] cvx-20241231 0000093410 false 2024 FY 367 http://fasb.org/us-gaap/2024#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2024#PropertyPlantAndEquipmentAndFinanceLeaseRightOfUseAssetAfterAccumulatedDepreciationAndAmortization http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2024#AccruedLiabilitiesCurrent 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us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2021-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2021-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2021-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2022-01-01 2022-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-01-01 2022-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2022-01-01 2022-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2022-01-01 2022-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2022-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2022-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2022-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealized [...TRUNCATED...] Power of Attorney for certain directors of Chevron Corporation, authorizing the signing of the Annual Report on Form 10-K on their behalf. 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer (page E-3). 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer (page E-4).   32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer (page E-5).   32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer (page E-6). 97.1+ Chevron Corporation Dodd-Frank Clawback Policy , filed as Exh i bit 97.1 to Ch ev ron Corporation ’ s Annual Report on Form 10-K for the year ended December 31, 2023, and incorporated herein by r eference . 99.1* Definitions of Selected Energy and Financial Terms (pages E-7 through E-10). 101* Interactive data files (formatted as Inline XBRL). 104* Cover Page Interactive Data File (contained in Exhibit 101).   ___________________________________________ + Indicates a management contract or compensatory plan or arrangement. *      Filed herewith. **      Furnished herewith. Pursuant to Item 601(b)(4) of Regulation S-K, certain instruments with respect to the company’s long-term debt are not filed with this Annual Report on Form 10-K. A copy of any such instrument will be furnished to the Securities and Exchange Commission upon request. 120 Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on the 21st day of February, 2025.  Chevron Corporation   By: /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities indicated on the 21st day of February, 2025.   Principal Executive Officer (and Director) /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer Principal Financial Officer /s/ EIMEAR P. BONNER Eimear P. Bonner, Vice President and Chief Financial Officer Principal Accounting Officer /s/ ALANA K. KNOWLES Alana K. Knowles, Vice President and Controller * By:  /s/ MARY A. FRANCIS Mary A. Francis, Attorney-in-Fact Directors WANDA M. AUSTIN * Wanda M. Austin JOHN B. FRANK * John B. Frank ALICE P. GAST * Alice P. Gast ENRIQUE HERNANDEZ, JR. * Enrique Hernandez, Jr. MARILLYN A. HEWSON * Marillyn A. Hewson JON M. HUNTSMAN JR. * Jon M. Huntsman Jr. CHARLES W. MOORMAN * Charles W. Moorman DAMBISA F. MOYO * Dambisa F. Moyo DEBRA REED-KLAGES * Debra Reed-Klages D. JAMES UMPLEBY III * D. James Umpleby III CYNTHIA J. WARNER * Cynthia J. Warner 121\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": "-0.0133", "answer_numeric": -0.013269, "explanation": "Historical simulation VaR at 95%: sort the 59 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%) = -0.0203.", "metadata": {"var": -0.013269, "cvar": -0.020267, "confidence": 0.95, "n_returns": 59, "has_text": true, "text_chars": 9045}} +{"id": "T2_all_20250205_0683", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["PALL"], "decision_date": "2025-02-05", "context_summary": "PALL: 60-day return history, mean=0.0020, std=0.0168.", "question": "Asset: PALL\nDaily returns (past 60 days): mean=0.0020, std=0.0168, min=-0.0359, max=0.0580\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": "-0.0256", "answer_numeric": -0.025632, "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%) = -0.0310.", "metadata": {"var": -0.025632, "cvar": -0.030959, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20250103_0686", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-01-03", "context_summary": "LINK-USD: 60-day return history, mean=0.0115, std=0.0649.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0115, std=0.0649, min=-0.1453, max=0.1799\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for LINK-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0732", "answer_numeric": -0.073186, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0732 (i.e., on a bad day with 5% probability, the loss exceeds 7.32%). CVaR(95%) = -0.1103.", "metadata": {"var": -0.073186, "cvar": -0.110322, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250723_0689", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-07-23", "context_summary": "XLB: 60-day return history, mean=0.0017, std=0.0094.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0017, std=0.0094, min=-0.0208, max=0.0255\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-22] [\"CoreWeave, Opendoor, Apple: Trending Tickers CoreWeave (CRWV) stock pops after announcing a $1.5 billion bond sale to fund its debt payments. Opendoor (OPEN) stock skyrockets after more than doubling the week prior. Apple (AAPL) is reportedly working on a foldable phone, according to TF International Securities analysts and Bloomberg. To watch more expert insights and analysis on the latest market action, check out more Market Catalysts here.\", \"CTL Expands Leadership Team with New Sales Executive West Interian brings 30+ years of EdTech sales experience; will help CTL expand into education and commercial markets BEAVERTON, Ore., July 22, 2025 /PRNewswire/ -- CTL Corporation, a global cloud-computing solution leader for education and enterprise, announced today the appointment of West Interian as senior vice president of sales. Interian brings decades of B2B technology sales experience to CTL, including a strong background in EdTech, a proven record of penetrating new commercial markets, and sales leadership roles at Apple, Xerox, and Cisco. \\\"As CTL continues to grow and evolve, West will help us build on our existing foundation of sales as well as implement a unified and coordinated sales strategy across our education and commercial markets both here and abroad,\\\" said Jason Mendenhall, CEO of CTL. \\\"We are excited to welcome him to the team and look forward to the continued growth trajectory ahead.\\\" \\\"CTL is well-positioned within the EdTech community as a provider of ChromeOS products and services, and I'm looking forward to scaling this solution set both within the EdTech market and beyond to enterprise markets such as healthcare, retail, hospitality, and others,\\\" said West Interian, senior vice president of sales at CTL. \\\"Cloud computing has never been more pertinent to more industries, and I look forward to bringing CTL's solutions to additional markets.\\\" Interian joins the CTL leadership team with a distinguished background in sales. Particularly in the K-12 education market. His career includes sales leadership roles at Apple Education, where he helped launch the iPad in schools, as well as senior roles at Cisco and Xerox. A passionate advocate for educational technology, he has also served as senior vice president of sales at EdTech innovators including VEX Robotics and Ozobot. He also serves on the board of the PS I Love You Foundation, supporting at-risk youth. Mr. Interian assumed his role at CTL on July 14, 2025, and is currently working with the existing sales teams. About CTL CTL is a global computing solutions manufacturer empowering success at school and in the workplace with award-winning technology products and comprehensive lifecycle services. For more than 35 years, customers in more than 65 countries have relied on CTL's award-winning offerings of Chromebooks, Chromeboxes, and video collaboration tools, as well as ITAD, solution configuration, and maintenance services. As a technology partner, CTL serves as a solution\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": "-0.0118", "answer_numeric": -0.011803, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0118 (i.e., on a bad day with 5% probability, the loss exceeds 1.18%). CVaR(95%) = -0.0160.", "metadata": {"var": -0.011803, "cvar": -0.015969, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250211_0692", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-02-11", "context_summary": "ADA-USD: 60-day return history, mean=-0.0065, std=0.0475.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0065, std=0.0475, min=-0.1071, max=0.1342\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for ADA-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0860", "answer_numeric": -0.086007, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0860 (i.e., on a bad day with 5% probability, the loss exceeds 8.60%). CVaR(95%) = -0.1004.", "metadata": {"var": -0.086007, "cvar": -0.10036, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250321_0695", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-03-21", "context_summary": "AVAX-USD: 60-day return history, mean=-0.0091, std=0.0555.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0091, std=0.0555, min=-0.1606, max=0.1404\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.1208", "answer_numeric": -0.12084, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.1208 (i.e., on a bad day with 5% probability, the loss exceeds 12.08%). CVaR(95%) = -0.1421.", "metadata": {"var": -0.12084, "cvar": -0.14214, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250110_0698", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-01-10", "context_summary": "AVAX-USD: 60-day return history, mean=0.0039, std=0.0623.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0039, std=0.0623, min=-0.1614, max=0.2028\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for AVAX-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0917", "answer_numeric": -0.091665, "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%) = -0.1254.", "metadata": {"var": -0.091665, "cvar": -0.12539, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250728_0701", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-07-28", "context_summary": "XLU: 60-day return history, mean=0.0012, std=0.0085.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0012, std=0.0085, min=-0.0184, max=0.0211\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-25] [\"Warren Buffett's Favorite Stock Is Up Over 4,470,000% Since 1965, but You Won't Find It in His Portfolio Warren Buffett's simple investment strategy has propelled Berkshire Hathaway to market-beating returns since 1965. Buffett has invested in over 100 different companies, including giants like Apple, Coca-Cola, GEICO Insurance, and American Express. But Buffett has plowed more money into one particular company than any other, and investors won't find it listed in Berkshire's portfolio. 10 stocks we like better than Berkshire Hathaway \\u203a In 1965, Warren Buffett took a controlling stake in a struggling textiles company called Berkshire Hathaway (NYSE: BRK.A)(NYSE: BRK.B). After realizing its operations were no longer viable, he converted it into a holding company for his various investments. Berkshire now manages numerous wholly owned subsidiaries and a $292 billion portfolio of publicly traded stocks and securities. Despite owning a stake in more than a hundred different companies during the past 60 years, Buffett has never expressly named a favorite. But if we follow the money, it's clear he likes some much more than others. For example, he bought about $38 billion worth of Apple (NASDAQ: AAPL) stock on Berkshire's behalf between 2016 and 2023, which is the most he has ever invested in a single company. With that said, Buffett has spent more than twice that much buying shares in another name that has soared by more than 4,470,000% since 1965 -- except you won't find it in Berkshire's portfolio. Buffett likes to invest in companies with steady growth, reliable profits, and strong management teams. He especially likes those with shareholder-friendly initiatives like dividend plans and stock buyback programs, because they compound his money significantly faster. But his most important weapon is time -- when he buys a stake in a company, his preferred holding period is forever. Berkshire's Coca-Cola (NYSE: KO) investment is a great example of Buffett's strategy in action. He bought 400 million shares of the soft-drink giant between 1988 and 1994, for a total cost of $1.3 billion. He has never sold a single share, and today that position is worth a whopping $27.8 billion. Plus, it paid Berkshire $776 million in dividends in 2024, so the conglomerate now recoups its original investment every two years or so. Apple is another company that ticks all of Buffett's boxes, and it has netted Berkshire an enormous profit to date. Heading into 2024, Berkshire's $38 billion investment was worth more than $170 billion and accounted for half of the value of the conglomerate's entire portfolio of stocks and securities. Buffett and his team have since sold two-thirds of Berkshire's Apple stake to cash in some of those gains and to reduce risk. Kraft Heinz, Visa, Bank of America, and American Express are just a few of Berkshire's other long-term holdings that continue to match Buffett's criteria. While Buffett's $38 billion Apple investment remains his biggest\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": "-0.0141", "answer_numeric": -0.014073, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0141 (i.e., on a bad day with 5% probability, the loss exceeds 1.41%). CVaR(95%) = -0.0168.", "metadata": {"var": -0.014073, "cvar": -0.016807, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 3020}} +{"id": "T2_all_20250930_0706", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-09-30", "context_summary": "SOL-USD: 60-day return history, mean=0.0044, std=0.0418.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0044, std=0.0418, min=-0.0915, max=0.1130\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for SOL-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0560", "answer_numeric": -0.056, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0560 (i.e., on a bad day with 5% probability, the loss exceeds 5.60%). CVaR(95%) = -0.0832.", "metadata": {"var": -0.056, "cvar": -0.083231, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250507_0709", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-05-07", "context_summary": "XRP-USD: 60-day return history, mean=-0.0009, std=0.0408.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0009, std=0.0408, min=-0.1053, max=0.1433\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for XRP-USD. Express as a decimal (e.g., -0.02).", "answer": "-0.0546", "answer_numeric": -0.05462, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0546 (i.e., on a bad day with 5% probability, the loss exceeds 5.46%). CVaR(95%) = -0.0813.", "metadata": {"var": -0.05462, "cvar": -0.081333, "confidence": 0.95, "n_returns": 60, "has_text": true, "text_chars": 20}} +{"id": "T2_all_20250325_0712", "template": "T2", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["INDS"], "decision_date": "2025-03-25", "context_summary": "INDS: 60-day return history, mean=0.0007, std=0.0109.", "question": "Asset: INDS\nDaily returns (past 60 days): mean=0.0007, std=0.0109, min=-0.0231, max=0.0249\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": "-0.0162", "answer_numeric": -0.016157, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = -0.0162 (i.e., on a bad day with 5% probability, the loss exceeds 1.62%). CVaR(95%) = -0.0192.", "metadata": {"var": -0.016157, "cvar": -0.019231, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T2_all_20251021_0715", "template": "T2", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BIL"], "decision_date": "2025-10-21", "context_summary": "BIL: 60-day return history, mean=0.0002, std=0.0001.", "question": "Asset: BIL\nDaily returns (past 60 days): mean=0.0002, std=0.0001, min=0.0000, max=0.0004\nMarket regime: bull\n\nUsing the historical simulation method, compute the 1-day VaR at 95% confidence level for BIL. Express as a decimal (e.g., -0.02).", "answer": "0.0000", "answer_numeric": 0.0, "explanation": "Historical simulation VaR at 95%: sort the 60 daily returns and take the 5th percentile. VaR(95%) = 0.0000 (i.e., on a bad day with 5% probability, the loss exceeds 0.00%). CVaR(95%) = 0.0000.", "metadata": {"var": 0.0, "cvar": 0.0, "confidence": 0.95, "n_returns": 60, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251226_0002", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DBC"], "decision_date": "2025-12-26", "context_summary": "DBC: 60-day history, VaR(99%)=-0.0161, max drawdown threshold=10%.", "question": "Asset: DBC\nDaily returns (past 60 days): mean=0.0011, std=0.0083, worst_day=-0.0213\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 = 0.0161 (i.e., a 1.61% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0161 = 6.2262, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016061, "expected_loss": 0.016061, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251027_0005", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-10-27", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0899, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0008, std=0.0332, worst_day=-0.1204\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0899 (i.e., a 8.99% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0899 = 1.1126, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.089876, "expected_loss": 0.089876, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251209_0008", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-12-09", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1287, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0085, std=0.0476, worst_day=-0.1761\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7770", "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": true, "text_chars": 20}} +{"id": "T3_all_20250716_0010", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-07-16", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0190, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0025, std=0.0095, worst_day=-0.0210\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-15] [\"Jamf Announces Strategic Reinvestment Plan Q2 2025 Financial Results Expected to Exceed High End of Guidance Ranges MINNEAPOLIS, July 15, 2025 (GLOBE NEWSWIRE) -- Jamf (NASDAQ: JAMF), the standard in managing and securing Apple at work, today announced a strategic reinvestment plan to help drive long-term growth, improve operational efficiency and enhance shareholder value. Jamf\\u2019s recent comprehensive systems update, spanning both front- and back-office operations, has provided enhanced insights into Jamf\\u2019s business and growth opportunities. As a result, Jamf is embarking on a strategic reinvestment plan to support the continued success of the business. This plan includes strategic reallocation of resources to allow for investment in areas with the highest potential to fuel growth and drive additional operational leverage in the business. Two key focus areas are: 1. Go-To-Market Enhancement Jamf is taking steps to realign its go-to-market organization to allow for investment in areas that have the greatest opportunity for growth and align with our platform strategy via the Jamf for Mac, Jamf for Mobile, Jamf for K-12, and Jamf for SMB solutions. Enhance growth in Enterprise: increasing investment and resources to support Enterprise customers, which deliver higher growth, stronger retention, and greater return on investment. Simplify approach to SMB: scaling through the channel while also developing a more automated customer solution and experience to deliver greater customer value and improve operational efficiency. 2. AI Investments In addition to the efficiencies experienced over the last year from deploying AI within the sales, product and customer success groups, Jamf is further accelerating investments in AI capabilities that improve the customer experience in the Jamf product platform and drive further productivity enhancements by accelerating delivery of AI- and automation-driven solutions across the entire organization. In order to facilitate the strategic reinvestment plan, the Company will reduce its workforce by approximately 6.4%. The Company will reduce roles across its go-to-market and other functions to align with the strategic reinvestment plan, as well as reducing spans and layers throughout the organization. Jamf currently estimates that it will incur charges of approximately $11.0 to $12.5 million in connection with the workforce reduction, consisting of cash expenditures for notice period and severance payments, employee benefits, and related costs. The Company expects that most of the charges will be incurred in the third quarter of 2025 and that the execution of the Plan will be substantially complete by the end of the fourth quarter of 2025. The Company intends to exclude the charges associated with the workforce reduction from certain of its non-GAAP financial measures. Q2 2025 Financial Results Expected to Exceed High End of Guidance Ranges Jamf expects to exceed the high end of the guidance ranges previously \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 = 0.0190 (i.e., a 1.90% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0190 = 5.2674, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018985, "expected_loss": 0.018985, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250424_0013", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-04-24", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0263, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0006, std=0.0118, worst_day=-0.0289\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent 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us-gaap:EmployeeStockOptionMember ba:AntidilutiveOrPerformanceConditionNotMetMember 2025-01-01 2025-03-31 0000012927 us-gaap:Employee [...TRUNCATED...] 160;Yet be Purchased Under the Plans or Programs 1/1/2025 thru 1/31/2025 33,204  $171.87  2/1/2025 thru 2/28/2025 46,784  183.15  3/1/2025 thru 3/31/2025 842  158.96  Total 80,830  $178.26  (1) A total of 80,830 shares were transferred to us from employees in satisfaction of minimum tax withholding obligations associated with the vesting of restricted stock units during the period. We did not purchase any shares of our common stock in the open market pursuant to a repurchase program. Item 3. Defaults Upon Senior Securities Not applicable. Item 4. Mine Safety Disclosures Not applicable. 51 Table of Contents Item 5. Other Information During the three months ended March 31, 2025, none of our directors or officers adopted , modified or terminated a “Rule 10b5-1 trading arrangement” or a “non-Rule 10b5-1 trading arrangement” as such terms are defined under Item 408 of Regulation S-K. 52 Table of Contents Item 6. Exhibits 10.1 Form of U.S. Notice of Terms of Long-Term Incentive Non-Qualified Premium-Priced Stock Option* 10.2 Form of Non-U.S. Notice of Terms of Long-Term Incentive Non-Qualified Premium-Priced Stock Option* 10.3 Form of U.S. Notice of Terms of Long-Term Incentive Restricted Stock Units* 10.4 Form of Non-U.S. Notice of Terms of Long-Term Incentive Restricted Stock Units* 10.5 Form of U.S. Notice of Terms of Supplemental Restricted Stock Units* 15 Letter from Independent Registered Public Accounting Firm regarding unaudited interim financial information 31.1 Certification of Chief Executive Officer pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certification of Chief Executive Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 32.2 Certification of Chief Financial Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File (formatted as inline XBRL and contained in Exhibit 101) * Management contract or compensatory plan 53 Table of Contents Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. THE BOEING COMPANY (Registrant) April 23, 2025 /s/ Michael J. Cleary (Date) Michael J. Cleary Senior Vice President and Controller 54\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 = 0.0263 (i.e., a 2.63% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0263 = 3.8082, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026259, "expected_loss": 0.026259, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9044}} +{"id": "T3_all_20250711_0016", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-07-11", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0808, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0022, std=0.0408, worst_day=-0.0876\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0808 (i.e., a 8.08% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0808 = 1.2381, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.080772, "expected_loss": 0.080772, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250421_0019", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-04-21", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0372, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=-0.0010, std=0.0137, worst_day=-0.0372\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-17] Trump Trade: Nvidia sees Q1 charges of $5.5B due to H20 restrictions Catch up on the top industries and stocks that were impacted, or were predicted to be impacted, by the comments, actions and policies of President Donald Trump with this daily recap compiled by The Fly: Discover outperforming stocks and invest smarter with Top Smart Score Stocks. Filter, analyze, and streamline your search for investment opportunities using Tipranks' Stock Screener. RESTRICTIONS: In a regulatory filing, Nvidia (NVDA) stated, \u201cOn April 9, 2025, the U.S. government, or USG, informed NVIDIA Corporation, or the company, that the USG requires a license for export to China (including Hong Kong and Macau) and D:5 countries, or to companies headquartered or with an ultimate parent therein, of the Company\u2019s H20 integrated circuits and any other circuits achieving the H20\u2019s memory bandwidth, interconnect bandwidth, or combination thereof. The USG indicated that the license requirement addresses the risk that the covered products may be used in, or diverted to, a supercomputer in China. On April 14, 2025, the USG informed the company that the license requirement will be in effect for the indefinite future. The company\u2019s first quarter of fiscal year 2026 ends on April 27, 2025. First quarter results are expected to include up to approximately $5.5 billion of charges associated with H20 products for inventory, purchase commitments, and related reserves.\u201d Wells Fargo notes that following Nvidia\u2019s 8K announcement last night, AMD (AMD) has filed an 8K this morning announcing that it too expects new U.S. Government license controls on GPU sales into China to impact the company\u2019s MI308X. AMD says that while it expects to apply for licenses, there are no assurances that licenses will be granted. Therefore, the company is announcing that it expects to take up to an $800M inventory, purchase commitment, and related reserve charge, likely in Q2, says Wells. The firm has an Overweight rating on AMD with a price target of $140. PARTS FROM CHINA: Tesla\u2019s (TSLA) plans to ship parts from China for the Cybercab and Semi electric trucks in the U.S. were suspended after President Donald Trump raised tariffs on Chinese goods, Reuters reports, citing a person with direct knowledge. The move may disrupt the company\u2019s plans to begin mass production of the models. Tesla was prepared to absorb the costs when Trump imposed the 34% tariff on Chinese goods but could not do so when the tariffs were increased, leaving shipping plans suspended, the person told Reuters. DELISTING: Officials in President Donald Trump\u2019s administration and the president\u2019s supporters are \u201cleaning further into the prospect of delisting the nearly 300 Chinese companies that trade on U.S. exchanges,\u201d according to a recap from Politico. On April 10, Fox Business Network\u2019s Charles Gasparino previously reported, citing sources, that the Trump administration was proceeding toward a possible delisting of Chinese public company share\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLF, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0372 (i.e., a 3.72% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0372 = 2.6872, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.037214, "expected_loss": 0.037214, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250425_0022", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-04-25", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0708, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0011, std=0.0277, worst_day=-0.0767\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0708 (i.e., a 7.08% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0708 = 1.4116, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.070844, "expected_loss": 0.070844, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250131_0027", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2025-01-31", "context_summary": "TLH: 60-day history, VaR(99%)=-0.0119, max drawdown threshold=10%.", "question": "Asset: TLH\nDaily returns (past 60 days): mean=0.0002, std=0.0063, worst_day=-0.0129\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 = 0.0119 (i.e., a 1.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0119 = 8.3912, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.011917, "expected_loss": 0.011917, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250228_0030", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EMB"], "decision_date": "2025-02-28", "context_summary": "EMB: 60-day history, VaR(99%)=-0.0093, max drawdown threshold=10%.", "question": "Asset: EMB\nDaily returns (past 60 days): mean=0.0003, std=0.0041, worst_day=-0.0150\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 = 0.0093 (i.e., a 0.93% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0093 = 10.7228, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.009326, "expected_loss": 0.009326, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250327_0033", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VCIT"], "decision_date": "2025-03-27", "context_summary": "VCIT: 60-day history, VaR(99%)=-0.0054, max drawdown threshold=10%.", "question": "Asset: VCIT\nDaily returns (past 60 days): mean=0.0004, std=0.0030, 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 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 = 0.0054 (i.e., a 0.54% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0054 = 18.5936, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.005378, "expected_loss": 0.005378, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250225_0036", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DBC"], "decision_date": "2025-02-25", "context_summary": "DBC: 60-day history, VaR(99%)=-0.0145, max drawdown threshold=10%.", "question": "Asset: DBC\nDaily returns (past 60 days): mean=0.0013, std=0.0075, worst_day=-0.0153\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 = 0.0145 (i.e., a 1.45% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0145 = 6.9083, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014475, "expected_loss": 0.014475, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250520_0039", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2025-05-20", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0336, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0012, std=0.0141, worst_day=-0.0336\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-19] [\"Zacks Investment Ideas feature highlights: Arista Networks, Apple and Applied Industrial Technologies Chicago, IL \\u2013 May 19, 2025\\u2013 Today, Zacks Investment Ideas feature highlights Arista Networks ANET, Apple AAPL and Applied Industrial Technologies AIT. There are many ways that companies can keep shareholders happy, whether that be through robust financial performance or consistent dividend payouts, just for a few simple examples. Companies can also demonstrate a shareholder-friendly nature through share repurchase programs, also commonly known as stock buybacks. Several companies, including Arista Networks, Apple and Applied Industrial Technologies, recently unveiled fresh buybacks. Let's take a closer look at the benefits and the announcements of each. Stock buybacks, also known as share repurchase programs, are commonly deployed by companies to boost shareholder value. A stock buyback occurs when a company purchases outstanding shares of its stock. In its simplest form, buybacks represent companies essentially re-investing in themselves. Reducing the number of outstanding shares can boost earnings per share (EPS), also helping to put a floor under shares, reflective of consistent buying pressure. Still, it's worth mentioning that buybacks can sometimes bring out critics, as some believe the cash could be better deployed elsewhere, such as R&D. Nonetheless, buybacks are generally a net positive for shareholders, particularly those of mature companies with a much smaller growth runway. Arista Networks' latest set of quarterly results beat our consensus EPS and sales estimates handily, with revenue of $2.0 billion showing nearly 30% growth year-over-year. The company's sales growth has been fueled by the AI frenzy, as the company is an industry leader in data-driven, client-to-cloud networking for large AI, data center, campus, and routing environments. The stock also sports a favorable Zacks Rank #2 (Buy), with EPS expectations increasing across the board. Arista Networks unveiled an additional $1.5 billion repurchase program in the release. Down 15% year-to-date, Apple shares have struggled in 2025, underperforming relative to the S&P 500 in a big way and driven lower by initial tariff headlines. Shares faced pressure as a result, but the recent de-escalation announcement between the US and China has brought back positivity. Apple unveiled a massive $100 billion additional repurchase program in its latest quarterly report, putting some of its cash to work. The earnings outlook for the tech titan remains under pressure, with analysts taking their EPS expectations lower across the board over recent months. The evolving EPS outlook of Apple is certainly going to be interesting, particularly so amid all the back-and-forth news we've received concerning tariffs and other economic developments. It's worth remembering that the company is no longer the growth machine it used to be, with EPS forecasted to climb 6% on 3% higher sales in its cu\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_20250725_0041", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2025-07-25", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0161, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0017, std=0.0076, worst_day=-0.0162\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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2024-06-30 0001652044 goog:SubscriptionsPlatformsAndDevicesRevenueMember goog:GoogleServicesMember 2025-04-01 [...TRUNCATED...] 2.500% notes due 2029 Current Report on Form 8-K (File No. 001-37580) May 06, 2025 4.03 Form of Global Note representing the Registrant’s 3.000% notes due 2033 Current Report on Form 8-K (File No. 001-37580) May 06, 2025 4.04 Form of Global Note representing the Registrant’s 3.375% notes due 2037 Current Report on Form 8-K (File No. 001-37580) May 06, 2025 4.05 Form of Global Note representing the Registrant’s 3.875% notes due 2045 Current Report on Form 8-K (File No. 001-37580) May 06, 2025 4.06 Form of Global Note representing the Registrant’s 4.000% notes due 2054 Current Report on Form 8-K (File No. 001-37580) May 06, 2025 4.07 Form of Global Note representing the Registrant’s 4.000% notes due 2030 Current Report on Form 8-K (File No. 001-37580) May 01, 2025 4.08 Form of Global Note representing the Registrant’s 4.500% notes due 2035 Current Report on Form 8-K (File No. 001-37580) May 01, 2025 4.09 Form of Global Note representing the Registrant’s 5.250% notes due 2055 Current Report on Form 8-K (File No. 001-37580) May 01, 2025 4.10 Form of Global Note representing the Registrant’s 5.300% notes due 2065 Current Report on Form 8-K (File No. 001-37580) May 01, 2025 31.01 * Certification of Chief Executive Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.02 * Certification of Chief Financial Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.01 ‡ Certifications of Chief Executive Officer and Chief Financial Officer pursuant to 18 U.S.C. Section 1350, as adopted pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS * Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH * Inline XBRL Taxonomy Extension Schema Document 101.CAL * Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF * Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB * Inline XBRL Taxonomy Extension Label Linkbase Document 54 101.PRE * Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 * Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) __________________________  * Filed herewith. ‡ Furnished herewith. 55 SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. ALPHABET INC. July 23, 2025 By: /s/ ANAT ASHKENAZI Anat Ashkenazi Senior Vice President, Chief Financial Officer ALPHABET INC. July 23, 2025 By: /s/    AMIE THUENER O'TOOLE         Amie Thuener O'Toole Vice President, Corporate Controller and Principal Accounting Officer 56\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 = 0.0161 (i.e., a 1.61% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0161 = 6.2203, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016076, "expected_loss": 0.016076, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9047}} +{"id": "T3_all_20250917_0044", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-09-17", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0898, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0059, std=0.0516, worst_day=-0.0939\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0898 (i.e., a 8.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0898 = 1.1130, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.089849, "expected_loss": 0.089849, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250221_0046", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-02-21", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1067, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0020, std=0.0478, worst_day=-0.1137\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9374", "answer_numeric": 0.9374, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1067 (i.e., a 10.67% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1067 = 0.9374, capped at 1.0.\nMaximum position size = 0.9374 (93.7% of portfolio).", "metadata": {"var_99": -0.106682, "expected_loss": 0.106682, "max_drawdown_threshold": 0.1, "position_size": 0.9374, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250317_0049", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-03-17", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0238, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0005, std=0.0104, worst_day=-0.0242\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent 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0000104169 wmt:SamsClubUSMember 2025-01-31 0000104169 us-gaap:FairValueInputsLev [...TRUNCATED...] Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. (C) This Exhibit is a management contract or compensatory plan or arrangement (P) This Exhibit was originally filed in paper format. Accordingly, a hyperlink has not been provided. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Company hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. (c)    Financial Statement Schedules: None. ITEM 16. FORM 10-K SUMMARY None. 85 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.   Walmart Inc. Date: March 14, 2025   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities and on the dates indicated: Date: March 14, 2025   By   /s/ C. Douglas McMillon     C. Douglas McMillon     President and Chief Executive Officer and Director     (Principal Executive Officer) Date: March 14, 2025   By   /s/ Gregory B. Penner     Gregory B. Penner     Chairman of the Board and Director Date: March 14, 2025   By   /s/ John David Rainey     John David Rainey     Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: March 14, 2025   By   /s/ David M. Chojnowski     David M. Chojnowski     Senior Vice President and Controller (Principal Accounting Officer) Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2025 86 Date: March 14, 2025   By   /s/ Cesar Conde     Cesar Conde     Director Date: March 14, 2025 By /s/ Timothy P. Flynn Timothy P. Flynn Director Date: March 14, 2025 By /s/ Sarah Friar Sarah Friar Director Date: March 14, 2025 By /s/ Carla A. Harris Carla A. Harris Director Date: March 14, 2025 By /s/ Thomas W. Horton Thomas W. Horton Director Date: March 14, 2025 By /s/ Marissa A. Mayer Marissa A. Mayer Director Date: March 14, 2025 By /s/ Robert E. Moritz, Jr. Robert E. Moritz, Jr. Director Date: March 14, 2025 By /s/ Brian Niccol Brian Niccol Director Date: March 14, 2025 By /s/ Randall L. Stephenson Randall L. Stephenson Director Date: March 14, 2025   By   /s/ Steuart L. Walton     Steuart L. Walton     Director Signature Page to Walmart Inc. Form 10-K for the Fiscal Year Ended January 31, 2025 87\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 = 0.0238 (i.e., a 2.38% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0238 = 4.2019, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023799, "expected_loss": 0.023799, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250324_0052", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-03-24", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0215, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0009, std=0.0103, worst_day=-0.0242\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-03-21] [\"Top Research Reports for Apple, Meta Platforms & Chevron Thursday, March 20, 2025 The Zacks Research Daily presents the best research output of our analyst team. Today's Research Daily features new research reports on 16 major stocks, including Apple Inc. (AAPL), Meta Platforms, Inc. (META) and Chevron Corp. (CVX), as well as two micro-cap stocks Taylor Devices, Inc. (TAYD) and GSI Technology, Inc. (GSIT). The Zacks microcap research is unique as our research content on these small and under-the-radar companies is the only research of its type in the country. 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 >>> Ahead of Wall Street The daily 'Ahead of Wall Street' article is a must-read for all investors who would like to be ready for that day's trading action. The article comes out before the market opens and attempts to make sense of that morning's economic releases and how they will affect that day's market action. You can read this article for free on our home page and can actually sign up there to get an email notification as this article comes out each morning. You can read today's AWS here >>> Pre-Markets Lower; Economic News Decent Today's Featured Research Reports Apple\\u2019s shares have outperformed the Zacks Computer - Micro Computers industry over the past year (+26.7% vs. +24.8%). The company is benefiting from strong growth in Services revenues. It now has more than 1 billion paid subscribers across its Services portfolio, more than double what it had four years ago. The expanding content portfolio of Apple TV+ and Apple Arcade helped in driving subscriber growth. Apple expects the March quarter\\u2019s (second-quarter fiscal 2025) revenues to grow low to mid-single digits on a year-over-year basis. For the Services segment, It expects a low double-digit growth rate. Introduction of Apple Intelligence, an advanced personal intelligence system seamlessly integrated into iOS 18, iPadOS 18 and macOS Sequoia will help Apple shares to push higher. However, weakness in iPhone sales particularly in China is a concern. Increasing regulatory headwinds is a headwind. (You can read the full research report on Apple here >>>) Shares of Meta Platforms have outperformed the Zacks Internet - Software industry over the past year (+20.1% vs. +3.8%). The company is benefiting from steady user growth across all regions, particularly Asia Pacific. Increased engagement for its offerings like Instagram, WhatsApp, Messenger and Facebook has been a major growth driver. META has been leveraging AI to improve the potency of its platform offerings. These services currently reach more than 3.35 billion people daily. Meta\\u2019s growing footprint among young adults, driven by improving recommendations, boosts its competitive prowess. AI usage is making it a popular name among advertisers. This is expected to drive top-line growth. Meta now expect\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EEM, given the drawdown constraint. 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goog:GoogleCloudMember 2024-01-01 2024-12-31 0001652044 us-gaap:AllOtherSegmentsMember 2022-01-01 2022-12-31 000165 [...TRUNCATED...] undersigned, thereunto duly authorized. Date: February 4, 2025   ALPHABET INC. By: / S /    S UNDAR P ICHAI         Sundar Pichai Chief Executive Officer (Principal Executive Officer of the Registrant) POWER OF ATTORNEY KNOW ALL PERSONS BY THESE PRESENTS, that each person whose signature appears below constitutes and appoints Sundar Pichai and Anat Ashkenazi, jointly and severally, his or her attorney-in-fact, 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 or her 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 Annual Report on Form 10-K has been signed below by the following persons on behalf of the Registrant and in the capacities and on the dates indicated.     97. Table of Contents Alphabet Inc. Signature Title Date / S / S UNDAR P ICHAI Chief Executive Officer and Director (Principal Executive Officer) February 4, 2025 Sundar Pichai / S /    A NAT A SHKENAZI         Senior Vice President and Chief Financial Officer (Principal Financial Officer) February 4, 2025 Anat Ashkenazi / S /    A MIE T HUENER O'T OOLE         Vice President, Corporate Controller and Principal Accounting Officer February 4, 2025 Amie Thuener O'Toole / S /    F RANCES H. A RNOLD          Director February 4, 2025 Frances H. Arnold / S /    S ERGEY B RIN          Co-Founder and Director February 4, 2025 Sergey Brin / S /   R. M ARTIN C HAVEZ        Director February 4, 2025 R. Martin Chávez / S /    L. J OHN D OERR         Director February 4, 2025 L. John Doerr / S /    R OGER W. F ERGUSON  J R .         Director February 4, 2025 Roger W. Ferguson Jr. / S /    J OHN L. H ENNESSY          Director, Chair February 4, 2025 John L. Hennessy / S /    L ARRY P AGE         Co-Founder and Director February 4, 2025 Larry Page / S /    K. R AM S HRIRAM        Director February 4, 2025 K. Ram Shriram / S /    R OBIN L. W ASHINGTON        Director February 4, 2025 Robin L. Washington 98.\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 = 0.0194 (i.e., a 1.94% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0194 = 5.1514, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019412, "expected_loss": 0.019412, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9047}} +{"id": "T3_all_20251111_0058", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLP"], "decision_date": "2025-11-11", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0200, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0011, std=0.0073, worst_day=-0.0239\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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(2) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections During the three months ended September 30, 2025, none of our directors or executive officers adopted, modified or terminated a Rule 10b5-1 trading arrangement or a non-Rule 10b5-1 trading arrangement, as such terms are defined in Item 408 of Regulation S-K. 47 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 4.1 Fourth Supplemental Indenture, dated as of August 13, 2025, among Chevron U.S.A. Inc., Chevron Corporation, as guarantor, and Deutsche Bank Trust Company Americas, as trustee, filed as Exhibit 4. 2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 4.2 Forms of 3.950% Notes Due 2027, 4.050% Notes Due 2028, Floating Rate Notes Due 2028-B, 4.300% Notes Due 2030, Floating Rate Notes due 2030, 4.500% Notes Due 2032 and 4.850% Notes Due 2035, contained in Exhibit 4.2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 10.1+* Aircraft Time-Sharing Agreement, dated as of February 24, 2015, between Hess Corporation and John B. Hess. 10.2* Transition Services Agreement, dated as of July 14, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.3* Amendment One to Transition Services Agreement, dated as of August 27, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.4* Membership Interest Purchase Agreement, dated as of September 10, 2025, between Hess Corporation and JBH Ventures, LLC . 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ + Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 48 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 6, 2025 49\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 = 0.0200 (i.e., a 2.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0200 = 5.0097, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019961, "expected_loss": 0.019961, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250203_0061", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2025-02-03", "context_summary": "ICSH: 60-day history, VaR(99%)=-0.0004, max drawdown threshold=10%.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0002, std=0.0003, worst_day=-0.0007\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 = 239.2273, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000418, "expected_loss": 0.000418, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251008_0064", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IAU"], "decision_date": "2025-10-08", "context_summary": "IAU: 60-day history, VaR(99%)=-0.0152, max drawdown threshold=10%.", "question": "Asset: IAU\nDaily returns (past 60 days): mean=0.0032, std=0.0085, worst_day=-0.0171\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IAU, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; 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 = 6.5811, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015195, "expected_loss": 0.015195, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250108_0067", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-01-08", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1214, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0265, std=0.0756, worst_day=-0.1493\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8235", "answer_numeric": 0.8235, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1214 (i.e., a 12.14% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1214 = 0.8235, capped at 1.0.\nMaximum position size = 0.8235 (82.3% of portfolio).", "metadata": {"var_99": -0.121439, "expected_loss": 0.121439, "max_drawdown_threshold": 0.1, "position_size": 0.8235, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250212_0070", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2025-02-12", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0298, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=-0.0001, std=0.0108, worst_day=-0.0375\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2024-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsoli [...TRUNCATED...] Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy (incorporated by reference to the Company's Annual Report on Form 10-K for the Year ended December 31, 2023). 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2024, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2024, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 76 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 6, 2025.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 6, 2025.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Andrew Y. Ng Andrew Y. Ng Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 77\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 = 0.0298 (i.e., a 2.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0298 = 3.3539, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029816, "expected_loss": 0.029816, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20251105_0073", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-11-05", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1583, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0054, std=0.0472, worst_day=-0.1934\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.6318", "answer_numeric": 0.6318, "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 = 0.6318, capped at 1.0.\nMaximum position size = 0.6318 (63.2% of portfolio).", "metadata": {"var_99": -0.15827, "expected_loss": 0.15827, "max_drawdown_threshold": 0.1, "position_size": 0.6318, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251106_0075", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2025-11-06", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0180, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0002, std=0.0078, worst_day=-0.0224\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q JPM 2025-11-04] jpm-20250930 0000019617 FALSE 2025 Q3 12/31 true false http://fasb.org/us-gaap/2025#NoninterestIncomeOther http://fasb.org/us-gaap/2025#NoninterestIncomeOther http://fasb.org/us-gaap/2025#NoninterestIncomeOther http://fasb.org/us-gaap/2025#NoninterestIncomeOther March 31, 2026 235 March 31, 2026 237 March 31, 2026 235 March 31, 2026 242 March 31, 2026 229 March 31, 2026 230 March 31, 2026 235 March 31, 2026 232 March 31, 2026 249 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:USD utr:bbl iso4217:USD utr:MMBTU jpm:loan_segment jpm:loan_payment jpm:fund jpm:segment 0000019617 2025-01-01 2025-09-30 0000019617 us-gaap:CommonStockMember 2025-01-01 2025-09-30 0000019617 jpm:DepositarySharesOneFourHundredthInterestinaShareof5.75NonCumulativePreferredStockSeriesDDMember 2025-01-01 2025-09-30 0000019617 jpm:DepositarySharesOneFourHundredthInterestinaShareof6.00NonCumulativePreferredStockSeriesEEMember 2025-01-01 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2025-06-30 0000019617 us-gaap:TreasuryStockCommonMember 2024-06-30 0000019617 us-gaap:T [...TRUNCATED...] 05 Item 6.    Exhibits. Exhibit No. Description of Exhibit 3.1 Restate d Certificat e of Incorporation of JPMorgan Chase & Co., effective September 16, 202 5 . (a) 3.2 B y-laws of J P Morgan Chase & Co., as amended, effec tive Sept ember 12 , 202 5 ( incor porated by re ference to Exhibit 3. 2 to the Current Report on Form 8-K of J PM organ Ch a se & Co. (File No. 1-5805) filed S eptember 1 2, 202 5 ). 15 Letter re: Unaudited Interim Financial Information. (a) 22 Subsidiary Guarantors and Issuers of Guaranteed Securities . (a) 31.1 Certification. (a) 31.2 Certification. (a) 32 Certification Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002. (b) 101.INS The instance document does not appear in the interactive data file because its XBRL tags are embedded within the Inline XBRL document. (c) 101.SCH XBRL Taxonomy Extension Schema Document. (a) 101.CAL XBRL Taxonomy Extension Calculation Linkbase Document. (a) 101.DEF XBRL Taxonomy Extension Definition Linkbase Document. (a) 101.LAB XBRL Taxonomy Extension Label Linkbase Document. (a) 101.PRE XBRL Taxonomy Extension Presentation Linkbase Document. (a) 104 Cover Page Interactive Data File (embedded within the Inline XBRL document and included in Exhibit 101). (a) Filed herewith. (b) Furnished herewith. This exhibit shall not be deemed “filed” for purposes of Section 18 of the Securities Exchange Act of 1934, or otherwise subject to the liability of that Section. Such exhibit shall not be deemed incorporated into any filing under the Securities Act of 1933 or the Securities Exchange Act of 1934. (c) Pursuant to Rule 405 of Regulation S-T, includes the following financial information included in the Firm’s Quarterly Report on Form 10-Q for the quarterly period ended September 30, 2025, formatted in XBRL (eXtensible Business Reporting Language) interactive data files: (i) the Consolidated statements of income (unaudited) for the three and nine months ended September 30, 2025 and 2024, (ii) the Consolidated statements of comprehensive income (unaudited) for the three and nine months ended September 30, 2025 and 2024, (iii) the Consolidated balance sheets (unaudited) as of September 30, 2025 and December 31, 2024, (iv) the Consolidated statements of changes in stockholders’ equity (unaudited) for the three and nine months ended September 30, 2025 and 2024, (v) the Consolidated statements of cash flows (unaudited) for the nine months ended September 30, 2025 and 2024, and (vi) the Notes to Consolidated Financial Statements (unaudited). 206 SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. JPMorgan Chase & Co. (Registrant) By: /s/ Elena Korablina Elena Korablina Managing Director and Firmwide Controller (Principal Accounting Officer) Date: November 4, 2025 207\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 = 0.0180 (i.e., a 1.80% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0180 = 5.5693, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017956, "expected_loss": 0.017956, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250318_0078", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-03-18", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.1503, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0109, std=0.0564, worst_day=-0.1606\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.6655", "answer_numeric": 0.6655, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1503 (i.e., a 15.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1503 = 0.6655, capped at 1.0.\nMaximum position size = 0.6655 (66.5% of portfolio).", "metadata": {"var_99": -0.150254, "expected_loss": 0.150254, "max_drawdown_threshold": 0.1, "position_size": 0.6655, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251121_0081", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["PALL"], "decision_date": "2025-11-21", "context_summary": "PALL: 60-day history, VaR(99%)=-0.0619, max drawdown threshold=10%.", "question": "Asset: PALL\nDaily returns (past 60 days): mean=0.0042, std=0.0253, worst_day=-0.0619\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to PALL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0619 (i.e., a 6.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0619 = 1.6161, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.061877, "expected_loss": 0.061877, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250326_0084", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-03-26", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0228, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0002, std=0.0108, worst_day=-0.0234\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-03-25] [\"AEP Announces Pricing of Common Stock Offering with a Forward Component COLUMBUS, Ohio, March 24, 2025 /PRNewswire/ -- American Electric Power (Nasdaq: AEP) today announced the pricing of a registered underwritten offering of 19,607,844 shares of its common stock at a price to the public of $102.00 per share. Subject to certain conditions, all shares are expected to be borrowed by the forward counterparties (as defined below) (or their respective affiliates) from third parties and sold to the underwriters and offered in connection with the forward sale agreements described below. Citigroup, Barclays, BofA Securities and Wells Fargo Securities are acting as lead book-running managers for this offering. Goldman Sachs & Co. LLC, J.P. Morgan, Mizuho, Morgan Stanley, MUFG and Scotiabank are also acting as lead book-running managers and RBC Capital Markets and KeyBanc Capital Markets are acting as co-managers for this offering. In connection with the offering, AEP entered into forward sale agreements with each of Citibank, N.A. and Barclays Bank PLC (the \\\"forward counterparties\\\") under which AEP agreed to issue and sell to the forward counterparties an aggregate of 19,607,844 shares of its common stock. In addition, the underwriters of the offering have been granted a 30-day option to purchase up to an additional 2,941,176 shares of AEP's common stock upon the same terms. If the underwriters exercise their option to purchase additional shares, AEP expects to enter into additional forward sale agreements with the forward counterparties with respect to the additional shares. Settlement of the forward sale agreements is expected to occur on or prior to December 31, 2026. AEP may, subject to certain conditions, elect cash settlement or net share settlement for all or a portion of its rights or obligations under the forward sale agreements. If AEP elects physical settlement of the forward sale agreements, it expects to use the net proceeds for general corporate purposes, which may include capital contributions to its utility subsidiaries, acquisitions and/or repayment of debt. The offering is made under an effective shelf registration statement filed with the U.S. Securities and Exchange Commission. This news release does not constitute an offer to sell or a solicitation of an offer to buy the securities described herein, nor shall there be any sale of these securities in any state or jurisdiction in which such an offer, solicitation or sale would be unlawful prior to registration or qualification under the securities law of any such jurisdiction. The offer may be made only by means of a prospectus and the related prospectus supplement. Copies of these documents may be obtained by contacting Citigroup by calling 1-800-831-9146, or by mail at Citigroup c/o Broadridge Financial Solutions, 1155 Long Island Avenue, Edgewood, New York 11717; Barclays Capital Inc. by calling 1-888-603-5847, or by mail at Barclays c/o 1155 Long Island Avenue, Edgewood, New Yor\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 = 0.0228 (i.e., a 2.28% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0228 = 4.3791, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022836, "expected_loss": 0.022836, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250529_0087", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-05-29", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0912, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0062, std=0.0416, worst_day=-0.1210\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0912 (i.e., a 9.12% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0912 = 1.0970, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.091161, "expected_loss": 0.091161, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251205_0089", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-12-05", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1614, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0068, std=0.0561, worst_day=-0.1989\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.6194", "answer_numeric": 0.6194, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1614 (i.e., a 16.14% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1614 = 0.6194, capped at 1.0.\nMaximum position size = 0.6194 (61.9% of portfolio).", "metadata": {"var_99": -0.161446, "expected_loss": 0.161446, "max_drawdown_threshold": 0.1, "position_size": 0.6194, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251020_0092", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-10-20", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0142, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0015, std=0.0078, worst_day=-0.0184\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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 = 0.0142 (i.e., a 1.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0142 = 7.0317, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014221, "expected_loss": 0.014221, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20251031_0095", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2025-10-31", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1661, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0000, std=0.0718, worst_day=-0.1825\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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2024-09-30 0001652044 goog:SubscriptionsPlatformsAndDevicesRevenueMember goog:GoogleServicesMember 2025-07-01 2025 [...TRUNCATED...] ass C Capital Stock (excluding the dividend equivalent units), in addition to 50% of the (net) shares of any future grants awarded during the term of the plan (in each case, net shares are net of tax withholding). There were no “non-Rule 10b5-1 trading arrangements” (as defined in Item 408 of Regulation S-K of the Exchange Act) adopted , modified, or terminated during the quarter ended September 30, 2025 by our directors and Section 16 officers. Required Disclosure Pursuant to Section 13(r) of the Exchange Act During the quarter ended September 30, 2025, Google LLC, a subsidiary of Alphabet, filed a notification with the Russian Federal Security Service (FSB) pursuant to Russian encryption control requirements, which must be complied with prior to the import of covered items. Neither we nor our subsidiaries generated any gross revenues or 52 net profits directly from such activity and neither we nor our subsidiaries sell to the FSB. In the ordinary course of its business, Alphabet expects that Google LLC will continue to file these notifications as required under Russian law. 53 ITEM 6. EXHIBITS Exhibit Number    Description Incorporated by reference herein Form Date 31.01 * Certification of Chief Executive Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.02 * Certification of Chief Financial Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.01 ‡ Certifications of Chief Executive Officer and Chief Financial Officer pursuant to 18 U.S.C. Section 1350, as adopted pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS * Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH * Inline XBRL Taxonomy Extension Schema Document 101.CAL * Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF * Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB * Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE * Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 * Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) __________________________  * Filed herewith. ‡ Furnished herewith. 54 SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. ALPHABET INC. October 29, 2025 By: /s/ ANAT ASHKENAZI Anat Ashkenazi Senior Vice President, Chief Financial Officer ALPHABET INC. October 29, 2025 By: /s/    AMIE THUENER O'TOOLE         Amie Thuener O'Toole Vice President, Corporate Controller and Principal Accounting Officer 55\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": "0.6020", "answer_numeric": 0.602, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1661 (i.e., a 16.61% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1661 = 0.6020, capped at 1.0.\nMaximum position size = 0.6020 (60.2% of portfolio).", "metadata": {"var_99": -0.166118, "expected_loss": 0.166118, "max_drawdown_threshold": 0.1, "position_size": 0.602, "has_text": true, "text_chars": 9047}} +{"id": "T3_all_20250422_0097", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-04-22", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1219, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0039, std=0.0432, worst_day=-0.1391\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8201", "answer_numeric": 0.8201, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1219 (i.e., a 12.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1219 = 0.8201, capped at 1.0.\nMaximum position size = 0.8201 (82.0% of portfolio).", "metadata": {"var_99": -0.121938, "expected_loss": 0.121938, "max_drawdown_threshold": 0.1, "position_size": 0.8201, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250603_0099", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-06-03", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0742, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0012, std=0.0409, worst_day=-0.0792\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0742 (i.e., a 7.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0742 = 1.3485, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.074157, "expected_loss": 0.074157, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250430_0101", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2025-04-30", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1825, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=0.0069, std=0.0963, worst_day=-0.1825\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-29] AEP Names Joseph Sauvage to Board of Directors COLUMBUS, Ohio, April 29, 2025 /PRNewswire/ -- Joseph G. Sauvage, retired vice chairman and chairman of Global Power, Utilities and Renewables of Citigroup, today was elected to the American Electric Power (Nasdaq: AEP) Board of Directors. Sauvage led Citigroup's Global Power, Utilities and Renewables practice for more than 16 years. Prior to joining Citigroup, he held various investment banking roles at Lehman Brothers, including vice chairman and global head of Power, Utilities and Renewables. Sauvage served as a vice chairman of the Wall Street Advisory Group and was a member of the executive committee for the Electric Power Research Institute Advisory Council. \"AEP strives to achieve a mix of directors with skills and experience that align with the company's long-term strategy,\" said Sara Martinez Tucker, chairman of the AEP Board of Directors. \"Joe's deep understanding of the opportunities facing our industry, as well as his insight into complex capital raises and market dynamics, will bring a valuable perspective to the Board.\" \"Joe's strategic and financial expertise will be helpful as we invest in a reliable, modern energy system to serve our customers and support once-in-a-generation load growth,\" said AEP President and Chief Executive Officer Bill Fehrman. \"We are grateful to have Joe on the Board and welcome his guidance.\" Donna James did not stand for re-election to the Board of Directors for personal reasons. \"We thank Donna for her leadership and contributions to the company and wish her all the best moving forward,\" Tucker said. About AEP Our team at American Electric Power (Nasdaq: AEP) is committed to improving our customers' lives with reliable, affordable power. We are investing $54 billion from 2025 through 2029 to enhance service for customers and support the growing energy needs of our communities. Our nearly 16,000 employees operate and maintain the nation's largest electric transmission system with 40,000 line miles, along with more than 225,000 miles of distribution lines to deliver energy to 5.6 million customers in 11 states. AEP also is one of the nation's largest electricity producers with approximately 29,000 megawatts of diverse generating capacity. We are focused on safety and operational excellence, creating value for our stakeholders and bringing opportunity to our service territory through economic development and community engagement. Our family of companies includes AEP Ohio, AEP Texas, Appalachian Power (in Virginia, West Virginia and Tennessee), Indiana Michigan Power, Kentucky Power, Public Service Company of Oklahoma, and Southwestern Electric Power Company (in Arkansas, Louisiana, east Texas and the Texas Panhandle). AEP also owns AEP Energy, which provides innovative competitive energy solutions nationwide. AEP is headquartered in Columbus, Ohio. For more information, visit aep.com. View original content to download multimedia:https://www.prnewswire.com/news\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_20251218_0103", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-12-18", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0684, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0040, std=0.0271, worst_day=-0.0847\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0684 (i.e., a 6.84% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0684 = 1.4609, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.06845, "expected_loss": 0.06845, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250303_0106", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-03-03", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0505, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0003, std=0.0253, worst_day=-0.0505\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0505 (i.e., a 5.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0505 = 1.9816, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.050464, "expected_loss": 0.050464, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251017_0108", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-10-17", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0215, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0007, std=0.0095, worst_day=-0.0284\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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 = 0.0215 (i.e., a 2.15% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0215 = 4.6489, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.02151, "expected_loss": 0.02151, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20251009_0110", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["TLT"], "decision_date": "2025-10-09", "context_summary": "TLT: 60-day history, VaR(99%)=-0.0089, max drawdown threshold=10%.", "question": "Asset: TLT\nDaily returns (past 60 days): mean=0.0008, std=0.0065, worst_day=-0.0103\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to TLT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0089 (i.e., a 0.89% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0089 = 11.2135, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.008918, "expected_loss": 0.008918, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250602_0113", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2025-06-02", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0325, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0008, std=0.0132, worst_day=-0.0325\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-30] 4 Dividend-Paying Dow Jones Growth Stocks to Buy in June and Hold for Decades Apple could be heavily impacted by tariffs, but the long-term investment thesis is sound. Microsoft continues to fire on all cylinders and deserves to be near an all-time high. Visa and American Express benefit from network effects that help them steadily grow over time. 10 stocks we like better than Apple \u203a The modern-day Dow Jones Industrial Average contains a variety of industry-leading companies across stock market sectors -- making it an excellent way to discover blue chip companies to build a portfolio around. Here's why Apple (NASDAQ: AAPL), Microsoft (NASDAQ: MSFT), Visa (NYSE: V), and American Express (NYSE: AXP) are particularly compelling Dow stocks to buy in June and hold for decades to come. Apple used to be the most valuable company in the world, but it has taken a back seat behind Microsoft and Nvidia as Apple is down 22% year to date at the time of this writing, while Microsoft is up nearly 7%. Microsoft has given investors everything they could have asked for amid tariff tensions. The company continues to grow at an impressive rate while maintaining high operating margins. Microsoft is investing in artificial intelligence (AI) and cloud computing at a breakneck pace while buying back a significant amount of stock, raising its dividend by around 10% per year, and maintaining an exceptional balance sheet. The company's business model is relatively insulated from trade risks, so it's no wonder why the stock is knocking on the door of a new all-time high. But the same can't be said of Apple. It assembles the vast majority of key products, like iPhones, in China -- making it extremely vulnerable to tariffs. Apple stock has been on a roller coaster in 2025 as investors try to digest policies that seem to change overnight. President Trump has cast Apple onto the front lines of the trade war with China, with the latest decision being a 25% tariff on iPhones not made in the U.S. While Apple can adjust its supply chain to offset some tariff risk, it would be extremely difficult for Apple to make iPhones as cost-effectively outside of China. So, in the near term, Apple may just have to absorb the tariff hit and hope resolutions come soon or pass along a portion of the costs to consumers. The good news is that Apple has highly anticipated products with AI features coming this fall which may be enough to pique consumer interest and justify higher price tags. Investors can catch a glimpse of Apple's latest technology updates and features by tuning into its Worldwide Developers Conference from June 9 to June 13. Given tariff risks, some folks may want to take a wait-and-see approach to Apple. But the stock is fairly beaten down, and folks who think Apple has the brand power and innovation to justify price hikes may want to consider buying the stock in June. Apple's valuation is at reasonable levels with a price-to-earnings (P/E) ratio of 30.4 and a forward P/E of 27.2\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EWJ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0325 (i.e., a 3.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0325 = 3.0761, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032508, "expected_loss": 0.032508, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250523_0116", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-05-23", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0335, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=-0.0007, std=0.0148, worst_day=-0.0335\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-22] [\"Game On: Take-Two reports mixed Q4 earnings results \\u201cGame On\\u201d is The Fly\\u2019s weekly recap of the stories powering up or beating down video game stocks. Easily unpack a company's performance with TipRanks' new KPI Data for smart investment decisions Easily unpack a company's performance with TipRanks' new KPI Data for smart investment decisions Receive undervalued, market resilient stocks right to your inbox with TipRanks' Smart Value Newsletter Receive undervalued, market resilient stocks right to your inbox with TipRanks' Smart Value Newsletter TAKE-TWO REPORTS MIXED Q4 EARNINGS RESULTS: Last week, Take-Two (TTWO) reported a fourth quarter loss per share of ($21.08) on net bookings of $1.58B, which compared to a loss per share of ($17.02) for the same period last year and analyst net bookings estimates of $1.55B. GAAP results include impairment charges of $3.55B related to goodwill and $176.3M for acquisition-related intangible assets. The company also guided to a Q1 loss per share of (78c) to (65c) on net bookings of $1.25B-$1.3B, which compared to analyst estimates of (78c) and $1.28B, respectively. Additionally, Take-Two forecast a FY26 loss per share of ($2.79) to ($2.45) on net bookings of $5.9B-$6B. \\u201cWe achieved outstanding results in our 2025 Fiscal Year, with each of our labels contributing meaningfully to our performance. Our Fiscal 2026 outlook reflects continuing positive momentum, with Net Bookings guidance of $5.9B to $6B. As we bring our exciting lineup to market, including Grand Theft Auto VI in Fiscal 2027, we expect to achieve record levels of Net Bookings that will establish a new baseline for our business and set us on a path of enhanced profitability,\\u201d said CEO Strauss Zelnick. Following the report, JPMorgan raised the firm\\u2019s price target on Take-Two to $250 from $225 and kept an Overweight rating on the shares. The company reported strong fiscal Q4 results, with broad-based outperformance across key titles driving bookings to the top-end of guidance, the analyst said. The firm added the biggest news of the quarter came a few weeks ago when Take-Two announced the delay of GTA VI, \\u201cwhich made it all the more important that other franchises delivered in the near-term.\\u201d Meanwhile, Benchmark raised the firm\\u2019s price target on Take-Two to $250 from $225 and kept a Buy rating on the shares after what the firm calls \\u201ca strong finish to fiscal 2025,\\u201d driven by broad based performance across core franchises and mobile. Excitement for Grand Theft Auto VI continues to build, as evidenced by trailer two having surpassed 475M cross platform views in its first 24 hours, noted the analyst, who sees this \\u201creinforcing the franchise\\u2019s global cultural resonance and the anticipated impact of its fiscal 2027 release.\\u201d Additionally, Wedbush raised the firm\\u2019s price target on Take-Two to $269 from $253 and kept an Outperform rating on the shares. The firm noted that the practi\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_20251216_0119", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-12-16", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0957, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0079, std=0.0422, worst_day=-0.1171\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0957 (i.e., a 9.57% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0957 = 1.0447, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.095719, "expected_loss": 0.095719, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250109_0121", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["INDS"], "decision_date": "2025-01-09", "context_summary": "INDS: 60-day history, VaR(99%)=-0.0325, max drawdown threshold=10%.", "question": "Asset: INDS\nDaily returns (past 60 days): mean=-0.0025, std=0.0117, worst_day=-0.0381\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 = 0.0325 (i.e., a 3.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0325 = 3.0750, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.03252, "expected_loss": 0.03252, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251223_0124", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-12-23", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0684, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0042, std=0.0259, worst_day=-0.0847\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0684 (i.e., a 6.84% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0684 = 1.4609, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.06845, "expected_loss": 0.06845, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250924_0125", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-09-24", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0205, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0005, std=0.0098, worst_day=-0.0208\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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 = 0.0205 (i.e., a 2.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0205 = 4.8684, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020541, "expected_loss": 0.020541, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250721_0127", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IVV"], "decision_date": "2025-07-21", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0134, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0029, std=0.0076, worst_day=-0.0168\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-18] [\"MP Materials (MP) Completes US$650 Million Equity Offering MP Materials has made significant announcements recently, including the completion of a follow-on equity offering of nearly $650 million and new high-profile partnerships with Apple and the Department of Defense. These developments coincide with a remarkable share price increase of 122% over the last quarter. The equity offering indicates strong market confidence, while the strategic partnerships bolster MP's long-term prospects in the rare earth sector. The broader market, with major indexes reaching record highs, provides a favorable backdrop, further enhancing MP's upward momentum. Such positive corporate maneuvers align well with the ongoing bullish trends in stock markets. Every company has risks, and we've spotted 1 warning sign for MP Materials you should know about. AI is about to change healthcare. These 27 stocks are working on everything from early diagnostics to drug discovery. The best part - they are all under $10b in market cap - there's still time to get in early. The recent announcements of MP Materials' successful equity offering and strategic partnerships with Apple and the Department of Defense could significantly impact its long-term narrative as it positions itself strongly within the rare earths sector. These developments are expected to enhance production capabilities and revenue opportunities, aligning with the company's strategy to expand into ex-China markets. Potential advancements in efficiency and sales volumes could positively influence future earnings and revenue forecasts, which analysts anticipate to grow robustly over the next three years. Over a five-year period, MP Materials has achieved a total return of 293.48%, which underscores its substantial growth trajectory. Notably, over the past year, its performance surpassed the US Metals and Mining industry, which returned 6.1%. However, despite recent impressive share price gains, the current price of US$58.55 contrasts with the consensus price target of US$38. This discrepancy highlights a potential overvaluation according to analysts, suggesting investors might benefit from tempering expectations in light of market factors and the company's execution of future growth plans. The strategic moves could help mitigate risks associated with heavy reliance on NdPr pricing and variable Chinese policies. However, executing its growth strategy without significant revenue or margin interruptions remains crucial. Although the company's long-term viability appears promising, as evidenced by planned expansions in the Upstream and Midstream segments, immediate financial forecasts also depend on external factors and successful integration of new processes. Thus, MP Materials' future prospects will largely depend on its ability to navigate these challenges effectively while aligning with analyst earnings forecasts and market expectations. Explore historical data to track MP Materials' performance over time in our past\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 = 0.0134 (i.e., a 1.34% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0134 = 7.4370, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013446, "expected_loss": 0.013446, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250319_0129", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-03-19", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.1752, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0073, std=0.0645, worst_day=-0.2043\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.5706", "answer_numeric": 0.5706, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1752 (i.e., a 17.52% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1752 = 0.5706, capped at 1.0.\nMaximum position size = 0.5706 (57.1% of portfolio).", "metadata": {"var_99": -0.17524, "expected_loss": 0.17524, "max_drawdown_threshold": 0.1, "position_size": 0.5706, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250804_0131", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2025-08-04", "context_summary": "VNQ: 60-day history, VaR(99%)=-0.0251, max drawdown threshold=10%.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=0.0002, std=0.0091, worst_day=-0.0266\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\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 = 0.0251 (i.e., a 2.51% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0251 = 3.9823, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.025111, "expected_loss": 0.025111, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250826_0134", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-08-26", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0833, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0058, std=0.0401, worst_day=-0.0902\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0833 (i.e., a 8.33% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0833 = 1.1999, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.083338, "expected_loss": 0.083338, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251030_0137", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-10-30", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0245, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0002, std=0.0086, worst_day=-0.0282\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[SEC 10-Q BA 2025-10-29] ba-20250930 FALSE 2025 Q3 0000012927 --12-31 P1Y http://fasb.org/us-gaap/2025#OtherAssetsCurrent http://fasb.org/us-gaap/2025#OtherAssetsCurrent http://fasb.org/us-gaap/2025#AccruedLiabilitiesCurrent http://fasb.org/us-gaap/2025#AccruedLiabilitiesCurrent xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure ba:extension_period ba:aircraft ba:tanker ba:lot ba:simulator ba:segment 0000012927 2025-01-01 2025-09-30 0000012927 us-gaap:CommonStockMember 2025-01-01 2025-09-30 0000012927 ba:DepositarySharesMember 2025-01-01 2025-09-30 0000012927 2025-10-22 0000012927 us-gaap:ProductMember 2025-01-01 2025-09-30 0000012927 us-gaap:ProductMember 2024-01-01 2024-09-30 0000012927 us-gaap:ProductMember 2025-07-01 2025-09-30 0000012927 us-gaap:ProductMember 2024-07-01 2024-09-30 0000012927 us-gaap:ServiceMember 2025-01-01 2025-09-30 0000012927 us-gaap:ServiceMember 2024-01-01 2024-09-30 0000012927 us-gaap:ServiceMember 2025-07-01 2025-09-30 0000012927 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ba:CommercialAirplanesSegmentMember 2024-07-01 2024-09-30 0000012927 us-gaap:OperatingSegmentsMem [...TRUNCATED...] #160;of Shares That May Yet be Purchased Under the Plans or Programs 7/1/2025 thru 7/31/2025 28,866  $232.93  8/1/2025 thru 8/31/2025 6,963  229.15  9/1/2025 thru 9/30/2025 3,728  235.24  Total 39,557  $232.48  (1) A total of 39,557 shares were transferred to us from employees in satisfaction of minimum tax withholding obligations associated with the vesting of restricted stock units during the period. We did not purchase any shares of our common stock in the open market pursuant to a repurchase program. Item 3. Defaults Upon Senior Securities Not applicable. Item 4. Mine Safety Disclosures Not applicable. 57 Table of Contents Item 5. Other Information During the three months ended September 30, 2025, none of our directors or officers adopted , modified or terminated a “Rule 10b5-1 trading arrangement” or a “non-Rule 10b5-1 trading arrangement” as such terms are defined under Item 408 of Regulation S-K. 58 Table of Contents Item 6. Exhibits 10.1 364-Day Credit Agreement, dated as of August 25, 2025, among The Boeing Company for itself and on behalf of its Subsidiaries, as a Borrower, the Lenders party hereto, Citibank, N.A., as Administrative Agent, JPMorgan Chase Bank, N.A. as Syndication Agent and Citibank, N.A. and JPMorgan Chase Bank N.A., as Joint Lead Arrangers and Joint Book Managers (Exhibit 10.1 to the Company’s Current Report on Form 8-K, dated August 25, 2025) 15 Letter from Independent Registered Public Accounting Firm regarding unaudited interim financial information 31.1 Certification of Chief Executive Officer pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certification of Chief Executive Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 32.2 Certification of Chief Financial Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File (formatted as inline XBRL and contained in Exhibit 101) 59 Table of Contents Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. THE BOEING COMPANY (Registrant) October 29, 2025 /s/ Michael J. Cleary (Date) Michael J. Cleary Senior Vice President and Controller 60\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 = 0.0245 (i.e., a 2.45% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0245 = 4.0756, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024536, "expected_loss": 0.024536, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9044}} +{"id": "T3_all_20250709_0140", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-07-09", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0653, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0041, std=0.0337, worst_day=-0.0764\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0653 (i.e., a 6.53% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0653 = 1.5318, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.065281, "expected_loss": 0.065281, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250120_0143", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-01-20", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0780, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0021, std=0.0475, worst_day=-0.0817\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0780 (i.e., a 7.80% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0780 = 1.2824, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.077977, "expected_loss": 0.077977, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251229_0145", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2025-12-29", "context_summary": "CSHI: 60-day history, VaR(99%)=-0.0006, max drawdown threshold=10%.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=0.0002, std=0.0005, worst_day=-0.0006\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to CSHI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0006 (i.e., a 0.06% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0006 = 165.9805, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000602, "expected_loss": 0.000602, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250812_0148", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2025-08-12", "context_summary": "ACWI: 60-day history, VaR(99%)=-0.0126, max drawdown threshold=10%.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0013, std=0.0062, worst_day=-0.0127\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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2024-12-31 0000731766 2025-07-01 2025-06-30 0000731766 us-gaap:USTreasuryAndGovernmentMember 2025-06-30 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2025-06-30 0000731766 us-gaap:CorporateDebtSecuritiesMember 2025-06-30 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2025-06-30 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2025-06-30 0000731766 us-gaap:USTreasuryAndGovernmentMember 2024-12-31 0000731766 us-gaap:USStatesAndPoliticalSubdivisionsMember 2024-12-31 0000731766 us-gaap:CorporateDebtSecuritiesMember 2024-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByUSGovernmentSponsoredEnterprisesMember 2024-12-31 0000731766 us-gaap:MortgageBackedSecuritiesIssuedByPrivateEnterprisesMember 2024-12-31 0000731766 us-gaap:DebtSecuritiesMember 2025-06-30 0000731766 us-gaap:DebtSecuritiesMember 2024-12-31 0000731766 us-gaap:FairValueInputsLevel1Member 2025-06-30 0000731766 us-gaap:FairValueInputsLevel2Member 2025-06-30 0000731766 us-gaap:FairValueInputsLevel3Member 2025-06-30 0000731766 us-gaap:USTr [...TRUNCATED...] #8217;s Current Report on Form 8-K filed on February 26, 2021) 4.1 Amended and Restated Indenture, dated as of April 27, 2023, between UnitedHealth Group Incorporated and Wilmington Trust Company, as successor trustee (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 28, 2023) 4.2 Indenture, dated as of February 4, 2008, between UnitedHealth Group Incorporated and U.S. Bank National Association (incorporated by reference to Exhibit 4.1 to the Company’s Registration Statement on Form S-3, SEC File Number 333-149031, filed on February 4, 2008) 4.3 Supplemental Indenture, dated as of April 18, 2023, between UnitedHealth Group Incorporated and U.S. Bank Trust Company, National Association, as trustee, relating to the 6.875% Senior Notes due 2038 (incorporated by reference to Exhibit 4.1 to UnitedHealth Group Incorporated’s Current Report on Form 8-K filed on April 24, 2023) * 10. 1 Employment Agreeme nt, effective as of May 12, 2025, between United HealthC are Services, Inc. and Stephen Hemsely 31.1 Certifications pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certifications pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document. 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document. 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document. 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document. 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document. 104  Cover Page Interactive Data File (formatted as Inline XBRL and embedded within Exhibit 101).  ________________ * Denotes management contracts and compensation plans in which certain directors and named executive officers participate and which are being filed pursuant to Item 601(b)(10)(iii)(A) of Regulation S-K. ** Pursuant to Item 601(b)(4)(iii) of Regulation S-K, copies of instruments defining the rights of certain holders of long-term debt are not filed. The Company will furnish copies thereof to the SEC upon request. 27 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   UNITEDHEALTH GROUP INCORPORATED   /s/ S TEPHEN H EMSLEY Chair and Chief Executive Officer (principal executive officer) Dated: August 11, 2025 Stephen Hemsley    /s/ J OHN R EX President and Chief Financial Officer (principal financial officer) Dated: August 11, 2025 John Rex    /s/ T HOMAS R OOS Senior Vice President and Chief Accounting Officer (principal accounting officer) Dated: August 11, 2025 Thomas Roos    28\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 = 0.0126 (i.e., a 1.26% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0126 = 7.9600, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012563, "expected_loss": 0.012563, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250819_0152", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLI"], "decision_date": "2025-08-19", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0129, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0012, std=0.0068, worst_day=-0.0150\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-08-18] [\"FRT- A Retail REIT Targeting Markets with Strong Demographics Federal Realty Investment Trust (FRT) is among the oldest US Real Estate Investment Trusts (REITs) and ranks first in terms of dividend growth. The company focuses on the ownership, operation, and development of high-quality retail properties, from grocery-anchored shopping centers to large-scale mixed-use malls, writes Martin Fridson, editor of Forbes/Fridson Income Securities Investor. To get more articles and chart analysis from MoneyShow, subscribe to our Top Pros\\u2019 Top Picks newsletter here.) FRT\\u2019s properties are largely centered in nine major metropolitan markets with excellent demographics: Washington DC, New York, Boston, Philadelphia, Miami, Chicago, Phoenix, Southern California, and Silicon Valley. Federal Realty Investment Trust (FRT) The portfolio is well diversified, with a broad property mix and wide range of tenants that include TJX Companies, Williams Sonoma Companies, Whole Foods, PetSmart, Apple, AT&T, Verizon, Chipotle, and Gold\\u2019s Gym. As of March 31, the portfolio consisted of 103 properties with approximately 3,500 tenants and 3,100 residential units. Occupancy was a strong 93.6% at quarter-end, with limited troubled retailer exposure. FRT reported Q1 2025 funds from operations (FFO) of $146.5 million, or $1.70 per share, topping analyst estimates by a penny. FFO climbed 7.2% from a year ago. Quarterly rental income of $309.2 million rose 6.1% year-over-year and was slightly ahead of consensus. Higher operating results were driven by increased same-property operating income and strong leasing activity. See also: VNT: A New \\\"Buy\\\" in the Industrial Tech Space FRT has demonstrated a proven history of delivering solid operating results and the longest record of dividend growth, with 57 consecutive years of increased dividends. FRT\\u2019s common shares are suitable for low- to medium-risk tax-deferred portfolios. Dividends are taxed as ordinary income. Recommended Action: Buy FRT. More From MoneyShow.com: TXRH: A Casual Dining Chain with Solid Q2 Sales Growth ORLY: A \\\"Cannibal\\\" Stock that You Should Consider Market Minute 8/15/25: UNH Gets Buffett Boost, AMAT Falls Flat!\", \"Buffett's Shot in the Arm Sends UnitedHealth Soaring Against the Odds Shares of UnitedHealth Group Incorporated UNH jumped nearly 12% last Friday after Warren Buffett's Berkshire Hathaway Inc. (BRK.B) revealed that it had snapped up a significant number of shares of the troubled health insurer. As of June 30, 2025, Berkshire had amassed more than 5 million UNH shares, a stake worth roughly $1.57 billion. The disclosure came despite Berkshire maintaining its broader net-seller stance, marking the 11th consecutive quarter in which it sold more than it bought. That contrast underscores the significance of this investment: a classic Buffett-style contrarian bet on long-term value. When Buffett takes a stake, it sends a powerful message that he sees enduring potential, sparking a wave \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 = 0.0129 (i.e., a 1.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0129 = 7.7352, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012928, "expected_loss": 0.012928, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250130_0155", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2025-01-30", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0215, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0004, std=0.0079, worst_day=-0.0265\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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J OLLA Alice L. Jolla Corporate Vice President and Chief Accounting Officer (Duly Authorized Officer) January 29, 2025   67\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 = 0.0215 (i.e., a 2.15% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0215 = 4.6614, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021453, "expected_loss": 0.021453, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20250307_0159", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2025-03-07", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0383, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=-0.0008, std=0.0140, worst_day=-0.0383\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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ITEM 16. FORM 10-K SUMMARY None. SIGNATURES Under the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, this report was signed on behalf of the Registrant by the authorized person named below. Pfizer Inc. Dated: February 27, 2025 By: /S/    MARGARET M. MADDEN Margaret M. Madden Senior Vice President and Corporate Secretary Chief Governance Counsel We, the undersigned directors and officers of Pfizer Inc., hereby severally constitute Douglas M. Lankler and Margaret M. Madden, and each of them singly, our true and lawful attorneys with full power to them and each of them to sign for us, in our names in the capacities indicated below, any and all amendments to this Annual Report on Form 10-K filed with the Securities and Exchange Commission. Under the requirements of the Securities Exchange Act of 1934, this report was signed by the following persons on behalf of the Registrant and in the capacities and on the date indicated . Pfizer Inc. 2024 Form 10-K 113 Signature Title Date /S/    ALBERT BOURLA Albert Bourla Chairman, Chief Executive Officer and Director (Principal Executive Officer) February 27, 2025 /S/    DAVID M. DENTON David M. Denton Chief Financial Officer, Executive Vice President (Principal Financial Officer) February 27, 2025 /S/    JENNIFER B. DAMICO Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer) February 27, 2025 /S/    RONALD E. BLAYLOCK Ronald E. Blaylock Director February 27, 2025 /S/    MORTIMER J. BUCKLEY Mortimer J. Buckley Director February 27, 2025 /S/    SUSAN DESMOND-HELLMANN Susan Desmond-Hellmann Director February 27, 2025 /S/    JOSEPH J. ECHEVARRIA Joseph J. Echevarria Director February 27, 2025 /S/    SCOTT GOTTLIEB Scott Gottlieb Director February 27, 2025 /S/    HELEN H. HOBBS Helen H. Hobbs Director February 27, 2025 /S/    SUSAN HOCKFIELD Susan Hockfield Director February 27, 2025 /S/    DAN R. LITTMAN Dan R. Littman Director February 27, 2025 /S/    SHANTANU NARAYEN Shantanu Narayen Director February 27, 2025 /S/    SUZANNE NORA JOHNSON Suzanne Nora Johnson Director February 27, 2025 /S/    JAMES QUINCEY James Quincey Director February 27, 2025 /S/    JAMES C. SMITH James C. Smith Director February 27, 2025 /S/    CYRUS TARAPOREVALA Cyrus Taraporevala Director February 27, 2025 Pfizer Inc. 2024 Form 10-K 114\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": 9045}} +{"id": "T3_all_20250512_0161", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-05-12", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0335, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=-0.0014, std=0.0144, worst_day=-0.0335\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-09] [\"Cathie Wood Just Bought These 2 Stocks Down 42% and 87%. Should You? Airbnb looks like a value stock today, but it's planning a new launch next week that could boost its position. Roku is still reporting strong growth, but investors are still waiting for profits. 10 stocks we like better than Airbnb \\u203a Cathie Wood has made a name for herself as a top growth investor. She has made some bold moves as head of investing company Ark Invest. Although some of Ark's exchange-traded funds (ETFs) have a spotty track record, some of them have outperformed the market, and she has drawn attention to her company's trades, which are reported daily. Although Wood has a specific, innovation-driven approach to investing, her model is the same \\\"buy low, sell high\\\" model that underpins most successful investing. When stocks she likes go on sale, you're more likely to see them in Ark's shopping cart. Airbnb (NASDAQ: ABNB) and Roku (NASDAQ: ROKU) are two disruptive, high-opportunity stocks Ark just bought. Should they be in your shopping cart, too? Airbnb is a top brand name in travel, but its stock has been in the doldrums for quite a while. It's a case of skyrocketing too quickly based on market hype, and the stock has never been able to find its ground. Each time it looks compelling, the stock soars before dropping down in the aftermath. With all that volatility, it's only gained 84% since its first-day closing price. Will things finally start changing for this beleaguered stock? There are a lot of things happening at Airbnb, and the time might be ripe for taking off. Performance-wise, things have only been so-so. Revenue increased 6% year over year in the 2025 first quarter, which doesn't sound like a growth stock. Airbnb has made the jump from unprofitable growth stock to profitable industry leader, which is when many value investors might jump in if the price is right. Net income was lower in Q1, but the company is generating lots of cash, and trailing 12-month free cash flow is $4.4 billion with a 39% margin. The question is how much bigger Airbnb can grow. Management is expecting revenue to increase about 10% year over year in the second quarter, which would be a welcome acceleration. It's keeping a lid on a major launch that it's unveiling next week, but that's going to expand \\\"beyond the core,\\\" something it's been talking about for years already. As the platform it is today, investors can expect continued growth from tech enhancements, more hosts, and better features, but these are likely to be incremental. A huge shift in business could boost growth potential, so investors should follow what the company announced on May 13. At the current price, Airbnb stock trades at a forward, 1-year price-to-earnings (P/E) ratio of 25, and price-to-free cash flow is a strong value at 18. I wouldn't call it bargain territory, but it doesn't look overvalued. If you have a long time horizon, Airbnb stock should eventually find its footing and reward investors, but\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_20250530_0163", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-05-30", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0964, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=0.0024, std=0.0428, worst_day=-0.1251\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0964 (i.e., a 9.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0964 = 1.0377, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.096366, "expected_loss": 0.096366, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250129_0166", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-01-29", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0534, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0009, std=0.0231, worst_day=-0.0575\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0534 (i.e., a 5.34% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0534 = 1.8742, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.053357, "expected_loss": 0.053357, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250402_0168", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["PDBC"], "decision_date": "2025-04-02", "context_summary": "PDBC: 60-day history, VaR(99%)=-0.0157, max drawdown threshold=10%.", "question": "Asset: PDBC\nDaily returns (past 60 days): mean=0.0005, std=0.0073, worst_day=-0.0178\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to PDBC, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0157 (i.e., a 1.57% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0157 = 6.3572, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01573, "expected_loss": 0.01573, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251118_0171", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2025-11-18", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0200, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=-0.0011, std=0.0072, worst_day=-0.0239\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CVX 2025-11-06] cvx-20250930 0000093410 12/31 2025 Q3 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cvx:segment cvx:lawsuit cvx:state cvx:tribe cvx:parish 0000093410 2025-01-01 2025-09-30 0000093410 2025-09-30 0000093410 2025-07-01 2025-09-30 0000093410 2024-07-01 2024-09-30 0000093410 2024-01-01 2024-09-30 0000093410 2024-12-31 0000093410 2023-12-31 0000093410 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-06-30 0000093410 us-gaap:RetainedEarningsMember 2024-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-06-30 0000093410 us-gaap:ParentMember 2024-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-06-30 0000093410 2024-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-07-01 2024-09-30 0000093410 us-gaap:ParentMember 2024-07-01 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 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us-gaap:TreasuryStockCommonMember 2023-12-31 0000093410 us-gaap:ParentMember 2023-12-31 0000093410 us-gaap:NoncontrollingInterestMember 2023-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-01-01 2024-09-30 0000093410 us-gaap:ParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:RetainedEarningsMember 2024-01-01 2024-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-01 2024-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-01-01 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-12-31 0000093410 us-gaap:RetainedEarningsMember 2024-12-31 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-12-31 0000093410 us-gaap:TreasuryStockCommonMember 2024-12-31 0000093410 us-gaap:ParentMember 2024-12-31 0000093410 us-gaap:NoncontrollingInterestMember 2024-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-01-01 2025-09-30 0000093410 us-gaap:ParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-01-01 2025-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-01-01 2025-09-30 0000093410 us-gaap:RetainedEarningsMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-09-30 0000093410 [...TRUNCATED...] 160; $154.38 16,620,000   (1) Includes common shares repurchased from participants in the company’s executive compensation plans for personal income tax withholdings. (2) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections During the three months ended September 30, 2025, none of our directors or executive officers adopted, modified or terminated a Rule 10b5-1 trading arrangement or a non-Rule 10b5-1 trading arrangement, as such terms are defined in Item 408 of Regulation S-K. 47 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 4.1 Fourth Supplemental Indenture, dated as of August 13, 2025, among Chevron U.S.A. Inc., Chevron Corporation, as guarantor, and Deutsche Bank Trust Company Americas, as trustee, filed as Exhibit 4. 2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 4.2 Forms of 3.950% Notes Due 2027, 4.050% Notes Due 2028, Floating Rate Notes Due 2028-B, 4.300% Notes Due 2030, Floating Rate Notes due 2030, 4.500% Notes Due 2032 and 4.850% Notes Due 2035, contained in Exhibit 4.2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 10.1+* Aircraft Time-Sharing Agreement, dated as of February 24, 2015, between Hess Corporation and John B. Hess. 10.2* Transition Services Agreement, dated as of July 14, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.3* Amendment One to Transition Services Agreement, dated as of August 27, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.4* Membership Interest Purchase Agreement, dated as of September 10, 2025, between Hess Corporation and JBH Ventures, LLC . 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ + Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 48 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 6, 2025 49\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 = 0.0200 (i.e., a 2.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0200 = 5.0097, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019961, "expected_loss": 0.019961, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250609_0174", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2025-06-09", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1825, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0056, std=0.0920, worst_day=-0.1825\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-06-06] wmt-20250430 0000104169 1/31 2026 Q1 false 440 440 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-04-30 0000104169 dei:FormerAddressMember 2025-02-01 2025-04-30 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-04-30 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-04-30 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-04-30 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-04-30 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-04-30 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-04-30 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-04-30 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-04-30 0000104169 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us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-31 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedTranslationAdjustmentMember 2024-04-30 0000104169 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-04-30 0000104169 us-gaap:RevolvingCreditFacilityMember us-gaap:DomesticLineOfCreditMember 2025-04-01 2025-04-30 0000104169 us-gaap:RevolvingCreditFacilityMember us-gaap:DomesticLineOfCreditMember 2025-04-30 0000104169 wmt:FiveYearCreditFacilityMember us-gaap:DomesticLineOfCreditMember 2025-04-01 2025-04-30 0000104169 wmt:FiveYearCreditFacilityMember us-gaap:DomesticLineOfCreditMember 2025-04-30 0000104169 us-gaap:DomesticLineOfCreditMember 2025-01-31 0000104169 us-gaap:DomesticLineOfCreditMember 2025-04-30 0000104169 wmt:FloatingDebtDue2027Member wmt:SeniorUnsecuredNotesMember 2025-04-30 0000104169 wmt:FloatingDebtDue2027Member wmt:SeniorUnsecuredNotesMember 2025-02-01 2025-04-30 0000104169 wmt:A4.100DebtDue2027Member wmt:SeniorUnsecuredNotesMember 2025-04-30 0000104169 wmt:A4.100DebtDue2027Member wmt:SeniorUnsecuredNotesMember 2025-02-01 2025-04-30 0000104169 wmt:A4.350DebtDue2030Member wmt:SeniorUnsecuredNotesMember 2025-04-30 0000104169 wmt:A4.350DebtDue2030Member wmt:SeniorUnsecuredNotesMember 2025-02-01 2025-04-30 0000104169 wmt:A4.900DebtDue2035Member wmt:SeniorUnsecuredNotesMember 2025-04-30 0000104169 wmt:A4.900DebtDue2035Member wmt:SeniorUnsecuredNotesMember 2025-02-01 2025-04-30 0000104169 wmt:SeniorUnsecuredNotesMember 2025-02-01 2025-04-30 0000104169 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember 2025-04-30 0000104169 us-gaap:FairValueInputsLevel1Member us-gaap:FairValueMeasurementsRecurringMember 2025-01-31 0000104169 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2025-04-30 0000104169 us-gaap:FairValueInputsLevel2Member us-gaap:FairValueMeasurementsRecurringMember 2025-01-31 0000104169 us-gaap:FairValueMeasurementsRecurringMember 2025 [...TRUNCATED...] 2 to the Report on Form 8-K filed by the Company on April 28, 2025 Exhibit 4.3 S eries Terms Certificate Pursuant to the Indenture Relating to 4.350% Notes Due 20 30 of the Company is incorporated herein by reference to Exhibit 4.3 to the Report on Form 8-K filed by the Company on April 28, 2025 Exhibit 4.4 S eries Terms Certificate Pursuant to the Indenture Relating to 4.900% Notes Due 2035 of the Company is incorporated herein by reference to Exhibit 4.4 to the Report on Form 8-K filed by the Company on April 28, 2025 Exhibit 4.5 Form of Global Note to represent the Floating Rate Notes Due 2027 of the Company is inc orporated herein by reference to Exhibit 4.5 to the Report on Form 8-K filed by the Company on April 28, 2025 Exhibit 4.6 F or m of Global Note to represent the 4.100% Notes Due 2027 of the Company is incorporated herein by reference to Exhibit 4.6 to the Report on Form 8-K filed by the Company on April 28, 2025 Exhibit 4.7 F orm of Global Note to represent the 4.350% Notes Due 2030 of the Company is incorporated herein by reference to Exhibit 4.7 to the Report on Form 8-K filed by the Company on April 28, 2025 Exhibit 4.8 F orm of Global Note to represent the 4.900% Notes Due 2035 of the Company is incorporated herein by reference to Exhibit 4.8 to the Report on Form 8-K filed by the Company on April 28, 2025 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended April 30, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 34 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: June 6, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: June 6, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: June 6, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 35\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": 9045}} +{"id": "T3_all_20250909_0176", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-09-09", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0139, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=0.0014, std=0.0064, worst_day=-0.0167\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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 = 0.0139 (i.e., a 1.39% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0139 = 7.2145, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013861, "expected_loss": 0.013861, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20251231_0179", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-12-31", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1022, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0065, std=0.0510, worst_day=-0.1354\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9782", "answer_numeric": 0.9782, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1022 (i.e., a 10.22% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1022 = 0.9782, capped at 1.0.\nMaximum position size = 0.9782 (97.8% of portfolio).", "metadata": {"var_99": -0.102227, "expected_loss": 0.102227, "max_drawdown_threshold": 0.1, "position_size": 0.9782, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251024_0181", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-10-24", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0509, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0003, std=0.0188, worst_day=-0.0698\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0509 (i.e., a 5.09% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0509 = 1.9653, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.050884, "expected_loss": 0.050884, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251113_0184", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["TLH"], "decision_date": "2025-11-13", "context_summary": "TLH: 60-day history, VaR(99%)=-0.0087, max drawdown threshold=10%.", "question": "Asset: TLH\nDaily returns (past 60 days): mean=0.0006, std=0.0047, 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 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 = 0.0087 (i.e., a 0.87% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0087 = 11.4797, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.008711, "expected_loss": 0.008711, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250528_0187", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-05-28", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0356, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0005, std=0.0143, worst_day=-0.0356\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-27] [\"Company News for May 27, 2025 Shares of Apple Inc. AAPL lost 3% after Donald Trump warned the company it could face potential 25% tariffs on phones sold domestically in the United States, but are manufactured outside. Shares of Booz Allen Hamilton Holding Corporation BAH plummeted 16.5% after reporting fourth-quarter 2025 revenues of $2.97 billion, missing the Zacks Consensus Estimate of $3.01 billion. Shares of Intuit Inc. INTU gained 8.1% after reporting third-quarter fiscal 2025 earnings of $11.65 per share, beating the Zacks Consensus Estimate of $10.89. Shares of National Grid plc NGG rose 1.6% on Utilities emerging as the biggest winning sector of the day. 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 Intuit Inc. (INTU) : Free Stock Analysis Report National Grid Transco, PLC (NGG) : Free Stock Analysis Report Booz Allen Hamilton Holding Corporation (BAH) : Free Stock Analysis Report This article originally published on Zacks Investment Research (zacks.com). Zacks Investment Research\", \"Apple Shares Face More Pain as Trump\\u2019s Tariff Threat Looms (Bloomberg) -- Apple Inc. shares are coming off their longest selloff in more than three years, as escalating attacks from the White House threaten to further erode the company\\u2019s profit outlook, suggesting the stock\\u2019s struggles this year are far from over. Most Read from Bloomberg UAE\\u2019s AI University Aims to Become Stanford of the Gulf Pacific Coast Highway to Reopen Near Malibu After January Fires NY Wins Order Against US Funding Freeze in Congestion Fight President Donald Trump on Friday threatened to levy a 25% tariff on the company\\u2019s products if it doesn\\u2019t shift iPhone production to the US. Shares fell 3% to end the week, their eighth straight negative session, the longest such selloff since January 2022. The stock rose 1.7% on Tuesday. Some analysts are skeptical that the tariffs will come to pass, but any movement in this direction will put the company in a position where it either has to absorb the higher costs, weighing on its earnings and margins, or pass along higher prices to consumers, which could erode demand at a time when Apple is already struggling with tepid growth and difficulties with its artificial intelligence offerings. \\u201cThe threat may be politically motivated but markets can\\u2019t ignore the headline risk,\\u201d said Haris Khurshid, chief investment officer at Karobaar Capital. \\u201cThis kind of tariff rhetoric, even if it never materializes, chips away at investor confidence. You can\\u2019t run a $3 trillion company with a trade grenade hanging overhead.\\u201d Apple is the worst-performing Magnificent Seven stock this year, and its 2025 drop of 21% stands in stark contrast to the 1% rise of the Nasdaq 100 Index. The stock has broken under key moving averages, but isn\\u2019t yet at the le\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_20250101_0190", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-01-01", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0235, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=-0.0011, std=0.0107, worst_day=-0.0239\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to 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 = 0.0235 (i.e., a 2.35% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0235 = 4.2519, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023519, "expected_loss": 0.023519, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20251124_0192", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-11-24", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0110, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0000, std=0.0052, worst_day=-0.0127\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2025-11-19] nvda-20251026 0001045810 1/25 2026 Q3 FALSE 478 469 278 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:investment nvda:segment 0001045810 2025-01-27 2025-10-26 0001045810 2025-11-14 0001045810 2025-07-28 2025-10-26 0001045810 2024-07-29 2024-10-27 0001045810 2024-01-29 2024-10-27 0001045810 2025-10-26 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 2025-07-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-27 0001045810 us-gaap:RetainedEarningsMember 2025-07-27 0001045810 2025-07-27 0001045810 us-gaap:RetainedEarningsMember 2025-07-28 2025-10-26 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-28 2025-10-26 0001045810 us-gaap:CommonStockMember 2025-07-28 2025-10-26 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-28 2025-10-26 0001045810 us-gaap:CommonStockMember 2025-10-26 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-10-26 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-26 0001045810 us-gaap:RetainedEarningsMember 2025-10-26 0001045810 us-gaap:CommonStockMember 2024-07-28 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-07-28 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-28 0001045810 us-gaap:RetainedEarningsMember 2024-07-28 0001045810 2024-07-28 0001045810 us-gaap:RetainedEarningsMember 2024-07-29 2024-10-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-29 2024-10-27 0001045810 us-gaap:CommonStockMember 2024-07-29 2024-10-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-07-29 2024-10-27 0001045810 us-gaap:CommonStockMember 2024-10-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-10-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-27 0001045810 us-gaap:RetainedEarningsMember 2024-10-27 0001045810 2024-10-27 0001045810 us-gaap:CommonStockMember 2025-01-26 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-01-26 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-26 0001045810 us-gaap:RetainedEarningsMember 2025-01-26 0001045810 us-gaap:RetainedEarningsMember 2025-01-27 2025-10-26 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-27 2025-10-26 0001045810 us-gaap:CommonStockMember 2025-01-27 2025-10-26 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-01-27 2025-10-26 0001045810 us-gaap:CommonStockMember 2024-01-28 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-01-28 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-28 0001045810 us-gaap:RetainedEarningsMember 2024-01-28 0001045810 2024-01-28 0001045810 us-gaap:RetainedEarningsMember 2024-01-29 2024-10-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-29 2024-10-27 0001045810 us-gaap:CommonStockMember 2024-01-29 2024-10-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-01-29 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nvda:RSUsPSUsandMarketbasedPSUsMember 2025-01-27 2025-10-26 0001045810 nvda:RSUsPSUsandMarketbasedPSUsMember 2025-10-26 0001045810 us-gaap:EmployeeStockMember 2025-01-27 2025-10-26 0001045810 us-gaap:USTreasurySecuritiesMember 2025-10-26 0001045810 us-gaap:CorporateDebtSecuritiesMember 2025-10-26 0001045810 us-gaap:MoneyMarketFundsMember 2025-10-26 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-10-26 0001045810 us-gaap:CertificatesOfDepositMember 2025-10-26 0001045810 us-gaap:ForeignGovernmentDebtMember 2025-10-26 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2025-10-26 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2025-10-26 0001045810 2025-01-27 2025-04-27 0001045810 us-gaap:CorporateDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:USTreasurySecuritiesMember 2025-01-26 0001045810 us-gaap:MoneyMarketFundsMember 2025-01-26 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:ForeignGovernmentDebtMember 2025-01-26 0001045810 us-gaap:CertificatesOfDepositMember 2025-01-26 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2025-01-26 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2025-01-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-10-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-01-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-10-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:CustomerOneMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerTwoMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerThreeMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerFourMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:Cust [...TRUNCATED...] President, Operations Adoption 9/9/2025 309,840 12/31/2026 Donald Robertson Vice President and Chief Accounting Officer Adoption 9/18/2025 138,042 * 12/31/2026 Ajay Puri Executive Vice President, Worldwide Field Operations Adoption 9/19/2025 1,000,000 6/24/2026 * Includes 38,042 shares from future vests of equity awards, and the actual number of shares to be sold will be net of shares withheld by the Company for taxes. 42 Item 6. Exhibits Exhibit No.  Exhibit Description 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 43 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 19, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 44\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 = 0.0110 (i.e., a 1.10% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0110 = 9.0925, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.010998, "expected_loss": 0.010998, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20251015_0195", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-10-15", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.1140, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0025, std=0.0471, worst_day=-0.1463\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to 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": "0.8775", "answer_numeric": 0.8775, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1140 (i.e., a 11.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1140 = 0.8775, capped at 1.0.\nMaximum position size = 0.8775 (87.8% of portfolio).", "metadata": {"var_99": -0.11396, "expected_loss": 0.11396, "max_drawdown_threshold": 0.1, "position_size": 0.8775, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250227_0198", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-02-27", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1099, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0013, std=0.0500, worst_day=-0.1161\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9099", "answer_numeric": 0.9099, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1099 (i.e., a 10.99% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1099 = 0.9099, capped at 1.0.\nMaximum position size = 0.9099 (91.0% of portfolio).", "metadata": {"var_99": -0.109904, "expected_loss": 0.109904, "max_drawdown_threshold": 0.1, "position_size": 0.9099, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250613_0200", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-06-13", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0606, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0010, std=0.0286, worst_day=-0.0675\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0606 (i.e., a 6.06% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0606 = 1.6508, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.060575, "expected_loss": 0.060575, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250121_0203", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-01-21", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0553, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0020, std=0.0310, worst_day=-0.0718\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0553 (i.e., a 5.53% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0553 = 1.8067, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.055349, "expected_loss": 0.055349, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250926_0206", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLE"], "decision_date": "2025-09-26", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0208, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0012, std=0.0104, worst_day=-0.0227\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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 = 0.0208 (i.e., a 2.08% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0208 = 4.8070, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020803, "expected_loss": 0.020803, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20251204_0208", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI"], "decision_date": "2025-12-04", "context_summary": "FXI: 60-day history, VaR(99%)=-0.0299, max drawdown threshold=10%.", "question": "Asset: FXI\nDaily returns (past 60 days): mean=-0.0001, std=0.0121, worst_day=-0.0438\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-10-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-10-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-10-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-10-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-10-31 0000104169 2025-12-02 0000104169 2025-08-01 2025-10-31 0000104169 2024-08-01 2024-10-31 0000104169 2024-02-01 2024-10-31 0000104169 2025-10-31 0000104169 2025-01-31 0000104169 2024-10-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 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us-gaap:ParentMember 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-08-01 2025-10-31 0000104169 us-gaap:ParentMember 2025-08-01 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-08-01 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-08-01 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to 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 = 0.0299 (i.e., a 2.99% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0299 = 3.3442, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029902, "expected_loss": 0.029902, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250417_0211", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-04-17", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1498, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0053, std=0.0603, worst_day=-0.1701\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.6678", "answer_numeric": 0.6678, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1498 (i.e., a 14.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1498 = 0.6678, capped at 1.0.\nMaximum position size = 0.6678 (66.8% of portfolio).", "metadata": {"var_99": -0.149754, "expected_loss": 0.149754, "max_drawdown_threshold": 0.1, "position_size": 0.6678, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251104_0214", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-11-04", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1614, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0036, std=0.0448, worst_day=-0.1989\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.6194", "answer_numeric": 0.6194, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1614 (i.e., a 16.14% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1614 = 0.6194, capped at 1.0.\nMaximum position size = 0.6194 (61.9% of portfolio).", "metadata": {"var_99": -0.161446, "expected_loss": 0.161446, "max_drawdown_threshold": 0.1, "position_size": 0.6194, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250801_0216", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-08-01", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0795, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0010, std=0.0352, worst_day=-0.0949\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0795 (i.e., a 7.95% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0795 = 1.2585, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.07946, "expected_loss": 0.07946, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251014_0219", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-10-14", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0996, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0003, std=0.0408, worst_day=-0.1204\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0996 (i.e., a 9.96% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0996 = 1.0043, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.099571, "expected_loss": 0.099571, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250617_0221", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV"], "decision_date": "2025-06-17", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0328, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0007, std=0.0133, worst_day=-0.0328\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-16] [\"My Top 5 AI Stocks to Buy Before the Second Half AI stocks drove market gains over the past two years, but earlier this year they led declines. Investors, worried about the potential impact of import tariffs on the economy, avoided growth stocks. Since, pressure has eased, opening up the door to more possible gains for AI players. 10 stocks we like better than Nvidia \\u203a The first half of the year was a turbulent one for stocks in general amid concern President Trump's planned import tariffs would hurt the economy. And this problem weighed most heavily on stocks that depend on growth and investment -- such as those in the field of artificial intelligence (AI). These particular players led indexes higher over the past two years on optimism about spending and the technology's potential, but they lost momentum in March and April. Since, though, the U.S. has made progress on trade talks, and this has lifted market sentiment. Meanwhile, tech companies' earnings reports show no signs of a slowdown in AI spending. This has spurred new gains in AI stocks, and if the U.S. trade situation resolves without excessively high tariffs, these players could continue to advance. With this in mind, here are my top five AI stocks to buy before the second half. Nvidia (NASDAQ: NVDA) soared more than 800% over the past two years as investors piled into this stock driving the AI revolution. The company dominates the AI chip market, and these chips are used for the most essential AI tasks. Nvidia hasn't had to wait to benefit from the AI market. The company already has delivered double- or triple-digit growth, with revenue attaining record levels. This momentum is likely to continue as Nvidia is well positioned to power AI across every stage of development, from training through the creation of humanoid robots. I'm confident about this thanks to Nvidia's commitment to innovation -- it's already set out a calendar of chip updates through 2028. This makes it very difficult for rivals to upset its position. Now is a great time to get in on this high-potential player as it's on sale, trading for 33 times forward earnings estimates -- down from more than 50 earlier in the year. Amazon (NASDAQ: AMZN), which sells some imported goods on its e-commerce site and also works with sellers that import goods, may benefit as trade tensions ease. The company also is winning from AI in two ways: Amazon uses AI tools to streamline operations, resulting in lower costs and greater efficiency. And Amazon, through its cloud unit Amazon Web Services (AWS), sells AI services to customers. AI services already have helped AWS reach a $117 billion annual revenue run rate. All of this could make Amazon a winner in the second half of this year and beyond. On top of this, the company already has demonstrated its earnings strength, growing revenue and profit over time. And its overhaul of its cost structure in recent years should drive even more gains moving forward. Amazon's valuation has falle\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_20250522_0223", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2025-05-22", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0339, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=-0.0009, std=0.0141, worst_day=-0.0339\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-21] [\"China AI Rally Laggard Baidu Faces Low Bar for Earnings Boost (Bloomberg) -- The current earnings season has largely been a letdown for China\\u2019s big tech stocks, lowering the hurdle for Baidu Inc. to impress investors seeking a fresh angle on the artificial intelligence theme. Most Read from Bloomberg Can Frank Gehry\\u2019s \\u2018Grand LA\\u2019 Make Downtown Feel Like a Neighborhood? Chicago\\u2019s O\\u2019Hare Airport Seeks Up to $4.3 Billion of Muni Debt NJ Transit Makes Deal With Engineers, Ending Three-Day Strike China\\u2019s top search engine had made early advances in AI but fell behind as DeepSeek shocked the world with its low-cost model and Alibaba Group Holding Ltd. grabbed headlines as well. Baidu\\u2019s shares are up 6% in Hong Kong this year, while Alibaba has surged 48% and the Hang Seng Tech Index has climbed 19%. The street has drastically lowered its view on Baidu ahead of its results due later Wednesday, with the average 12-month analyst price target for the stock down 26% over the past year. It\\u2019s also now trading at a big discount relative to peers and historical levels. In a similar vein to Alphabet Inc.\\u2019s results beat last month, \\u201cif Baidu can build a strong case that search is not an ex-growth business and GenAI can boost its existing business including search, that will make the low expectation into the earnings play in favor of the stock price,\\u201d said Xiadong Bao, a fund manager at Edmond de Rothschild Asset Management. China tech stocks have lost some steam since March\\u2019s DeepSeek-fueled peak amid concerns over tensions with the US, the health of China\\u2019s economy and Beijing\\u2019s stimulus plans. Recent earnings from Alibaba and Tencent Holdings Ltd. underwhelmed investors looking for a new catalyst. Advertising still accounts for the bulk of Baidu\\u2019s revenue, and investors will be closely watching for clear signs of improvement in the macro-dependent business. UBS AG estimates its ad revenue declined 5.7%, a smaller drop than in the December quarter. The slow ad recovery has been weighing on Baidu\\u2019s shares the most, said Kai Wang, a Morningstar Inc. analyst. \\u201cOnce advertising comes back, Baidu\\u2019s valuation should come up pretty quickly, as that\\u2019s likely holding the AI business back,\\u201d he said. \\u201cIt\\u2019s one of the few players in China that can actually build out the data centers and AI infrastructure, while its AI offerings with the Ernie model have improved.\\u201d The stock\\u2019s underperformance has made it cheaper, currently trading at 8.6 times forward earnings estimates, well below its longer-term averages as well as the Hang Seng Tech Index\\u2019s 16 times. On the positive side, UBS, Morgan Stanley and others expect Baidu to post robust cloud sales growth of more than 20% for the three months ended March, extending the December period\\u2019s AI-driven momentum. Analysts project it will report a narrower decline in overall quarterly revenue and retur\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 = 0.0339 (i.e., a 3.39% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0339 = 2.9513, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033883, "expected_loss": 0.033883, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250314_0226", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-03-14", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.1252, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0083, std=0.0444, worst_day=-0.1485\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7989", "answer_numeric": 0.7989, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1252 (i.e., a 12.52% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1252 = 0.7989, capped at 1.0.\nMaximum position size = 0.7989 (79.9% of portfolio).", "metadata": {"var_99": -0.125179, "expected_loss": 0.125179, "max_drawdown_threshold": 0.1, "position_size": 0.7989, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250218_0229", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-02-18", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0415, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0001, std=0.0209, worst_day=-0.0505\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0415 (i.e., a 4.15% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0415 = 2.4082, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.041524, "expected_loss": 0.041524, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250516_0232", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-05-16", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0337, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=-0.0008, std=0.0149, worst_day=-0.0337\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-15] [\"Trump Says India Offered to Remove All Tariffs on US Goods (Bloomberg) -- Sign up for the India Edition newsletter by Menaka Doshi \\u2013 an insider's guide to the emerging economic powerhouse, and the billionaires and businesses behind its rise, delivered weekly. Most Read from Bloomberg As Coastline Erodes, One California City Considers \\u2018Retreat Now\\u2019 As Coastline Erodes, One California City Considers \\u2018Retreat Now\\u2019 How a Highway Became San Francisco\\u2019s Newest Park How a Highway Became San Francisco\\u2019s Newest Park Power-Hungry Data Centers Are Warming Homes in the Nordics Power-Hungry Data Centers Are Warming Homes in the Nordics Maryland\\u2019s Credit Rating Gets Downgraded as Governor Blames Trump Maryland\\u2019s Credit Rating Gets Downgraded as Governor Blames Trump NYC Commuters Brace for Chaos as NJ Transit Rail Strike Looms NYC Commuters Brace for Chaos as NJ Transit Rail Strike Looms President Donald Trump said India has made an offer to drop tariffs on US goods, as the Asian nation negotiates a deal to avert higher import taxes. Speaking Thursday at an event with business leaders in Qatar, Trump said the Indian government has \\u201coffered us a deal where basically they are willing to literally charge us no tariff.\\u201d Trump didn\\u2019t provide further details of New Delhi\\u2019s apparent offer and the Indian Ministry of Commerce and Industry didn\\u2019t immediately respond to a request for comment. India\\u2019s External Affairs Minister Subrahmanyam Jaishankar told reporters later in the day that trade talks between India and the US are ongoing and \\u201cany judgment on it would be premature\\u201d until a \\u201cmutually beneficial\\u201d agreement is reached, according to local media. India was one of the first countries to begin trade negotiations with the US following Prime Minister Narendra Modi\\u2019s visit to the White House in February, with both sides agreeing to finalize the first phase of a bilateral deal by the fall. India\\u2019s trade minister is expected to meet Trump administration officials in the US from May 17-20 for further negotiations. Trump\\u2019s comments came days after India threatened to impose retaliatory tariffs in response to higher US duties on steel and aluminum, a sign that New Delhi may be adopting a more assertive approach in its trade negotiations with the White House. The trade talks remain on track though, people familiar with the matter have said. Some analysts in New Delhi suggested that Trump\\u2019s remarks could indicate either that India is close to finalizing a deal, or that the comments are a negotiating tactic by the White House. \\u201cAn India\\u2013US trade deal may be on the cards,\\u201d said Ajay Srivastava, founder of New Delhi-based think tank Global Trade Research Institute. \\u201cBut the deal must ensure strict reciprocity, with both sides eliminating tariffs equally.\\u201d Market reaction was relatively muted after Trump\\u2019s comments with the rupee recou\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_20250825_0235", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX"], "decision_date": "2025-08-25", "context_summary": "^VIX: 60-day history, VaR(99%)=-0.1527, max drawdown threshold=10%.", "question": "Asset: ^VIX\nDaily returns (past 60 days): mean=-0.0051, std=0.0637, worst_day=-0.1548\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-08-22] [\"Sector Update: Tech Stocks Decline Thursday Afternoon Tech stocks retreated Thursday afternoon, with the Technology Select Sector SPDR Fund (XLK) decreasi\", \"Steve Jobs didn\\u2019t actually become a billionaire thanks to leading Apple\\u2014but rather from his work with a film company he bought off George Lucas The late billionaire Steve Jobs is known for being cofounder and CEO of Apple\\u2014and introducing the iPhone, iPad, and iMac to the world. However, his time at the computer company wasn\\u2019t what helped strike gold for his net worth. Jobs actually made the billions in 1995\\u2014three years before the iMac hit shelves\\u2014after using an unexpected career roadblock to his advantage, with a little help from Tom Hanks and Tim Allen. \\u201cTo infinity and beyond!\\u201d wasn\\u2019t just the catchphrase of Toy Story\\u2019s Buzz Lightyear\\u2014it was the turning point that turned Steve Jobs into a billionaire. After a power struggle that forced Jobs out of Apple in 1985, Jobs bought Lucasfilm\\u2019s computer graphics division the next year for $10 million. The seller was George Lucas, fresh off creating the Star Wars empire. That small acquisition would soon be renamed Pixar\\u2014and would change both Hollywood and Jobs\\u2019 fortune forever. The company got off to a rocky start, with Jobs questioning whether to sell it multiple times, thanks in part to having to personally cover its monthly cash shortfall. But by 1995, Jobs believed Pixar was ready for primetime. In a week\\u2019s span in November, it would release its first major film, Toy Story, as well as launch an IPO. Lawrence Levy, the company\\u2019s then-CFO, wrote that it reminded him of the 100-meter sprint in the Olympic Games: a lifetime of training that comes down to a snapshot performance. \\u201cIf the world fell in love with Toy Story, Pixar would have a chance to usher in a new era of animated entertainment,\\u201d he said in his book, To Pixar and Beyond: My Unlikely Journey With Steve Jobs to Make Entertainment History. \\u201cIf it didn\\u2019t, Pixar might be written off as another company that tried but never quite hit the mark.\\u201d As the 80% owner of Pixar, the IPO stakes were even higher for Jobs. If everything went well, he was hoping to finally see some return on his Pixar investment. If everything went south, it might have shut the door on any future collaboration with Disney and led to the waste of a decade of his entrepreneurial life. Luckily, all expectations were shattered. Pixar\\u2019s initial stock price was predicted to reach between $12 and $14, but at the end of the first day of trading, it was worth 175% more, at $39 a share. This was thanks largely to Toy Story, with Tom Hanks and Tim Allen as lead voices, nearly doubling its box office expectations. Jobs\\u2019 stake sent his net worth soaring to over $1 billion. Jobs would later rejoin Apple in 1997, but he remained involved in Pixar as it churned out hit after hit, including Finding Nemo, The Incredibles,\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": "0.6550", "answer_numeric": 0.655, "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 = 0.6550, capped at 1.0.\nMaximum position size = 0.6550 (65.5% of portfolio).", "metadata": {"var_99": -0.152663, "expected_loss": 0.152663, "max_drawdown_threshold": 0.1, "position_size": 0.655, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250328_0237", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNDX"], "decision_date": "2025-03-28", "context_summary": "BNDX: 60-day history, VaR(99%)=-0.0064, max drawdown threshold=10%.", "question": "Asset: BNDX\nDaily returns (past 60 days): mean=-0.0001, std=0.0025, worst_day=-0.0064\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 = 0.0064 (i.e., a 0.64% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0064 = 15.7147, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.006363, "expected_loss": 0.006363, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251219_0241", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-12-19", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0974, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0053, std=0.0425, worst_day=-0.1339\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0974 (i.e., a 9.74% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0974 = 1.0265, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.097422, "expected_loss": 0.097422, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250506_0244", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2025-05-06", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0371, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=-0.0023, std=0.0160, worst_day=-0.0371\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q PFE 2025-05-05] pfe-20250330 0000078003 12/31 2025 Q1 false P1Y P3Y P5Y P7Y xbrli:shares iso4217:USD iso4217:USD xbrli:shares pfe:segment xbrli:pure pfe:company pfe:patent pfe:complaint pfe:treatment_course 0000078003 2025-01-01 2025-03-30 0000078003 us-gaap:CommonStockMember 2025-01-01 2025-03-30 0000078003 pfe:NotesDue20271.000Member 2025-01-01 2025-03-30 0000078003 2025-04-30 0000078003 us-gaap:ProductMember 2025-01-01 2025-03-30 0000078003 us-gaap:ProductMember 2024-01-01 2024-03-31 0000078003 2024-01-01 2024-03-31 0000078003 us-gaap:RoyaltyMember 2025-01-01 2025-03-30 0000078003 us-gaap:RoyaltyMember 2024-01-01 2024-03-31 0000078003 2025-03-30 0000078003 2024-12-31 0000078003 us-gaap:CommonStockMember 2024-12-31 0000078003 us-gaap:AdditionalPaidInCapitalMember 2024-12-31 0000078003 us-gaap:TreasuryStockCommonMember 2024-12-31 0000078003 us-gaap:RetainedEarningsMember 2024-12-31 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-12-31 0000078003 us-gaap:ParentMember 2024-12-31 0000078003 us-gaap:NoncontrollingInterestMember 2024-12-31 0000078003 us-gaap:RetainedEarningsMember 2025-01-01 2025-03-30 0000078003 us-gaap:ParentMember 2025-01-01 2025-03-30 0000078003 us-gaap:NoncontrollingInterestMember 2025-01-01 2025-03-30 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-01 2025-03-30 0000078003 us-gaap:CommonStockMember 2025-01-01 2025-03-30 0000078003 us-gaap:AdditionalPaidInCapitalMember 2025-01-01 2025-03-30 0000078003 us-gaap:TreasuryStockCommonMember 2025-01-01 2025-03-30 0000078003 us-gaap:CommonStockMember 2025-03-30 0000078003 us-gaap:AdditionalPaidInCapitalMember 2025-03-30 0000078003 us-gaap:TreasuryStockCommonMember 2025-03-30 0000078003 us-gaap:RetainedEarningsMember 2025-03-30 0000078003 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-03-30 0000078003 us-gaap:ParentMember 2025-03-30 0000078003 us-gaap:NoncontrollingInterestMember 2025-03-30 0000078003 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pfe:NetSalesAndRoyaltyAgreementTermsMember pfe:BlackstoneMember 2025-03-30 0000078003 pfe:NetSalesAndRoyaltyAgreementTermsMember pfe:BlackstoneMember srt:MinimumMember 2025-03-30 0000078003 pfe:NetSalesAndRoyaltyAgreementTermsMember pfe:BlackstoneMember srt:MaximumMember 2025-03-30 0000078003 pfe:RealigningOurCostBaseProgramInitialPhaseMember 2025-03-30 0000078003 pfe:RealigningOurCostBaseProgramInitialPhaseMember pfe:BiopharmaSegmentMember 2025-03-30 0000078003 us-gaap:OtherRestructuringMember pfe:RealigningOurCostBaseProgramSellingInformationalAndAdministrativeInitiativeMember us-gaap:SubsequentEventMember 2025-05-05 0000078003 us-gaap:OtherRestructuringMember pfe:RealigningOurCostBaseProgramSellingInformationalAndAdministrativeInitiativeMember us-gaap:SubsequentEventMember pfe:BiopharmaSegmentMember 2025-05-05 0000078003 us-gaap:OtherRestructuringMember pfe:RealigningOurCostBaseProgramResearchAndDevelopmentMember pfe:BiopharmaSegmentMember 2025-03-30 0000078003 pfe:RealigningOurCostBaseProgramMember us-gaap:SubsequentEventMember 2025-05-05 0000078003 pfe:RealigningOurCostBaseProgramMember us-gaap:SubsequentEventMember pfe:BiopharmaSegmentMember 2025-05-05 0000078003 pfe:RealigningOurCostBaseProgramMember 2025-03-30 0000078003 pfe:RealigningOurCostBaseProgramMember pfe:BiopharmaSegmentMember 2025-03-30 0000078003 pfe:RealigningOurCostBaseProgramMember pfe:BiopharmaSegmentMember 2023-10-02 2025-03-30 0000078003 pfe:ManufacturingOptimizationProgramPhaseOneMember pfe:BiopharmaSegmentMember 2025-03-30 0000078003 pfe:ManufacturingOptimizationProgramMember pfe:BiopharmaSegmentMember 2025-03-30 0000078003 us-gaap:OtherNonoperatingIncomeExpenseMember 2025-01-01 2025-03-30 0000078003 us-gaap:OtherNonoperatingIncomeExpenseMember 2024-01-01 2024-03-31 0000078003 us-gaap:CostOfSalesMember 2025-01-01 2025-03-30 0000078003 us-gaap:CostOfSalesMember 2024-01-01 2024-03-31 0000078003 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2025-01-01 2025-03-30 0000078003 us-gaap:SellingGeneralAndAdministrativeExpensesMember 2024-01-01 2024-03-31 0000078003 us-gaap:ResearchAnd [...TRUNCATED...] f Shares Purchased as Part of Publicly Announced Plan Approximate Value of Shares That May Yet Be Purchased Under the Plan (b) January 1 through January 26, 2025 25,387  $ 26.65  —  $ 3,292,882,444  January 27 through February 23, 2025 1,107,921  $ 26.29  —  $ 3,292,882,444  February 24 through March 30, 2025 8,191,799  $ 26.23  —  $ 3,292,882,444  Total 9,325,107  $ 26.24  —  50 (a) Represents (i) 9,321,821 shares of common stock surrendered to the Company to satisfy tax withholding obligations in connection with the vesting of awards under our long-term incentive programs and (ii) the open market purchase by the trustee of 3,286 shares of common stock in connection with the reinvestment of dividends paid on common stock held in trust for employees who deferred receipt of performance share awards. (b) See Note 12 in our 2024 Form 10-K. ITEM 5. OTHER INFORMATION During the three months ended March 30, 2025, none of our directors or officers adopted or terminated a “Rule 10b5-1 trading arrangement” or “non-Rule 10b5-1 trading arrangement,” as each term is defined in Item 408 of Regulation S-K. ITEM 6. EXHIBITS   Exhibit 31.1 Certification by the Chief Executive Officer Pursuant to Section 302 of the Sarbanes-Oxley Act of 2002.   Exhibit 31.2 Certification by the Chief Financial Officer Pursuant to Section 302 of the Sarbanes-Oxley Act of 2002.   Exhibit 32.1 Certification by the Chief Executive Officer Pursuant to 18 U.S.C. Section 1350, as Adopted Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002.   Exhibit 32.2 Certification by the Chief Financial Officer Pursuant to 18 U.S.C. Section 1350, as Adopted Pursuant to Section 906 of the Sarbanes-Oxley Act of 2002.   Exhibit 101:     EX-101.INS XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document.   EX-101.SCH EX-101.CAL EX-101.LAB EX-101.PRE EX-101.DEF   Inline XBRL Taxonomy Extension Schema Inline XBRL Taxonomy Extension Calculation Linkbase Inline XBRL Taxonomy Extension Label Linkbase Inline XBRL Taxonomy Extension Presentation Linkbase Inline XBRL Taxonomy Extension Definition Document Exhibit 104 Cover Page Interactive Data File––the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   Pfizer Inc.   (Registrant)         Dated: May 5, 2025 /s/ Jennifer B. Damico   Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) 51\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": 9045}} +{"id": "T3_all_20250107_0246", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2025-01-07", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0226, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=-0.0006, std=0.0095, worst_day=-0.0254\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to 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 = 0.0226 (i.e., a 2.26% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0226 = 4.4193, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022628, "expected_loss": 0.022628, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250918_0249", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2025-09-18", "context_summary": "VNQ: 60-day history, VaR(99%)=-0.0197, max drawdown threshold=10%.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=0.0004, std=0.0089, worst_day=-0.0241\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\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 = 0.0197 (i.e., a 1.97% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0197 = 5.0883, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019653, "expected_loss": 0.019653, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250306_0252", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-03-06", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0192, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0012, std=0.0083, worst_day=-0.0248\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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0000078003 us-gaap:OtherCurrentLiabilitiesMember 2023-12-31 0 [...TRUNCATED...] my Extension Presentation Linkbase *101.DEF Inline XBRL Taxonomy Extension Definition Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. ITEM 16. FORM 10-K SUMMARY None. SIGNATURES Under the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, this report was signed on behalf of the Registrant by the authorized person named below. Pfizer Inc. Dated: February 27, 2025 By: /S/    MARGARET M. MADDEN Margaret M. Madden Senior Vice President and Corporate Secretary Chief Governance Counsel We, the undersigned directors and officers of Pfizer Inc., hereby severally constitute Douglas M. Lankler and Margaret M. Madden, and each of them singly, our true and lawful attorneys with full power to them and each of them to sign for us, in our names in the capacities indicated below, any and all amendments to this Annual Report on Form 10-K filed with the Securities and Exchange Commission. Under the requirements of the Securities Exchange Act of 1934, this report was signed by the following persons on behalf of the Registrant and in the capacities and on the date indicated . Pfizer Inc. 2024 Form 10-K 113 Signature Title Date /S/    ALBERT BOURLA Albert Bourla Chairman, Chief Executive Officer and Director (Principal Executive Officer) February 27, 2025 /S/    DAVID M. DENTON David M. Denton Chief Financial Officer, Executive Vice President (Principal Financial Officer) February 27, 2025 /S/    JENNIFER B. DAMICO Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer) February 27, 2025 /S/    RONALD E. BLAYLOCK Ronald E. Blaylock Director February 27, 2025 /S/    MORTIMER J. BUCKLEY Mortimer J. Buckley Director February 27, 2025 /S/    SUSAN DESMOND-HELLMANN Susan Desmond-Hellmann Director February 27, 2025 /S/    JOSEPH J. ECHEVARRIA Joseph J. Echevarria Director February 27, 2025 /S/    SCOTT GOTTLIEB Scott Gottlieb Director February 27, 2025 /S/    HELEN H. HOBBS Helen H. Hobbs Director February 27, 2025 /S/    SUSAN HOCKFIELD Susan Hockfield Director February 27, 2025 /S/    DAN R. LITTMAN Dan R. Littman Director February 27, 2025 /S/    SHANTANU NARAYEN Shantanu Narayen Director February 27, 2025 /S/    SUZANNE NORA JOHNSON Suzanne Nora Johnson Director February 27, 2025 /S/    JAMES QUINCEY James Quincey Director February 27, 2025 /S/    JAMES C. SMITH James C. Smith Director February 27, 2025 /S/    CYRUS TARAPOREVALA Cyrus Taraporevala Director February 27, 2025 Pfizer Inc. 2024 Form 10-K 114\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 = 0.0192 (i.e., a 1.92% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0192 = 5.1997, 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": true, "text_chars": 9045}} +{"id": "T3_all_20250401_0255", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-04-01", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0206, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0004, std=0.0100, worst_day=-0.0211\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-03-31] LTRX Transforms Edge AI Computing by Unveiling Open-Q 8550CS SOM Lantronix, Inc. LTRX introduced its latest offering, the Open-Q 8550CS System-on-Module (SOM). Powered by Qualcomm\u2019s Dragonwing QCS8550 processor, this production-ready module is designed to bring low-power, high-performance AI and Machine Learning capabilities to the Edge computing. This innovation aims to accelerate the development of AI-driven applications across a broad spectrum of industries like smart warehousing, manufacturing, transportation, logistics and retail. Lantronix\u2019s Open-Q 8550CS SOM is built specifically to meet the extreme Edge AI demands, making it an ideal solution for advanced video applications, robotics, drones, industrial automation and smart warehousing. This Lantronix platform exhibits characteristics similar to all its embedded compute technology and delivers a full solution with hardware, software, Device Management, and services, allowing customers to accelerate time to market. Lantronix Open-Q solutions are TAA and NDAA-compliant, ensuring a minimum of 10 years of longevity with strict quality control. With more than 20 years of expertise, LTRX has delivered more than 1,200 hardware and software projects, fostering reliability and innovation. The state-of-the-art solution is a high-performance, power-efficient computing platform designed with best-in-class AI capabilities, security and connectivity. It has a powerful 4nm Octa-core CPU (up to 3.2 GHz), Adreno A740 GPU, dual AI engines, and strong security. Supports Wi-Fi 7 (5.8Gbps), up to 8GB LPDDR5 RAM, 128GB UFS storage, and runs Android 13 & Linux Yocto Kirkstone. It also features a Computer Vision Engine, multiple camera/display ports, and Qualcomm Sensing Hub 3.0 for top-tier AI, multimedia, and connectivity performance. This platform boosts video conferencing, AGV pathing, smart camera quality and Edge AI scalability with octa-core computing and 48 AI TOPS tensor performance. The platform handles 3D rendering and computer vision with Adreno 740 GPU, ray tracing and 4K/8K video support while enabling Edge AI with 2.5G and 10G Ethernet. To support developers in evaluating and integrating the Open-Q 8550CS SOM, Lantronix offers a comprehensive Development Kit. This kit provides a fully-featured carrier board exposing all I/O interfaces, support for multiple camera configurations (C-PHY and D-PHY MIPI CSI, GMSL), AI accelerators for always-on applications (voice, contextual data, sensors) and comprehensive connectivity options, including Gigabit Ethernet, GNSS and DisplayPort. This kit is designed to reduce development time, allowing developers to quickly test, validate and deploy AI-powered solutions. Apart from hardware and software, Lantronix Engineering Services provides turn-key product development support for Open-Q platforms and kits. With expertise in more than 1,500 successful products, the team specializes in camera tuning, voice control, machine learning, RF and mechanical design and powe\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 = 0.0206 (i.e., a 2.06% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0206 = 4.8577, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020586, "expected_loss": 0.020586, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250407_0258", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-04-07", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1460, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0066, std=0.0598, worst_day=-0.1761\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.6849", "answer_numeric": 0.6849, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1460 (i.e., a 14.60% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1460 = 0.6849, capped at 1.0.\nMaximum position size = 0.6849 (68.5% of portfolio).", "metadata": {"var_99": -0.145999, "expected_loss": 0.145999, "max_drawdown_threshold": 0.1, "position_size": 0.6849, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250527_0263", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP"], "decision_date": "2025-05-27", "context_summary": "XLP: 60-day history, VaR(99%)=-0.0232, max drawdown threshold=10%.", "question": "Asset: XLP\nDaily returns (past 60 days): mean=0.0000, std=0.0106, worst_day=-0.0250\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-23] [\"Gold Climbs After Trump\\u2019s EU and Apple Threats Stoke Trade Fears (Bloomberg) -- Gold extended its weekly gain toward 5% after Donald Trump threatened to impose sweeping tariffs on the European Union and Apple Inc., fueling demand for haven assets. Most Read from Bloomberg NY Private School Pleads for Donors to Stay Open After Declaring Bankruptcy Can Frank Gehry\\u2019s \\u2018Grand LA\\u2019 Make Downtown Feel Like a Neighborhood? UAE\\u2019s AI University Aims to Become Stanford of the Gulf NYC\\u2019s War on Trash Gets a Glam Squad Chicago\\u2019s O\\u2019Hare Airport Seeks Up to $4.3 Billion of Muni Debt Spot bullion rose by as much as 2.1% after the US President threatened a 50% tariff on goods from the European Union starting on June 1, saying \\u201cour discussions with them are going nowhere.\\u201d US equity futures fell. Trump also threatened Apple with a tariff of at least 25% if it does not manufacture its iPhones in the US. Bullion has surged by more than a quarter this year and is about $150 below the all-time-high reached last month. Its ascent has been underpinned by the fallout from the US-led tariff war, which sent investors fleeing from equities exposed to the disruptions in trade. Concerns about the fiscal position of the US government have also supported demand for haven assets. After the decision by Moody\\u2019s Ratings to strip the US of its top credit rating, investors are now concerned that President Donald Trump\\u2019s signature tax bill \\u2014 which passed the House and now goes to the Senate \\u2014 will boost the already swelling deficit. Yields on 10-year US Treasuries pushed higher this week, hovering around 4.5%. In earlier years, such a move would have been a major headwind for gold as it doesn\\u2019t pay interest, with bullion prices and yields typically moving inversely. That correlation has now weakened, as investors forgo higher interest payments for safe havens. Meanwhile platinum rose to the highest in two years and is on track for a weekly gain of more than 10%, the biggest such advance in more than four years. Gold traded 1.9% higher to $3,357.78 an ounce as of 11:33 a.m. in New York. The Bloomberg Dollar Spot Index slipped 0.6%, on course for a weekly drop. Silver advanced while palladium slipped. --With assistance from John Deane, Jason Scott, Yihui Xie and Yvonne Yue Li. Most Read from Bloomberg Businessweek Why Apple Still Hasn\\u2019t Cracked AI How Coach Handbags Became a Gen Z Status Symbol Inside the First Stargate AI Data Center Microsoft\\u2019s CEO on How AI Will Remake Every Company, Including His Anthropic Is Trying to Win the AI Race Without Losing Its Soul \\u00a92025 Bloomberg L.P.\", \"US Long-Term Borrowing Costs Surge Over Deficit Concerns (Bloomberg) -- Bond investors are demanding more and more compensation to hold long-dated US debt as global markets grow anxious about the widening fiscal deficit in the world\\u2019s biggest economy. Most Read from Bloomberg NY Private School Pleads for Donors\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 = 0.0232 (i.e., a 2.32% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0232 = 4.3067, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.02322, "expected_loss": 0.02322, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20251112_0265", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-11-12", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.1475, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0059, std=0.0497, worst_day=-0.1912\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.6781", "answer_numeric": 0.6781, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1475 (i.e., a 14.75% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1475 = 0.6781, capped at 1.0.\nMaximum position size = 0.6781 (67.8% of portfolio).", "metadata": {"var_99": -0.147463, "expected_loss": 0.147463, "max_drawdown_threshold": 0.1, "position_size": 0.6781, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251028_0267", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-10-28", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1119, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0024, std=0.0399, worst_day=-0.1761\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8938", "answer_numeric": 0.8938, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1119 (i.e., a 11.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1119 = 0.8938, capped at 1.0.\nMaximum position size = 0.8938 (89.4% of portfolio).", "metadata": {"var_99": -0.111879, "expected_loss": 0.111879, "max_drawdown_threshold": 0.1, "position_size": 0.8938, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250414_0270", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-04-14", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1219, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0050, std=0.0428, worst_day=-0.1391\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8201", "answer_numeric": 0.8201, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1219 (i.e., a 12.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1219 = 0.8201, capped at 1.0.\nMaximum position size = 0.8201 (82.0% of portfolio).", "metadata": {"var_99": -0.121938, "expected_loss": 0.121938, "max_drawdown_threshold": 0.1, "position_size": 0.8201, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250219_0273", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-02-19", "context_summary": "EFA: 59-day history, VaR(99%)=-0.0193, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 59 days): mean=0.0013, std=0.0075, worst_day=-0.0248\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000018230 cat:StockOptionsandShareAppreciationRightsSARsMember 2023-01-01 2023-12-31 0000018230 cat:StockOptionsandShareApprecia [...TRUNCATED...] ulation Linkbase Document 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive File (embedded within the Inline XBRL document and included in Exhibit 101) _________________________________________ *Management contracts and compensatory plans and arrangements required to be filed as exhibits pursuant to Item 15(b) of this report. The agreements and other documents filed as exhibits to this report are not intended to provide factual information or other disclosure other than with respect to the terms of the agreements or other documents themselves, and you should not rely on them for that purpose. In particular, any representations and warranties made by us in these agreements or other documents were made solely within the specific context of the relevant agreement or document and may not describe the actual state of affairs as of the date they were made or at any other time. Item 16.  Form 10-K Summary. None. 129 Table of Contents Form 10-K   SIGNATURES   Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.     CATERPILLAR INC.   Registrant     February 14, 2025 By: /s/ Derek Owens     Derek Owens Chief Legal Officer and General Counsel   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities and on the dates indicated.       Chairman of the Board  and Chief Executive Officer February 14, 2025 /s/ D. James Umpleby III   D. James Umpleby III       February 14, 2025 /s/ Andrew R.J. Bonfield Chief Financial Officer Andrew R.J. Bonfield     February 14, 2025 /s/ William E. Schaupp Vice President and Chief Accounting Officer   William E. Schaupp             February 14, 2025 /s/ Daniel M. Dickinson Director   Daniel M. Dickinson   February 14, 2025 /s/ James C. Fish, Jr. Director James C. Fish, Jr.       130 Table of Contents February 14, 2025 /s/ Gerald Johnson Director   Gerald Johnson   February 14, 2025 /s/ Nazzic S. Keene Director Nazzic S. Keene       February 14, 2025 /s/ David W. MacLennan Director   David W. MacLennan   February 14, 2025 /s/ Judith F. Marks Director Judith F. Marks February 14, 2025 /s/ Debra L. Reed-Klages Presiding Director Debra L. Reed-Klages       February 14, 2025 /s/ Susan C. Schwab Director   Susan C. Schwab             February 14, 2025 /s/ Rayford Wilkins, Jr. Director   Rayford Wilkins, Jr.   131\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EFA, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0193 (i.e., a 1.93% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0193 = 5.1742, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019327, "expected_loss": 0.019327, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250115_0276", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2025-01-15", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0218, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=-0.0006, std=0.0090, worst_day=-0.0287\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 2024-12-04 0000104169 2024-08-01 2024-10-31 0000104169 2023-08-01 2023-10-31 0000104169 2023-02-01 2023-10-31 0000104169 2024-10-31 0000104169 2024-01-31 0000104169 2023-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 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0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to 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 = 0.0218 (i.e., a 2.18% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0218 = 4.5899, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021787, "expected_loss": 0.021787, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250827_0279", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-08-27", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0152, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0008, std=0.0077, worst_day=-0.0176\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-08-26] [\"Apple\\u2019s August Stock Revival Gives Hope to Concerned Investors (Bloomberg) -- Apple Inc.\\u2019s stock is showing signs of life after struggling through most of 2025, as the tariff-related risks that have weighed on the company start to ease. Shares of the tech giant entered August down 17% for the year due in part to concerns about the impact of President Donald Trump\\u2019s sweeping levies, which cost the company $800 million in its fiscal third quarter alone. The US president has long criticized Apple for its reliance on overseas production partners, at one point even threatening to punish the company with tariffs if it didn\\u2019t make its iPhones in the US. Most Read from Bloomberg In Trump\\u2019s DC Crackdown, the National Park Service Leads Homeless Sweeps Germany Revives a Building Style With a Bleak History: Prefab Housing Chicago Schools\\u2019 Late Pension Payment Magnifies Fiscal Mess To Boost Housing, Chicago Kills Parking Minimums Central Glasgow Could Be Poised for a Revival Then, at an event in the Oval Office on Aug. 6, Apple Chief Executive Officer Tim Cook committed to spending an additional $100 billion on manufacturing in the US. Combined with the iPhone maker\\u2019s expansion of a long-standing deal with glass-supplier Corning Inc., the risk of additional Trump tariffs were seen as diminishing and the stock took off, soaring 8.7% in August, putting it on pace for its best month since June 2024. The stock fell 0.7% on Tuesday. \\u201cThe picture is a lot clearer from a tariff standpoint,\\u201d said George Cipolloni, a veteran portfolio manager. Apple \\u201cwas in Trump\\u2019s crosshairs, but Cook kissed the ring and now it no longer seems to be, which removes a headwind.\\u201d It\\u2019s been a strange stretch for Apple. The stock has been a reliable winner for years, soaring more than 240% from 2020 through 2024, putting it among the 20 best performers in the tech-heavy Nasdaq 100 Index. But this year has been different. Even with its August run, the shares are still down 10% in 2025, putting them among the worst performers in the benchmark. In addition to tariffs, the company is facing skepticism about its artificial intelligence plans and sluggish sales growth. The stock also remains relatively expensive. Even with this year\\u2019s selloff, it\\u2019s trading at 29 times projected earnings, a premium to its average over the past decade of 21 times and to the Nasdaq 100\\u2019s multiple of 27. However, sentiment is clearly improving. Late last month, Apple reported its fastest quarterly revenue growth in more than three years, supported by its iPhone business and strength in the China market. AI Strategy More importantly, the Cupertino, California-based company is working on a revamped AI strategy that will include robots, a lifelike version of its Siri digital assistant, and a smart speaker with a display, Bloomberg News reported two weeks ago. It\\u2019s also said to be in early discussions about using Google Gemini to po\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 = 0.0152 (i.e., a 1.52% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0152 = 6.5947, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015164, "expected_loss": 0.015164, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250304_0281", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-03-04", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1341, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0065, std=0.0510, worst_day=-0.1391\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7458", "answer_numeric": 0.7458, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1341 (i.e., a 13.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1341 = 0.7458, capped at 1.0.\nMaximum position size = 0.7458 (74.6% of portfolio).", "metadata": {"var_99": -0.134089, "expected_loss": 0.134089, "max_drawdown_threshold": 0.1, "position_size": 0.7458, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251126_0283", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2025-11-26", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0175, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0008, std=0.0073, worst_day=-0.0246\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2025-11-19] nvda-20251026 0001045810 1/25 2026 Q3 FALSE 478 469 278 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:investment nvda:segment 0001045810 2025-01-27 2025-10-26 0001045810 2025-11-14 0001045810 2025-07-28 2025-10-26 0001045810 2024-07-29 2024-10-27 0001045810 2024-01-29 2024-10-27 0001045810 2025-10-26 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 2025-07-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-27 0001045810 us-gaap:RetainedEarningsMember 2025-07-27 0001045810 2025-07-27 0001045810 us-gaap:RetainedEarningsMember 2025-07-28 2025-10-26 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-28 2025-10-26 0001045810 us-gaap:CommonStockMember 2025-07-28 2025-10-26 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-28 2025-10-26 0001045810 us-gaap:CommonStockMember 2025-10-26 0001045810 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us-gaap:ForeignGovernmentDebtMember 2025-01-26 0001045810 us-gaap:CertificatesOfDepositMember 2025-01-26 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2025-01-26 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2025-01-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-10-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-01-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-10-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:CustomerOneMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerTwoMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerThreeMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerFourMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:Cust [...TRUNCATED...] President, Operations Adoption 9/9/2025 309,840 12/31/2026 Donald Robertson Vice President and Chief Accounting Officer Adoption 9/18/2025 138,042 * 12/31/2026 Ajay Puri Executive Vice President, Worldwide Field Operations Adoption 9/19/2025 1,000,000 6/24/2026 * Includes 38,042 shares from future vests of equity awards, and the actual number of shares to be sold will be net of shares withheld by the Company for taxes. 42 Item 6. Exhibits Exhibit No.  Exhibit Description 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 43 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 19, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 44\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 = 0.0175 (i.e., a 1.75% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0175 = 5.7169, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017492, "expected_loss": 0.017492, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20250818_0286", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-08-18", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0682, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0123, std=0.0466, worst_day=-0.0752\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0682 (i.e., a 6.82% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0682 = 1.4661, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.068209, "expected_loss": 0.068209, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250320_0289", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA"], "decision_date": "2025-03-20", "context_summary": "VEA: 60-day history, VaR(99%)=-0.0184, max drawdown threshold=10%.", "question": "Asset: VEA\nDaily returns (past 60 days): mean=0.0018, std=0.0085, worst_day=-0.0233\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-03-19] KLA Corporation (KLAC): Among Stocks to Buy That May Be Splitting Soon We recently published a list of the 12 Stocks to Buy That May Be Splitting Soon. In this article, we are going to take a look at where KLA Corporation (NASDAQ:KLAC) stands against other stocks that may be splitting soon. Stock splits change the number of outstanding shares of a company, but not the company\u2019s overall value. A forward split makes each share cheaper and easier to buy. Splits can range from 2-for-1 to 100-for-1 or more. In a 2-for-1 split, one share becomes two by cutting the price in half. For instance, a $100 share becomes two $50 shares. This makes shares more affordable and attracts more investors. Even though the price per share drops, the total value held by shareholders stays the same. So, splits don\u2019t change who controls the company. The main reason for a split is to make the stock more appealing, or accessible for retail investors. Dan Suzuki, Deputy CIO at Bernstein Advisors, joined CNBC\u2019s \u2018Squawk on the Street\u2019 on March 14 to share his perspective on the recent persistent three-week downtrend in the indexes during an interview. He explained that the sell-off is largely driven by uncertainty and its negative impact on sentiment. According to Suzuki, analyzing market movements reveals that the stocks that rallied most after the election until mid-February have seen significant declines since then and create a mirror image effect. Additionally, the most expensive and high-beta stocks have been hit hardest as the market prices are in an uncertainty risk premium. These dynamics are central to what is driving markets currently. Despite this, Suzuki noted that hard economic data remains strong and suggests that relief from headline uncertainties could reduce the risk premium. Suzuki noted concerns over soft retail sales and spending figures, which might be due to weather or seasonal factors. However, he highlighted resilience in weekly retail sales and strong leading indicators. Prolonged uncertainty could still impact growth. Suzuki linked consumer trends to disappointing corporate guidance and persistently high inflation, which affected sentiment. He also pointed out the wealth effect caused by a stock market decline of 10% or more, particularly for investors in crowded names. Markets are adjusting to persistent uncertainty, which will continue even with relief anticipated within the next month or two, which will prevent a return to the high multiples seen in 2020-2023. In an uncertain market with heightened risk premiums, companies considering stock splits may need to weigh the potential benefits against the backdrop of overall market sentiment. The ongoing economic uncertainty and changes in consumer behavior might impact how companies approach decisions about stock splits, especially if they are concerned about maintaining investor confidence in a volatile market. With that being said, we\u2019re here with a list of the 12 stocks to buy that may be splitting s\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 = 0.0184 (i.e., a 1.84% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0184 = 5.4301, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018416, "expected_loss": 0.018416, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250616_0291", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2025-06-16", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0481, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0004, std=0.0176, worst_day=-0.0481\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-13] [\"Warren Buffett Is Wagering 72% of Berkshire Hathaway's $283 Billion of Invested Capital on These 7 Unstoppable Stocks Riding Warren Buffett's coattails and mirroring his trading activity has been a profitable venture for decades. Buffett and his late right-hand man Charlie Munger have long believed in putting most of Berkshire's capital to work in their top ideas. Seven magnificent stocks account for more than $203 billion of Berkshire Hathaway's $283 billion investment portfolio. 10 stocks we like better than Apple \\u203a There's probably not a money manager on Wall Street who garners as much attention as Berkshire Hathaway (NYSE: BRK.A)(NYSE: BRK.B) CEO Warren Buffett. The appropriately named \\\"Oracle of Omaha\\\" has overseen a nearly 6,000,000% aggregate return in his company's Class A shares (BRK.A) through the closing bell on June 9. For the sake of comparison, the broad-based S&P 500's total return, including dividends, is a shade over 40,000% over the same 60-year timeline. Despite Buffett being 94 years old and planning to step down as CEO by the end of the year, investors still eagerly follow his investing activity. Riding Buffett's coattails and mirroring his trading activity has been a profitable venture for decades. But one of the most defining aspects of Warren Buffett's investment philosophy has been his penchant for portfolio concentration. Both Buffett and late right-hand man Charlie Munger believed in putting an outsized percentage of their company's invested assets to work in their best ideas. With less than seven months to go before Buffett officially cedes his long-held executive role to Greg Abel, he's wagering 72% ($203.3 billion) of Berkshire Hathaway's $283 billion of invested assets on just seven unstoppable stocks. Despite Buffett paring down 67% of Berkshire's stake in Apple (NASDAQ: AAPL) since Sept. 30, 2023, it still represents the Oracle of Omaha's largest holding by a substantial amount. While Apple's calling card has often been its innovation, as well as its ongoing transformation into a higher-margin subscription-driven operating model, Buffett's investment in Apple primarily revolves around his keen understanding of consumer behaviors. Apple has an exceptionally loyal customer base, and most importantly consumers trust the brand. Additionally, Apple has the world's leading share-repurchase program. Since kicking off its buyback initiative in 2013, Apple has spent more than $750 billion to reduce its outstanding share count by 43.3%. Lowering its share count has undoubtedly had a positive impact on the company's earnings per share. Credit-services titan American Express (NYSE: AXP) is one of eight holdings Berkshire's chief has no intention of ever selling, based on his 2023 annual letter to shareholders. Shares of AmEx, as American Express is more-commonly known, have been held continuously by Berkshire Hathaway since 1991. What's made AmEx so special is its ability to benefit from both sides of a transaction. \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 = 0.0481 (i.e., a 4.81% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0481 = 2.0787, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.048107, "expected_loss": 0.048107, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250610_0293", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2025-06-10", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0339, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0007, std=0.0133, worst_day=-0.0339\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-09] [\"Apple's WWDC: Analyst Sees AI Unveil, Siri Revamp And Alibaba Deal As Catalyst For iPhone Upgrade Wedbush analyst Daniel Ives maintained an Outperform rating on Apple Inc (NASDAQ:AAPL) with a price forecast of $270. On Monday, Apple will host WWDC in Cupertino at Apple Park, where it will present its key annual conference for developers. Ives stated in the analyst note that Apple\\u2019s AI strategy has faced many challenges since the launch of Apple Intelligence, as this ultimately unlocks the developer ecosystem, which remains the heart and lungs of the Apple story. Also Read: Tariffs, AI And Trade War: Apple\\u2019s Smartphone Growth To Take A Hit, Experts Say While many on the Street are heading into WWDC as underwhelming, given the slower-than-expected rollout of Apple Intelligence, the analyst strongly noted that this will be the start of the AI monetization period of the Apple ecosystem as the company will continue to lay the foundation through its new operating system updates across Mac, iOS, iPad, and others with its \\u201c26\\u201d update. Ives will seek the blueprint for the next frontier of the AI and developer strategy from Chief Tim Cook and Apple. The analyst continues to view this first launch of Apple Intelligence as just the beginning of a broader AI strategy for Apple, as he estimated roughly 25% of the world\\u2019s population will eventually access AI through an Apple device over the next few years. Ives said the company will provide a wide array of new features through Apple Intelligence, including a revamped operating system, while answering key questions about the overall AI strategy that has recently come under fire from the Street. The company will likely provide some crucial updates on Siri\\u2019s integration with Gemini and ChatGPT and the progress of integrating this technology deeper into its app ecosystem, which will be key to unlocking the iPhone upgrade cycle for iPhone 17, as per the analyst. Ives expects Alibaba Group Holding (NYSE:BABA) to be announced as its AI partner in China before the Fall timeframe, ideally ahead of iPhone 17. The analyst said Apple Intelligence is a catalyst for upgrades in the U.S., and now, heading into 2026, the Golden Goose China region will be getting this technology launched. This Alibaba partnership is key to the long-awaited growth catalyst in this region. Ives estimates that over 100 million of the roughly 200 million iPhones in China are in the window of an upgrade opportunity. Ives projected fiscal 2025 revenue of $404.09 billion and EPS of $6.90. AAPL Price Action: Apple stock is up 0.45% to $204.83 at last check Monday. Read Next: Apple App Store Sales Jump In May, Boosting Outlook For Services Growth Image via Shutterstock View More Analyst Ratings for AAPL View the Latest Analyst Ratings UNLOCKED: 5 NEW TRADES EVERY WEEK. Click now to get top trade ideas daily, plus unlimited access to cutting-edge tools and strategies to gain an edge in the markets. Get the latest stock ana\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 = 0.0339 (i.e., a 3.39% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0339 = 2.9513, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033883, "expected_loss": 0.033883, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250704_0296", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-07-04", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0606, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0012, std=0.0308, worst_day=-0.0675\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0606 (i.e., a 6.06% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0606 = 1.6508, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.060575, "expected_loss": 0.060575, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251225_0299", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-12-25", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0148, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0019, std=0.0087, worst_day=-0.0151\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-10-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-10-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-10-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-10-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-10-31 0000104169 2025-12-02 0000104169 2025-08-01 2025-10-31 0000104169 2024-08-01 2024-10-31 0000104169 2024-02-01 2024-10-31 0000104169 2025-10-31 0000104169 2025-01-31 0000104169 2024-10-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-04-30 0000104169 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2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-08-01 2025-10-31 0000104169 us-gaap:ParentMember 2025-08-01 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-08-01 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-08-01 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0148 (i.e., a 1.48% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0148 = 6.7764, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014757, "expected_loss": 0.014757, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250701_0302", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2025-07-01", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0481, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=-0.0004, std=0.0180, worst_day=-0.0481\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-30] [\"Simon Boosts Portfolio With Brickell City Centre's Retail Arm Buyout Simon Property Group SPG recently announced that it has purchased Swire Properties\\u2019 stake in Brickell City Centre\\u2019s open-air shopping center and will now wholly own and manage the asset. Earlier, SPG held a 25% non-managing interest in the retail at the property. The move will boost Simon\\u2019s portfolio, aiding leasing and future revenue growth and creating shareholder value. A mixed-use destination, Brickell City Centre spans five million square feet and is well-recognized for its architectural sophistication. It features a 500,000-square-foot open-air shopping center completed in 2016. Located in the heart of the Brickell district of downtown Miami, the shopping center is anchored by a Saks Fifth Avenue with a Casa Tua Cucina location. The property comprises four levels of dining and entertainment interconnected across three city blocks. With more than 90 retail stores, including the likes of Apple, Zara, and Coach and more than 15 premium dining and entertainment locations, the center will act as a major footfall driver for SPG. Simon Property owns a diversified portfolio of premium retail assets in some of the key markets across the United States and globally. For the past several years, the company has been investing billions to transform its properties and is focused on creating value and driving footfall at the properties. The company has been restructuring its portfolio, aiming at premium acquisitions and transformative redevelopments. In January 2025, Simon Property announced that it had taken over 100% of The Mall Luxury Outlets entities from Kering. In February 2025, Simon Property announced that it would launch a multimillion-dollar redevelopment at Smith Haven Mall, which it plans to begin this summer and complete in 2026. However, growing e-commerce adoption and high debt burden raise concerns for Simon. Moreover, macroeconomic uncertainty can result in strain on retailers' balance sheets, leading to bankruptcies. In the past three months, shares of this Zacks Rank #3 (Hold) company have lost 3.4% compared to the industry\\u2019s decline of 3.1%. Analysts seem bearish on the stock, with its 2025 funds from operations (FFO) per share revised marginally southward to $12.45 over the past month. Image Source: Zacks Investment Research Some better-ranked stocks from the broader REIT sector are VICI Properties VICI and W.P. Carey WPC, each carrying a Zacks Rank #2 (Buy) at present. You can see the complete list of today\\u2019s Zacks #1 Rank (Strong Buy) stocks here. The Zacks Consensus Estimate for VICI\\u2019s 2025 FFO per share is pegged at $2.35, implying year-over-year growth of 4%. The Zacks Consensus Estimate for WPC\\u2019s 2025 FFO per share is pegged at $4.88, indicating an increase of 3.8% from the year-ago reported figure. Note: Anything related to earnings presented in this write-up represents funds from operations (FFO), a widely used metric to ga\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 = 0.0481 (i.e., a 4.81% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0481 = 2.0787, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.048107, "expected_loss": 0.048107, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250214_0305", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-02-14", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1035, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0019, std=0.0478, worst_day=-0.1056\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9658", "answer_numeric": 0.9658, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1035 (i.e., a 10.35% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1035 = 0.9658, capped at 1.0.\nMaximum position size = 0.9658 (96.6% of portfolio).", "metadata": {"var_99": -0.103538, "expected_loss": 0.103538, "max_drawdown_threshold": 0.1, "position_size": 0.9658, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250910_0308", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-09-10", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0122, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0004, std=0.0074, worst_day=-0.0134\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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 = 0.0122 (i.e., a 1.22% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0122 = 8.1943, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012204, "expected_loss": 0.012204, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20251003_0311", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLI"], "decision_date": "2025-10-03", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0129, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0005, std=0.0070, worst_day=-0.0150\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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 = 0.0129 (i.e., a 1.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0129 = 7.7352, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012928, "expected_loss": 0.012928, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250908_0314", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2025-09-08", "context_summary": "SCHP: 60-day history, VaR(99%)=-0.0041, max drawdown threshold=10%.", "question": "Asset: SCHP\nDaily returns (past 60 days): mean=0.0006, std=0.0024, worst_day=-0.0045\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\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 = 0.0041 (i.e., a 0.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0041 = 24.6835, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.004051, "expected_loss": 0.004051, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251201_0316", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2025-12-01", "context_summary": "ICSH: 60-day history, VaR(99%)=-0.0003, max drawdown threshold=10%.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0002, 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 = 0.0003 (i.e., a 0.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0003 = 359.5645, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000278, "expected_loss": 0.000278, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250606_0319", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["UNG"], "decision_date": "2025-06-06", "context_summary": "UNG: 60-day history, VaR(99%)=-0.0665, max drawdown threshold=10%.", "question": "Asset: UNG\nDaily returns (past 60 days): mean=-0.0036, std=0.0361, worst_day=-0.0709\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 = 0.0665 (i.e., a 6.65% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0665 = 1.5036, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.066509, "expected_loss": 0.066509, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250717_0321", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-07-17", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0176, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0018, std=0.0102, worst_day=-0.0208\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-16] [\"Tariffs Are Showing Up in Inflation. Why Trump Can\\u2019t Afford to Ditch Powell. House deals a blow to \\u201cCrypto Week,\\u201d ASML warns on 2026 growth, a promising Chinese weight-loss drug, and more news to start your day.\", \"Top Midday Gainers Longevity Health (XAGE) shares almost doubled amid heavy trading after the company said late Monday\", \"Why Is Jamf (JAMF) Stock Soaring Today Shares of apple device management company, Jamf (NASDAQ:JAMF) jumped 7.2% in the morning session after the company announced it expects to exceed the high end of its second-quarter 2025 guidance and revealed a new strategic reinvestment plan. The Apple device management company now anticipates both revenue and non-GAAP operating income to surpass its previous forecasts. The original guidance for the second quarter, which ended June 30, projected total revenue between $167.5 million and $169.5 million, with non-GAAP operating income of $29.5 million to $30.5 million. In a move to bolster long-term growth, Jamf also announced a strategic plan that includes reducing its workforce by about 6.4% and reallocating resources. The company will increase its focus on enterprise customers and accelerate investments in artificial intelligence. While the restructuring will result in one-time charges of $11.0 million to $12.5 million, investors appear to be focused on the positive outlook and the company's efforts to improve operational efficiency and drive future profitability. After the initial pop the shares cooled down to $8.30, up 1% from previous close. Is now the time to buy Jamf? Access our full analysis report here, it\\u2019s free. Jamf\\u2019s shares are somewhat volatile and have had 12 moves greater than 5% over the last year. In that context, today\\u2019s move indicates the market considers this news meaningful but not something that would fundamentally change its perception of the business. The previous big move we wrote about was 4 days ago when the stock dropped 3.9% after a broader market sell-off triggered by renewed trade tensions. U.S. stock indices fell after the Trump administration announced intentions to impose a 35% tariff on many goods imported from Canada. This move is far more than a typical trade dispute; it targets the United States' largest and most deeply integrated trading partner. Canada is not merely a neighbor but a critical component of North American supply chains, particularly in sectors like automotive, energy, and critical minerals. This move sparked concerns about potential retaliatory actions and a wider impact on the North American economy, leading to a risk-off sentiment among investors. The S&P 500, Dow Jones Industrial Average, and Nasdaq all opened lower, pulling back from recent record highs and heading for their first weekly loss in three weeks. Jamf is down 41.1% since the beginning of the year, and at $8.30 per share, it is trading 56.1% below its 52-week high of $18.91 from July 2024. Investors who bought $1,000 worth of Jam\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 = 5.6921, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017568, "expected_loss": 0.017568, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250626_0324", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-06-26", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0339, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0023, std=0.0179, worst_day=-0.0393\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0339 (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": 20}} +{"id": "T3_all_20250627_0327", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-06-27", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0606, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0007, std=0.0305, worst_day=-0.0675\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0606 (i.e., a 6.06% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0606 = 1.6508, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.060575, "expected_loss": 0.060575, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250313_0330", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-03-13", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.1503, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0095, std=0.0573, worst_day=-0.1606\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.6655", "answer_numeric": 0.6655, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1503 (i.e., a 15.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1503 = 0.6655, capped at 1.0.\nMaximum position size = 0.6655 (66.5% of portfolio).", "metadata": {"var_99": -0.150254, "expected_loss": 0.150254, "max_drawdown_threshold": 0.1, "position_size": 0.6655, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250916_0333", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-09-16", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0825, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0020, std=0.0352, worst_day=-0.1033\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0825 (i.e., a 8.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0825 = 1.2117, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.082529, "expected_loss": 0.082529, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250625_0336", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-06-25", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0356, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0008, std=0.0135, worst_day=-0.0356\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-24] [\"Trump\\u2019s Chip Tariff Threat Sparks Pushback From Auto Industry to Tech (Bloomberg) -- Blowback to President Donald Trump\\u2019s idea of tariffs on imported semiconductors is proving to be broad and deep, stretching from auto companies and boat makers to the technology industry and crypto enthusiasts, according to a review of more than 150 public comments on the proposal. Most Read from Bloomberg Bezos Wedding Draws Protests, Soul-Searching Over Tourism in Venice US State Budget Wounds Intensify From Trump, DOGE Policy Shifts US Renters Face Storm of Rising Costs Commuters Are Caught in Johannesburg's Taxi Feuds as Transit Lags The possible levy of up to 25% has united rivals like Tesla Inc., General Motors Co. and Ford Motor Co. in voicing reservations. It\\u2019s brought together industry lobbies from the Crypto Council for Innovation to the National Marine Manufacturers Association. Even Taiwan and the People\\u2019s Republic of China are finding common cause, along with predictable parts of the tech sector including chipmakers and wireless providers. The reason is that chips are now in almost everything: refrigerators and microwaves, tire pressure sensors and navigation systems, electronic bidets and sonar equipment and, of course, smartphones and computers. Tariffs threaten to snarl supply lines and jack up costs for consumers. \\u201cThere\\u2019s a large mismatch between the amount of chips we use in this country in various products and the supply created here in the US,\\u201d JoAnne Feeney, a partner and portfolio manager at Advisors Capital Management, said in an interview. \\u201cPutting a tax on those imports will simply raise the cost, and that\\u2019s not a good thing for consumers.\\u201d Case in point is the marine association, which warns the impact would be felt by more than 1,300 manufacturers who face higher expenses for essentials like propulsion technology, engines and GPS systems. \\u201cThese systems are not optional luxuries \\u2014 they are fundamental to safety, function and performance,\\u201d the association said. \\u201cMany components have no US equivalent or are only available from highly concentrated suppliers overseas.\\u201d The boating sector\\u2019s concerns were among comments from 154 stakeholders submitted to a Commerce Department review of whether to slap tariffs on chips as part of Trump\\u2019s campaign to redraw global supply lines and boost domestic manufacturing. Predictable tech sources weighed in, including chipmakers Taiwan Semiconductor Manufacturing Co. and Intel Corp. But feedback also landed from a wide spectrum of sectors, along with trading partners like Japan and Brazil. The companies, trade groups and individuals who commented on the chips investigation largely signaled support for the president\\u2019s vision of deepening the US manufacturing base and expanding the American workforce. Yet most expressed concern over the potential consequences and urged making any levies that emerge as targeted as 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 = 0.0356 (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_20250821_0339", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-08-21", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0195, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0010, std=0.0082, worst_day=-0.0206\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-08-20] [\"SoftBank and Trump may not be enough to save Intel Intel (INTC) rose roughly 7% on Tuesday, a day after SoftBank Group announced it would take a $2 billion stake in the struggling chipmaker. News of SoftBank's investment follows a Bloomberg report last week that said the Trump administration is considering taking up to a 10% position in the company. Treasury Secretary Scott Bessent confirmed in a CNBC interview Tuesday that the investment would involve the US government converting Intel's grants from the Biden-era CHIPS and Science Act \\u2014 worth $10.9 billion \\u2014 into an equity stake aimed at stabilizing the company's US manufacturing business. Bessent did not confirm the size of the stake the government would take. Intel has fallen behind in an industry it once dominated. Its manufacturing division is bleeding cash, just as its legacy computer chip segment forfeits market share to rivals Advanced Micro Devices (AMD) and Qualcomm (QCOM) in the PC space. Intel is also woefully behind AMD and Nvidia (NVDA) in the AI race. The company's market capitalization of $111 billion is less than half of its value in 2021. And CEO Lip-Bu Tan has been forced to lay off 15% of the company's workforce and shelve plans to build plants in Europe. But the troubled chipmaker is the only large-scale US-based leading-edge chip manufacturer, giving it geopolitical significance as the nation looks to reshore semiconductor production. Intel's problems, however, may be too big for either SoftBank or the Trump administration to solve on their own. Deutsche Bank analyst Ross Seymore said news of the US potentially taking a stake in Intel, combined with the SoftBank investment, shows that \\\"[Tan] is taking bold actions to solidify Intel's financial and strategic positioning during its ongoing difficult transformation process.\\\" Tan became CEO in March after Intel's board ousted former CEO Pat Gelsinger late last year. But others on Wall Street expressed skepticism that those investments would be enough to save Intel from its decline, which resulted from years of missteps. Loop Capital analyst Gary Mobley wrote in a recent note to clients that the support from SoftBank and, potentially, the US government may be \\\"akin to a lifeline with no secure anchor at the other end,\\\" because while Intel may be \\\"finding new buyers of its primary equity capital,\\\" that may not guarantee it can find customers for its manufacturing business. Gelsinger established Intel's third-party chip manufacturing business, otherwise known as its Foundry, in 2021 as a means of competing with rival TSMC, which produces chips for companies including Nvidia, Apple (AAPL), AMD, and others. But so far, its Foundry business has been a disappointment, struggling to secure customers. While Intel has said it reached agreements to build chips for Amazon (AMZN) and Microsoft (MSFT), the company is still its own largest manufacturing client. Intel's plan includes building chips based on newer technologies,\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 = 0.0195 (i.e., a 1.95% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0195 = 5.1341, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019478, "expected_loss": 0.019478, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250707_0341", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-07-07", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0739, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0005, std=0.0420, worst_day=-0.0759\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0739 (i.e., a 7.39% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0739 = 1.3525, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.073939, "expected_loss": 0.073939, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251016_0346", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2025-10-16", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0244, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0016, std=0.0110, worst_day=-0.0325\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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 = 0.0244 (i.e., a 2.44% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0244 = 4.0942, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024425, "expected_loss": 0.024425, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20251211_0349", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USO"], "decision_date": "2025-12-11", "context_summary": "USO: 60-day history, VaR(99%)=-0.0414, max drawdown threshold=10%.", "question": "Asset: USO\nDaily returns (past 60 days): mean=-0.0004, std=0.0160, worst_day=-0.0430\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 = 0.0414 (i.e., a 4.14% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0414 = 2.4147, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.041414, "expected_loss": 0.041414, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250724_0352", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-07-24", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0570, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0065, std=0.0321, worst_day=-0.0737\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0570 (i.e., a 5.70% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0570 = 1.7548, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.056988, "expected_loss": 0.056988, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250404_0355", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VTI"], "decision_date": "2025-04-04", "context_summary": "VTI: 60-day history, VaR(99%)=-0.0300, max drawdown threshold=10%.", "question": "Asset: VTI\nDaily returns (past 60 days): mean=-0.0015, std=0.0112, worst_day=-0.0335\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-03] SMCI Stock Set to Transition from Micro to Mighty as Wall St. Analysts Eye 40% Upside Super Micro Computer (SMCI) might have the word \u201cmicro\u201d in its name, but make no mistake\u2014this Silicon Valley-based server and storage powerhouse has been delivering mighty growth over the past three years. With the boom in AI training, cloud data centers, and enterprise IT, Super Micro has surged 829%, alongside some of the hottest trends in technology. Discover the latest stocks recommended by top Wall Street analysts, all in one place with Analyst Top Stocks. Make smarter investments with weekly expert stock picks from the Smart Investor Newsletter. While the company\u2019s most explosive alpha years\u20142023 and 2024\u2014are now behind us, I believe the runway is far from finished. Based on projected earnings per share growth and only a slight expansion in the price-to-earnings ratio, I\u2019m targeting a 40% return from the stock over the next twelve months. Let\u2019s start with the obvious: Super Micro\u2019s growth has been anything but modest. The surge in artificial intelligence workloads and expansion in cloud infrastructure has created ideal conditions for the company to thrive. Management has been bold, too. They\u2019ve described the AI revolution as \u201cmuch more impactful than the Industrial Revolution,\u201d and they\u2019re positioning Super Micro accordingly. If that thesis holds true\u2014and I believe it does\u2014then the company is in a superb position to capitalize over the coming years. One specific area where Super Micro stands out is liquid-cooled server design. According to the company\u2019s CEO, roughly 30% of new data centers are expected to adopt direct liquid cooling over the next twelve months. That\u2019s significant\u2014and Super Micro is already a frontrunner in this space. According to Main Street Data, SMCI\u2019s revenues have grown as segment proportions have remained broadly consistent. Let\u2019s talk numbers. In FY2024, SMCI posted 110% year-over-year revenue growth. GAAP net income also surged, climbing 80% from the previous year. Looking further back, from FY2021 through FY2024, Super Micro pulled off a stunning 60% compound annual growth rate in revenue\u2014while only growing its operating expenses by 25%. The company is scaling with discipline and efficiency, an increasingly rare feat in today\u2019s hyper-growth tech landscape. We\u2019re already well into FY2025, with Q3 results expected in May. For the full year, management is guiding toward approximately $24 billion in revenue, representing about 60% year-over-year growth. They\u2019re also quite bullish about FY2026, setting expectations for $40 billion in annual revenue. That forecast may be optimistic, but the broader growth trajectory is undeniably strong\u2014and the valuation doesn\u2019t seem overstretched given the potential upside ahead. Currently, Super Micro stock is trading at ~$35 per share after a sharp pullback, meaning it\u2019s priced at less than its trailing twelve-month revenue\u2014a clear signal of value. But investor sentiment has understandably cooled. Th\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 = 0.0300 (i.e., a 3.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0300 = 3.3316, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030016, "expected_loss": 0.030016, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20251001_0358", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-10-01", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0101, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0003, std=0.0052, worst_day=-0.0114\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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 = 0.0101 (i.e., a 1.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0101 = 9.9213, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.010079, "expected_loss": 0.010079, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20251128_0361", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-11-28", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0986, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0009, std=0.0415, worst_day=-0.1186\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0986 (i.e., a 9.86% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0986 = 1.0142, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.098602, "expected_loss": 0.098602, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250807_0363", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-08-07", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0795, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0009, std=0.0350, worst_day=-0.0949\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0795 (i.e., a 7.95% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0795 = 1.2585, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.07946, "expected_loss": 0.07946, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250311_0366", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2025-03-11", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0248, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=-0.0008, std=0.0096, worst_day=-0.0287\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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0000078003 us-gaap:OtherCurrentLiabilitiesMember 2023-12-31 0 [...TRUNCATED...] my Extension Presentation Linkbase *101.DEF Inline XBRL Taxonomy Extension Definition Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. ITEM 16. FORM 10-K SUMMARY None. SIGNATURES Under the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, this report was signed on behalf of the Registrant by the authorized person named below. Pfizer Inc. Dated: February 27, 2025 By: /S/    MARGARET M. MADDEN Margaret M. Madden Senior Vice President and Corporate Secretary Chief Governance Counsel We, the undersigned directors and officers of Pfizer Inc., hereby severally constitute Douglas M. Lankler and Margaret M. Madden, and each of them singly, our true and lawful attorneys with full power to them and each of them to sign for us, in our names in the capacities indicated below, any and all amendments to this Annual Report on Form 10-K filed with the Securities and Exchange Commission. Under the requirements of the Securities Exchange Act of 1934, this report was signed by the following persons on behalf of the Registrant and in the capacities and on the date indicated . Pfizer Inc. 2024 Form 10-K 113 Signature Title Date /S/    ALBERT BOURLA Albert Bourla Chairman, Chief Executive Officer and Director (Principal Executive Officer) February 27, 2025 /S/    DAVID M. DENTON David M. Denton Chief Financial Officer, Executive Vice President (Principal Financial Officer) February 27, 2025 /S/    JENNIFER B. DAMICO Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer) February 27, 2025 /S/    RONALD E. BLAYLOCK Ronald E. Blaylock Director February 27, 2025 /S/    MORTIMER J. BUCKLEY Mortimer J. Buckley Director February 27, 2025 /S/    SUSAN DESMOND-HELLMANN Susan Desmond-Hellmann Director February 27, 2025 /S/    JOSEPH J. ECHEVARRIA Joseph J. Echevarria Director February 27, 2025 /S/    SCOTT GOTTLIEB Scott Gottlieb Director February 27, 2025 /S/    HELEN H. HOBBS Helen H. Hobbs Director February 27, 2025 /S/    SUSAN HOCKFIELD Susan Hockfield Director February 27, 2025 /S/    DAN R. LITTMAN Dan R. Littman Director February 27, 2025 /S/    SHANTANU NARAYEN Shantanu Narayen Director February 27, 2025 /S/    SUZANNE NORA JOHNSON Suzanne Nora Johnson Director February 27, 2025 /S/    JAMES QUINCEY James Quincey Director February 27, 2025 /S/    JAMES C. SMITH James C. Smith Director February 27, 2025 /S/    CYRUS TARAPOREVALA Cyrus Taraporevala Director February 27, 2025 Pfizer Inc. 2024 Form 10-K 114\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 = 0.0248 (i.e., a 2.48% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0248 = 4.0295, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024817, "expected_loss": 0.024817, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250729_0371", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-07-29", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0570, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0066, std=0.0322, worst_day=-0.0737\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0570 (i.e., a 5.70% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0570 = 1.7548, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.056988, "expected_loss": 0.056988, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250409_0374", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-04-09", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0708, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0002, std=0.0311, worst_day=-0.0767\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0708 (i.e., a 7.08% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0708 = 1.4116, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.070844, "expected_loss": 0.070844, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251007_0377", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-10-07", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0776, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0028, std=0.0374, worst_day=-0.0908\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0776 (i.e., a 7.76% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0776 = 1.2888, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.077589, "expected_loss": 0.077589, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251127_0380", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2025-11-27", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0235, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0003, std=0.0107, worst_day=-0.0294\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:Cust [...TRUNCATED...] President, Operations Adoption 9/9/2025 309,840 12/31/2026 Donald Robertson Vice President and Chief Accounting Officer Adoption 9/18/2025 138,042 * 12/31/2026 Ajay Puri Executive Vice President, Worldwide Field Operations Adoption 9/19/2025 1,000,000 6/24/2026 * Includes 38,042 shares from future vests of equity awards, and the actual number of shares to be sold will be net of shares withheld by the Company for taxes. 42 Item 6. Exhibits Exhibit No.  Exhibit Description 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 43 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 19, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 44\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 = 0.0235 (i.e., a 2.35% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0235 = 4.2472, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.023545, "expected_loss": 0.023545, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20250128_0382", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE"], "decision_date": "2025-01-28", "context_summary": "XLRE: 60-day history, VaR(99%)=-0.0314, max drawdown threshold=10%.", "question": "Asset: XLRE\nDaily returns (past 60 days): mean=-0.0007, std=0.0119, worst_day=-0.0375\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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us-gaap:PreferredStockMember 2023-06-30 0000080424 us-gaap:AdditionalPaidInCapitalMember 2023-06-30 0000080424 pg:R [...TRUNCATED...] 7 billion in fiscal year 2025, notwithstanding any purchases under the Company's compensation and benefit plans. Purchases may be made in the open market and/or private transactions and purchases may be increased, decreased or discontinued at any time without prior notice. The share repurchases are authorized pursuant to a resolution issued by the Company's Board of Directors and are expected to be financed by a combination of operating cash flows and issuance of debt.      Item 5. Other Information During the three months ended December 31, 2024, none of our directors or officers adopted or terminated a \"Rule 10b5-1 trading arrangement\" or \"non-Rule 10b5-1 trading arrangement\" as defined in Item 408 of Regulation S-K. 30 The Procter & Gamble Company Item 6. Exhibits 3.1 Amended Articles of Incorporation (as amended by shareholders at the annual meeting on October 11, 2011 and consolidated by the Board of Directors on April 8, 2016) (Incorporated by reference to Exhibit (3-1) of the Company's Form 10-K for the year ended June 30, 2016) 3.2 Regulations (as approved by the Board of Directors on December 13, 2022, pursuant to authority granted by shareholders at the annual meeting on October 13, 2009) (Incorporated by reference to Exhibit (3-2) of the Company’s Current Report on Form 8-K filed December 13, 2022) 4.1 Indenture, dated as of September 3, 2009, between the Company and Deutsche Bank Trust Company Americas, as Trustee (Incorporated by reference to Exhibit (4-1) of the Company's Annual Report on Form 10-K for the year ended June 30, 2015) 31.1 Rule 13a-14(a)/15d-14(a) Certification – Chief Executive Officer + 31.2 Rule 13a-14(a)/15d-14(a) Certification – Chief Financial Officer + 32.1 Section 1350 Certifications – Chief Executive Officer + 32.2 Section 1350 Certifications – Chief Financial Officer + 101.SCH (1) Inline XBRL Taxonomy Extension Schema Document 101.CAL (1) Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF (1) Inline XBRL Taxonomy Definition Linkbase Document 101.LAB (1) Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE (1) Inline XBRL Taxonomy Extension Presentation Linkbase Document 104  Cover Page Interactive Data File (formatted in Inline XBRL and contained in Exhibit 101) + Filed herewith (1) Pursuant to Rule 406T of Regulation S-T, this information is furnished and not filed for purposes of Sections 11 or 12 of the Securities Act of 1933 and Section 18 of the Securities Exchange Act of 1934, and otherwise is not subject to liability under these sections. Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this Report to be signed on its behalf by the undersigned thereunto duly authorized. THE PROCTER & GAMBLE COMPANY January 22, 2025 /s/ MATTHEW W. JANZARUK Date (Matthew W. Janzaruk) Senior Vice President - Chief Accounting Officer (Principal Accounting Officer)\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 = 0.0314 (i.e., a 3.14% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0314 = 3.1890, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.031358, "expected_loss": 0.031358, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9044}} +{"id": "T3_all_20251107_0385", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-11-07", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0202, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=-0.0011, std=0.0087, worst_day=-0.0207\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-09-30 0000093410 [...TRUNCATED...] 160; $154.38 16,620,000   (1) Includes common shares repurchased from participants in the company’s executive compensation plans for personal income tax withholdings. (2) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections During the three months ended September 30, 2025, none of our directors or executive officers adopted, modified or terminated a Rule 10b5-1 trading arrangement or a non-Rule 10b5-1 trading arrangement, as such terms are defined in Item 408 of Regulation S-K. 47 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 4.1 Fourth Supplemental Indenture, dated as of August 13, 2025, among Chevron U.S.A. Inc., Chevron Corporation, as guarantor, and Deutsche Bank Trust Company Americas, as trustee, filed as Exhibit 4. 2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 4.2 Forms of 3.950% Notes Due 2027, 4.050% Notes Due 2028, Floating Rate Notes Due 2028-B, 4.300% Notes Due 2030, Floating Rate Notes due 2030, 4.500% Notes Due 2032 and 4.850% Notes Due 2035, contained in Exhibit 4.2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 10.1+* Aircraft Time-Sharing Agreement, dated as of February 24, 2015, between Hess Corporation and John B. Hess. 10.2* Transition Services Agreement, dated as of July 14, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.3* Amendment One to Transition Services Agreement, dated as of August 27, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.4* Membership Interest Purchase Agreement, dated as of September 10, 2025, between Hess Corporation and JBH Ventures, LLC . 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ + Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 48 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 6, 2025 49\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 = 0.0202 (i.e., a 2.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0202 = 4.9486, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020208, "expected_loss": 0.020208, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250123_0388", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-01-23", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1240, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0000, std=0.0520, worst_day=-0.1578\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8061", "answer_numeric": 0.8061, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1240 (i.e., a 12.40% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1240 = 0.8061, capped at 1.0.\nMaximum position size = 0.8061 (80.6% of portfolio).", "metadata": {"var_99": -0.124047, "expected_loss": 0.124047, "max_drawdown_threshold": 0.1, "position_size": 0.8061, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250416_0390", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-04-16", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1498, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=-0.0059, std=0.0603, worst_day=-0.1701\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.6678", "answer_numeric": 0.6678, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1498 (i.e., a 14.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1498 = 0.6678, capped at 1.0.\nMaximum position size = 0.6678 (66.8% of portfolio).", "metadata": {"var_99": -0.149754, "expected_loss": 0.149754, "max_drawdown_threshold": 0.1, "position_size": 0.6678, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250102_0393", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-01-02", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0605, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0041, std=0.0324, worst_day=-0.0718\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0605 (i.e., a 6.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0605 = 1.6520, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.060534, "expected_loss": 0.060534, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250305_0396", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-03-05", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.1341, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0084, std=0.0498, worst_day=-0.1391\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7458", "answer_numeric": 0.7458, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1341 (i.e., a 13.41% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1341 = 0.7458, capped at 1.0.\nMaximum position size = 0.7458 (74.6% of portfolio).", "metadata": {"var_99": -0.134089, "expected_loss": 0.134089, "max_drawdown_threshold": 0.1, "position_size": 0.7458, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250220_0399", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2025-02-20", "context_summary": "QQQ: 59-day history, VaR(99%)=-0.0326, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 59 days): mean=0.0012, std=0.0112, worst_day=-0.0367\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000034088 xom:GovernmentAssistanceAffordableFuelPricingMember 2022-01-01 2022-12-31 0000034088 srt:ParentCompanyMember 2021-12-31 0000034088 srt:ParentCompanyMember 202 [...TRUNCATED...] ted as Inline XBRL and contained in Exhibit 101). * Management contract or compensatory plan or arrangement required to be identified pursuant to Item 15(a)(3) of this Annual Report on Form 10-K. The registrant has not filed with this report copies of the instruments defining the rights of holders of long-term debt of the registrant and its subsidiaries for which consolidated or unconsolidated financial statements are required to be filed. The registrant agrees to furnish a copy of any such instrument to the Securities and Exchange Commission upon request. 135 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.         EXXON MOBIL CORPORATION         By: /s/ DARREN W. WOODS Dated February 19, 2025   Darren W. Woods, Chairman of the Board POWER OF ATTORNEY Each person whose signature appears below constitutes and appoints Matthew R. Rasmussen, Brian J. Conjelko, and Antony E. Peters and each of them, his or her true and lawful attorneys-in-fact and agents, with full power of substitution and resubstitution, for him or her and in his or her name, place and stead, in any and all capacities, to sign any and all amendments to this Annual Report on Form 10-K, and to file the same, with all exhibits thereto, and other documents in connection therewith, with the Securities and Exchange Commission, granting unto said attorneys-in-fact and agents, and each of them, full power and authority to do and perform each and every act and thing requisite and necessary to be done, as fully to all intents and purposes as he or she might or could do in person, hereby ratifying and confirming all that said attorneys-in-fact and agents or any of them, or their or his or her substitute or substitutes, may lawfully do or cause to be done by virtue hereof.       Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities indicated and on February 19, 2025. Principal Executive Officer Directors /s/ DARREN W. WOODS /s/ MICHAEL J. ANGELAKIS /s/ STEVEN A. KANDARIAN Darren W. Woods, Chairman of the Board Michael J. Angelakis Steven A. Kandarian /s/ ANGELA F. BRALY /s/ ALEXANDER A. KARSNER Principal Financial Officer Angela F. Braly Alexander A. Karsner   /s/ KATHRYN A. MIKELLS /s/ MARIA S. DREYFUS /s/ LAWRENCE W. KELLNER Kathryn A. Mikells, Senior Vice President and Chief Financial Officer Maria S. Dreyfus Lawrence W. Kellner   /s/ JOHN D. HARRIS II /s/ DINA POWELL MCCORMICK Principal Accounting Officer John D. Harris II Dina Powell McCormick /s/ LEN M. FOX /s/ KAISA H. HIETALA /s/ JEFFREY W. UBBEN Len M. Fox, Vice President, Controller and Tax Kaisa H. Hietala Jeffrey W. Ubben /s/ JOSEPH L. HOOLEY Joseph L. Hooley 136\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 = 0.0326 (i.e., a 3.26% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0326 = 3.0703, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.03257, "expected_loss": 0.03257, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250213_0402", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-02-13", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0192, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0010, std=0.0073, worst_day=-0.0248\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2024-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsoli [...TRUNCATED...] Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy (incorporated by reference to the Company's Annual Report on Form 10-K for the Year ended December 31, 2023). 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2024, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2024, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 76 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 6, 2025.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 6, 2025.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Andrew Y. Ng Andrew Y. Ng Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 77\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 = 0.0192 (i.e., a 1.92% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0192 = 5.1997, 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": true, "text_chars": 9046}} +{"id": "T3_all_20251023_0405", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2025-10-23", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0165, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=0.0007, std=0.0077, worst_day=-0.0240\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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us-gaap:NetInvestmentHedgingMember us-gaap:NetInvestmentHedgingMember us-gaap:CostOfSalesMember 2025-06-30 2025-09-28 0000200406 us-gaap:NetInve [...TRUNCATED...] 2025 through July 27, 2025 868,779 167.40 — — July 28, 2025 through August 24, 2025 4,103,196 175.64 — — August 25, 2025 through September 28, 2025 5,828,766 177.70 — — Total 10,800,741 176.09 — — (1) During the fiscal third quarter of 2025, the Company repurchased an aggregate of 10,800,741 shares of Johnson & Johnson Common Stock in open-market transactions, all of which were purchased as part of a systematic plan to meet the needs of the Company’s compensation programs. 58   Table of Contents Item 5 — Other information Securities trading plans of Directors and Executive Officers . During the fiscal third quarter of 2025, none of our directors or officers (as defined in Rule 16a-1(f) of the Exchange Act) informed us of the adoption or termination of a “Rule 10b5-1 trading arrangement” or “non-Rule 10b5-1 trading arrangement,” each as defined in Item 408 of Regulation S-K. Item 6 — Exhibits Exhibit 31.1 Certification of Chief Executive Officer under Rule 13a-14(a) of the Securities Exchange Act pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 — Filed with this document. Exhibit 31.2 Certification of Chief Financial Officer under Rule 13a-14(a) of the Securities Exchange Act pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 — Filed with this document. Exhibit 32.1 Certification of Chief Executive Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 — Furnished with this document. Exhibit 32.2 Certification of Chief Financial Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 — Furnished with this document. Exhibit 101: EX-101.INS Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document EX-101.SCH Inline XBRL Taxonomy Extension Schema EX-101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase EX-101.LAB Inline XBRL Taxonomy Extension Label Linkbase EX-101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase EX-101.DEF Inline XBRL Taxonomy Extension Definition Document Exhibit 104: Cover Page Interactive Data File––the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. Form 10-Q 59 Table of Contents Signatures Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: October 22, 2025 Date: October 22, 2025 JOHNSON & JOHNSON (Registrant) By  /s/ J. J. Wolk J. J. Wolk , Executive Vice President, Chief Financial Officer (Principal Financial Officer)  By  /s/  R. J. Decker Jr. R. J. Decker Jr. , Controller (Principal Accounting Officer) 60  \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 = 0.0165 (i.e., a 1.65% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0165 = 6.0781, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.016453, "expected_loss": 0.016453, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20251013_0407", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2025-10-13", "context_summary": "ICSH: 60-day history, VaR(99%)=-0.0002, max drawdown threshold=10%.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0003, std=0.0003, worst_day=-0.0002\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ICSH, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0002 (i.e., a 0.02% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0002 = 506.3960, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000197, "expected_loss": 0.000197, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250604_0410", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-06-04", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0830, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0016, std=0.0375, worst_day=-0.1053\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0830 (i.e., a 8.30% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0830 = 1.2045, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.083024, "expected_loss": 0.083024, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250122_0413", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2025-01-22", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0283, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0005, std=0.0121, worst_day=-0.0371\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to 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 = 0.0283 (i.e., a 2.83% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0283 = 3.5300, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.028329, "expected_loss": 0.028329, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250806_0416", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VNQ"], "decision_date": "2025-08-06", "context_summary": "VNQ: 60-day history, VaR(99%)=-0.0251, max drawdown threshold=10%.", "question": "Asset: VNQ\nDaily returns (past 60 days): mean=0.0005, std=0.0092, worst_day=-0.0266\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\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 = 0.0251 (i.e., a 2.51% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0251 = 3.9823, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.025111, "expected_loss": 0.025111, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250901_0419", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-09-01", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0898, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0103, std=0.0521, worst_day=-0.0939\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0898 (i.e., a 8.98% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0898 = 1.1130, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.089849, "expected_loss": 0.089849, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250929_0422", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOYB"], "decision_date": "2025-09-29", "context_summary": "SOYB: 60-day history, VaR(99%)=-0.0187, max drawdown threshold=10%.", "question": "Asset: SOYB\nDaily returns (past 60 days): mean=-0.0003, std=0.0082, worst_day=-0.0265\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOYB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0187 (i.e., a 1.87% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0187 = 5.3551, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018674, "expected_loss": 0.018674, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250502_0425", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["TIP"], "decision_date": "2025-05-02", "context_summary": "TIP: 60-day history, VaR(99%)=-0.0033, max drawdown threshold=10%.", "question": "Asset: TIP\nDaily returns (past 60 days): mean=0.0004, std=0.0015, worst_day=-0.0037\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\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 = 0.0033 (i.e., a 0.33% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0033 = 29.8975, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.003345, "expected_loss": 0.003345, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250509_0427", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-05-09", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0356, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=-0.0008, std=0.0136, worst_day=-0.0356\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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cvx:TengizchevroilLlpMember 2025-01-01 2025-03-31 0000093410 cvx:TengizchevroilLlpMember 2024-01-01 2024-03-31 0000093410 cvx:ChevronUsaIncMember 2025-01-01 2025-03-31 0000093410 cvx:ChevronUsaIncMember 2024-01-01 2024-03-31 0000093410 cvx:ChevronUsaIncMember 2025-03-31 0000093410 cvx:ChevronUsaIncMember 2024-12-31 0000093410 country:US us-gaap:OperatingSegmentsMember cvx:UpstreamSegmentMember 2025-01-01 2025-03-31 0000093410 us-gaap:NonUsMember us-gaap:OperatingSegmentsMember cvx:UpstreamSegmentMember 2025-01-01 2025-03-31 0000093410 country:US us-gaap:OperatingSegmentsMember cvx:DownstreamSegmentMember 2025-01-01 2025-03-31 0000093410 us-gaap:NonUsMember us-gaap:OperatingSegmentsMember cvx:DownstreamSegmentMember 2025-01-01 2025-03-31 0000093410 us-gaap:OperatingSegmentsMember us-gaap:ReportableSegmentAggregationBeforeOtherOperatingSegmentMember 2025-01-01 2025-03-31 0000093410 us-gaap:OperatingSegmentsMember us-gaap:AllOtherSegmentsMember 2025-01-01 2025-03-31 0000093410 us-gaap:OperatingSegmentsMember 2025-01-01 2025-03-31 0000093410 country:US us-gaap:IntersegmentEliminationMember cvx:UpstreamSegmentMember 2025-01-01 2025-03-31 0000093410 us-gaap:NonUsMember us [...TRUNCATED...] e President and Controller , entered into a pre-arranged stock trading plan on February 21, 2025 . Ms. Knowles’ plan provides for the potential exercise of vested stock options and the associated sale of up to 18,334 shares of Chevron common stock between May 23, 2025 and February 20, 2026 . Mark A. Nelson , Vice Chairman , entered into a pre-arranged stock trading plan on February 18, 2025 . Mr. Nelson’s plan provides for the potential exercise of vested stock options and the associated sale of up to 45,800 shares of Chevron common stock between May 20, 2025 and December 31, 2025 . R. Hewitt Pate , Vice President and General Counsel , entered into a pre-arranged stock trading plan on February 24, 2025 . Mr. Pate’s plan provides for the potential exercise of vested stock options and the associated sale of up to 306,909 shares of Chevron common stock between May 26, 2025 and February 20, 2026 . These trading plans were entered into during an open insider trading window and are intended to satisfy the affirmative defense of Rule 10b5-1(c) under the Securities Exchange Act of 1934, as amended, and Chevron’s policies regarding transactions in Chevron securities. 43 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 4.1 Third Supplemental Indenture, dated as of February 26, 2025, among Chevron U.S.A. Inc., Chevron Corporation, as guarantor, and Deutsche Bank Trust Company Americas, as trustee, filed as Exhibit 4.2 to Chevron Corporation’s Current Report on Form 8-K filed February 26, 2025, and incorporated herein by reference . 4.2 Forms of 4.405% Notes Due 2027, Floating Rate Notes Due 2027, 4.475% Notes Due 2028, Floating Rate Notes Due 2028, 4.687% Notes Due 2030, 4.819% Notes Due 2032, and 4.980% Notes Due 2035 , contained in Exhibit 4.2 to Chevron Corporation ’ s Current R e port on Form 8-K filed February 26, 2025, and incorporated herein by reference . 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ *    Filed herewith. **     Furnished herewith. 44 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: May 8, 2025 45\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": 9045}} +{"id": "T3_all_20251114_0429", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-11-14", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.1283, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0073, std=0.0459, worst_day=-0.1463\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7797", "answer_numeric": 0.7797, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1283 (i.e., a 12.83% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1283 = 0.7797, capped at 1.0.\nMaximum position size = 0.7797 (78.0% of portfolio).", "metadata": {"var_99": -0.128251, "expected_loss": 0.128251, "max_drawdown_threshold": 0.1, "position_size": 0.7797, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251202_0431", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2025-12-02", "context_summary": "ACWI: 60-day history, VaR(99%)=-0.0200, max drawdown threshold=10%.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=0.0008, std=0.0076, worst_day=-0.0265\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q NVDA 2025-11-19] nvda-20251026 0001045810 1/25 2026 Q3 FALSE 478 469 278 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure nvda:investment nvda:segment 0001045810 2025-01-27 2025-10-26 0001045810 2025-11-14 0001045810 2025-07-28 2025-10-26 0001045810 2024-07-29 2024-10-27 0001045810 2024-01-29 2024-10-27 0001045810 2025-10-26 0001045810 2025-01-26 0001045810 us-gaap:CommonStockMember 2025-07-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-27 0001045810 us-gaap:RetainedEarningsMember 2025-07-27 0001045810 2025-07-27 0001045810 us-gaap:RetainedEarningsMember 2025-07-28 2025-10-26 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-28 2025-10-26 0001045810 us-gaap:CommonStockMember 2025-07-28 2025-10-26 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-07-28 2025-10-26 0001045810 us-gaap:CommonStockMember 2025-10-26 0001045810 us-gaap:AdditionalPaidInCapitalMember 2025-10-26 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-26 0001045810 us-gaap:RetainedEarningsMember 2025-10-26 0001045810 us-gaap:CommonStockMember 2024-07-28 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-07-28 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-28 0001045810 us-gaap:RetainedEarningsMember 2024-07-28 0001045810 2024-07-28 0001045810 us-gaap:RetainedEarningsMember 2024-07-29 2024-10-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-29 2024-10-27 0001045810 us-gaap:CommonStockMember 2024-07-29 2024-10-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-07-29 2024-10-27 0001045810 us-gaap:CommonStockMember 2024-10-27 0001045810 us-gaap:AdditionalPaidInCapitalMember 2024-10-27 0001045810 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-10-27 0001045810 us-gaap:RetainedEarningsMember 2024-10-27 0001045810 2024-10-27 0001045810 us-gaap:CommonStockMember 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nvda:RSUsPSUsandMarketbasedPSUsMember 2025-01-27 2025-10-26 0001045810 nvda:RSUsPSUsandMarketbasedPSUsMember 2025-10-26 0001045810 us-gaap:EmployeeStockMember 2025-01-27 2025-10-26 0001045810 us-gaap:USTreasurySecuritiesMember 2025-10-26 0001045810 us-gaap:CorporateDebtSecuritiesMember 2025-10-26 0001045810 us-gaap:MoneyMarketFundsMember 2025-10-26 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-10-26 0001045810 us-gaap:CertificatesOfDepositMember 2025-10-26 0001045810 us-gaap:ForeignGovernmentDebtMember 2025-10-26 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2025-10-26 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2025-10-26 0001045810 2025-01-27 2025-04-27 0001045810 us-gaap:CorporateDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:USTreasurySecuritiesMember 2025-01-26 0001045810 us-gaap:MoneyMarketFundsMember 2025-01-26 0001045810 us-gaap:USGovernmentAgenciesDebtSecuritiesMember 2025-01-26 0001045810 us-gaap:ForeignGovernmentDebtMember 2025-01-26 0001045810 us-gaap:CertificatesOfDepositMember 2025-01-26 0001045810 nvda:MarketableSecuritiesWithFairValueAdjustmentsRecordedInOtherComprehensiveIncomeMember 2025-01-26 0001045810 nvda:PubliclyHeldEquitySecuritiesMember 2025-01-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-10-26 0001045810 nvda:IntangibleAssetsArisingFromBusinessCombinationMember 2025-01-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-10-26 0001045810 nvda:PatentsAndLicensedTechnologyMember 2025-01-26 0001045810 nvda:CustomerOneMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerTwoMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerThreeMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:CustomerFourMember us-gaap:CustomerConcentrationRiskMember us-gaap:AccountsReceivableMember 2025-01-27 2025-10-26 0001045810 nvda:Cust [...TRUNCATED...] President, Operations Adoption 9/9/2025 309,840 12/31/2026 Donald Robertson Vice President and Chief Accounting Officer Adoption 9/18/2025 138,042 * 12/31/2026 Ajay Puri Executive Vice President, Worldwide Field Operations Adoption 9/19/2025 1,000,000 6/24/2026 * Includes 38,042 shares from future vests of equity awards, and the actual number of shares to be sold will be net of shares withheld by the Company for taxes. 42 Item 6. Exhibits Exhibit No.  Exhibit Description 31.1* Certification of Chief Executive Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 31.2* Certification of Chief Financial Officer as required by Rule 13a-14(a) of the Securities Exchange Act of 1934 32.1#* Certification of Chief Executive Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 32.2#* Certification of Chief Financial Officer as required by Rule 13a-14(b) of the Securities Exchange Act of 1934 101.INS* Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH* Inline XBRL Taxonomy Extension Schema Document 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB* Inline XBRL Taxonomy Extension Labels Linkbase Document 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page interactive data file does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. * Filed herewith. # In accordance with Item 601(b)(32)(ii) of Regulation S-K and SEC Release Nos. 33-8238 and 34-47986, Final Rule: Management's Reports on Internal Control Over Financial Reporting and Certification of Disclosure in Exchange Act Periodic Reports, the certifications furnished in Exhibits 32.1 and 32.2 hereto are deemed to accompany this Quarterly Report on Form 10-Q and will not be deemed “filed” for purpose of Section 18 of the Exchange Act. Such certifications will not be deemed to be incorporated by reference into any filing under the Securities Act or the Exchange Act, except to the extent that the registrant specifically incorporates it by reference. Copies of above exhibits not contained herein are available to any shareholder upon written request to: Investor Relations: NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, CA 95051. 43 Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: November 19, 2025   NVIDIA Corporation  By:    /s/ Colette M. Kress   Colette M. Kress   Executive Vice President and Chief Financial Officer (Duly Authorized Officer and Principal Financial Officer) 44\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 = 0.0200 (i.e., a 2.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0200 = 5.0103, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019959, "expected_loss": 0.019959, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20250312_0434", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-03-12", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0733, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0034, std=0.0303, worst_day=-0.0767\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0733 (i.e., a 7.33% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0733 = 1.3641, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.073307, "expected_loss": 0.073307, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250722_0437", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-07-22", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0723, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=-0.0010, std=0.0343, worst_day=-0.0792\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0723 (i.e., a 7.23% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0723 = 1.3838, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.072264, "expected_loss": 0.072264, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251125_0440", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SGOV"], "decision_date": "2025-11-25", "context_summary": "SGOV: 60-day history, VaR(99%)=-0.0000, max drawdown threshold=10%.", "question": "Asset: SGOV\nDaily returns (past 60 days): mean=0.0002, std=0.0001, worst_day=-0.0001\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SGOV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0000 (i.e., a 0.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0000 = 2450.9114, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -4.1e-05, "expected_loss": 4.1e-05, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251119_0443", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-11-19", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0153, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0001, std=0.0067, worst_day=-0.0186\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CVX 2025-11-06] cvx-20250930 0000093410 12/31 2025 Q3 false xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cvx:segment cvx:lawsuit cvx:state cvx:tribe cvx:parish 0000093410 2025-01-01 2025-09-30 0000093410 2025-09-30 0000093410 2025-07-01 2025-09-30 0000093410 2024-07-01 2024-09-30 0000093410 2024-01-01 2024-09-30 0000093410 2024-12-31 0000093410 2023-12-31 0000093410 2024-09-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-06-30 0000093410 us-gaap:RetainedEarningsMember 2024-06-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-06-30 0000093410 us-gaap:TreasuryStockCommonMember 2024-06-30 0000093410 us-gaap:ParentMember 2024-06-30 0000093410 us-gaap:NoncontrollingInterestMember 2024-06-30 0000093410 2024-06-30 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2024-07-01 2024-09-30 0000093410 us-gaap:ParentMember 2024-07-01 2024-09-30 0000093410 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2024-12-31 0000093410 us-gaap:CommonStockIncludingAdditionalPaidInCapitalMember 2025-01-01 2025-09-30 0000093410 us-gaap:ParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:TreasuryStockCommonMember 2025-01-01 2025-09-30 0000093410 us-gaap:NoncontrollingInterestMember 2025-01-01 2025-09-30 0000093410 us-gaap:RetainedEarningsMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-01-01 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2024-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2024-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2024-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2025-01-01 2025-09-30 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2025-09-30 0000093410 [...TRUNCATED...] 160; $154.38 16,620,000   (1) Includes common shares repurchased from participants in the company’s executive compensation plans for personal income tax withholdings. (2) Refer to “Liquidity and Capital Resources” for additional information regarding the company’s authorized stock repurchase program. Item 5. Other Information Rule 10b5-1 Plan Elections During the three months ended September 30, 2025, none of our directors or executive officers adopted, modified or terminated a Rule 10b5-1 trading arrangement or a non-Rule 10b5-1 trading arrangement, as such terms are defined in Item 408 of Regulation S-K. 47 Table of Contents Item 6. Exhibits Exhibit Index Exhibit Number Description 4.1 Fourth Supplemental Indenture, dated as of August 13, 2025, among Chevron U.S.A. Inc., Chevron Corporation, as guarantor, and Deutsche Bank Trust Company Americas, as trustee, filed as Exhibit 4. 2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 4.2 Forms of 3.950% Notes Due 2027, 4.050% Notes Due 2028, Floating Rate Notes Due 2028-B, 4.300% Notes Due 2030, Floating Rate Notes due 2030, 4.500% Notes Due 2032 and 4.850% Notes Due 2035, contained in Exhibit 4.2 to Chevron Corporation’s Current Report on Form 8-K filed August 13, 2025, and incorporated herein by reference . 10.1+* Aircraft Time-Sharing Agreement, dated as of February 24, 2015, between Hess Corporation and John B. Hess. 10.2* Transition Services Agreement, dated as of July 14, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.3* Amendment One to Transition Services Agreement, dated as of August 27, 2025, between Chevron U.S.A. Inc. and HFO Holdings LLC . 10.4* Membership Interest Purchase Agreement, dated as of September 10, 2025, between Hess Corporation and JBH Ventures, LLC . 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer 32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer 32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer 101* Interactive data files (formatted as Inline XBRL) 104* Cover Page Interactive Data File (contained in Exhibit 101) ____________________________________________ + Indicates a management contract or compensatory plan or arrangement. *    Filed herewith. **     Furnished herewith. 48 Table of Contents SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   C HEVRON C ORPORATION (R EGISTRANT ) / S /   A LANA K. K NOWLES Alana K. Knowles, Vice President and Controller (Principal Accounting Officer and Duly Authorized Officer) Date: November 6, 2025 49\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 = 0.0153 (i.e., a 1.53% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0153 = 6.5151, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015349, "expected_loss": 0.015349, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250715_0446", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLE"], "decision_date": "2025-07-15", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0268, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=0.0020, std=0.0131, worst_day=-0.0273\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-14] [\"1 Small-Cap Stock on Our Buy List and 2 to Turn Down Small-cap stocks can be incredibly lucrative investments because their lack of analyst coverage leads to frequent mispricings. However, these businesses (and their stock prices) often stay small because their subscale operations make it harder to expand their competitive moats. These trade-offs can cause headaches for even the most seasoned professionals, which is why we started StockStory - to help you separate the good companies from the bad. That said, here is one small-cap stock that could amplify your portfolio\\u2019s returns and two best left ignored. Market Cap: $3.30 billion Co-founded by former Apple CEO John Sculley, Zeta Global (NYSE:ZETA) provides software and data analytics tools that help companies market their products to billions of customers. Why Does ZETA Give Us Pause? Zeta\\u2019s stock price of $13.92 implies a valuation ratio of 2.3x forward price-to-sales. To fully understand why you should be careful with ZETA, check out our full research report (it\\u2019s free). Market Cap: $2.85 billion Constructing electrical and phone lines in the American Midwest dating back to the 1890s, MYR Group (NASDAQ:MYRG) is a specialty contractor in the electrical construction industry. Why Is MYRG Risky? At $183.66 per share, MYR Group trades at 29.3x forward P/E. Read our free research report to see why you should think twice about including MYRG in your portfolio, it\\u2019s free. Market Cap: $1.53 billion Pioneering the intersection of traditional banking and financial technology in the Pacific Northwest, Coastal Financial (NASDAQ:CCB) operates as a bank holding company that provides traditional banking services and Banking-as-a-Service (BaaS) solutions to consumers and businesses. Why Are We Bullish on CCB? Coastal Financial is trading at $101.56 per share, or 3.1x forward P/B. Is now the time to initiate a position? Find out in our full research report, it\\u2019s free. The market surged in 2024 and reached record highs after Donald Trump\\u2019s presidential victory in November, but questions about new economic policies are adding much uncertainty for 2025. While the crowd speculates what might happen next, we\\u2019re homing in on the companies that can succeed regardless of the political or macroeconomic environment. Put yourself in the driver\\u2019s seat and build a durable portfolio by checking out our Top 6 Stocks for this week. This is a curated list of our High Quality stocks that have generated a market-beating return of 183% over the last five years (as of March 31st 2025). Stocks that made our list in 2020 include now familiar names such as Nvidia (+1,545% between March 2020 and March 2025) as well as under-the-radar businesses like the once-micro-cap company Tecnoglass (+1,754% five-year return). Find your next big winner with StockStory today for free. Find your next big winner with StockStory today. Find your next big winner with StockStory today StockStory is growing and hi\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 = 0.0268 (i.e., a 2.68% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0268 = 3.7274, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026828, "expected_loss": 0.026828, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250718_0448", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-07-18", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0607, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=0.0060, std=0.0325, worst_day=-0.0737\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0607 (i.e., a 6.07% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0607 = 1.6466, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.060731, "expected_loss": 0.060731, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250805_0452", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-08-05", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0143, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0008, std=0.0078, worst_day=-0.0162\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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0000080424 us-gaap:AdditionalPaidInCapitalMember 2024-07-01 2025-06-30 0000080424 us-gaap:PreferredStockMember 2024-07-01 2025-06-30 [...TRUNCATED...]    (99-1)  - Summary of Directors and Officers Insurance Program . + 101.INS (1) Inline XBRL Instance Document 101.SCH (1)    Inline XBRL Taxonomy Extension Schema Document 101.CAL (1)    Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF (1)    Inline XBRL Taxonomy Definition Linkbase Document 101.LAB (1)    Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE (1)    Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File (formatted in Inline XBRL and contained in Exhibit 101) (1) Pursuant to Rule 406T of Regulation S-T, these interactive data files are deemed not filed or part of a registration statement or prospectus for purposes of Sections 11 or 12 of the Securities Act of 1933 or Section 18 of the Securities Exchange Act of 1934 and otherwise are not subject to liability. * Compensatory plan or arrangement. + Filed herewith. Item 16. Form 10-K Summary. Not applicable. The Procter & Gamble Company 71 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized in the city of Cincinnati, State of Ohio. THE PROCTER & GAMBLE COMPANY By /s/ JON R. MOELLER (Jon R. Moeller) Chairman of the Board, President and Chief Executive Officer August 04, 2025 Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons in the capacities and on the dates indicated. Signature Title Date /s/ JON R. MOELLER (Jon R. Moeller) Chairman of the Board, President and Chief Executive Officer (Principal Executive Officer) August 04, 2025 /s/ ANDRE SCHULTEN (Andre Schulten) Chief Financial Officer (Principal Financial Officer) August 04, 2025 /s/ MATTHEW W. JANZARUK (Matthew W. Janzaruk) Senior Vice President - Chief Accounting Officer (Principal Accounting Officer) August 04, 2025 /s/ B. MARC ALLEN (B. Marc Allen) Director August 04, 2025 /s/ CRAIG ARNOLD (Craig Arnold) Director August 04, 2025 /s/ BRETT BIGGS (Brett Biggs) Director August 04, 2025 /s/ SHEILA BONINI (Sheila Bonini) Director August 04, 2025 /s/ AMY L. CHANG (Amy L. Chang) Director August 04, 2025 /s/ JOSEPH JIMENEZ (Joseph Jimenez) Director August 04, 2025 /s/ CHRISTOPHER J. KEMPCZINSKI (Christopher J. Kempczinski) Director August 04, 2025 /s/ DEBRA L. LEE (Debra L. Lee) Director August 04, 2025 /s/ TERRY J. LUNDGREN (Terry J. Lundgren) Director August 04, 2025 /s/ CHRISTINE M. MCCARTHY (Christine M. McCarthy) Director August 04, 2025 /s/ ASHLEY MCEVOY (Ashley McEvoy) Director August 04, 2025 /s/ ROBERT J. PORTMAN (Robert J. Portman) Director August 04, 2025 /s/ RAJESH SUBRAMANIAM (Rajesh Subramaniam) Director August 04, 2025 /s/ PATRICIA A. WOERTZ (Patricia A. Woertz) Director August 04, 2025\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 = 0.0143 (i.e., a 1.43% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0143 = 7.0075, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01427, "expected_loss": 0.01427, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9044}} +{"id": "T3_all_20251224_0455", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-12-24", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0265, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0017, std=0.0103, worst_day=-0.0286\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to 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 = 0.0265 (i.e., a 2.65% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0265 = 3.7800, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.026455, "expected_loss": 0.026455, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250106_0458", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["PPLT"], "decision_date": "2025-01-06", "context_summary": "PPLT: 60-day history, VaR(99%)=-0.0301, max drawdown threshold=10%.", "question": "Asset: PPLT\nDaily returns (past 60 days): mean=-0.0003, std=0.0135, worst_day=-0.0337\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to PPLT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0301 (i.e., a 3.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0301 = 3.3236, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.030088, "expected_loss": 0.030088, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251222_0460", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM"], "decision_date": "2025-12-22", "context_summary": "EEM: 60-day history, VaR(99%)=-0.0249, max drawdown threshold=10%.", "question": "Asset: EEM\nDaily returns (past 60 days): mean=0.0006, std=0.0098, worst_day=-0.0341\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EEM, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0249 (i.e., a 2.49% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0249 = 4.0159, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024901, "expected_loss": 0.024901, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20251217_0463", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-12-17", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0957, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0071, std=0.0419, worst_day=-0.1171\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0957 (i.e., a 9.57% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0957 = 1.0447, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.095719, "expected_loss": 0.095719, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251117_0466", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-11-17", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1287, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0086, std=0.0442, worst_day=-0.1761\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7770", "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": true, "text_chars": 20}} +{"id": "T3_all_20250410_0469", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-04-10", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0708, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0004, std=0.0308, worst_day=-0.0767\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0708 (i.e., a 7.08% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0708 = 1.4116, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.070844, "expected_loss": 0.070844, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251010_0472", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SHV"], "decision_date": "2025-10-10", "context_summary": "SHV: 60-day history, VaR(99%)=-0.0001, max drawdown threshold=10%.", "question": "Asset: SHV\nDaily returns (past 60 days): mean=0.0002, std=0.0002, worst_day=-0.0001\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SHV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0001 (i.e., a 0.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0001 = 1101.4218, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -9.1e-05, "expected_loss": 9.1e-05, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250808_0475", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-08-08", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0649, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0030, std=0.0359, worst_day=-0.0785\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0649 (i.e., a 6.49% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0649 = 1.5415, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.064874, "expected_loss": 0.064874, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251120_0478", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-11-20", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1287, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0090, std=0.0443, worst_day=-0.1761\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7770", "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": true, "text_chars": 20}} +{"id": "T3_all_20250903_0480", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-09-03", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0382, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=0.0006, std=0.0163, worst_day=-0.0404\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0382 (i.e., a 3.82% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0382 = 2.6150, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.03824, "expected_loss": 0.03824, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250919_0483", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-09-19", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0810, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0067, std=0.0456, worst_day=-0.0912\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0810 (i.e., a 8.10% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0810 = 1.2346, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.080999, "expected_loss": 0.080999, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250623_0486", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ"], "decision_date": "2025-06-23", "context_summary": "QQQ: 60-day history, VaR(99%)=-0.0399, max drawdown threshold=10%.", "question": "Asset: QQQ\nDaily returns (past 60 days): mean=0.0004, std=0.0161, worst_day=-0.0399\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-20] [\"Alibaba\\u2019s (BABA) New Qwen3 AI Models Now Compatible With Apple Devices Alibaba Group Holding Limited (NYSE:BABA) is one of the 10 AI Stocks Getting Wall Street\\u2019s Attention. On June 17, South China Morning Post reported that the company updated its Qwen3 family of artificial intelligence (AI) models that could signal the potential roll-out in China of machine-learning technology on a range of Apple devices, including iPhones, iPads, and MacBooks. Alibaba announced the launch of new Qwen3 artificial intelligence models for Apple\\u2019s MLX architecture, announcing in a post on Wechat that the models will be able to run on a range of Apple devices, including iPhone, iPad, MacBook, and Mac. A busy sidewalk filled with people using Apple devices like iPhones, iPads and Apple Watches. The MLX framework is designed to be user-friendly and efficient in training and deploying AI models on Apple\\u2019s silicon hardware. Through this development, Apple is aiming to expand the availability of its Apple Intelligence suite to China. Alibaba Group Holding Limited (NYSE:BABA) is an internet giant that offers e-commerce services in China and internationally. While we acknowledge the potential of BABA as an investment, we believe certain AI stocks offer greater upside potential and carry less downside risk. If you\\u2019re looking for an extremely undervalued AI stock that also stands to benefit significantly from Trump-era tariffs and the onshoring trend, see our free report on the best short-term AI stock. READ NEXT: 10 AI Stocks on Wall Street\\u2019s Radar and 15 AI Stocks Making Waves on Wall Street. Disclosure: None.\", \"Trump Hints He\\u2019ll Hold Off Iran Strike, Give Diplomacy Time (Bloomberg) -- US President Donald Trump signaled he would give diplomacy a chance before deciding whether to strike Iran, dialing back on recent comments that suggested military action could be imminent. Most Read from Bloomberg Security Concerns Hit Some of the World\\u2019s \\u2018Most Livable Cities\\u2019 One Architect\\u2019s Quest to Save Mumbai\\u2019s Heritage From Disappearing JFK AirTrain Cuts Fares 50% This Summer to Lure Riders Off Roads NYC Congestion Toll Cuts Manhattan Gridlock by 25%, RPA Reports Taser-Maker Axon Triggers a NIMBY Backlash in its Hometown \\u201cBased on the fact that there\\u2019s a substantial chance of negotiations that may or may not take place with Iran in the near future, I will make my decision whether or not to go within the next two weeks,\\u201d Trump said in a dictated message, according to White House spokeswoman Karoline Leavitt. Subscribe to the Bloomberg Daybreak Podcast on Apple, Spotify and other Podcast Platforms. Iran maintained Friday it won\\u2019t negotiate with the US while an Israeli assault continues. The only way to end the imposed war is to \\u201cunconditionally stop\\u201d the enemy\\u2019s aggression, Iranian President Masoud Pezeshkian said Friday in a post on X. Oil prices fell following a report from Reuters that Ir\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_20251230_0488", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-12-30", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.0818, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0038, std=0.0338, worst_day=-0.0860\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0818 (i.e., a 8.18% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0818 = 1.2221, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.08183, "expected_loss": 0.08183, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250224_0490", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2025-02-24", "context_summary": "XLE: 59-day history, VaR(99%)=-0.0290, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 59 days): mean=-0.0010, std=0.0124, worst_day=-0.0300\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent 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us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2022-01-01 2022-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2022-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2022-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2022-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2022-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-01-01 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedNetUnrealizedInvestmentGainLossMember 2023-12-31 0000093410 us-gaap:AccumulatedGainLossNetCashFlowHedgeParentMember 2023-12-31 0000093410 us-gaap:AccumulatedDefinedBenefitPlansAdjustmentMember 2023-12-31 0000093410 us-gaap:AccumulatedTranslationAdjustmentMember 2024-01-01 2024-12-31 0000093410 us-gaap:AccumulatedNetUnrealized [...TRUNCATED...] Power of Attorney for certain directors of Chevron Corporation, authorizing the signing of the Annual Report on Form 10-K on their behalf. 31.1* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Executive Officer (page E-3). 31.2* Rule 13a-14(a)/15d-14(a) Certification by the company’s Chief Financial Officer (page E-4).   32.1** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Executive Officer (page E-5).   32.2** Rule 13a-14(b)/15d-14(b) Certification by the company’s Chief Financial Officer (page E-6). 97.1+ Chevron Corporation Dodd-Frank Clawback Policy , filed as Exh i bit 97.1 to Ch ev ron Corporation ’ s Annual Report on Form 10-K for the year ended December 31, 2023, and incorporated herein by r eference . 99.1* Definitions of Selected Energy and Financial Terms (pages E-7 through E-10). 101* Interactive data files (formatted as Inline XBRL). 104* Cover Page Interactive Data File (contained in Exhibit 101).   ___________________________________________ + Indicates a management contract or compensatory plan or arrangement. *      Filed herewith. **      Furnished herewith. Pursuant to Item 601(b)(4) of Regulation S-K, certain instruments with respect to the company’s long-term debt are not filed with this Annual Report on Form 10-K. A copy of any such instrument will be furnished to the Securities and Exchange Commission upon request. 120 Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized, on the 21st day of February, 2025.  Chevron Corporation   By: /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities indicated on the 21st day of February, 2025.   Principal Executive Officer (and Director) /s/ MICHAEL K. WIRTH Michael K. Wirth, Chairman of the Board and Chief Executive Officer Principal Financial Officer /s/ EIMEAR P. BONNER Eimear P. Bonner, Vice President and Chief Financial Officer Principal Accounting Officer /s/ ALANA K. KNOWLES Alana K. Knowles, Vice President and Controller * By:  /s/ MARY A. FRANCIS Mary A. Francis, Attorney-in-Fact Directors WANDA M. AUSTIN * Wanda M. Austin JOHN B. FRANK * John B. Frank ALICE P. GAST * Alice P. Gast ENRIQUE HERNANDEZ, JR. * Enrique Hernandez, Jr. MARILLYN A. HEWSON * Marillyn A. Hewson JON M. HUNTSMAN JR. * Jon M. Huntsman Jr. CHARLES W. MOORMAN * Charles W. Moorman DAMBISA F. MOYO * Dambisa F. Moyo DEBRA REED-KLAGES * Debra Reed-Klages D. JAMES UMPLEBY III * D. James Umpleby III CYNTHIA J. WARNER * Cynthia J. Warner 121\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 = 0.0290 (i.e., a 2.90% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0290 = 3.4431, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.029043, "expected_loss": 0.029043, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250714_0493", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IEF"], "decision_date": "2025-07-14", "context_summary": "IEF: 60-day history, VaR(99%)=-0.0079, max drawdown threshold=10%.", "question": "Asset: IEF\nDaily returns (past 60 days): mean=0.0002, std=0.0038, worst_day=-0.0080\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to IEF, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; 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 = 12.7275, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.007857, "expected_loss": 0.007857, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251203_0495", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-12-03", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1287, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0094, std=0.0475, worst_day=-0.1761\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7770", "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": true, "text_chars": 20}} +{"id": "T3_all_20250612_0498", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["JNK"], "decision_date": "2025-06-12", "context_summary": "JNK: 60-day history, VaR(99%)=-0.0142, max drawdown threshold=10%.", "question": "Asset: JNK\nDaily returns (past 60 days): mean=0.0001, std=0.0051, worst_day=-0.0142\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to JNK, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0142 (i.e., a 1.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0142 = 7.0283, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014228, "expected_loss": 0.014228, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250814_0500", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLY"], "decision_date": "2025-08-14", "context_summary": "XLY: 60-day history, VaR(99%)=-0.0249, max drawdown threshold=10%.", "question": "Asset: XLY\nDaily returns (past 60 days): mean=0.0009, std=0.0109, worst_day=-0.0255\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-08-13] [\"Meet the Monster Stock That Continues to Crush the Market Dutch Bros is developing products and creating a consumer experience that's generating loyalty. It reported outstanding second-quarter earnings. It sees the opportunity to increase its store count sevenfold. 10 stocks we like better than Dutch Bros \\u203a The market has been getting plenty of good news lately, and stocks are starting to climb again. President Donald Trump met with Apple CEO Tim Cook last week, with Apple announcing a $600 billion investment in U.S. operations, while Nvidia and Advanced Micro Devices agreed to give 15% of revenue from Chinese goods to the U.S. government in exchange for the ability to sell chips to China. But coffee chain Dutch Bros' (NYSE: BROS) stock soared last week on its own news, and after middling performance for most of the year, it's up more than 26%, beating the S&P 500's 9% rise. Here's why the market is loving Dutch Bros. Investors love to get into a detailed earnings report or 10-K filing to see how a company's finances are doing. But the beginning of any great company is a great product. Dutch Bros sells coffee through its chain of just over 1,000 stores today, but its concept was built on innovative products, and that vibrant approach to coffee still drives the business. Don't get me wrong; the economics here are excellent, which furthers the investment thesis. But it starts with great coffee that customers love, and the high sales follow. CEO Christine Barone detailed the company's three-part plan to generate higher transaction growth. It involves menu innovation, paid advertising to enhance brand awareness as it rolls out in new regions, and leaning into the loyalty program. Dutch Bros has always differentiated itself by launching its own branded beverages, and that's one way it stands out. Barone called it a mix of art and science, understanding what's trending in the coffee world and translating it into products that its customers want to drink. Some of the innovation is in the customized beverages, such as protein coffee and flavors like lavender, and some of that is in the menu itself. One of the initiatives it's working on is a pilot of a morning food menu, which is driving higher engagement and sales in the morning coffee run. Part of the product is the experience, and making its stores a positive experience involves rigorous systems and technology to ensure speed and effective customer service. The company takes things slow in that respect to ensure it has its systems in check before opening new stores or making any changes. Barone said that the food menu will roll out slowly through 2026 even though it's already demonstrating positive metrics, to ensure that stores are ready to handle it. This fresh approach is driving incredible growth. Revenue increased 28% year over year in the 2025 second quarter, with a 6.1% increase in same-shop sales and a 3.7% increase in transactions. Company-operated shop contribution margin was 31.1%, 0\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 = 0.0249 (i.e., a 2.49% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0249 = 4.0197, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.024877, "expected_loss": 0.024877, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250618_0503", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL"], "decision_date": "2025-06-18", "context_summary": "QUAL: 60-day history, VaR(99%)=-0.0339, max drawdown threshold=10%.", "question": "Asset: QUAL\nDaily returns (past 60 days): mean=0.0002, std=0.0132, worst_day=-0.0339\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-17] [\"Life360 Stock Rises On Upbeat Report For Family Tracker Service Life360 stock rose Monday after a Wall Street analyst raised his price target on the family connection and safety company.\", \"Herbal Medicine Stock With No Sales Rallies 64,000% (Bloomberg) \\u2014 A biotech stock focused on herbal medicine has surged by more than 46,000% so far this year and yet, the company itself has made zero revenue \\u2014 much less turned a profit. Most Read from Bloomberg As Part of a $45 Billion Push, ICE Prepares for a Vast Expansion of Detention Space As American Architects Gather in Boston, Retrofits Are All the Rage The unbelievable rally has transformed Regencell Bioscience Holdings Limited, a penny stock as recently as April, to one worth nearly $30 billion in market value. A year ago, the stock had a market capitalization of just $53 million. This is despite the company having a net loss of $4.4 million for its fiscal year that ended June 2024, a 28% decrease from the previous year. Earlier this month the company said its board approved a 38-for-1 stock split. When the split took effect Monday, shares rose 283% \\u2014 their biggest one-day jump in nearly a year on a closing basis \\u2014 to a record high, triggering more than 10 volatility halts. Shares of the company have been on a bizarre, 460-fold tear in 2025, with little to no news from the firm. The Hong Kong-based firm, which debuted on the Nasdaq Capital Market in 2021, is in the research and development stage and has not generated any revenue since inception, according to its most-recent annual filing with the US Securities and Exchange Commission. A representative for Regencell didn\\u2019t respond to a Bloomberg News request for comment. Incorporated in the Cayman Islands, the firm aims to treat neurological disorders like ADHD and autism spectrum disorder through traditional herb-based medicines, according to its website. Its traditional Chinese medicine (TCM) formula, which forms the basis of its product candidates, \\u201ccontains only natural ingredients without any synthetic components.\\u201d \\u201cWe have not generated revenue from any TCM formulae candidates or applied for any regulatory approvals, nor have distribution capabilities or experience or any granted patents or pending patent applications and may never be profitable,\\u201d the company said in an October filing. The company also made its foray into treatments for Covid-19, conducting trials in 2022 for an \\u201cholistic approach\\u201d with its experimental therapy. Regencell said data from a 2022 trial showed the treatment was effective in reducing and eliminating Covid symptoms within six days, although the results were yet to be peer-reviewed. The firm has funded its operations so far, primarily from shareholder loans and proceeds from its initial public offering, the SEC filing showed. It said its gross proceeds from its IPO were $21.85 million, with additional net proceeds of $2.85 million from the issue of the over allotm\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 = 0.0339 (i.e., a 3.39% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0339 = 2.9513, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.033883, "expected_loss": 0.033883, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250513_0506", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ICSH"], "decision_date": "2025-05-13", "context_summary": "ICSH: 60-day history, VaR(99%)=-0.0006, max drawdown threshold=10%.", "question": "Asset: ICSH\nDaily returns (past 60 days): mean=0.0003, std=0.0004, worst_day=-0.0006\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to 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 = 168.4027, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.000594, "expected_loss": 0.000594, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250429_0509", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SCHP"], "decision_date": "2025-04-29", "context_summary": "SCHP: 60-day history, VaR(99%)=-0.0090, max drawdown threshold=10%.", "question": "Asset: SCHP\nDaily returns (past 60 days): mean=0.0005, std=0.0034, worst_day=-0.0090\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\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 = 0.0090 (i.e., a 0.90% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0090 = 11.0906, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.009017, "expected_loss": 0.009017, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250822_0512", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["MORT"], "decision_date": "2025-08-22", "context_summary": "MORT: 60-day history, VaR(99%)=-0.0156, max drawdown threshold=10%.", "question": "Asset: MORT\nDaily returns (past 60 days): mean=0.0012, std=0.0092, worst_day=-0.0167\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\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 = 0.0156 (i.e., a 1.56% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0156 = 6.4078, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015606, "expected_loss": 0.015606, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250922_0515", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-09-22", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0372, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0053, std=0.0239, worst_day=-0.0410\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0372 (i.e., a 3.72% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0372 = 2.6872, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.037213, "expected_loss": 0.037213, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251208_0518", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-12-08", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0600, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0049, std=0.0243, worst_day=-0.0698\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0600 (i.e., a 6.00% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0600 = 1.6675, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.059968, "expected_loss": 0.059968, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250912_0521", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-09-12", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0103, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0004, std=0.0056, worst_day=-0.0114\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USMV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0103 (i.e., a 1.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0103 = 9.7234, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.010284, "expected_loss": 0.010284, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250923_0524", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-09-23", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0382, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0007, std=0.0151, worst_day=-0.0404\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0382 (i.e., a 3.82% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0382 = 2.6150, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.03824, "expected_loss": 0.03824, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250114_0526", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-01-14", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1217, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0061, std=0.0631, worst_day=-0.1453\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8214", "answer_numeric": 0.8214, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1217 (i.e., a 12.17% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1217 = 0.8214, capped at 1.0.\nMaximum position size = 0.8214 (82.1% of portfolio).", "metadata": {"var_99": -0.121746, "expected_loss": 0.121746, "max_drawdown_threshold": 0.1, "position_size": 0.8214, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250911_0529", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IVV"], "decision_date": "2025-09-11", "context_summary": "IVV: 60-day history, VaR(99%)=-0.0116, max drawdown threshold=10%.", "question": "Asset: IVV\nDaily returns (past 60 days): mean=0.0015, std=0.0059, worst_day=-0.0163\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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 = 0.0116 (i.e., a 1.16% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0116 = 8.6359, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01158, "expected_loss": 0.01158, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250605_0531", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-06-05", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0337, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=0.0004, std=0.0141, worst_day=-0.0337\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-04] [\"Qualcomm CEO: We're diversifying beyond declining Apple business Listen and subscribe to Opening Bid on Apple Podcasts, Spotify, Amazon Music, YouTube or wherever you find your favorite podcasts. Qualcomm's (QCOM) next 40 years will look different than its past four decades as it seeks to diversify into data centers and cash in on the AI gold rush. But that also likely means going at things other than its lucrative business with Apple's (AAPL) iPhone. Qualcomm has been Apple's largest cellular modem provider, but the tech giant is transitioning to its own in-house C1 modem in a bid to boost margins. \\\"That's our contract, you know, and if we don't get a new contract, that's what it is,\\\" Qualcomm CEO Cristiano Amon said on Yahoo Finance's Opening Bid podcast (see video above; listen below). \\\"And there's so much drama and association about the Apple relationship, which I think it's not warranted, to be honest.\\\" The tech duo's licensing agreement ends in 2027. Research firm Futurum estimates that Qualcomm's annual modem revenue from Apple is between $5.7 billion and $5.9 billion. Analysts estimate Qualcomm will pull in about $43.5 billion in sales this year. Qualcomm has said publicly it expects to have a 70% share in iPhones launching this fall. That will drop to 20% for iPhones next fall, and then stand to be zero for iPhones debuting in fall 2027. Yahoo Finance caught up with the globe-trotting Amon \\u2014 fresh off a visit to Saudi Arabia with other top execs and the Trump administration \\u2014 at the Nasdaq. Amon began his career at Qualcomm as an engineer in 1995. \\\"We're planning our business assuming that they [Apple] are going to use their own modem,\\\" Amon said. \\\"And what's exciting about the company is all of this growth that we're creating, all of those other markets, including on Android. Like, if you look at our Android business, it has continued to grow.\\\" To offset the lost Apple sales, Qualcomm continues to invest in the connected car cockpit and the internet of things domain. The company thinks it can grow its business from these two segments to $22 billion by 2030, up from $8.3 billion in fiscal year 2024. \\\"Qualcomm's diversified growth across these specific verticals is credibly expected to significantly exceed the revenue scale of modem-only handset customers well into the era of 6G,\\\" Futurum researchers wrote in a note. The company also announced in mid-May that it plans to launch processors designed for data centers to power artificial intelligence, which will connect to Nvidia (NVDA) chips. Qualcomm failed to successfully expand into data centers years ago and returns to the field with formidable rivals in AMD (AMD), Intel (INTC), and soon ARM (ARM). \\\"It's a massive TAM [total addressable market] and will continue to grow at very high growth rates for decades. If we can build something unique and disruptive, there's room for Qualcomm,\\\" Amon said of the data center push. The Street has taken a wait-and-see approach t\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_20250902_0533", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-09-02", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0925, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0015, std=0.0393, worst_day=-0.0949\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0925 (i.e., a 9.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0925 = 1.0809, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.092516, "expected_loss": 0.092516, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250116_0538", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNDX"], "decision_date": "2025-01-16", "context_summary": "BNDX: 60-day history, VaR(99%)=-0.0046, max drawdown threshold=10%.", "question": "Asset: BNDX\nDaily returns (past 60 days): mean=0.0001, std=0.0023, worst_day=-0.0049\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 = 0.0046 (i.e., a 0.46% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0046 = 21.8853, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.004569, "expected_loss": 0.004569, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250117_0541", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2025-01-17", "context_summary": "XHB: 60-day history, VaR(99%)=-0.0353, max drawdown threshold=10%.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=-0.0020, std=0.0150, 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 = 0.0353 (i.e., a 3.53% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0353 = 2.8312, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.035321, "expected_loss": 0.035321, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251212_0544", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-12-12", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0195, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0005, std=0.0082, worst_day=-0.0237\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2025-12-03] wmt-20251031 0000104169 1/31 2026 Q3 false 178 340 294 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure wmt:state wmt:territory wmt:case wmt:classAction wmt:securitiesClassAction wmt:pharmacist wmt:employee wmt:phase wmt:supplierContribution iso4217:MXN wmt:segment 0000104169 2025-02-01 2025-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2025-02-01 2025-10-31 0000104169 wmt:A2.550NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1050NotesDue2026Member 2025-02-01 2025-10-31 0000104169 wmt:A1500NotesDue2028Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2029Member 2025-02-01 2025-10-31 0000104169 wmt:A5750NotesDue2030Member 2025-02-01 2025-10-31 0000104169 wmt:A1800NotesDue2031Member 2025-02-01 2025-10-31 0000104169 wmt:A5625NotesDue2034Member 2025-02-01 2025-10-31 0000104169 wmt:A5250NotesDue2035Member 2025-02-01 2025-10-31 0000104169 wmt:A4875NotesDue2039Member 2025-02-01 2025-10-31 0000104169 2025-12-02 0000104169 2025-08-01 2025-10-31 0000104169 2024-08-01 2024-10-31 0000104169 2024-02-01 2024-10-31 0000104169 2025-10-31 0000104169 2025-01-31 0000104169 2024-10-31 0000104169 us-gaap:CommonStockMember 2025-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-01-31 0000104169 us-gaap:ParentMember 2025-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-01-31 0000104169 us-gaap:RetainedEarningsMember 2025-02-01 2025-04-30 0000104169 us-gaap:ParentMember 2025-02-01 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-02-01 2025-04-30 0000104169 2025-02-01 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-02-01 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-02-01 2025-04-30 0000104169 us-gaap:CommonStockMember 2025-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-30 0000104169 us-gaap:ParentMember 2025-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2025-04-30 0000104169 2025-04-30 0000104169 us-gaap:RetainedEarningsMember 2025-05-01 2025-07-31 0000104169 us-gaap:ParentMember 2025-05-01 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-05-01 2025-07-31 0000104169 2025-05-01 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-05-01 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-05-01 2025-07-31 0000104169 us-gaap:CommonStockMember 2025-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-07-31 0000104169 us-gaap:ParentMember 2025-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-07-31 0000104169 2025-07-31 0000104169 us-gaap:RetainedEarningsMember 2025-08-01 2025-10-31 0000104169 us-gaap:ParentMember 2025-08-01 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-08-01 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-08-01 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-08-01 2025-10-31 0000104169 us-gaap:CommonStockMember 2025-10-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2025-10-31 0000104169 us-gaap:RetainedEarningsMember 2025-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-10-31 0000104169 us-gaap:ParentMember 2025-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2025-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-04-30 0000104169 us-gaap:ParentMember 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-04-30 0000104169 2024-04-30 0000104169 us-gaap:RetainedEarningsMember 2024-05-01 2024-07-31 0000104169 us-gaap:ParentMember 2024-05-01 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-05-01 2024-07-31 0000104169 2024-05-01 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-05-01 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-05-01 2024-07-31 0000104169 us-gaap:CommonStockMember 2024-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-07-31 0000104169 us-gaap:ParentMember 2024-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-07-31 0000104169 2024-07-31 0000104169 us-gaap:RetainedEarningsMember 2024-08-01 2024-10-31 0000104169 us-gaap:ParentMember 2024-08-01 2024-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-08-01 2024-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-08-01 2024-10-31 0000104169 us- [...TRUNCATED...] port, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 10.1* Retirement Agreement between the Company and Doug McMillon dated November 13, 2025 Exhibit 10.2* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Restricted Stock Notification of Award and Terms and Conditions of Award Exhibit 10.3* Form of Walmart Inc. Stock Incentive Plan of 2025 Global Share-Settled Performance-Based Restricted Stock Unit Notification of Award and Terms and Condition s of Award Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Non-MDL Opioid-Related Litigation Case Citations Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2025, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 3, 2025 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 3, 2025 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 3, 2025 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to 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 = 0.0195 (i.e., a 1.95% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0195 = 5.1263, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.019507, "expected_loss": 0.019507, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250331_0547", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ETH-USD"], "decision_date": "2025-03-31", "context_summary": "ETH-USD: 60-day history, VaR(99%)=-0.1252, max drawdown threshold=10%.", "question": "Asset: ETH-USD\nDaily returns (past 60 days): mean=-0.0081, std=0.0435, worst_day=-0.1485\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7989", "answer_numeric": 0.7989, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1252 (i.e., a 12.52% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1252 = 0.7989, capped at 1.0.\nMaximum position size = 0.7989 (79.9% of portfolio).", "metadata": {"var_99": -0.125179, "expected_loss": 0.125179, "max_drawdown_threshold": 0.1, "position_size": 0.7989, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250925_0549", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2025-09-25", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0210, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0009, std=0.0099, worst_day=-0.0241\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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 = 0.0210 (i.e., a 2.10% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0210 = 4.7625, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020998, "expected_loss": 0.020998, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250403_0552", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-04-03", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.1503, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0079, std=0.0583, worst_day=-0.1606\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.6655", "answer_numeric": 0.6655, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1503 (i.e., a 15.03% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1503 = 0.6655, capped at 1.0.\nMaximum position size = 0.6655 (66.5% of portfolio).", "metadata": {"var_99": -0.150254, "expected_loss": 0.150254, "max_drawdown_threshold": 0.1, "position_size": 0.6655, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250217_0555", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-02-17", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0176, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0004, std=0.0062, worst_day=-0.0215\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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0000018230 cat:StockOptionsandShareAppreciationRightsSARsMember 2023-01-01 2023-12-31 0000018230 cat:StockOptionsandShareApprecia [...TRUNCATED...] ulation Linkbase Document 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive File (embedded within the Inline XBRL document and included in Exhibit 101) _________________________________________ *Management contracts and compensatory plans and arrangements required to be filed as exhibits pursuant to Item 15(b) of this report. The agreements and other documents filed as exhibits to this report are not intended to provide factual information or other disclosure other than with respect to the terms of the agreements or other documents themselves, and you should not rely on them for that purpose. In particular, any representations and warranties made by us in these agreements or other documents were made solely within the specific context of the relevant agreement or document and may not describe the actual state of affairs as of the date they were made or at any other time. Item 16.  Form 10-K Summary. None. 129 Table of Contents Form 10-K   SIGNATURES   Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized.     CATERPILLAR INC.   Registrant     February 14, 2025 By: /s/ Derek Owens     Derek Owens Chief Legal Officer and General Counsel   Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the Registrant and in the capacities and on the dates indicated.       Chairman of the Board  and Chief Executive Officer February 14, 2025 /s/ D. James Umpleby III   D. James Umpleby III       February 14, 2025 /s/ Andrew R.J. Bonfield Chief Financial Officer Andrew R.J. Bonfield     February 14, 2025 /s/ William E. Schaupp Vice President and Chief Accounting Officer   William E. Schaupp             February 14, 2025 /s/ Daniel M. Dickinson Director   Daniel M. Dickinson   February 14, 2025 /s/ James C. Fish, Jr. Director James C. Fish, Jr.       130 Table of Contents February 14, 2025 /s/ Gerald Johnson Director   Gerald Johnson   February 14, 2025 /s/ Nazzic S. Keene Director Nazzic S. Keene       February 14, 2025 /s/ David W. MacLennan Director   David W. MacLennan   February 14, 2025 /s/ Judith F. Marks Director Judith F. Marks February 14, 2025 /s/ Debra L. Reed-Klages Presiding Director Debra L. Reed-Klages       February 14, 2025 /s/ Susan C. Schwab Director   Susan C. Schwab             February 14, 2025 /s/ Rayford Wilkins, Jr. Director   Rayford Wilkins, Jr.   131\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 = 0.0176 (i.e., a 1.76% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0176 = 5.6783, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.017611, "expected_loss": 0.017611, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20251103_0558", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-11-03", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0154, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=0.0018, std=0.0082, worst_day=-0.0167\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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us-gaap:FairValueInputsLevel2Member 2024-09-28 0000320193 us-gaap:ForeignGovernmentDebtSecurities [...TRUNCATED...] overy Policy 10-K 97.1 9/28/24 Apple Inc. | 2025 Form 10-K | 56 Incorporated by Reference Exhibit Number Exhibit Description Form Exhibit Filing Date/ Period End Date 101** Inline XBRL Document Set for the consolidated financial statements and accompanying notes in Part II, Item 8, “Financial Statements and Supplementary Data” of this Annual Report on Form 10-K. 104** Inline XBRL for the cover page of this Annual Report on Form 10-K, included in the Exhibit 101 Inline XBRL Document Set. * Indicates management contract or compensatory plan or arrangement. ** Filed herewith. *** Furnished herewith. (1) Certain instruments defining the rights of holders of long-term debt securities of the Registrant are omitted pursuant to Item 601(b)(4)(iii) of Regulation S-K. The Registrant hereby undertakes to furnish to the SEC, upon request, copies of any such instruments. Item 16.    Form 10-K Summary None. Apple Inc. | 2025 Form 10-K | 57 SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Date: October 31, 2025 Apple Inc. By: /s/ Kevan Parekh Kevan Parekh 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 Kevan Parekh, 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 31, 2025 TIMOTHY D. COOK /s/ Kevan Parekh Senior Vice President, Chief Financial Officer (Principal Financial Officer) October 31, 2025 KEVAN PAREKH /s/ Chris Kondo Senior Director of Corporate Accounting (Principal Accounting Officer) October 31, 2025 CHRIS KONDO /s/ Wanda Austin Director October 31, 2025 WANDA AUSTIN /s/ Alex Gorsky Director October 31, 2025 ALEX GORSKY /s/ Andrea Jung Director October 31, 2025 ANDREA JUNG /s/ Arthur D. Levinson Director and Chair of the Board October 31, 2025 ARTHUR D. LEVINSON /s/ Monica Lozano Director October 31, 2025 MONICA LOZANO /s/ Ronald D. Sugar Director October 31, 2025 RONALD D. SUGAR /s/ Susan L. Wagner Director October 31, 2025 SUSAN L. WAGNER Apple Inc. | 2025 Form 10-K | 58\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 = 0.0154 (i.e., a 1.54% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0154 = 6.4836, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.015424, "expected_loss": 0.015424, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20250310_0561", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE"], "decision_date": "2025-03-10", "context_summary": "XLE: 60-day history, VaR(99%)=-0.0323, max drawdown threshold=10%.", "question": "Asset: XLE\nDaily returns (past 60 days): mean=-0.0005, std=0.0130, worst_day=-0.0356\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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ITEM 16. FORM 10-K SUMMARY None. SIGNATURES Under the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, this report was signed on behalf of the Registrant by the authorized person named below. Pfizer Inc. Dated: February 27, 2025 By: /S/    MARGARET M. MADDEN Margaret M. Madden Senior Vice President and Corporate Secretary Chief Governance Counsel We, the undersigned directors and officers of Pfizer Inc., hereby severally constitute Douglas M. Lankler and Margaret M. Madden, and each of them singly, our true and lawful attorneys with full power to them and each of them to sign for us, in our names in the capacities indicated below, any and all amendments to this Annual Report on Form 10-K filed with the Securities and Exchange Commission. Under the requirements of the Securities Exchange Act of 1934, this report was signed by the following persons on behalf of the Registrant and in the capacities and on the date indicated . Pfizer Inc. 2024 Form 10-K 113 Signature Title Date /S/    ALBERT BOURLA Albert Bourla Chairman, Chief Executive Officer and Director (Principal Executive Officer) February 27, 2025 /S/    DAVID M. DENTON David M. Denton Chief Financial Officer, Executive Vice President (Principal Financial Officer) February 27, 2025 /S/    JENNIFER B. DAMICO Jennifer B. Damico Senior Vice President and Controller (Principal Accounting Officer) February 27, 2025 /S/    RONALD E. BLAYLOCK Ronald E. Blaylock Director February 27, 2025 /S/    MORTIMER J. BUCKLEY Mortimer J. Buckley Director February 27, 2025 /S/    SUSAN DESMOND-HELLMANN Susan Desmond-Hellmann Director February 27, 2025 /S/    JOSEPH J. ECHEVARRIA Joseph J. Echevarria Director February 27, 2025 /S/    SCOTT GOTTLIEB Scott Gottlieb Director February 27, 2025 /S/    HELEN H. HOBBS Helen H. Hobbs Director February 27, 2025 /S/    SUSAN HOCKFIELD Susan Hockfield Director February 27, 2025 /S/    DAN R. LITTMAN Dan R. Littman Director February 27, 2025 /S/    SHANTANU NARAYEN Shantanu Narayen Director February 27, 2025 /S/    SUZANNE NORA JOHNSON Suzanne Nora Johnson Director February 27, 2025 /S/    JAMES QUINCEY James Quincey Director February 27, 2025 /S/    JAMES C. SMITH James C. Smith Director February 27, 2025 /S/    CYRUS TARAPOREVALA Cyrus Taraporevala Director February 27, 2025 Pfizer Inc. 2024 Form 10-K 114\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 = 0.0323 (i.e., a 3.23% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0323 = 3.0973, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032286, "expected_loss": 0.032286, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250619_0564", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-06-19", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.0653, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0000, std=0.0365, worst_day=-0.0764\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0653 (i.e., a 6.53% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0653 = 1.5318, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.065281, "expected_loss": 0.065281, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250620_0567", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2025-06-20", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0325, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0004, std=0.0128, worst_day=-0.0325\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-18] [\"AI Could Create the First $10 Trillion Company. This Stock Pro Lays Out How. A conversation with Ulrike Hoffmann-Burchardi of UBS Global Wealth Management. Where she sees the next \\u201ctransformational innovations.\\u201d\", \"Streaming Finally Outpaces Traditional TV. The Leading Platform Might Surprise You. YouTube represented 12.5% of all television viewing in May\\u2014the highest share of TV for any streamer to date.\", \"Texas Instruments plans to invest more than $60 billion to manufacture billions of foundational semiconductors in the U.S. Leading U.S. companies Apple, Ford, Medtronic, NVIDIA and SpaceX strengthen partnerships with TI to unleash the next era of American innovation NEWS HIGHLIGHTS: More than $60 billion investment includes seven U.S. semiconductor fabs across three manufacturing mega-sites in Texas and Utah supporting more than 60,000 new U.S. jobs Largest investment in foundational semiconductor manufacturing in U.S. history, building on TI's almost-100-year legacy TI's largest mega-site in Sherman, Texas includes investment of up to $40 billion dollars for four fabs: SM1 and SM2 \\u2013 already underway \\u2013 and two additional fabs, SM3 and SM4 Leverages TI's strengths as a global technology and manufacturing leader to advance critical innovations from vehicles to smartphones to data centers DALLAS, June 18, 2025 /PRNewswire/ -- Texas Instruments (TI) (Nasdaq: TXN) today announced its plans to invest more than $60 billion across seven U.S. semiconductor fabs, making this the largest investment in foundational semiconductor manufacturing in U.S. history. Working with the Trump administration and building on the company's nearly 100-year legacy, TI is expanding its U.S. manufacturing capacity to supply the growing need for semiconductors that will advance critical innovations from vehicles to smartphones to data centers. Combined, TI's new manufacturing mega-sites in Texas and Utah will support more than 60,000 U.S. jobs. \\\"TI is building dependable, low-cost 300mm capacity at scale to deliver the analog and embedded processing chips that are vital for nearly every type of electronic system,\\\" said Haviv Ilan, president and CEO of Texas Instruments. \\\"Leading U.S. companies such as Apple, Ford, Medtronic, NVIDIA and SpaceX rely on TI's world-class technology and manufacturing expertise, and we are honored to work alongside them and the U.S. government to unleash what's next in American innovation.\\\" \\\"For nearly a century, Texas Instruments has been a bedrock American company driving innovation in technology and manufacturing,\\\" said U.S. Secretary of Commerce, Howard Lutnick. \\\"President Trump has made it a priority to increase semiconductor manufacturing in America \\u2013 including these foundational semiconductors that go into the electronics that people use every day. Our partnership with TI will support U.S. chip manufacturing for decades to come.\\\" Unleashing what's next in American innovation Today, TI is the largest \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to EWJ, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0325 (i.e., a 3.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0325 = 3.0761, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032508, "expected_loss": 0.032508, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20251110_0569", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["INDS"], "decision_date": "2025-11-10", "context_summary": "INDS: 60-day history, VaR(99%)=-0.0197, max drawdown threshold=10%.", "question": "Asset: INDS\nDaily returns (past 60 days): mean=0.0010, std=0.0100, worst_day=-0.0223\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 = 0.0197 (i.e., a 1.97% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0197 = 5.0685, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.01973, "expected_loss": 0.01973, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250519_0572", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-05-19", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0372, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=0.0004, std=0.0150, worst_day=-0.0372\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-16] [\"Elite CEOs Don\\u2019t Need Earnings Guidance Avoiding the short-termism of Wall Street\\u2019s expectations game might be a good thing for more companies.\", \"How Apple, Consumer Tech Companies Got Ahead Of The Trump Tariffs The Trump tariffs may have surprised the general public but makers of consumer electronics and computer hardware had prepared for them.\", \"Trump Trade: Trump asks Apple to stop building iPhone plants in India Catch up on the top industries and stocks that were impacted, or were predicted to be impacted, by the comments, actions and policies of President Donald Trump with this daily recap compiled by The Fly: Quickly and easily unpack a company's performance with TipRanks' new KPI Data for smart investment decisions Receive undervalued, market resilient stocks straight to you inbox with TipRanks' Smart Value Newsletter IPHONE PLANTS: President Donald Trump is asking Apple (AAPL) CEO Tim Cook to stop building plants in India to make devices for the U.S., and is pushing for the iPhone maker to add domestic production, Bloomberg\\u2019s Jordan Fabian and Sankalp Phartiyal report. Apple plans to import most of the iPhones it sells in the U.S. from India by the end of next year, as Apple currently makes most of its iPhones in China. \\u201cI had a little problem with Tim Cook yesterday,\\u201d Trump said of his conversation with the Apple CEO in Qatar, where he\\u2019s on a state visit. \\u201cHe is building all over India. I don\\u2019t want you building in India.\\u201d As a result of their discussion, Trump said Apple will be \\u201cupping their production in the United States.\\u201d CHINESE PARTS: Tesla (TSLA) plans to resume shipping components from China to the U.S. for the production of Cybercab and Semi trucks at the end of May after the U.S. and China reached a truce over tariffs, Reuters\\u2019 reports, citing a person with direct knowledge of the matter. Tesla previously suspended plans to ship the components after U.S. President Donald Trump raised tariffs on Chinese goods to 145%, potentially disrupting Tesla\\u2019s plan to start mass production of the much-anticipated models. NUCLEAR DEAL: President Donald Trump said the U.S. may be getting closer to an agreement with Iran to curb the Islamic Republic\\u2019s nuclear program, Bloomberg\\u2019s Patrick Sykes reports. Trump referred to an NBC interview with Ali Shamkhani, an adviser to Iran\\u2019s Supreme Leader Ali Khamenei, in which Shamkhani reiterated Tehran\\u2019s position that it\\u2019s willing to limit uranium enrichment in exchange for sanctions relief. The U.S. and Iran have held four rounds of talks about the Islamic Republic\\u2019s atomic activities, mediated by Oman, with Trump seeking a deal that would prevent Iran from potentially building a nuclear weapon, and Tehran seeking a reprieve from U.S. sanctions. LAWSUIT SETTLEMENT: Paramount Global (PARA) executive George Cheeks is helping negotiate a settlement of President Trump\\u2019s $20B lawsuit against Paramount\\u20\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLF, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0372 (i.e., a 3.72% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0372 = 2.6872, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.037214, "expected_loss": 0.037214, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250505_0575", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV"], "decision_date": "2025-05-05", "context_summary": "XLV: 60-day history, VaR(99%)=-0.0288, max drawdown threshold=10%.", "question": "Asset: XLV\nDaily returns (past 60 days): mean=-0.0009, std=0.0112, worst_day=-0.0294\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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us-gaap:FairValueInputsLevel1Member us-gaap:MutualFundMember 2024-09-28 0000320193 us-gaap:FairValueInputsLevel1Member 2024-09-28 00003 [...TRUNCATED...] f Proceeds Purchases of Equity Securities by the Issuer and Affiliated Purchasers Share repurchase activity during the three months ended March 29, 2025 was as follows (in millions, except number of shares, which are reflected in thousands, and per-share amounts): Periods Total Number of Shares Purchased Average Price Paid Per Share Total Number of Shares Purchased as Part of Publicly Announced Plans or Programs Approximate Dollar Value of Shares That May Yet Be Purchased Under the Plans or Programs (1) December 29, 2024 to February 1, 2025: Open market and privately negotiated purchases 36,809  $ 235.43  36,809  February 2, 2025 to March 1, 2025: Open market and privately negotiated purchases 31,856  $ 238.07  31,856  March 2, 2025 to March 29, 2025: Open market and privately negotiated purchases 39,455  $ 221.77  39,455  Total 108,120  $ 40,779  (1) As of March 29, 2025, the Company was authorized by the Board of Directors to purchase up to $110 billion of the Company’s common stock under a share repurchase program announced on May 2, 2024, of which $69.2 billion had been utilized. On May 1, 2025, the Company announced the Board of Directors had authorized an additional program to repurchase up to $100 billion of the Company’s common stock. The programs do not obligate the Company to acquire a minimum amount of shares. Under the programs, shares may be repurchased in privately negotiated or open market transactions, including under plans complying with Rule 10b5-1 under the Exchange Act. Item 3.    Defaults Upon Senior Securities None. Item 4.    Mine Safety Disclosures Not applicable. Item 5.    Other Information Insider Trading Arrangements None. Item 6.    Exhibits Incorporated by Reference Exhibit Number Exhibit Description Form Exhibit Filing Date/ Period End Date 31.1* Rule 13a-14(a) / 15d-14(a) Certification of Chief Executive Officer. 31.2* Rule 13a-14(a) / 15d-14(a) Certification of Chief Financial Officer. 32.1** Section 1350 Certifications of Chief Executive Officer and Chief Financial Officer. 101* Inline XBRL Document Set for the condensed consolidated financial statements and accompanying notes in Part I, Item 1, “Financial Statements” of this Quarterly Report on Form 10-Q. 104* Inline XBRL for the cover page of this Quarterly Report on Form 10-Q, included in the Exhibit 101 Inline XBRL Document Set. *    Filed herewith. **    Furnished herewith. Apple Inc. | Q2 2025 Form 10-Q | 22 SIGNATURE Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. Date: May 2, 2025 Apple Inc. By: /s/ Kevan Parekh Kevan Parekh Senior Vice President, Chief Financial Officer Apple Inc. | Q2 2025 Form 10-Q | 23\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 = 0.0288 (i.e., a 2.88% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0288 = 3.4777, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.028755, "expected_loss": 0.028755, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20250113_0578", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-13", "context_summary": "SPY: 60-day history, VaR(99%)=-0.0229, max drawdown threshold=10%.", "question": "Asset: SPY\nDaily returns (past 60 days): mean=-0.0001, std=0.0079, worst_day=-0.0274\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q WMT 2024-12-06] wmt-20241031 0000104169 1/31 2025 Q3 false 451 xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure iso4217:JPY wmt:state wmt:county wmt:defendant wmt:case wmt:classAction wmt:securitiesClassAction wmt:shareholder wmt:derivativeAction wmt:pharmacist wmt:segment 0000104169 2024-02-01 2024-10-31 0000104169 wmt:CommonStockparvalue0.10pershareMember 2024-02-01 2024-10-31 0000104169 wmt:A2.550NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1050NotesDue2026Member 2024-02-01 2024-10-31 0000104169 wmt:A1500NotesDue2028Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2029Member 2024-02-01 2024-10-31 0000104169 wmt:A5750NotesDue2030Member 2024-02-01 2024-10-31 0000104169 wmt:A1800NotesDue2031Member 2024-02-01 2024-10-31 0000104169 wmt:A5625NotesDue2034Member 2024-02-01 2024-10-31 0000104169 wmt:A5250NotesDue2035Member 2024-02-01 2024-10-31 0000104169 wmt:A4875NotesDue2039Member 2024-02-01 2024-10-31 0000104169 2024-12-04 0000104169 2024-08-01 2024-10-31 0000104169 2023-08-01 2023-10-31 0000104169 2023-02-01 2023-10-31 0000104169 2024-10-31 0000104169 2024-01-31 0000104169 2023-10-31 0000104169 us-gaap:CommonStockMember 2024-01-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-01-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-01-31 0000104169 us-gaap:ParentMember 2024-01-31 0000104169 us-gaap:NoncontrollingInterestMember 2024-01-31 0000104169 us-gaap:RetainedEarningsMember 2024-02-01 2024-04-30 0000104169 us-gaap:ParentMember 2024-02-01 2024-04-30 0000104169 us-gaap:NoncontrollingInterestMember 2024-02-01 2024-04-30 0000104169 2024-02-01 2024-04-30 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-02-01 2024-04-30 0000104169 us-gaap:AdditionalPaidInCapitalMember 2024-02-01 2024-04-30 0000104169 us-gaap:CommonStockMember 2024-04-30 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0000104169 us-gaap:RetainedEarningsMember 2023-05-01 2023-07-31 0000104169 us-gaap:ParentMember 2023-05-01 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-05-01 2023-07-31 0000104169 2023-05-01 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-05-01 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-05-01 2023-07-31 0000104169 us-gaap:CommonStockMember 2023-07-31 0000104169 us-gaap:AdditionalPaidInCapitalMember 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-07-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-07-31 0000104169 us-gaap:ParentMember 2023-07-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-07-31 0000104169 2023-07-31 0000104169 us-gaap:RetainedEarningsMember 2023-08-01 2023-10-31 0000104169 us-gaap:ParentMember 2023-08-01 2023-10-31 0000104169 us-gaap:NoncontrollingInterestMember 2023-08-01 2023-10-31 0000104169 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SPY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0229 (i.e., a 2.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0229 = 4.3640, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022915, "expected_loss": 0.022915, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250415_0581", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["CSHI"], "decision_date": "2025-04-15", "context_summary": "CSHI: 60-day history, VaR(99%)=-0.0115, max drawdown threshold=10%.", "question": "Asset: CSHI\nDaily returns (past 60 days): mean=-0.0002, std=0.0032, worst_day=-0.0115\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to CSHI, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0115 (i.e., a 1.15% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0115 = 8.6981, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.011497, "expected_loss": 0.011497, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251022_0584", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLU"], "decision_date": "2025-10-22", "context_summary": "XLU: 60-day history, VaR(99%)=-0.0142, max drawdown threshold=10%.", "question": "Asset: XLU\nDaily returns (past 60 days): mean=0.0014, std=0.0078, worst_day=-0.0184\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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 = 0.0142 (i.e., a 1.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0142 = 7.0317, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014221, "expected_loss": 0.014221, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250813_0587", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-08-13", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0606, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=0.0047, std=0.0383, worst_day=-0.0739\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0606 (i.e., a 6.06% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0606 = 1.6493, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.060632, "expected_loss": 0.060632, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250207_0590", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-02-07", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1235, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=-0.0006, std=0.0522, worst_day=-0.1493\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8095", "answer_numeric": 0.8095, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1235 (i.e., a 12.35% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1235 = 0.8095, capped at 1.0.\nMaximum position size = 0.8095 (81.0% of portfolio).", "metadata": {"var_99": -0.123527, "expected_loss": 0.123527, "max_drawdown_threshold": 0.1, "position_size": 0.8095, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250423_0593", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLB"], "decision_date": "2025-04-23", "context_summary": "XLB: 60-day history, VaR(99%)=-0.0337, max drawdown threshold=10%.", "question": "Asset: XLB\nDaily returns (past 60 days): mean=-0.0015, std=0.0143, worst_day=-0.0337\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2025-04-22] Is This Fast-Growing Chain the Next Costco? You might not be familiar with BBB Foods (NYSE: TBBB). And that's OK. Most stateside investors aren't familiar with the rapidly expanding chain providing deeply discounted groceries and other household essentials to a widening audience with 2,772 locations at the start of this year. It's North America's fastest growing player in its space, but you have to travel to Mexico to see it in action. BBB is the parent company of Tiendas 3B, a small-box supermarket concept with big-time aspirations. The three Bs stand for Bueno, Bonito, and Barato in Spanish, translating to \"good, pretty, and cheap.\" The concept is a cross between Aldi and Costco, wedged into a smaller convenience store frame. Where to invest $1,000 right now? Our analyst team just revealed what they believe are the 10 best stocks to buy right now. Continue \u00bb It's not a household name, but that's more an opportunity than a problem. With a business model far removed from the intersection of headwinds holding back most retail concepts, it's a good time to look at BBB before it begins pinging on more growth investors' radars. Let's travel south to see why this stock could be headed north. When BBB went public 14 months ago, it became the first Mexican company to go public on a U.S. exchange in six years. It's fair to say that it's been a hit. Underwriters priced the offering at $17.50, and the hard discounter is currently trading nearly 50% higher. It's no broken IPO. BBB is earnings its upticks. Revenue soared 30% last year to reach the U.S. equivalent of nearly $2.8 billion, accelerating in its latest quarter with a 33% jump. Expansion is a big part of the growth story. BBB opened 484 net new stores last year. However, momentum is building at the store level. Comps climbed 13.3% last year, and that's stacked on top of a 17.6% same-store sales surge in 2023. It just turned profitable last year, breaking through with operating free cash the year before that. It's still cranking out negative working capital given the current opportunity for rapid expansion, but that deficit narrowed substantially last year. Supermarket chains historically crank out low net margins. They're in the business of providing modest markups to their goods, making that back by turning over its inventory as much as possible. Costco is a rock star in this realm, but its net margin has failed to break the 3% ceiling in any single year in more than three decades of public trading. Its annual membership fees account for 2% of the revenue mix, and -- like most grocers -- Tiendas 3B does not require paid memberships. BBB pales in comparison with its 0.6% net margin last year, but give it time. It just became profitable last year, and the benefits of scalability should fine the bottom line outpacing the still impressive forecast for top-line jumps. If you think Costco's selling a lot of its own Kirkland products, consider that private label sales account for just a little more than \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0337 (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_20250408_0596", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-04-08", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1460, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0056, std=0.0598, worst_day=-0.1761\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.6849", "answer_numeric": 0.6849, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1460 (i.e., a 14.60% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1460 = 0.6849, capped at 1.0.\nMaximum position size = 0.6849 (68.5% of portfolio).", "metadata": {"var_99": -0.145999, "expected_loss": 0.145999, "max_drawdown_threshold": 0.1, "position_size": 0.6849, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250204_0598", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK"], "decision_date": "2025-02-04", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0369, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0004, std=0.0137, worst_day=-0.0427\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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2022-01-01 2022-12-31 0000012927 ba:CorporateReconcilingItemsAndEliminationsMember 2024-01-01 2024-12-31 0000012927 ba:CorporateReconcilingItemsAndEliminationsMember 2023-01-01 2 [...TRUNCATED...] ation of Chief Financial Officer pursuant to Section 906 of Sarbanes-Oxley Act of 2002 135 Table of Contents 97 The Boeing Company Clawback Policy (Exhibit 97 to the Company ’ s Form 1 0-K for the year ended December 31, 2023) 99.1 Commercial Program Method of Accounting (Exhibit (99)(i) to the Company’s Form 10-K for the year ended December 31, 1997) 101.SCH XBRL Taxonomy Extension Schema Document 101.CAL XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF XBRL Taxonomy Extension Definition Linkbase Document 101.LAB XBRL Taxonomy Extension Label Linkbase Document 101.PRE XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File - the cover page XBRL tags are embedded within the Inline XBRL document contained in Exhibit 101      † Certain schedules have been omitted pursuant to Item 601(a)(5) of Regulation S-K. The Company will provide a copy of omitted schedule to the SEC upon request. * Management contract or compensatory plan In accordance with Item 601(b)(4)(iii)(A) of Regulation S-K, copies of certain instruments defining the rights of holders of long-term debt of the Company are not filed herewith. Pursuant to this regulation, we hereby agree to furnish a copy of any such instrument to the SEC upon request. Item 16. Form 10-K Summary None. 136 Table of Contents Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Date: February 3, 2025 THE BOEING COMPANY (Registrant) By:   /s/ Michael J. Cleary   Michael J. Cleary – Senior Vice President and Controller 137 Table of Contents Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities indicated on February 3, 2025. /s/ Robert K. Ortberg /s/ Lynn J. Good Robert K. Ortberg – President and Chief Executive Officer and Director Lynn J. Good – Director (Principal Executive Officer) /s/ Brian J. West /s/ Stayce D. Harris Brian J. West – Executive Vice President and Chief Financial Officer Stayce D. Harris – Director (Principal Financial Officer) /s/ Michael J. Cleary /s/ Akhil Johri Michael J. Cleary – Senior Vice President and Controller Akhil Johri – Director (Principal Accounting Officer) /s/ Robert A. Bradway /s/ David L. Joyce Robert A. Bradway – Director David L. Joyce – Director /s/ Mortimer J. Buckley III /s/ Steven M. Mollenkopf Mortimer J. Buckley – Director Steven M. Mollenkopf – Chair of the Board /s/ Lynne M. Doughtie /s/ John M. Richardson Lynne M. Doughtie – Director John M. Richardson – Director /s/ David L. Gitlin /s/ Sabrina Soussan David L. Gitlin – Director Sabrina Soussan – Director 138\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 = 0.0369 (i.e., a 3.69% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0369 = 2.7132, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.036857, "expected_loss": 0.036857, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9044}} +{"id": "T3_all_20250730_0601", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["USMV"], "decision_date": "2025-07-30", "context_summary": "USMV: 60-day history, VaR(99%)=-0.0122, max drawdown threshold=10%.", "question": "Asset: USMV\nDaily returns (past 60 days): mean=0.0004, std=0.0064, worst_day=-0.0132\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent 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2025-03-31 0000012927 us-gaap:TreasuryStockCommonMember 2025-03-31 0000012927 us-gaap:RetainedEarningsMember 2025-03-31 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-03-31 0000012927 us-gaap:NoncontrollingInterestMember 2025-03-31 0000012927 2025-03-31 0000012927 us-gaap:RetainedEarningsMember 2025-04-01 2025-06-30 0000012927 us-gaap:NoncontrollingInterestMember 2025-04-01 2025-06-30 0000012927 us-gaap:AccumulatedOtherComprehensiveIncomeMember 2025-04-01 2025-06-30 0000012927 us-gaap:AdditionalPaidInCapitalMember 2025-04-01 2025-06-30 0000012927 us-gaap:TreasuryStockCommonMember 2025-04-01 2025-06-30 0000012927 us-gaap:OperatingSegmentsMember ba:CommercialAirplanesSegmentMember 2025-01-01 2025-06-30 0000012927 us-gaap:OperatingSegmentsMember ba:CommercialAirplanesSegmentMember 2024-01-01 2024-06-30 0000012927 us-gaap:OperatingSegmentsMember ba:CommercialAirplanesSegmentMember 2025-04-01 2025-06-30 0000012927 us-gaap:OperatingSegmentsMember ba:CommercialAirplanesSegmentMember 2024-04-01 2024-06-30 0000012927 us-gaap:OperatingSegmentsMem [...TRUNCATED...] m 4. Mine Safety Disclosures Not applicable. Item 5. Other Information During the three months ended June 30, 2025, none of our directors or officers adopted , modified or terminated a “Rule 10b5-1 trading arrangement” or a “non-Rule 10b5-1 trading arrangement” as such terms are defined under Item 408 of Regulation S-K. 57 Table of Contents Item 6. Exhibits 2.1 Membership Interest Purchase Agreement, dated as of April 22, 2025, among The Boeing Company, JNPR Aero, LLC and Project Maroon, LLC (Exhibit 2.1 to the Company’s Current Report on Form 8-K, dated April 22, 2025) 10.1 Non-Prosecution Agreement, dated May 29, 2025 (Exhibit 10.1 to the Company’s Current Report on Form 8-K, dated May 29, 2025) 10.2 Form of U.S. Notice of Terms of Cash-Based Award (Exhibit 10.1 to the Company's Current Report on Form 8-K, dated June 27, 2025)* 10.3 Form of U.S. Notice of Terms of Supplemental Restricted Stock Units (Exhibit 10.5 to the Company's Form 10-Q for the quarter ended March 31, 2025)* 10.4 Form of U.S. Notice of Terms of Supplemental Non-Qualified Premium-Priced Stock Options (Exhibit 10.3 to the Company's Current Report on Form 8-K, dated June 27, 2025)* 10.5 Letter Agreement with Jesus Malave* † 15 Letter from Independent Registered Public Accounting Firm regarding unaudited interim financial information 31.1 Certification of Chief Executive Officer pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.1 Certification of Chief Executive Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 32.2 Certification of Chief Financial Officer pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH Inline XBRL Taxonomy Extension Schema Document 101.CAL Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive Data File (formatted as inline XBRL and contained in Exhibit 101) * Management contract or compensatory plan † Certain portions of this exhibit have been redacted pursuant to Item 601(b)(10)(iv) of Regulation S-K. The Company agrees to furnish supplementally an unredacted copy of the exhibit to the SEC upon request. 58 Table of Contents Signature Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. THE BOEING COMPANY (Registrant) July 29, 2025 /s/ Michael J. Cleary (Date) Michael J. Cleary Senior Vice President and Controller 59\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to USMV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0122 (i.e., a 1.22% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0122 = 8.2127, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012176, "expected_loss": 0.012176, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9044}} +{"id": "T3_all_20250124_0604", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-01-24", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.1217, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0053, std=0.0617, worst_day=-0.1453\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8214", "answer_numeric": 0.8214, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1217 (i.e., a 12.17% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1217 = 0.8214, capped at 1.0.\nMaximum position size = 0.8214 (82.1% of portfolio).", "metadata": {"var_99": -0.121746, "expected_loss": 0.121746, "max_drawdown_threshold": 0.1, "position_size": 0.8214, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250702_0607", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM"], "decision_date": "2025-07-02", "context_summary": "IWM: 60-day history, VaR(99%)=-0.0371, max drawdown threshold=10%.", "question": "Asset: IWM\nDaily returns (past 60 days): mean=0.0018, std=0.0148, worst_day=-0.0371\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-07-01] [\"Peter Thiel sold 20 million shares of Facebook just months after its IPO\\u2014but they\\u2019d be worth nearly $15 billion more if he had held on Billionaire Peter Thiel was Facebook\\u2019s first outside investor, but he may now have regrets for how soon he cashed out. Just months after the tech company\\u2019s IPO, he sold millions of shares for $20 each for a sum of $400 million; with the stock now worth 37 times more, he could have been $15 billion richer today. Investing is a game of risk and reward. Get it right, and you could build a billion-dollar fortune. Get it wrong, and it might all go up in smoke. For PayPal cofounder Peter Thiel, being the first outside Facebook investor was hardly a bust\\u2014but there may be some seller\\u2019s remorse. The tech entrepreneur first coughed up $500,000 in 2004 for a 10% stake in the company, just months into its creation\\u2014giving it a value of about $4.9 million. Nearly a decade later, following the company\\u2019s May 2012 IPO, Thiel decided it was time to cash out. Thiel sold about 20.1 million shares in the company\\u2014a majority of his stake\\u2014for $19.27 to $20.69 each, netting him about $400 million at the time. Had he held his shares until today, they would be worth about $14.76 billion (Meta\\u2019s stock price is $736 at the time of writing), a decision that may haunt even one of Silicon Valley\\u2019s savviest investors. What led him to invest in the first place? He believed the college market\\u2014which was Facebook\\u2019s original audience\\u2014had been underestimated. \\u201cI think investors always have a bias to invest in things they themselves use and they undervalue things they don\\u2019t use so there aren\\u2019t many investors who are in college,\\u201d he said to This Week in Startups in 2015. Fortune reached out to Thiel for comment. Despite selling a majority of his stake in the company, the 57-year-old remained heavily involved for many years, serving on the board until 2022. \\u201cPeter has been a valuable member of our board and I\\u2019m deeply grateful for everything he has done for our company\\u2014from believing in us when few others would, to teaching me so many lessons about business, economics, and the world,\\u201d Facebook cofounder and CEO Mark Zuckerberg said at the time of Thiel\\u2019s stepping down. Today, Thiel\\u2019s net worth sits at about $21.7 billion, according to Bloomberg, thanks in part to the billions he made from being the cofounder of PayPal and Palantir. And he\\u2019s not the only investor to have thrived off the success of Facebook; the social network\\u2019s growth has created countless millionaires\\u2014and multiple billionaires. Of course, no one has benefited more financially than Zuckerberg, who is currently the second-richest person in the world, according to Bloomberg, with an estimated net worth of $260 billion. In fact, his worth has increased more than any other billionaire this year, with a year-to-date growth of $52.8 billion. But the compan\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_20250210_0610", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XHB"], "decision_date": "2025-02-10", "context_summary": "XHB: 60-day history, VaR(99%)=-0.0322, max drawdown threshold=10%.", "question": "Asset: XHB\nDaily returns (past 60 days): mean=-0.0019, std=0.0149, 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 = 0.0322 (i.e., a 3.22% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0322 = 3.1068, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.032187, "expected_loss": 0.032187, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251215_0613", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-12-15", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0926, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=-0.0060, std=0.0380, worst_day=-0.1157\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0926 (i.e., a 9.26% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0926 = 1.0803, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.092563, "expected_loss": 0.092563, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250811_0615", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLK"], "decision_date": "2025-08-11", "context_summary": "XLK: 60-day history, VaR(99%)=-0.0201, max drawdown threshold=10%.", "question": "Asset: XLK\nDaily returns (past 60 days): mean=0.0023, std=0.0089, worst_day=-0.0218\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-08-08] [\"Jamf\\u2019s (NASDAQ:JAMF) Q2 Sales Beat Estimates, Stock Soars Apple device management company, Jamf (NASDAQ:JAMF) reported revenue ahead of Wall Street\\u2019s expectations in Q2 CY2025, with sales up 15.3% year on year to $176.5 million. Guidance for next quarter\\u2019s revenue was better than expected at $177 million at the midpoint, 0.7% above analysts\\u2019 estimates. Its non-GAAP profit of $0.18 per share was in line with analysts\\u2019 consensus estimates. Is now the time to buy Jamf? Find out in our full research report. Revenue: $176.5 million vs analyst estimates of $168.6 million (15.3% year-on-year growth, 4.7% beat) Adjusted EPS: $0.18 vs analyst estimates of $0.18 (in line) Adjusted Operating Income: $33.49 million vs analyst estimates of $30.46 million (19% margin, 10% beat) The company lifted its revenue guidance for the full year to $702.5 million at the midpoint from $693 million, a 1.4% increase Operating Margin: -8.5%, up from -13% in the same quarter last year Free Cash Flow Margin: 20.9%, up from 0.6% in the previous quarter Billings: $176.5 million at quarter end, up 11.2% year on year Market Capitalization: $941.5 million Founded in 2002 by Zach Halmstad and Chip Pearson, right around the time when Apple began to dominate the personal computing market, Jamf (NASDAQ:JAMF) provides software for companies to manage Apple devices such as Macs, iPads, and iPhones. A company\\u2019s long-term sales performance is one signal of its overall quality. Any business can put up a good quarter or two, but the best consistently grow over the long haul. Over the last three years, Jamf grew its sales at a 16.3% compounded annual growth rate. Although this growth is acceptable on an absolute basis, it fell slightly short of our standards for the software sector, which enjoys a number of secular tailwinds. This quarter, Jamf reported year-on-year revenue growth of 15.3%, and its $176.5 million of revenue exceeded Wall Street\\u2019s estimates by 4.7%. Company management is currently guiding for a 11.1% year-on-year increase in sales next quarter. Looking further ahead, sell-side analysts expect revenue to grow 8.6% over the next 12 months, a deceleration versus the last three years. This projection is underwhelming and suggests its products and services will face some demand challenges. Here at StockStory, we certainly understand the potential of thematic investing. Diverse winners from Microsoft (MSFT) to Alphabet (GOOG), Coca-Cola (KO) to Monster Beverage (MNST) could all have been identified as promising growth stories with a megatrend driving the growth. So, in that spirit, we\\u2019ve identified a relatively under-the-radar profitable growth stock benefiting from the rise of AI, available to you FREE via this link. Billings is a non-GAAP metric that is often called \\u201ccash revenue\\u201d because it shows how much money the company has collected from customers in a certain period. This is different from revenue, which must be recognized \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 = 0.0201 (i.e., a 2.01% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0201 = 4.9666, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020135, "expected_loss": 0.020135, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250411_0618", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-04-11", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0736, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0027, std=0.0322, worst_day=-0.0868\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0736 (i.e., a 7.36% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0736 = 1.3582, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.073628, "expected_loss": 0.073628, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251029_0620", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD"], "decision_date": "2025-10-29", "context_summary": "ADA-USD: 60-day history, VaR(99%)=-0.1119, max drawdown threshold=10%.", "question": "Asset: ADA-USD\nDaily returns (past 60 days): mean=-0.0024, std=0.0398, worst_day=-0.1761\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8938", "answer_numeric": 0.8938, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1119 (i.e., a 11.19% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1119 = 0.8938, capped at 1.0.\nMaximum position size = 0.8938 (89.4% of portfolio).", "metadata": {"var_99": -0.111879, "expected_loss": 0.111879, "max_drawdown_threshold": 0.1, "position_size": 0.8938, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250501_0623", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["STIP"], "decision_date": "2025-05-01", "context_summary": "STIP: 60-day history, VaR(99%)=-0.0033, max drawdown threshold=10%.", "question": "Asset: STIP\nDaily returns (past 60 days): mean=0.0004, std=0.0015, worst_day=-0.0037\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to STIP, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0033 (i.e., a 0.33% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0033 = 29.8975, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.003345, "expected_loss": 0.003345, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250127_0626", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-01-27", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1214, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0141, std=0.0646, worst_day=-0.1493\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.8235", "answer_numeric": 0.8235, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1214 (i.e., a 12.14% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1214 = 0.8235, capped at 1.0.\nMaximum position size = 0.8235 (82.3% of portfolio).", "metadata": {"var_99": -0.121439, "expected_loss": 0.121439, "max_drawdown_threshold": 0.1, "position_size": 0.8235, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250508_0629", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF"], "decision_date": "2025-05-08", "context_summary": "XLF: 60-day history, VaR(99%)=-0.0372, max drawdown threshold=10%.", "question": "Asset: XLF\nDaily returns (past 60 days): mean=-0.0003, std=0.0149, worst_day=-0.0372\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[SEC 10-Q CAT 2025-05-07] cat-20250331 0000018230 FALSE 12/31 2025 Q1 50 http://fasb.org/us-gaap/2024#Revenues http://fasb.org/us-gaap/2024#Revenues xbrli:shares iso4217:USD iso4217:USD xbrli:shares xbrli:pure cat:group_president cat:segment 0000018230 2025-01-01 2025-03-31 0000018230 us-gaap:CommonStockMember 2025-01-01 2025-03-31 0000018230 cat:A5.3DebenturesDueSeptember152035Member 2025-01-01 2025-03-31 0000018230 2025-03-31 0000018230 cat:MachineryEnergyTransportationMember 2025-01-01 2025-03-31 0000018230 cat:MachineryEnergyTransportationMember 2024-01-01 2024-03-31 0000018230 cat:FinancialProductsMember 2025-01-01 2025-03-31 0000018230 cat:FinancialProductsMember 2024-01-01 2024-03-31 0000018230 2024-01-01 2024-03-31 0000018230 cat:AllOtherExcludingFinancialProductsMember 2025-01-01 2025-03-31 0000018230 cat:AllOtherExcludingFinancialProductsMember 2024-01-01 2024-03-31 0000018230 2024-12-31 0000018230 cat:FinancialProductsMember 2025-03-31 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0000018230 us-gaap:CommodityContractMember us-gaap:NondesignatedMember 2024-01-01 2024-03-31 0000018230 us-gaap [...TRUNCATED...] ately 50,000 shares of Caterpillar common stock were purchased by the EIP Plans pursuant to the terms of such plans. Item 5. Other Information During the three months ended March 31, 2025, none of the company’s directors or officers (as defined in Rule 16a-1(f) of the Securities Exchange Act of 1934) adopted , terminated or modified a Rule 10b5-1 trading arrangement or non-Rule 10b5-1 trading arrangement (as such terms are defined in Item 408 of Regulation S-K of the Securities Act of 1933). 67 Table of Contents Item 6. Exhibits 31.1 Certification of Chief Executive Officer of Caterpillar Inc., as required pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.2 Certification of Chief Financial Officer of Caterpillar Inc., as required pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32 Certification of Chief Executive Officer of Caterpillar Inc. and Chief Financial Officer of Caterpillar Inc., as required pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS Inline XBRL Instance Document (the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document) 101.SCH   Inline XBRL Taxonomy Extension Schema Document 101.CAL   Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF   Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB   Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE   Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 Cover Page Interactive File (embedded within the Inline XBRL document and included in Exhibit 101) The agreements and other documents filed as exhibits to this report are not intended to provide factual information or other disclosure other than with respect to the terms of the agreements or other documents themselves, and you should not rely on them for that purpose. In particular, any representations and warranties made by us in these agreements or other documents were made solely within the specific context of the relevant agreement or document and may not describe the actual state of affairs as of the date they were made or at any other time. 68 Table of Contents SIGNATURES   Pursuant to the requirements of the Securities Exchange Act of 1934, the Registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.       CATERPILLAR INC.               May 7, 2025 /s/ Joseph E. Creed Chief Executive Officer   Joseph E. Creed         May 7, 2025 /s/ Andrew R.J. Bonfield Chief Financial Officer   Andrew R.J. Bonfield               May 7, 2025 /s/ Derek Owens Chief Legal Officer and General Counsel   Derek Owens             May 7, 2025 /s/ William E. Schaupp Vice President and Chief Accounting Officer   William E. Schaupp   69\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XLF, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0372 (i.e., a 3.72% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0372 = 2.6872, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.037214, "expected_loss": 0.037214, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250428_0631", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ACWI"], "decision_date": "2025-04-28", "context_summary": "ACWI: 60-day history, VaR(99%)=-0.0309, max drawdown threshold=10%.", "question": "Asset: ACWI\nDaily returns (past 60 days): mean=-0.0010, std=0.0128, worst_day=-0.0309\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\nRecent 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goog:AmericasExcludingUnitedStatesMember 2025-01-01 2025-03-31 0001652044 goog:AmericasExcludingUnitedStates [...TRUNCATED...] 0;  Repurchases are being executed from time to time, subject to general business and market conditions and other investment opportunities, through open market purchases or privately negotiated transactions, including through Rule 10b5-1 plans. The repurchase program does not have an expiration date. For additional information related to share repurchases, see Note 11 of the Notes to Consolidated Financial Statements included in Part I, Item 1 of this Quarterly Report on Form 10-Q. (2)      Average price paid per share includes costs associated with the repurchases. ITEM 5. OTHER INFORMATION 10b5-1 Trading Plans During the quarter ended March 31, 2025, no Section 16 director or officer adopted , modified, or terminated a “Rule 10b5-1 trading arrangement” (as defined in Item 408 of Regulation S-K of the Exchange Act). There were no “non-Rule 10b5-1 trading arrangements” (as defined in Item 408 of Regulation S-K of the Exchange Act) adopted, modified, or terminated during the quarter ended March 31, 2025 by our directors and Section 16 officers. 47 ITEM 6. EXHIBITS Exhibit Number    Description Incorporated by reference herein Form Date 31.01 * Certification of Chief Executive Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 31.02 * Certification of Chief Financial Officer pursuant to Exchange Act Rules 13a-14(a) and 15d-14(a), as adopted pursuant to Section 302 of the Sarbanes-Oxley Act of 2002 32.01 ‡ Certifications of Chief Executive Officer and Chief Financial Officer pursuant to 18 U.S.C. Section 1350, as adopted pursuant to Section 906 of the Sarbanes-Oxley Act of 2002 101.INS * Inline XBRL Instance Document - the instance document does not appear in the Interactive Data File because its XBRL tags are embedded within the Inline XBRL document. 101.SCH * Inline XBRL Taxonomy Extension Schema Document 101.CAL * Inline XBRL Taxonomy Extension Calculation Linkbase Document 101.DEF * Inline XBRL Taxonomy Extension Definition Linkbase Document 101.LAB * Inline XBRL Taxonomy Extension Label Linkbase Document 101.PRE * Inline XBRL Taxonomy Extension Presentation Linkbase Document 104 * Cover Page Interactive Data File (formatted as Inline XBRL and contained in Exhibit 101) __________________________  * Filed herewith. ‡ Furnished herewith. 48 SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized. ALPHABET INC. April 24, 2025 By: /s/ ANAT ASHKENAZI Anat Ashkenazi Senior Vice President, Chief Financial Officer ALPHABET INC. April 24, 2025 By: /s/    AMIE THUENER O'TOOLE         Amie Thuener O'Toole Vice President, Corporate Controller and Principal Accounting Officer 49\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": 9047}} +{"id": "T3_all_20250828_0634", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["TLT"], "decision_date": "2025-08-28", "context_summary": "TLT: 60-day history, VaR(99%)=-0.0132, max drawdown threshold=10%.", "question": "Asset: TLT\nDaily returns (past 60 days): mean=0.0001, std=0.0067, worst_day=-0.0138\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to TLT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0132 (i.e., a 1.32% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0132 = 7.5970, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.013163, "expected_loss": 0.013163, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20251210_0637", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD"], "decision_date": "2025-12-10", "context_summary": "BTC-USD: 60-day history, VaR(99%)=-0.0530, max drawdown threshold=10%.", "question": "Asset: BTC-USD\nDaily returns (past 60 days): mean=-0.0031, std=0.0230, worst_day=-0.0532\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0530 (i.e., a 5.30% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0530 = 1.8876, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.052977, "expected_loss": 0.052977, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251002_0640", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-10-02", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.0654, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0016, std=0.0328, worst_day=-0.0681\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0654 (i.e., a 6.54% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0654 = 1.5302, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.065352, "expected_loss": 0.065352, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250526_0643", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["JNK"], "decision_date": "2025-05-26", "context_summary": "JNK: 60-day history, VaR(99%)=-0.0142, max drawdown threshold=10%.", "question": "Asset: JNK\nDaily returns (past 60 days): mean=-0.0002, std=0.0053, worst_day=-0.0142\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to JNK, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0142 (i.e., a 1.42% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0142 = 7.0283, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.014228, "expected_loss": 0.014228, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250731_0646", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD"], "decision_date": "2025-07-31", "context_summary": "LINK-USD: 60-day history, VaR(99%)=-0.0704, max drawdown threshold=10%.", "question": "Asset: LINK-USD\nDaily returns (past 60 days): mean=0.0046, std=0.0372, worst_day=-0.0752\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to LINK-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0704 (i.e., a 7.04% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0704 = 1.4211, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.070367, "expected_loss": 0.070367, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250515_0649", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD"], "decision_date": "2025-05-15", "context_summary": "MATIC-USD: 43-day history, VaR(99%)=-0.1350, max drawdown threshold=10%.", "question": "Asset: MATIC-USD\nDaily returns (past 43 days): mean=-0.0075, std=0.0432, worst_day=-0.1586\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.7405", "answer_numeric": 0.7405, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1350 (i.e., a 13.50% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1350 = 0.7405, capped at 1.0.\nMaximum position size = 0.7405 (74.1% of portfolio).", "metadata": {"var_99": -0.135036, "expected_loss": 0.135036, "max_drawdown_threshold": 0.1, "position_size": 0.7405, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250815_0652", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD"], "decision_date": "2025-08-15", "context_summary": "SOL-USD: 60-day history, VaR(99%)=-0.0649, max drawdown threshold=10%.", "question": "Asset: SOL-USD\nDaily returns (past 60 days): mean=0.0045, std=0.0368, worst_day=-0.0785\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SOL-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0649 (i.e., a 6.49% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0649 = 1.5415, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.064874, "expected_loss": 0.064874, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250905_0655", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLI"], "decision_date": "2025-09-05", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0129, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0008, std=0.0073, worst_day=-0.0150\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-04] [\"Should You Buy MP Materials Corp Stock Right Now? Shares of MP Materials are being carried higher on a wave of optimism. Yet, risks and uncertainties lie ahead for this rare-earth minerals producer. 10 stocks we like better than MP Materials \\u203a The narrative surrounding MP Materials (NYSE: MP) is wonderful right now. Following two transformative deals with the U.S. government and Apple, the rare-earth minerals company is receiving heavy investment and commitments to purchase materials and magnets (with pricing floor commitments running for a decade). At the same time, the company is expanding its existing magnet-producing facility in Texas while setting out to build a brand-new magnet production facility. So, is this a good time to buy the stock? The positive news is not lost on investors, and the stock is up an incredible 356% this year as of the time of writing. In a nutshell, investors are buying into the idea that MP Materials can solve the problem of sourcing rare earth materials and magnets domestically, thereby reducing dependence on China -- the country that has a practical monopoly on global rare earth magnets. That's the good news, but before you hit the buy button, consider that this could prove the apex of optimism over the stock. Execution risk remains around the manufacturing plant expansion and new construction projects. The company remains loss-making and may require additional capital, which would dilute the interests of existing shareholders. The involvement of the government in a public-private partnership introduces additional political risk, particularly since the U.S. government is likely to hold a significant amount of stock in MP Materials. In addition, it's incredibly difficult to predict where rare earth product prices will be over an extended period. The risks outlined above are significant, but it's also worth noting that there's an upside risk from other companies seeking to secure a domestic supply of rare earth materials and magnets. MP Materials certainly has a bright future, but investors might be overlooking several risks ahead, and the upside is too uncertain to predict accurately. On that basis, this is a stock most investors will want to avoid for now. Before you buy stock in MP Materials, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now\\u2026 and MP Materials wasn\\u2019t one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you\\u2019d have $654,759!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you\\u2019d have $1,046,799!* Now, it\\u2019s worth noting Stock Advisor\\u2019s total average return is 1,042% \\u2014 a market-crushing outperformance compared to 183% for the S&P 500. Don\\u2019t miss out\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 = 0.0129 (i.e., a 1.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0129 = 7.7352, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012928, "expected_loss": 0.012928, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250418_0658", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["BNO"], "decision_date": "2025-04-18", "context_summary": "BNO: 60-day history, VaR(99%)=-0.0566, max drawdown threshold=10%.", "question": "Asset: BNO\nDaily returns (past 60 days): mean=-0.0015, std=0.0193, worst_day=-0.0619\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bear\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 = 0.0566 (i.e., a 5.66% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0566 = 1.7676, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.056574, "expected_loss": 0.056574, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T3_all_20250904_0660", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD"], "decision_date": "2025-09-04", "context_summary": "DOT-USD: 60-day history, VaR(99%)=-0.0925, max drawdown threshold=10%.", "question": "Asset: DOT-USD\nDaily returns (past 60 days): mean=0.0031, std=0.0389, worst_day=-0.0949\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0925 (i.e., a 9.25% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0925 = 1.0809, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.092516, "expected_loss": 0.092516, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250703_0663", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD"], "decision_date": "2025-07-03", "context_summary": "AVAX-USD: 60-day history, VaR(99%)=-0.0808, max drawdown threshold=10%.", "question": "Asset: AVAX-USD\nDaily returns (past 60 days): mean=-0.0007, std=0.0461, worst_day=-0.0876\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0808 (i.e., a 8.08% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0808 = 1.2381, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.080772, "expected_loss": 0.080772, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250226_0667", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD"], "decision_date": "2025-02-26", "context_summary": "XRP-USD: 60-day history, VaR(99%)=-0.1099, max drawdown threshold=10%.", "question": "Asset: XRP-USD\nDaily returns (past 60 days): mean=0.0025, std=0.0495, worst_day=-0.1161\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "0.9099", "answer_numeric": 0.9099, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.1099 (i.e., a 10.99% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.1099 = 0.9099, capped at 1.0.\nMaximum position size = 0.9099 (91.0% of portfolio).", "metadata": {"var_99": -0.109904, "expected_loss": 0.109904, "max_drawdown_threshold": 0.1, "position_size": 0.9099, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250205_0670", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2025-02-05", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0218, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0001, std=0.0096, worst_day=-0.0287\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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have been omitted pursuant to Item 601(a)(5) of Regulation S-K. The Company will provide a copy of omitted schedule to the SEC upon request. * Management contract or compensatory plan In accordance with Item 601(b)(4)(iii)(A) of Regulation S-K, copies of certain instruments defining the rights of holders of long-term debt of the Company are not filed herewith. Pursuant to this regulation, we hereby agree to furnish a copy of any such instrument to the SEC upon request. Item 16. Form 10-K Summary None. 136 Table of Contents Signatures Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned, thereunto duly authorized. Date: February 3, 2025 THE BOEING COMPANY (Registrant) By:   /s/ Michael J. Cleary   Michael J. Cleary – Senior Vice President and Controller 137 Table of Contents Pursuant to the requirements of the Securities Exchange Act of 1934, this report has been signed below by the following persons on behalf of the registrant and in the capacities indicated on February 3, 2025. /s/ Robert K. Ortberg /s/ Lynn J. Good Robert K. Ortberg – President and Chief Executive Officer and Director Lynn J. Good – Director (Principal Executive Officer) /s/ Brian J. West /s/ Stayce D. Harris Brian J. West – Executive Vice President and Chief Financial Officer Stayce D. Harris – Director (Principal Financial Officer) /s/ Michael J. Cleary /s/ Akhil Johri Michael J. Cleary – Senior Vice President and Controller Akhil Johri – Director (Principal Accounting Officer) /s/ Robert A. Bradway /s/ David L. Joyce Robert A. Bradway – Director David L. Joyce – Director /s/ Mortimer J. Buckley III /s/ Steven M. Mollenkopf Mortimer J. Buckley – Director Steven M. Mollenkopf – Chair of the Board /s/ Lynne M. Doughtie /s/ John M. Richardson Lynne M. Doughtie – Director John M. Richardson – Director /s/ David L. Gitlin /s/ Sabrina Soussan David L. Gitlin – Director Sabrina Soussan – Director 138\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 = 0.0218 (i.e., a 2.18% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0218 = 4.5899, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021787, "expected_loss": 0.021787, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9044}} +{"id": "T3_all_20250103_0673", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-03", "context_summary": "SPY: 60-day history, VaR(99%)=-0.0229, max drawdown threshold=10%.", "question": "Asset: SPY\nDaily returns (past 60 days): mean=0.0005, std=0.0076, worst_day=-0.0274\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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us-gaap:AccumulatedOtherComprehensiveIncomeMember 2023-08-01 2023-10-31 0000104169 us-gaap:Com [...TRUNCATED...] assumptions not being realized or other factors, the actual results relating to the subject matter of any forward-looking statement in this Quarterly Report on Form 10-Q may differ materially from the anticipated results expressed or implied in that forward-looking statement. The forward-looking statements included in this Quarterly Report on Form 10-Q are made only as of the date of this report, and Walmart undertakes no obligation to update any such statements to reflect subsequent events or circumstances. 35 Table of Contents Item 6. Exhibits The following documents are filed as an exhibit to this Quarterly Report on Form 10-Q: Exhibit 3.1(a) Restated Certificate of Incorporation of the Company dated February 1, 2018 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 1, 2018 Exhibit 3.1(b) Certificate of Amendment to the Restated Certificate of Incorporation of the Company, effective February 23, 2024 is incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on February 23, 2024 Exhibit 3.2 Amended and Restated Bylaws of the Company dated November 10, 2022 are incorporated herein by reference to Exhibit 3.1 to the Report on Form 8-K filed by the Company on November 16, 2022 Exhibit 31.1* Chief Executive Officer Section 302 Certification Exhibit 31.2* Chief Financial Officer Section 302 Certification Exhibit 32.1** Chief Executive Officer Section 906 Certification Exhibit 32.2** Chief Financial Officer Section 906 Certification Exhibit 99.1* Opioids-Related Litigation Case Citations and Currently Scheduled Trial Dates Exhibit 101.INS* Inline XBRL Instance Document Exhibit 101.SCH* Inline XBRL Taxonomy Extension Schema Document Exhibit 101.CAL* Inline XBRL Taxonomy Extension Calculation Linkbase Document Exhibit 101.DEF* Inline XBRL Taxonomy Extension Definition Linkbase Document Exhibit 101.LAB* Inline XBRL Taxonomy Extension Label Linkbase Document Exhibit 101.PRE* Inline XBRL Taxonomy Extension Presentation Linkbase Document Exhibit 104 The cover page from the Company's Quarterly Report on Form 10-Q for the quarter ended October 31, 2024, formatted in Inline XBRL (included in Exhibit 101) * Filed herewith as an Exhibit. ** Furnished herewith as an Exhibit. 36 Table of Contents SIGNATURES Pursuant to the requirements of the Securities Exchange Act of 1934, the registrant has duly caused this report to be signed on its behalf by the undersigned thereunto duly authorized.   WALMART INC. Date: December 6, 2024 By: /s/ C. Douglas McMillon C. Douglas McMillon President and Chief Executive Officer (Principal Executive Officer) Date: December 6, 2024 By: /s/ John David Rainey John David Rainey Executive Vice President and Chief Financial Officer (Principal Financial Officer) Date: December 6, 2024 By: /s/ David M. Chojnowski David M. Chojnowski Senior Vice President and Controller (Principal Accounting Officer) 37\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to SPY, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0229 (i.e., a 2.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0229 = 4.3640, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.022915, "expected_loss": 0.022915, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9045}} +{"id": "T3_all_20250211_0677", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI"], "decision_date": "2025-02-11", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0218, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=-0.0005, std=0.0087, worst_day=-0.0287\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: 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us-gaap:EquityMethodInvestmentNonconsolidatedInvesteeOrGroupOfInvesteesMember 2024-12-31 0001018724 us-gaap:EquityMethodInvestmentNonconsoli [...TRUNCATED...] Amazon.com, Inc., pursuant to 18 U.S.C. Section 1350. 97.1 Amazon.com, Inc. Clawback Policy (incorporated by reference to the Company's Annual Report on Form 10-K for the Year ended December 31, 2023). 101 The following financial statements from the Company’s Annual Report on Form 10-K for the year ended December 31, 2024, formatted in Inline XBRL: (i) Consolidated Statements of Cash Flows, (ii) Consolidated Statements of Operations, (iii) Consolidated Statements of Comprehensive Income (Loss), (iv) Consolidated Balance Sheets, (v) Consolidated Statements of Stockholders’ Equity, and (vi) Notes to Consolidated Financial Statements, tagged as blocks of text and including detailed tags. As permitted by Item 601(b)(4)(iii)(A) of Regulation S-K, the Company has not filed with this Annual Report on Form 10-K certain instruments defining the rights of holders of long-term debt of the Company and its subsidiaries because the total amount of securities authorized thereunder does not exceed 10 percent of the total assets of the Company and its subsidiaries on a consolidated basis. The Company agrees to furnish a copy of such agreements to the Commission upon request. 104 The cover page from the Company’s Annual Report on Form 10-K for the year ended December 31, 2024, formatted in Inline XBRL (included as Exhibit 101). __________________ †    Executive Compensation Plan or Agreement. Item 16. Form 10-K Summary None. 76 Table of Contents SIGNATURES Pursuant to the requirements of Section 13 or 15(d) of the Securities Exchange Act of 1934, the registrant has duly caused this Report to be signed on its behalf by the undersigned, thereunto duly authorized, as of February 6, 2025.   AMAZON.COM, INC. By: /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer Pursuant to the requirements of the Securities Exchange Act of 1934, this Report has been signed below by the following persons on behalf of the registrant and in the capacities indicated as of February 6, 2025.   Signature Title /s/ Andrew R. Jassy Andrew R. Jassy President and Chief Executive Officer (Principal Executive Officer) and Director /s/ Brian T. Olsavsky Brian T. Olsavsky Senior Vice President and Chief Financial Officer (Principal Financial Officer) /s/ Shelley L. Reynolds Shelley L. Reynolds Vice President, Worldwide Controller (Principal Accounting Officer) /s/ Jeffrey P. Bezos Jeffrey P. Bezos Executive Chair /s/ Keith B. Alexander Keith B. Alexander Director /s/ Edith W. Cooper Edith W. Cooper Director /s/ Jamie S. Gorelick Jamie S. Gorelick Director /s/ Daniel P. Huttenlocher Daniel P. Huttenlocher Director /s/ Andrew Y. Ng Andrew Y. Ng Director /s/ Indra K. Nooyi Indra K. Nooyi Director /s/ Jonathan J. Rubinstein Jonathan J. Rubinstein Director /s/ Brad D. Smith Brad D. Smith Director /s/ Patricia Q. Stonesifer Patricia Q. Stonesifer Director /s/ Wendell P. Weeks Wendell P. Weeks Director 77\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 = 0.0218 (i.e., a 2.18% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0218 = 4.5899, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.021787, "expected_loss": 0.021787, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 9046}} +{"id": "T3_all_20250321_0680", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA"], "decision_date": "2025-03-21", "context_summary": "EFA: 60-day history, VaR(99%)=-0.0188, max drawdown threshold=10%.", "question": "Asset: EFA\nDaily returns (past 60 days): mean=0.0019, std=0.0087, worst_day=-0.0239\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-03-20] Asset Management & Auction Services Stocks Q4 Highlights: OPENLANE (NYSE:KAR) As the Q4 earnings season wraps, let\u2019s dig into this quarter\u2019s best and worst performers in the asset management & auction services industry, including OPENLANE (NYSE:KAR) and its peers. Like in other industries, the shift to online platforms can lower transaction costs and improve liquidity for sellers. Increasing digitization, AI-driven pricing analytics, and automation in logistics can enhance efficiency for operators who invest in technology and software. On the other hand, challenges include potential regulatory scrutiny on auction transparency, data privacy concerns with AI-driven valuation models, and shifting environmental policies that could impact the resale market for internal combustion vehicles. Additionally, supply chain volatility in new car production may create unpredictable swings in used vehicle supply, impacting auction volumes. The 4 asset management & auction services stocks we track reported an exceptional Q4. As a group, revenues beat analysts\u2019 consensus estimates by 9.1%. While some asset management & auction services stocks have fared somewhat better than others, they have collectively declined. On average, share prices are down 1.4% since the latest earnings results. Facilitating the sale of approximately 1.3 million used vehicles in 2023, OPENLANE (NYSE:KAR) operates digital marketplaces that connect sellers and buyers of used vehicles across North America and Europe, facilitating wholesale transactions. OPENLANE reported revenues of $455 million, up 12% year on year. This print exceeded analysts\u2019 expectations by 8.2%. Overall, it was a satisfactory quarter for the company with a decent beat of analysts\u2019 EPS estimates but a slight miss of analysts\u2019 full-year EPS guidance estimates. The stock is up 6% since reporting and currently trades at $21.25. Is now the time to buy OPENLANE? Access our full analysis of the earnings results here, it\u2019s free. Powering what it calls the \"circular economy\" with over 5.5 million registered buyers across its platforms, Liquidity Services (NASDAQ:LQDT) operates online marketplaces that connect buyers and sellers of surplus assets, from consumer returns to industrial equipment to government property. Liquidity Services reported revenues of $122.3 million, up 71.5% year on year, outperforming analysts\u2019 expectations by 16.1%. The business had an incredible quarter with an impressive beat of analysts\u2019 EPS estimates. Liquidity Services scored the biggest analyst estimates beat and fastest revenue growth among its peers. Although it had a fine quarter compared its peers, the market seems unhappy with the results as the stock is down 7% since reporting. It currently trades at $30.47. Is now the time to buy Liquidity Services? Access our full analysis of the earnings results here, it\u2019s free. Starting as a single salvage yard in California in 1982, Copart (NASDAQ:CPRT) operates an online auction platform that connects se\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 = 0.0188 (i.e., a 1.88% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0188 = 5.3113, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.018828, "expected_loss": 0.018828, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250110_0683", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-01-10", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0605, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=0.0019, std=0.0320, worst_day=-0.0718\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0605 (i.e., a 6.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0605 = 1.6520, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.060534, "expected_loss": 0.060534, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20250728_0686", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ"], "decision_date": "2025-07-28", "context_summary": "EWJ: 60-day history, VaR(99%)=-0.0205, max drawdown threshold=10%.", "question": "Asset: EWJ\nDaily returns (past 60 days): mean=0.0006, std=0.0100, worst_day=-0.0241\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-07-25] [\"Warren Buffett's Favorite Stock Is Up Over 4,470,000% Since 1965, but You Won't Find It in His Portfolio Warren Buffett's simple investment strategy has propelled Berkshire Hathaway to market-beating returns since 1965. Buffett has invested in over 100 different companies, including giants like Apple, Coca-Cola, GEICO Insurance, and American Express. But Buffett has plowed more money into one particular company than any other, and investors won't find it listed in Berkshire's portfolio. 10 stocks we like better than Berkshire Hathaway \\u203a In 1965, Warren Buffett took a controlling stake in a struggling textiles company called Berkshire Hathaway (NYSE: BRK.A)(NYSE: BRK.B). After realizing its operations were no longer viable, he converted it into a holding company for his various investments. Berkshire now manages numerous wholly owned subsidiaries and a $292 billion portfolio of publicly traded stocks and securities. Despite owning a stake in more than a hundred different companies during the past 60 years, Buffett has never expressly named a favorite. But if we follow the money, it's clear he likes some much more than others. For example, he bought about $38 billion worth of Apple (NASDAQ: AAPL) stock on Berkshire's behalf between 2016 and 2023, which is the most he has ever invested in a single company. With that said, Buffett has spent more than twice that much buying shares in another name that has soared by more than 4,470,000% since 1965 -- except you won't find it in Berkshire's portfolio. Buffett likes to invest in companies with steady growth, reliable profits, and strong management teams. He especially likes those with shareholder-friendly initiatives like dividend plans and stock buyback programs, because they compound his money significantly faster. But his most important weapon is time -- when he buys a stake in a company, his preferred holding period is forever. Berkshire's Coca-Cola (NYSE: KO) investment is a great example of Buffett's strategy in action. He bought 400 million shares of the soft-drink giant between 1988 and 1994, for a total cost of $1.3 billion. He has never sold a single share, and today that position is worth a whopping $27.8 billion. Plus, it paid Berkshire $776 million in dividends in 2024, so the conglomerate now recoups its original investment every two years or so. Apple is another company that ticks all of Buffett's boxes, and it has netted Berkshire an enormous profit to date. Heading into 2024, Berkshire's $38 billion investment was worth more than $170 billion and accounted for half of the value of the conglomerate's entire portfolio of stocks and securities. Buffett and his team have since sold two-thirds of Berkshire's Apple stake to cash in some of those gains and to reduce risk. Kraft Heinz, Visa, Bank of America, and American Express are just a few of Berkshire's other long-term holdings that continue to match Buffett's criteria. While Buffett's $38 billion Apple investment remains his biggest\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 = 0.0205 (i.e., a 2.05% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0205 = 4.8673, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.020545, "expected_loss": 0.020545, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250611_0689", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE"], "decision_date": "2025-06-11", "context_summary": "VLUE: 60-day history, VaR(99%)=-0.0356, max drawdown threshold=10%.", "question": "Asset: VLUE\nDaily returns (past 60 days): mean=0.0007, std=0.0135, worst_day=-0.0356\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-06-10] [\"Heard on the Street: Warner Discovery Splitting Up What happened in markets yesterday: Export controls were at the top of the trade agenda. As U.S. and Chinese delegates met in London, American negotiators were expected to press Xi Jinping\\u2019s representatives to speed up exports of rare-earth minerals and magnets.\", \"Sector Update: Tech Stocks Higher Late Afternoon Tech stocks were higher late Monday afternoon, with the Technology Select Sector SPDR Fund (XLK) up\", \"Citi adds Qorvo and Skyworks Solutions to 90-day upside catalyst watch Investing.com -- Citi analysts have placed Qorvo (NASDAQ:QRVO) and Skyworks Solutions (NASDAQ:SWKS), Inc. on an \\\"upside 90-day catalyst watch,\\\" anticipating better-than-expected June and September quarter results for the Apple (NASDAQ:AAPL) suppliers. This outlook is primarily driven by \\\"pulled forward Apple demand due to tariffs.\\\" According to Citi\\u2019s China Technology analyst, data points from Asia suggest that the Apple supply chain could see improved performance. Furthermore, the \\\"Asia supply chain currently expects 80-95M or stable Y/Y growth for iPhone 17 build.\\\" Citi highlights that \\\"Apple supply chain stocks historically outperform AAPL stock from WWDC through iPhone launch event in September.\\\" Given these factors, Citi sees \\\"upside risk to Jun/Sep-Q results on pulled forward Apple demand due to tariffs\\\" for both companies, with earnings serving as the primary catalyst within the next 90 days. Apple accounts for a significant portion of both companies\\u2019 total sales, contributing approximately 66% to Skyworks Solutions\\u2019 last reported quarter total sales, and about 47% to Qorvo\\u2019s fiscal year 2025 total sales. Despite the short-term positive outlook, Citi maintains its \\\"long-term concerns around increasing RF semis competition and concentration risk\\\" for these suppliers. However, the immediate prospect of tariff-driven demand acceleration positions both Qorvo and Skyworks Solutions for potential upside in the near term. Related articles Citi adds Qorvo and Skyworks Solutions to 90-day upside catalyst watch Musk\\u2019s public clash with Trump likely calculated, says Morgan Stanley Mizuho upgrades Macerich as its sees risk-reward favorable\", \"Apple Fails to Clear a Low Bar on AI A program to allow developers to access its \\u201cfoundation models\\u201d was widely expected and could\\u2014over time\\u2014result in AI apps that work more easily on Apple\\u2019s devices. Apple\\u2019s share price, down 19% already this year, slipped further on Monday following the keynote. Apple no doubt wanted to avoid the trap it fell into last year, when it introduced its Apple Intelligence service to great hype only to have its later launch and subsequent updates fall short of promises.\", \"AMD price target lift, Apple's WWDC, Chewy downgrade Market Domination co-host Josh Lipton tracks today's top moving stocks and biggest market stories in this Market Minute. Advanced Micro Devices (AMD) stock gain\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_20250930_0692", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLI"], "decision_date": "2025-09-30", "context_summary": "XLI: 60-day history, VaR(99%)=-0.0129, max drawdown threshold=10%.", "question": "Asset: XLI\nDaily returns (past 60 days): mean=0.0005, std=0.0070, worst_day=-0.0150\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\nRecent filing/news:\n[Kaggle 2025-09-05] [\"Trump Warns of \\u2018Fairly Substantial\\u2019 Tariff on Semiconductors. What It Means for Chip Stocks. President Donald Trump said a tariff on imports of chips is coming \\u201cvery shortly\\u201d for companies that aren\\u2019t shifting production to the U.S.\", \"Inside eBay\\u2019s Quest to Become an AI Leader How the 30-year-old e-commerce giant is going all-in on artificial intelligence, hoping the technology can help it update its image and beat mounting competition.\", \"Trump Basks in Tech Leaders\\u2019 Spending Vows at White House Dinner (Bloomberg) \\u2014 Meta Platforms Inc.\\u2019s (META) Mark Zuckerberg and Apple Inc.\\u2019s (AAPL) Tim Cook joined tech industry leaders in touting their pledges to boost spending in the US on artificial intelligence during a dinner hosted by President Donald Trump that highlighted his deepening relationship with Silicon Valley. Most Read from Bloomberg One of World\\u2019s Most Liveable Cities Ends Euro-a-Day Travel Pass Chicago\\u2019s Citadel Center for Sale 3 Years After Miami Move Philadelphia Transit Cuts Portend \\u2018Mayhem\\u2019 for Commutes and Regional Economy One-Way Streets Are the Wrong Way to Tame Downtown Traffic Self-Driving Cars Take a Turn Toward the Villainous, in Movies and Real Life In his opening remarks, Trump addressed a key concern of tech companies: ensuring there\\u2019s enough energy to meet surging power demands from the data centers behind the AI boom. \\u201cWe\\u2019re making it very easy for you in terms of electric capacity and getting it for you, getting your permits,\\u201d Trump said in the White House State Dining Room. \\u201cWe\\u2019re leading China by a lot, by a really, by a great amount.\\u201d Thursday\\u2019s dinner marked a rare gathering in Washington of top executives and founders from some of the world\\u2019s most valuable tech companies \\u2014 all vying for an edge in the emerging field of AI. Attendees also included OpenAI Inc.\\u2019s (OPAI.PVT) Sam Altman, Alphabet Inc.\\u2019s (GOOG, GOOGL) Sundar Pichai and co-founder Sergey Brin, and Microsoft Corp.\\u2019s (MSFT) Satya Nadella and Bill Gates. The president went around the table asking executives to talk about their plans. Corporate leaders took turns highlighting their efforts to expand in the US, with each expressing gratitude for administration policies they see as bolstering efforts to advance AI. Trump asked Zuckerberg to speak first. \\u201cAll of the companies here are building, just making huge investments in the country in order to build out data centers and infrastructure to power the next wave of innovation,\\u201d the Meta CEO told Trump. Pressed by the president on how much his company was investing, Zuckerberg said \\u201cat least $600 billion\\u201d through 2028. \\u201cThat\\u2019s a lot,\\u201d Trump said. In recent days, the president has touted a massive data center Meta is building in Louisiana that will cost $50 billion. Trump has drawn tech executives into his orbit with an agenda aimed at lowering tax\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 = 0.0129 (i.e., a 1.29% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0129 = 7.7352, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.012928, "expected_loss": 0.012928, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 3020}} +{"id": "T3_all_20250507_0695", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM"], "decision_date": "2025-05-07", "context_summary": "MTUM: 60-day history, VaR(99%)=-0.0383, max drawdown threshold=10%.", "question": "Asset: MTUM\nDaily returns (past 60 days): mean=-0.0010, std=0.0180, worst_day=-0.0383\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2025-05-06] [\"ADP Announces Pricing of its Senior Notes Due 2032 ROSELAND, N.J., May 6, 2025 /PRNewswire/ -- ADP (Nasdaq: ADP), a leading global technology company providing comprehensive cloud-based human capital management (HCM) solutions, yesterday announced the pricing of a public offering of $1.0 billion aggregate principal amount of its 4.750% senior notes due 2032. ADP expects to receive the net offering proceeds upon closing on or about May 8, 2025. The intended use of proceeds from the offering is to refinance existing debt, and any remainder for general corporate purposes. ADP has filed a registration statement (including a prospectus and preliminary prospectus supplement) with the Securities and Exchange Commission (\\\"SEC\\\") for the offering to which this communication relates. Before you invest, you should read the base prospectus in that registration statement, the applicable preliminary prospectus supplement and the other documents ADP has filed with the SEC for more complete information about ADP and this offering. You may get these documents for free by visiting EDGAR on the SEC website at www.sec.gov. Alternatively, ADP, any underwriter or any dealer participating in the offering will arrange to send investors the prospectus and preliminary prospectus supplement upon request by contacting BofA Securities, Inc. by telephone at 1-800-294-1322 or by email at dg.prospectus_requests@bofa.com, J.P. Morgan Securities LLC by telephone (collect) at (212) 834-4533 or Morgan Stanley & Co. LLC by telephone at (866) 718-1649. This press release does not constitute an offer to sell or a solicitation of an offer to buy the debt securities or any other securities, nor shall there be any sale of these securities in any jurisdiction in which such an offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of any such jurisdiction. The offering of these securities may be made only by means of the prospectus supplement and the accompanying prospectus. This press release also does not constitute an offer to purchase, a solicitation of an offer to sell, or notice of redemption with respect to any securities of ADP. About ADP (NASDAQ \\u2013 ADP)Designing better ways to work through cutting-edge products, premium services and exceptional experiences that enable people to reach their full potential. HR, Talent, Time Management, Benefits and Payroll. Informed by data and designed for people. Forward-Looking Statements This document and other written or oral statements made from time to time by ADP may contain \\\"forward-looking statements\\\" within the meaning of the Private Securities Litigation Reform Act of 1995. Statements that are not historical in nature and which may be identified by the use of words like \\\"outlook,\\\" \\\"expects,\\\" \\\"assumes,\\\" \\\"projects,\\\" \\\"anticipates,\\\" \\\"estimates,\\\" \\\"we believe,\\\" \\\"could,\\\" \\\"is designed to\\\" and other words of similar meaning, are forward-looking statements. These st\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_20250325_0697", "template": "T3", "complexity": 1, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD"], "decision_date": "2025-03-25", "context_summary": "BNB-USD: 60-day history, VaR(99%)=-0.0733, max drawdown threshold=10%.", "question": "Asset: BNB-USD\nDaily returns (past 60 days): mean=-0.0008, std=0.0320, worst_day=-0.0767\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: sideways\nRecent filing/news:\n[Kaggle 2023-12-19] \n\nDetermine the maximum fraction of total portfolio capital that should be allocated to BNB-USD, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0733 (i.e., a 7.33% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0733 = 1.3641, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.073307, "expected_loss": 0.073307, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": true, "text_chars": 20}} +{"id": "T3_all_20251021_0700", "template": "T3", "complexity": 1, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["PALL"], "decision_date": "2025-10-21", "context_summary": "PALL: 60-day history, VaR(99%)=-0.0567, max drawdown threshold=10%.", "question": "Asset: PALL\nDaily returns (past 60 days): mean=0.0040, std=0.0240, worst_day=-0.0619\nMaximum acceptable portfolio drawdown: 10%\nMarket regime: bull\n\nDetermine the maximum fraction of total portfolio capital that should be allocated to PALL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g., 0.25 = 25%; maximum is 1.00 = 100% of portfolio).", "answer": "1.0000", "answer_numeric": 1.0, "explanation": "Step 1: Compute |VaR(99%)| from historical returns = 0.0567 (i.e., a 5.67% loss in the worst 1% of days).\nStep 2: Fixed-fractional formula: f* = 10% / 0.0567 = 1.7622, capped at 1.0.\nMaximum position size = 1.0000 (100.0% of portfolio).", "metadata": {"var_99": -0.056748, "expected_loss": 0.056748, "max_drawdown_threshold": 0.1, "position_size": 1.0, "has_text": false, "text_chars": 0}} +{"id": "T4_all_20251027_0003", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD", "HAUZ"], "decision_date": "2025-10-27", "context_summary": "DOT-USD \u03c3=0.0410, HAUZ \u03c3=0.0068, \u03c1=-0.040. Min-variance weights: DOT-USD=0.033, HAUZ=0.967.", "question": "Assets: DOT-USD, HAUZ\nDOT-USD: annualized_mean_return=-0.1260, daily_std=0.0410\nHAUZ: annualized_mean_return=0.2772, daily_std=0.0068\nMinimum required portfolio return (annualized): 0.0660\nMarket regime: bull\n\nCompute portfolio weights (w_DOT-USD, w_HAUZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_HAUZ=X.XXXX", "answer": "w_DOT-USD=0.0329, w_HAUZ=0.9671", "answer_numeric": 0.0329, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000047 - -0.000011) / (0.001685 + 0.000047 - -0.000022)\n Unconstrained: w_DOT-USD=0.0331\n After long-only clamp: w_DOT-USD=0.0331, w_HAUZ=0.9669.", "metadata": {"weights": {"DOT-USD": 0.0329, "HAUZ": 0.9671}, "sigma_1": 0.041048, "sigma_2": 0.006838, "covariance": -1.1e-05, "correlation": -0.04, "has_text": true, "text_chars": 20, "mu_floor": 0.066, "constraint_binding": false}} +{"id": "T4_all_20251209_0006", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BTC-USD"], "decision_date": "2025-12-09", "context_summary": "EEM \u03c3=0.0094, BTC-USD \u03c3=0.0241, \u03c1=-0.132. Min-variance weights: EEM=0.838, BTC-USD=0.162.", "question": "Assets: EEM, BTC-USD\nEEM: annualized_mean_return=0.2016, daily_std=0.0094\nBTC-USD: annualized_mean_return=-1.1592, daily_std=0.0241\nMinimum required portfolio return (annualized): 0.0916\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_BTC-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_BTC-USD=X.XXXX", "answer": "w_EEM=0.9192, w_BTC-USD=0.0808", "answer_numeric": 0.9192, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000579 - -0.000030) / (0.000088 + 0.000579 - -0.000060)\n Unconstrained: w_EEM=0.8381\n After long-only clamp: w_EEM=0.8381, w_BTC-USD=0.1619.", "metadata": {"weights": {"EEM": 0.9192, "BTC-USD": 0.0808}, "sigma_1": 0.009367, "sigma_2": 0.024063, "covariance": -3e-05, "correlation": -0.1325, "has_text": true, "text_chars": 9045, "mu_floor": 0.0916, "constraint_binding": true}} +{"id": "T4_all_20250716_0008", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD", "SGOV"], "decision_date": "2025-07-16", "context_summary": "LINK-USD \u03c3=0.0359, SGOV \u03c3=0.0001, \u03c1=-0.120. Min-variance weights: LINK-USD=0.001, SGOV=1.000.", "question": "Assets: LINK-USD, SGOV\nLINK-USD: annualized_mean_return=0.2520, daily_std=0.0359\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0969\nMarket regime: bull\n\nCompute portfolio weights (w_LINK-USD, w_SGOV) 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_SGOV=X.XXXX", "answer": "w_LINK-USD=0.2307, w_SGOV=0.7693", "answer_numeric": 0.2307, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.001291 + 0.000000 - -0.000001)\n Unconstrained: w_LINK-USD=0.0005\n After long-only clamp: w_LINK-USD=0.0005, w_SGOV=0.9995.", "metadata": {"weights": {"LINK-USD": 0.2307, "SGOV": 0.7693}, "sigma_1": 0.035929, "sigma_2": 0.00015, "covariance": -1e-06, "correlation": -0.1196, "has_text": true, "text_chars": 20, "mu_floor": 0.0969, "constraint_binding": true}} +{"id": "T4_all_20250424_0011", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["AVAX-USD", "IYR"], "decision_date": "2025-04-24", "context_summary": "AVAX-USD \u03c3=0.0603, IYR \u03c3=0.0134, \u03c1=-0.018. Min-variance weights: AVAX-USD=0.051, IYR=0.949.", "question": "Assets: AVAX-USD, IYR\nAVAX-USD: annualized_mean_return=-0.1512, daily_std=0.0603\nIYR: annualized_mean_return=-0.2016, daily_std=0.0134\nMinimum required portfolio return (annualized): -0.1997\nMarket regime: bear\n\nCompute portfolio weights (w_AVAX-USD, w_IYR) 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_IYR=X.XXXX", "answer": "w_AVAX-USD=0.0509, w_IYR=0.9491", "answer_numeric": 0.0509, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000181 - -0.000015) / (0.003640 + 0.000181 - -0.000029)\n Unconstrained: w_AVAX-USD=0.0508\n After long-only clamp: w_AVAX-USD=0.0508, w_IYR=0.9492.", "metadata": {"weights": {"AVAX-USD": 0.0509, "IYR": 0.9491}, "sigma_1": 0.060329, "sigma_2": 0.013448, "covariance": -1.5e-05, "correlation": -0.0179, "has_text": true, "text_chars": 20, "mu_floor": -0.1997, "constraint_binding": false}} +{"id": "T4_all_20250711_0014", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "STIP"], "decision_date": "2025-07-11", "context_summary": "XLRE \u03c3=0.0092, STIP \u03c3=0.0012, \u03c1=-0.067. Min-variance weights: XLRE=0.025, STIP=0.976.", "question": "Assets: XLRE, STIP\nXLRE: annualized_mean_return=0.3276, daily_std=0.0092\nSTIP: annualized_mean_return=0.0504, daily_std=0.0012\nMinimum required portfolio return (annualized): 0.2285\nMarket regime: sideways\n\nCompute portfolio weights (w_XLRE, w_STIP) 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_STIP=X.XXXX", "answer": "w_XLRE=0.6425, w_STIP=0.3575", "answer_numeric": 0.6425, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - -0.000001) / (0.000085 + 0.000001 - -0.000001)\n Unconstrained: w_XLRE=0.0245\n After long-only clamp: w_XLRE=0.0245, w_STIP=0.9755.", "metadata": {"weights": {"XLRE": 0.6425, "STIP": 0.3575}, "sigma_1": 0.009209, "sigma_2": 0.001188, "covariance": -1e-06, "correlation": -0.067, "has_text": true, "text_chars": 3020, "mu_floor": 0.2285, "constraint_binding": true}} +{"id": "T4_all_20250421_0017", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VTI", "SOYB"], "decision_date": "2025-04-21", "context_summary": "VTI \u03c3=0.0130, SOYB \u03c3=0.0097, \u03c1=0.337. Min-variance weights: VTI=0.291, SOYB=0.709.", "question": "Assets: VTI, SOYB\nVTI: annualized_mean_return=-0.6804, daily_std=0.0130\nSOYB: annualized_mean_return=-0.1008, daily_std=0.0097\nMinimum required portfolio return (annualized): -0.4758\nMarket regime: bear\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=0.2909, w_SOYB=0.7091", "answer_numeric": 0.2909, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000095 - 0.000043) / (0.000169 + 0.000095 - 0.000085)\n Unconstrained: w_VTI=0.2915\n After long-only clamp: w_VTI=0.2915, w_SOYB=0.7085.", "metadata": {"weights": {"VTI": 0.2909, "SOYB": 0.7091}, "sigma_1": 0.013014, "sigma_2": 0.009738, "covariance": 4.3e-05, "correlation": 0.3371, "has_text": true, "text_chars": 3020, "mu_floor": -0.4758, "constraint_binding": false}} +{"id": "T4_all_20250425_0020", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ADA-USD", "XLY"], "decision_date": "2025-04-25", "context_summary": "ADA-USD \u03c3=0.0611, XLY \u03c3=0.0179, \u03c1=0.182. Min-variance weights: ADA-USD=0.034, XLY=0.967.", "question": "Assets: ADA-USD, XLY\nADA-USD: annualized_mean_return=-0.8568, daily_std=0.0611\nXLY: annualized_mean_return=-0.9072, daily_std=0.0179\nMinimum required portfolio return (annualized): -0.8888\nMarket regime: bear\n\nCompute portfolio weights (w_ADA-USD, w_XLY) 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_XLY=X.XXXX", "answer": "w_ADA-USD=0.3651, w_XLY=0.6349", "answer_numeric": 0.3651, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000322 - 0.000199) / (0.003727 + 0.000322 - 0.000398)\n Unconstrained: w_ADA-USD=0.0335\n After long-only clamp: w_ADA-USD=0.0335, w_XLY=0.9665.", "metadata": {"weights": {"ADA-USD": 0.3651, "XLY": 0.6349}, "sigma_1": 0.061052, "sigma_2": 0.017935, "covariance": 0.000199, "correlation": 0.182, "has_text": true, "text_chars": 20, "mu_floor": -0.8888, "constraint_binding": true}} +{"id": "T4_all_20250521_0022", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "CSHI"], "decision_date": "2025-05-21", "context_summary": "VLUE \u03c3=0.0138, CSHI \u03c3=0.0032, \u03c1=-0.194. Min-variance weights: VLUE=0.087, CSHI=0.913.", "question": "Assets: VLUE, CSHI\nVLUE: annualized_mean_return=-0.0756, daily_std=0.0138\nCSHI: annualized_mean_return=-0.0252, daily_std=0.0032\nMinimum required portfolio return (annualized): -0.0267\nMarket regime: sideways\n\nCompute portfolio weights (w_VLUE, w_CSHI) 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_CSHI=X.XXXX", "answer": "w_VLUE=0.0298, w_CSHI=0.9702", "answer_numeric": 0.0298, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000010 - -0.000009) / (0.000191 + 0.000010 - -0.000017)\n Unconstrained: w_VLUE=0.0867\n After long-only clamp: w_VLUE=0.0867, w_CSHI=0.9133.", "metadata": {"weights": {"VLUE": 0.0298, "CSHI": 0.9702}, "sigma_1": 0.01382, "sigma_2": 0.003213, "covariance": -9e-06, "correlation": -0.1943, "has_text": true, "text_chars": 3020, "mu_floor": -0.0267, "constraint_binding": true}} +{"id": "T4_all_20250131_0025", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "CSHI"], "decision_date": "2025-01-31", "context_summary": "BNB-USD \u03c3=0.0297, CSHI \u03c3=0.0004, \u03c1=0.012. Min-variance weights: BNB-USD=0.000, CSHI=1.000.", "question": "Assets: BNB-USD, CSHI\nBNB-USD: annualized_mean_return=0.2520, daily_std=0.0297\nCSHI: annualized_mean_return=0.0756, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.0756\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_BNB-USD=0.0002, w_CSHI=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000884 + 0.000000 - 0.000000)\n Unconstrained: w_BNB-USD=0.0000\n After long-only clamp: w_BNB-USD=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"BNB-USD": 0.0002, "CSHI": 0.9998}, "sigma_1": 0.029727, "sigma_2": 0.000369, "covariance": 0.0, "correlation": 0.0122, "has_text": true, "text_chars": 20, "mu_floor": 0.0756, "constraint_binding": false}} +{"id": "T4_all_20250228_0027", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "SHV"], "decision_date": "2025-02-28", "context_summary": "XLI \u03c3=0.0084, SHV \u03c3=0.0001, \u03c1=0.034. Min-variance weights: XLI=0.000, SHV=1.000.", "question": "Assets: XLI, SHV\nXLI: annualized_mean_return=-0.2520, daily_std=0.0084\nSHV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0162\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_SHV) 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_SHV=X.XXXX", "answer": "w_XLI=0.0002, w_SHV=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000071 + 0.000000 - 0.000000)\n Unconstrained: w_XLI=-0.0003\n After long-only clamp: w_XLI=0.0000, w_SHV=1.0000.", "metadata": {"weights": {"XLI": 0.0002, "SHV": 0.9998}, "sigma_1": 0.008442, "sigma_2": 0.00013, "covariance": 0.0, "correlation": 0.0344, "has_text": true, "text_chars": 9045, "mu_floor": 0.0162, "constraint_binding": false}} +{"id": "T4_all_20250327_0030", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "SHV"], "decision_date": "2025-03-27", "context_summary": "XRP-USD \u03c3=0.0648, SHV \u03c3=0.0001, \u03c1=-0.149. Min-variance weights: XRP-USD=0.000, SHV=1.000.", "question": "Assets: XRP-USD, SHV\nXRP-USD: annualized_mean_return=-0.7308, daily_std=0.0648\nSHV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0504\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 - -0.000001) / (0.004196 + 0.000000 - -0.000003)\n Unconstrained: w_XRP-USD=0.0003\n After long-only clamp: w_XRP-USD=0.0003, w_SHV=0.9997.", "metadata": {"weights": {"XRP-USD": -0.0, "SHV": 1.0}, "sigma_1": 0.064779, "sigma_2": 0.000136, "covariance": -1e-06, "correlation": -0.1487, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": true}} +{"id": "T4_all_20250225_0032", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "IYR"], "decision_date": "2025-02-25", "context_summary": "QQQ \u03c3=0.0116, IYR \u03c3=0.0104, \u03c1=0.249. Min-variance weights: QQQ=0.427, IYR=0.573.", "question": "Assets: QQQ, IYR\nQQQ: annualized_mean_return=0.1260, daily_std=0.0116\nIYR: annualized_mean_return=-0.1512, daily_std=0.0104\nMinimum required portfolio return (annualized): 0.0900\nMarket regime: sideways\n\nCompute portfolio weights (w_QQQ, w_IYR) 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_IYR=X.XXXX", "answer": "w_QQQ=0.8701, w_IYR=0.1299", "answer_numeric": 0.8701, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000108 - 0.000030) / (0.000135 + 0.000108 - 0.000060)\n Unconstrained: w_QQQ=0.4267\n After long-only clamp: w_QQQ=0.4267, w_IYR=0.5733.", "metadata": {"weights": {"QQQ": 0.8701, "IYR": 0.1299}, "sigma_1": 0.011613, "sigma_2": 0.010396, "covariance": 3e-05, "correlation": 0.2494, "has_text": true, "text_chars": 9045, "mu_floor": 0.09, "constraint_binding": true}} +{"id": "T4_all_20250520_0035", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "ICSH"], "decision_date": "2025-05-20", "context_summary": "LINK-USD \u03c3=0.0462, ICSH \u03c3=0.0003, \u03c1=0.040. Min-variance weights: LINK-USD=0.000, ICSH=1.000.", "question": "Assets: LINK-USD, ICSH\nLINK-USD: annualized_mean_return=0.7056, daily_std=0.0462\nICSH: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0756\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=0.0000, w_ICSH=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.002132 + 0.000000 - 0.000001)\n Unconstrained: w_LINK-USD=-0.0002\n After long-only clamp: w_LINK-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"LINK-USD": 0.0, "ICSH": 1.0}, "sigma_1": 0.046171, "sigma_2": 0.000349, "covariance": 1e-06, "correlation": 0.04, "has_text": true, "text_chars": 20, "mu_floor": 0.0756, "constraint_binding": false}} +{"id": "T4_all_20250725_0037", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD", "ICSH"], "decision_date": "2025-07-25", "context_summary": "BTC-USD \u03c3=0.0154, ICSH \u03c3=0.0002, \u03c1=0.257. Min-variance weights: BTC-USD=0.000, ICSH=1.000.", "question": "Assets: BTC-USD, ICSH\nBTC-USD: annualized_mean_return=0.3780, daily_std=0.0154\nICSH: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: bull\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 - 0.000001) / (0.000236 + 0.000000 - 0.000001)\n Unconstrained: w_BTC-USD=-0.0028\n After long-only clamp: w_BTC-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"BTC-USD": 0.0, "ICSH": 1.0}, "sigma_1": 0.015371, "sigma_2": 0.000174, "covariance": 1e-06, "correlation": 0.2573, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20250917_0039", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD", "CSHI"], "decision_date": "2025-09-17", "context_summary": "ADA-USD \u03c3=0.0378, CSHI \u03c3=0.0005, \u03c1=0.138. Min-variance weights: ADA-USD=0.000, CSHI=1.000.", "question": "Assets: ADA-USD, CSHI\nADA-USD: annualized_mean_return=0.5040, daily_std=0.0378\nCSHI: annualized_mean_return=0.0504, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: bull\n\nCompute portfolio weights (w_ADA-USD, w_CSHI) 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_CSHI=X.XXXX", "answer": "w_ADA-USD=0.0000, w_CSHI=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000003) / (0.001432 + 0.000000 - 0.000005)\n Unconstrained: w_ADA-USD=-0.0017\n After long-only clamp: w_ADA-USD=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"ADA-USD": 0.0, "CSHI": 1.0}, "sigma_1": 0.037844, "sigma_2": 0.000516, "covariance": 3e-06, "correlation": 0.1384, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20250221_0042", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "CPER"], "decision_date": "2025-02-21", "context_summary": "AVAX-USD \u03c3=0.0460, CPER \u03c3=0.0130, \u03c1=0.112. Min-variance weights: AVAX-USD=0.047, CPER=0.953.", "question": "Assets: AVAX-USD, CPER\nAVAX-USD: annualized_mean_return=-1.2852, daily_std=0.0460\nCPER: annualized_mean_return=0.2772, daily_std=0.0130\nMinimum required portfolio return (annualized): 0.2623\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_CPER) 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_CPER=X.XXXX", "answer": "w_AVAX-USD=0.0095, w_CPER=0.9905", "answer_numeric": 0.0095, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000168 - 0.000067) / (0.002114 + 0.000168 - 0.000134)\n Unconstrained: w_AVAX-USD=0.0470\n After long-only clamp: w_AVAX-USD=0.0470, w_CPER=0.9530.", "metadata": {"weights": {"AVAX-USD": 0.0095, "CPER": 0.9905}, "sigma_1": 0.045977, "sigma_2": 0.01296, "covariance": 6.7e-05, "correlation": 0.1124, "has_text": true, "text_chars": 20, "mu_floor": 0.2623, "constraint_binding": true}} +{"id": "T4_all_20250317_0045", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLI", "DBC"], "decision_date": "2025-03-17", "context_summary": "XLI \u03c3=0.0100, DBC \u03c3=0.0074, \u03c1=0.171. Min-variance weights: XLI=0.326, DBC=0.674.", "question": "Assets: XLI, DBC\nXLI: annualized_mean_return=-0.1764, daily_std=0.0100\nDBC: annualized_mean_return=0.1764, daily_std=0.0074\nMinimum required portfolio return (annualized): -0.0775\nMarket regime: bear\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=0.3251, w_DBC=0.6749", "answer_numeric": 0.3251, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000055 - 0.000013) / (0.000100 + 0.000055 - 0.000025)\n Unconstrained: w_XLI=0.3260\n After long-only clamp: w_XLI=0.3260, w_DBC=0.6740.", "metadata": {"weights": {"XLI": 0.3251, "DBC": 0.6749}, "sigma_1": 0.010009, "sigma_2": 0.007416, "covariance": 1.3e-05, "correlation": 0.1708, "has_text": true, "text_chars": 9045, "mu_floor": -0.0775, "constraint_binding": false}} +{"id": "T4_all_20250324_0048", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "BNO"], "decision_date": "2025-03-24", "context_summary": "SOL-USD \u03c3=0.0596, BNO \u03c3=0.0139, \u03c1=-0.165. Min-variance weights: SOL-USD=0.082, BNO=0.918.", "question": "Assets: SOL-USD, BNO\nSOL-USD: annualized_mean_return=-2.3184, daily_std=0.0596\nBNO: annualized_mean_return=-0.1008, daily_std=0.0139\nMinimum required portfolio return (annualized): -0.1974\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_BNO) 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_BNO=X.XXXX", "answer": "w_SOL-USD=0.0436, w_BNO=0.9564", "answer_numeric": 0.0436, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000192 - -0.000136) / (0.003551 + 0.000192 - -0.000273)\n Unconstrained: w_SOL-USD=0.0818\n After long-only clamp: w_SOL-USD=0.0818, w_BNO=0.9182.", "metadata": {"weights": {"SOL-USD": 0.0436, "BNO": 0.9564}, "sigma_1": 0.05959, "sigma_2": 0.013862, "covariance": -0.000136, "correlation": -0.165, "has_text": true, "text_chars": 20, "mu_floor": -0.1974, "constraint_binding": true}} +{"id": "T4_all_20250206_0051", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "MORT"], "decision_date": "2025-02-06", "context_summary": "IWM \u03c3=0.0109, MORT \u03c3=0.0107, \u03c1=0.697. Min-variance weights: IWM=0.470, MORT=0.529.", "question": "Assets: IWM, MORT\nIWM: annualized_mean_return=-0.1008, daily_std=0.0109\nMORT: annualized_mean_return=0.2016, daily_std=0.0107\nMinimum required portfolio return (annualized): -0.0297\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_MORT) 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_MORT=X.XXXX", "answer": "w_IWM=0.4707, w_MORT=0.5293", "answer_numeric": 0.4707, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000115 - 0.000081) / (0.000119 + 0.000115 - 0.000163)\n Unconstrained: w_IWM=0.4705\n After long-only clamp: w_IWM=0.4705, w_MORT=0.5295.", "metadata": {"weights": {"IWM": 0.4707, "MORT": 0.5293}, "sigma_1": 0.0109, "sigma_2": 0.010706, "covariance": 8.1e-05, "correlation": 0.6965, "has_text": true, "text_chars": 9047, "mu_floor": -0.0297, "constraint_binding": false}} +{"id": "T4_all_20251111_0054", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EFA", "SHY"], "decision_date": "2025-11-11", "context_summary": "EFA \u03c3=0.0064, SHY \u03c3=0.0007, \u03c1=0.105. Min-variance weights: EFA=0.001, SHY=0.999.", "question": "Assets: EFA, SHY\nEFA: annualized_mean_return=0.1512, daily_std=0.0064\nSHY: annualized_mean_return=0.0504, daily_std=0.0007\nMinimum required portfolio return (annualized): 0.0774\nMarket regime: bull\n\nCompute portfolio weights (w_EFA, w_SHY) 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_SHY=X.XXXX", "answer": "w_EFA=0.2679, w_SHY=0.7321", "answer_numeric": 0.2679, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000000) / (0.000042 + 0.000001 - 0.000001)\n Unconstrained: w_EFA=0.0011\n After long-only clamp: w_EFA=0.0011, w_SHY=0.9989.", "metadata": {"weights": {"EFA": 0.2679, "SHY": 0.7321}, "sigma_1": 0.006449, "sigma_2": 0.000737, "covariance": 0.0, "correlation": 0.1052, "has_text": true, "text_chars": 9045, "mu_floor": 0.0774, "constraint_binding": true}} +{"id": "T4_all_20250203_0057", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "DBB"], "decision_date": "2025-02-03", "context_summary": "EWJ \u03c3=0.0098, DBB \u03c3=0.0073, \u03c1=-0.063. Min-variance weights: EWJ=0.364, DBB=0.635.", "question": "Assets: EWJ, DBB\nEWJ: annualized_mean_return=0.0756, daily_std=0.0098\nDBB: annualized_mean_return=-0.1512, daily_std=0.0073\nMinimum required portfolio return (annualized): -0.1122\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_DBB) 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_DBB=X.XXXX", "answer": "w_EWJ=0.3637, w_DBB=0.6363", "answer_numeric": 0.3637, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000053 - -0.000004) / (0.000096 + 0.000053 - -0.000009)\n Unconstrained: w_EWJ=0.3645\n After long-only clamp: w_EWJ=0.3645, w_DBB=0.6355.", "metadata": {"weights": {"EWJ": 0.3637, "DBB": 0.6363}, "sigma_1": 0.009797, "sigma_2": 0.00729, "covariance": -4e-06, "correlation": -0.0629, "has_text": true, "text_chars": 9046, "mu_floor": -0.1122, "constraint_binding": false}} +{"id": "T4_all_20251008_0060", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD", "XLY"], "decision_date": "2025-10-08", "context_summary": "BTC-USD \u03c3=0.0168, XLY \u03c3=0.0099, \u03c1=-0.247. Min-variance weights: BTC-USD=0.299, XLY=0.701.", "question": "Assets: BTC-USD, XLY\nBTC-USD: annualized_mean_return=0.2016, daily_std=0.0168\nXLY: annualized_mean_return=0.2520, daily_std=0.0099\nMinimum required portfolio return (annualized): 0.2450\nMarket regime: bull\n\nCompute portfolio weights (w_BTC-USD, w_XLY) 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_XLY=X.XXXX", "answer": "w_BTC-USD=0.1389, w_XLY=0.8611", "answer_numeric": 0.1389, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000097 - -0.000041) / (0.000282 + 0.000097 - -0.000082)\n Unconstrained: w_BTC-USD=0.2991\n After long-only clamp: w_BTC-USD=0.2991, w_XLY=0.7009.", "metadata": {"weights": {"BTC-USD": 0.1389, "XLY": 0.8611}, "sigma_1": 0.016805, "sigma_2": 0.009853, "covariance": -4.1e-05, "correlation": -0.247, "has_text": true, "text_chars": 20, "mu_floor": 0.245, "constraint_binding": true}} +{"id": "T4_all_20250108_0063", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "BIL"], "decision_date": "2025-01-08", "context_summary": "XLRE \u03c3=0.0110, BIL \u03c3=0.0001, \u03c1=-0.164. Min-variance weights: XLRE=0.002, BIL=0.998.", "question": "Assets: XLRE, BIL\nXLRE: annualized_mean_return=-0.2520, daily_std=0.0110\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.1266\nMarket regime: sideways\n\nCompute portfolio weights (w_XLRE, w_BIL) 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_BIL=X.XXXX", "answer": "w_XLRE=0.0002, w_BIL=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000122 + 0.000000 - -0.000001)\n Unconstrained: w_XLRE=0.0024\n After long-only clamp: w_XLRE=0.0024, w_BIL=0.9976.", "metadata": {"weights": {"XLRE": 0.0002, "BIL": 0.9998}, "sigma_1": 0.011025, "sigma_2": 0.000148, "covariance": -0.0, "correlation": -0.1645, "has_text": true, "text_chars": 9045, "mu_floor": -0.1266, "constraint_binding": false}} +{"id": "T4_all_20250212_0066", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "PDBC"], "decision_date": "2025-02-12", "context_summary": "BNB-USD \u03c3=0.0247, PDBC \u03c3=0.0072, \u03c1=-0.003. Min-variance weights: BNB-USD=0.079, PDBC=0.921.", "question": "Assets: BNB-USD, PDBC\nBNB-USD: annualized_mean_return=-0.4284, daily_std=0.0247\nPDBC: annualized_mean_return=0.2268, daily_std=0.0072\nMinimum required portfolio return (annualized): 0.2097\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_PDBC) 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_PDBC=X.XXXX", "answer": "w_BNB-USD=0.0261, w_PDBC=0.9739", "answer_numeric": 0.0261, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000052 - -0.000001) / (0.000610 + 0.000052 - -0.000001)\n Unconstrained: w_BNB-USD=0.0789\n After long-only clamp: w_BNB-USD=0.0789, w_PDBC=0.9211.", "metadata": {"weights": {"BNB-USD": 0.0261, "PDBC": 0.9739}, "sigma_1": 0.024704, "sigma_2": 0.007198, "covariance": -1e-06, "correlation": -0.003, "has_text": true, "text_chars": 20, "mu_floor": 0.2097, "constraint_binding": true}} +{"id": "T4_all_20251105_0068", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "GLD"], "decision_date": "2025-11-05", "context_summary": "XLB \u03c3=0.0091, GLD \u03c3=0.0113, \u03c1=-0.089. Min-variance weights: XLB=0.595, GLD=0.406.", "question": "Assets: XLB, GLD\nXLB: annualized_mean_return=-0.1512, daily_std=0.0091\nGLD: annualized_mean_return=0.8568, daily_std=0.0113\nMinimum required portfolio return (annualized): 0.4682\nMarket regime: sideways\n\nCompute portfolio weights (w_XLB, w_GLD) 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_GLD=X.XXXX", "answer": "w_XLB=0.3855, w_GLD=0.6145", "answer_numeric": 0.3855, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000127 - -0.000009) / (0.000084 + 0.000127 - -0.000018)\n Unconstrained: w_XLB=0.5945\n After long-only clamp: w_XLB=0.5945, w_GLD=0.4055.", "metadata": {"weights": {"XLB": 0.3855, "GLD": 0.6145}, "sigma_1": 0.00914, "sigma_2": 0.011258, "covariance": -9e-06, "correlation": -0.0888, "has_text": true, "text_chars": 9045, "mu_floor": 0.4682, "constraint_binding": true}} +{"id": "T4_all_20251106_0070", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "BIL"], "decision_date": "2025-11-06", "context_summary": "SPY \u03c3=0.0066, BIL \u03c3=0.0001, \u03c1=0.005. Min-variance weights: SPY=0.000, BIL=1.000.", "question": "Assets: SPY, BIL\nSPY: annualized_mean_return=0.2268, daily_std=0.0066\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.1455\nMarket regime: sideways\n\nCompute portfolio weights (w_SPY, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SPY=X.XXXX, w_BIL=X.XXXX", "answer": "w_SPY=0.5391, w_BIL=0.4609", "answer_numeric": 0.5391, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000044 + 0.000000 - 0.000000)\n Unconstrained: w_SPY=0.0003\n After long-only clamp: w_SPY=0.0003, w_BIL=0.9997.", "metadata": {"weights": {"SPY": 0.5391, "BIL": 0.4609}, "sigma_1": 0.006639, "sigma_2": 0.000131, "covariance": 0.0, "correlation": 0.0049, "has_text": true, "text_chars": 9045, "mu_floor": 0.1455, "constraint_binding": true}} +{"id": "T4_all_20250318_0073", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "SGOV"], "decision_date": "2025-03-18", "context_summary": "BNB-USD \u03c3=0.0320, SGOV \u03c3=0.0001, \u03c1=-0.136. Min-variance weights: BNB-USD=0.001, SGOV=0.999.", "question": "Assets: BNB-USD, SGOV\nBNB-USD: annualized_mean_return=-0.3528, daily_std=0.0320\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.1275\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=0.0010, w_SGOV=0.9990", "answer_numeric": 0.001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.001026 + 0.000000 - -0.000001)\n Unconstrained: w_BNB-USD=0.0006\n After long-only clamp: w_BNB-USD=0.0006, w_SGOV=0.9994.", "metadata": {"weights": {"BNB-USD": 0.001, "SGOV": 0.999}, "sigma_1": 0.032037, "sigma_2": 0.00014, "covariance": -1e-06, "correlation": -0.1361, "has_text": true, "text_chars": 20, "mu_floor": -0.1275, "constraint_binding": false}} +{"id": "T4_all_20251121_0076", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "SGOV"], "decision_date": "2025-11-21", "context_summary": "EFA \u03c3=0.0068, SGOV \u03c3=0.0001, \u03c1=0.080. Min-variance weights: EFA=0.000, SGOV=1.000.", "question": "Assets: EFA, SGOV\nEFA: annualized_mean_return=-0.0252, daily_std=0.0068\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_SGOV) 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_SGOV=X.XXXX", "answer": "w_EFA=-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) / (0.000047 + 0.000000 - 0.000000)\n Unconstrained: w_EFA=-0.0012\n After long-only clamp: w_EFA=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"EFA": -0.0, "SGOV": 1.0}, "sigma_1": 0.006845, "sigma_2": 0.000133, "covariance": 0.0, "correlation": 0.0797, "has_text": true, "text_chars": 9046, "mu_floor": 0.0504, "constraint_binding": true}} +{"id": "T4_all_20250326_0078", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "SGOV"], "decision_date": "2025-03-26", "context_summary": "ETH-USD \u03c3=0.0428, SGOV \u03c3=0.0001, \u03c1=0.076. Min-variance weights: ETH-USD=0.000, SGOV=1.000.", "question": "Assets: ETH-USD, SGOV\nETH-USD: annualized_mean_return=-1.7388, daily_std=0.0428\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_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) / (0.001832 + 0.000000 - 0.000001)\n Unconstrained: w_ETH-USD=-0.0002\n After long-only clamp: w_ETH-USD=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"ETH-USD": -0.0, "SGOV": 1.0}, "sigma_1": 0.0428, "sigma_2": 0.000124, "covariance": 0.0, "correlation": 0.0762, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": true}} +{"id": "T4_all_20250529_0081", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ICSH"], "decision_date": "2025-05-29", "context_summary": "XLP \u03c3=0.0104, ICSH \u03c3=0.0003, \u03c1=-0.142. Min-variance weights: XLP=0.006, ICSH=0.994.", "question": "Assets: XLP, ICSH\nXLP: annualized_mean_return=-0.0504, daily_std=0.0104\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0415\nMarket regime: sideways\n\nCompute portfolio weights (w_XLP, w_ICSH) 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_ICSH=X.XXXX", "answer": "w_XLP=0.0010, w_ICSH=0.9990", "answer_numeric": 0.001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000108 + 0.000000 - -0.000001)\n Unconstrained: w_XLP=0.0056\n After long-only clamp: w_XLP=0.0056, w_ICSH=0.9944.", "metadata": {"weights": {"XLP": 0.001, "ICSH": 0.999}, "sigma_1": 0.01041, "sigma_2": 0.000336, "covariance": -0.0, "correlation": -0.1418, "has_text": true, "text_chars": 9046, "mu_floor": 0.0415, "constraint_binding": false}} +{"id": "T4_all_20251205_0082", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "SHV"], "decision_date": "2025-12-05", "context_summary": "ADA-USD \u03c3=0.0475, SHV \u03c3=0.0001, \u03c1=-0.196. Min-variance weights: ADA-USD=0.001, SHV=1.000.", "question": "Assets: ADA-USD, SHV\nADA-USD: annualized_mean_return=-2.1672, daily_std=0.0475\nSHV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0496\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_SHV) 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_SHV=X.XXXX", "answer": "w_ADA-USD=0.0004, w_SHV=0.9996", "answer_numeric": 0.0004, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.002257 + 0.000000 - -0.000002)\n Unconstrained: w_ADA-USD=0.0005\n After long-only clamp: w_ADA-USD=0.0005, w_SHV=0.9995.", "metadata": {"weights": {"ADA-USD": 0.0004, "SHV": 0.9996}, "sigma_1": 0.047513, "sigma_2": 0.000123, "covariance": -1e-06, "correlation": -0.1957, "has_text": true, "text_chars": 20, "mu_floor": 0.0496, "constraint_binding": true}} +{"id": "T4_all_20251020_0084", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD", "IGOV"], "decision_date": "2025-10-20", "context_summary": "LINK-USD \u03c3=0.0465, IGOV \u03c3=0.0051, \u03c1=-0.111. Min-variance weights: LINK-USD=0.023, IGOV=0.977.", "question": "Assets: LINK-USD, IGOV\nLINK-USD: annualized_mean_return=-1.3860, daily_std=0.0465\nIGOV: annualized_mean_return=0.0504, daily_std=0.0051\nMinimum required portfolio return (annualized): 0.0423\nMarket regime: bull\n\nCompute portfolio weights (w_LINK-USD, w_IGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_IGOV=X.XXXX", "answer": "w_LINK-USD=0.0056, w_IGOV=0.9944", "answer_numeric": 0.0056, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000026 - -0.000026) / (0.002158 + 0.000026 - -0.000053)\n Unconstrained: w_LINK-USD=0.0234\n After long-only clamp: w_LINK-USD=0.0234, w_IGOV=0.9766.", "metadata": {"weights": {"LINK-USD": 0.0056, "IGOV": 0.9944}, "sigma_1": 0.046458, "sigma_2": 0.005096, "covariance": -2.6e-05, "correlation": -0.1112, "has_text": true, "text_chars": 20, "mu_floor": 0.0423, "constraint_binding": true}} +{"id": "T4_all_20251031_0086", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD", "SHY"], "decision_date": "2025-10-31", "context_summary": "XRP-USD \u03c3=0.0330, SHY \u03c3=0.0008, \u03c1=0.002. Min-variance weights: XRP-USD=0.001, SHY=1.000.", "question": "Assets: XRP-USD, SHY\nXRP-USD: annualized_mean_return=-0.4032, daily_std=0.0330\nSHY: annualized_mean_return=0.0504, daily_std=0.0008\nMinimum required portfolio return (annualized): 0.0502\nMarket regime: bull\n\nCompute portfolio weights (w_XRP-USD, w_SHY) 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_SHY=X.XXXX", "answer": "w_XRP-USD=0.0004, w_SHY=0.9996", "answer_numeric": 0.0004, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000000) / (0.001090 + 0.000001 - 0.000000)\n Unconstrained: w_XRP-USD=0.0005\n After long-only clamp: w_XRP-USD=0.0005, w_SHY=0.9995.", "metadata": {"weights": {"XRP-USD": 0.0004, "SHY": 0.9996}, "sigma_1": 0.033019, "sigma_2": 0.000754, "covariance": 0.0, "correlation": 0.0019, "has_text": true, "text_chars": 20, "mu_floor": 0.0502, "constraint_binding": true}} +{"id": "T4_all_20250422_0088", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["USMV", "SGOV"], "decision_date": "2025-04-22", "context_summary": "USMV \u03c3=0.0089, SGOV \u03c3=0.0001, \u03c1=-0.116. Min-variance weights: USMV=0.002, SGOV=0.998.", "question": "Assets: USMV, SGOV\nUSMV: annualized_mean_return=-0.0756, daily_std=0.0089\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: bear\n\nCompute portfolio weights (w_USMV, w_SGOV) 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_SGOV=X.XXXX", "answer": "w_USMV=-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) / (0.000079 + 0.000000 - -0.000000)\n Unconstrained: w_USMV=0.0021\n After long-only clamp: w_USMV=0.0021, w_SGOV=0.9979.", "metadata": {"weights": {"USMV": -0.0, "SGOV": 1.0}, "sigma_1": 0.008873, "sigma_2": 0.000139, "covariance": -0.0, "correlation": -0.1162, "has_text": true, "text_chars": 3020, "mu_floor": 0.0504, "constraint_binding": true}} +{"id": "T4_all_20250603_0091", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "ICSH"], "decision_date": "2025-06-03", "context_summary": "VLUE \u03c3=0.0137, ICSH \u03c3=0.0003, \u03c1=-0.254. Min-variance weights: VLUE=0.006, ICSH=0.994.", "question": "Assets: VLUE, ICSH\nVLUE: annualized_mean_return=-0.0000, daily_std=0.0137\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0228\nMarket regime: sideways\n\nCompute portfolio weights (w_VLUE, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VLUE=X.XXXX, w_ICSH=X.XXXX", "answer": "w_VLUE=0.0058, w_ICSH=0.9942", "answer_numeric": 0.0058, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.000188 + 0.000000 - -0.000002)\n Unconstrained: w_VLUE=0.0064\n After long-only clamp: w_VLUE=0.0064, w_ICSH=0.9936.", "metadata": {"weights": {"VLUE": 0.0058, "ICSH": 0.9942}, "sigma_1": 0.0137, "sigma_2": 0.000323, "covariance": -1e-06, "correlation": -0.2535, "has_text": true, "text_chars": 3020, "mu_floor": 0.0228, "constraint_binding": false}} +{"id": "T4_all_20250430_0094", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EWJ", "PPLT"], "decision_date": "2025-04-30", "context_summary": "EWJ \u03c3=0.0132, PPLT \u03c3=0.0114, \u03c1=0.327. Min-variance weights: EWJ=0.392, PPLT=0.608.", "question": "Assets: EWJ, PPLT\nEWJ: annualized_mean_return=0.1764, daily_std=0.0132\nPPLT: annualized_mean_return=-0.0504, daily_std=0.0114\nMinimum required portfolio return (annualized): 0.0675\nMarket regime: bear\n\nCompute portfolio weights (w_EWJ, w_PPLT) 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_PPLT=X.XXXX", "answer": "w_EWJ=0.5198, w_PPLT=0.4802", "answer_numeric": 0.5198, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000129 - 0.000049) / (0.000173 + 0.000129 - 0.000098)\n Unconstrained: w_EWJ=0.3920\n After long-only clamp: w_EWJ=0.3920, w_PPLT=0.6080.", "metadata": {"weights": {"EWJ": 0.5198, "PPLT": 0.4802}, "sigma_1": 0.013169, "sigma_2": 0.011368, "covariance": 4.9e-05, "correlation": 0.3274, "has_text": true, "text_chars": 3020, "mu_floor": 0.0675, "constraint_binding": true}} +{"id": "T4_all_20251218_0097", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "WEAT"], "decision_date": "2025-12-18", "context_summary": "XLF \u03c3=0.0088, WEAT \u03c3=0.0105, \u03c1=-0.020. Min-variance weights: XLF=0.587, WEAT=0.413.", "question": "Assets: XLF, WEAT\nXLF: annualized_mean_return=0.0756, daily_std=0.0088\nWEAT: annualized_mean_return=-0.2016, daily_std=0.0105\nMinimum required portfolio return (annualized): -0.1251\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_WEAT) 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_WEAT=X.XXXX", "answer": "w_XLF=0.5866, w_WEAT=0.4134", "answer_numeric": 0.5866, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000110 - -0.000002) / (0.000077 + 0.000110 - -0.000004)\n Unconstrained: w_XLF=0.5868\n After long-only clamp: w_XLF=0.5868, w_WEAT=0.4132.", "metadata": {"weights": {"XLF": 0.5866, "WEAT": 0.4134}, "sigma_1": 0.008782, "sigma_2": 0.010502, "covariance": -2e-06, "correlation": -0.0203, "has_text": true, "text_chars": 9045, "mu_floor": -0.1251, "constraint_binding": false}} +{"id": "T4_all_20250303_0100", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "IWM"], "decision_date": "2025-03-03", "context_summary": "AVAX-USD \u03c3=0.0494, IWM \u03c3=0.0106, \u03c1=0.098. Min-variance weights: AVAX-USD=0.025, IWM=0.975.", "question": "Assets: AVAX-USD, IWM\nAVAX-USD: annualized_mean_return=-1.4112, daily_std=0.0494\nIWM: annualized_mean_return=-0.4536, daily_std=0.0106\nMinimum required portfolio return (annualized): -0.4665\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_IWM) 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_IWM=X.XXXX", "answer": "w_AVAX-USD=0.0135, w_IWM=0.9865", "answer_numeric": 0.0135, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000112 - 0.000051) / (0.002436 + 0.000112 - 0.000102)\n Unconstrained: w_AVAX-USD=0.0249\n After long-only clamp: w_AVAX-USD=0.0249, w_IWM=0.9751.", "metadata": {"weights": {"AVAX-USD": 0.0135, "IWM": 0.9865}, "sigma_1": 0.049359, "sigma_2": 0.010589, "covariance": 5.1e-05, "correlation": 0.0978, "has_text": true, "text_chars": 20, "mu_floor": -0.4665, "constraint_binding": true}} +{"id": "T4_all_20251017_0103", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD", "TLT"], "decision_date": "2025-10-17", "context_summary": "XRP-USD \u03c3=0.0355, TLT \u03c3=0.0066, \u03c1=0.097. Min-variance weights: XRP-USD=0.017, TLT=0.984.", "question": "Assets: XRP-USD, TLT\nXRP-USD: annualized_mean_return=-1.0080, daily_std=0.0355\nTLT: annualized_mean_return=0.2268, daily_std=0.0066\nMinimum required portfolio return (annualized): -0.2822\nMarket regime: bull\n\nCompute portfolio weights (w_XRP-USD, w_TLT) 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_TLT=X.XXXX", "answer": "w_XRP-USD=0.0163, w_TLT=0.9837", "answer_numeric": 0.0163, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000044 - 0.000023) / (0.001261 + 0.000044 - 0.000046)\n Unconstrained: w_XRP-USD=0.0165\n After long-only clamp: w_XRP-USD=0.0165, w_TLT=0.9835.", "metadata": {"weights": {"XRP-USD": 0.0163, "TLT": 0.9837}, "sigma_1": 0.03551, "sigma_2": 0.006599, "covariance": 2.3e-05, "correlation": 0.0973, "has_text": true, "text_chars": 20, "mu_floor": -0.2822, "constraint_binding": false}} +{"id": "T4_all_20251009_0106", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY", "ADA-USD"], "decision_date": "2025-10-09", "context_summary": "SPY \u03c3=0.0054, ADA-USD \u03c3=0.0372, \u03c1=-0.223. Min-variance weights: SPY=0.951, ADA-USD=0.049.", "question": "Assets: SPY, ADA-USD\nSPY: annualized_mean_return=0.3528, daily_std=0.0054\nADA-USD: annualized_mean_return=0.3528, daily_std=0.0372\nMinimum required portfolio return (annualized): 0.3528\nMarket regime: bull\n\nCompute portfolio weights (w_SPY, w_ADA-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SPY=X.XXXX, w_ADA-USD=X.XXXX", "answer": "w_SPY=0.9506, w_ADA-USD=0.0494", "answer_numeric": 0.9506, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001383 - -0.000045) / (0.000029 + 0.001383 - -0.000090)\n Unconstrained: w_SPY=0.9507\n After long-only clamp: w_SPY=0.9507, w_ADA-USD=0.0493.", "metadata": {"weights": {"SPY": 0.9506, "ADA-USD": 0.0494}, "sigma_1": 0.005401, "sigma_2": 0.03719, "covariance": -4.5e-05, "correlation": -0.2231, "has_text": true, "text_chars": 3020, "mu_floor": 0.3528, "constraint_binding": false}} +{"id": "T4_all_20250523_0110", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BIL"], "decision_date": "2025-05-23", "context_summary": "XLI \u03c3=0.0141, BIL \u03c3=0.0002, \u03c1=-0.147. Min-variance weights: XLI=0.002, BIL=0.998.", "question": "Assets: XLI, BIL\nXLI: annualized_mean_return=0.2016, daily_std=0.0141\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.1256\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_BIL=X.XXXX", "answer": "w_XLI=0.4974, w_BIL=0.5026", "answer_numeric": 0.4974, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000200 + 0.000000 - -0.000001)\n Unconstrained: w_XLI=0.0017\n After long-only clamp: w_XLI=0.0017, w_BIL=0.9983.", "metadata": {"weights": {"XLI": 0.4974, "BIL": 0.5026}, "sigma_1": 0.014146, "sigma_2": 0.000157, "covariance": -0.0, "correlation": -0.1466, "has_text": true, "text_chars": 3020, "mu_floor": 0.1256, "constraint_binding": true}} +{"id": "T4_all_20251216_0112", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "MORT"], "decision_date": "2025-12-16", "context_summary": "DOT-USD \u03c3=0.0491, MORT \u03c3=0.0090, \u03c1=0.287. Min-variance weights: DOT-USD=0.000, MORT=1.000.", "question": "Assets: DOT-USD, MORT\nDOT-USD: annualized_mean_return=-1.6380, daily_std=0.0491\nMORT: annualized_mean_return=0.1008, daily_std=0.0090\nMinimum required portfolio return (annualized): -0.3696\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_MORT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_MORT=X.XXXX", "answer": "w_DOT-USD=0.0000, w_MORT=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000082 - 0.000127) / (0.002414 + 0.000082 - 0.000255)\n Unconstrained: w_DOT-USD=-0.0204\n After long-only clamp: w_DOT-USD=0.0000, w_MORT=1.0000.", "metadata": {"weights": {"DOT-USD": 0.0, "MORT": 1.0}, "sigma_1": 0.04913, "sigma_2": 0.00904, "covariance": 0.000127, "correlation": 0.2868, "has_text": true, "text_chars": 20, "mu_floor": -0.3696, "constraint_binding": false}} +{"id": "T4_all_20250109_0114", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "STIP"], "decision_date": "2025-01-09", "context_summary": "DOT-USD \u03c3=0.0697, STIP \u03c3=0.0009, \u03c1=-0.067. Min-variance weights: DOT-USD=0.001, STIP=0.999.", "question": "Assets: DOT-USD, STIP\nDOT-USD: annualized_mean_return=2.1924, daily_std=0.0697\nSTIP: annualized_mean_return=0.0252, daily_std=0.0009\nMinimum required portfolio return (annualized): 0.5628\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_STIP) 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_STIP=X.XXXX", "answer": "w_DOT-USD=0.2481, w_STIP=0.7519", "answer_numeric": 0.2481, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - -0.000004) / (0.004862 + 0.000001 - -0.000009)\n Unconstrained: w_DOT-USD=0.0011\n After long-only clamp: w_DOT-USD=0.0011, w_STIP=0.9989.", "metadata": {"weights": {"DOT-USD": 0.2481, "STIP": 0.7519}, "sigma_1": 0.069727, "sigma_2": 0.000935, "covariance": -4e-06, "correlation": -0.0668, "has_text": true, "text_chars": 20, "mu_floor": 0.5628, "constraint_binding": true}} +{"id": "T4_all_20251223_0117", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "WEAT"], "decision_date": "2025-12-23", "context_summary": "SPY \u03c3=0.0081, WEAT \u03c3=0.0103, \u03c1=0.155. Min-variance weights: SPY=0.641, WEAT=0.359.", "question": "Assets: SPY, WEAT\nSPY: annualized_mean_return=0.1512, daily_std=0.0081\nWEAT: annualized_mean_return=-0.0000, daily_std=0.0103\nMinimum required portfolio return (annualized): 0.0456\nMarket regime: sideways\n\nCompute portfolio weights (w_SPY, w_WEAT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SPY=X.XXXX, w_WEAT=X.XXXX", "answer": "w_SPY=0.6411, w_WEAT=0.3589", "answer_numeric": 0.6411, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000106 - 0.000013) / (0.000065 + 0.000106 - 0.000026)\n Unconstrained: w_SPY=0.6407\n After long-only clamp: w_SPY=0.6407, w_WEAT=0.3593.", "metadata": {"weights": {"SPY": 0.6411, "WEAT": 0.3589}, "sigma_1": 0.008051, "sigma_2": 0.010274, "covariance": 1.3e-05, "correlation": 0.1549, "has_text": true, "text_chars": 9045, "mu_floor": 0.0456, "constraint_binding": false}} +{"id": "T4_all_20250924_0119", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD", "XLK"], "decision_date": "2025-09-24", "context_summary": "AVAX-USD \u03c3=0.0445, XLK \u03c3=0.0088, \u03c1=-0.126. Min-variance weights: AVAX-USD=0.059, XLK=0.942.", "question": "Assets: AVAX-USD, XLK\nAVAX-USD: annualized_mean_return=1.6632, daily_std=0.0445\nXLK: annualized_mean_return=0.4788, daily_std=0.0088\nMinimum required portfolio return (annualized): 0.5358\nMarket regime: bull\n\nCompute portfolio weights (w_AVAX-USD, w_XLK) 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_XLK=X.XXXX", "answer": "w_AVAX-USD=0.0584, w_XLK=0.9416", "answer_numeric": 0.0584, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000077 - -0.000049) / (0.001981 + 0.000077 - -0.000098)\n Unconstrained: w_AVAX-USD=0.0585\n After long-only clamp: w_AVAX-USD=0.0585, w_XLK=0.9415.", "metadata": {"weights": {"AVAX-USD": 0.0584, "XLK": 0.9416}, "sigma_1": 0.044509, "sigma_2": 0.008773, "covariance": -4.9e-05, "correlation": -0.1261, "has_text": true, "text_chars": 20, "mu_floor": 0.5358, "constraint_binding": false}} +{"id": "T4_all_20250721_0122", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD", "CPER"], "decision_date": "2025-07-21", "context_summary": "AVAX-USD \u03c3=0.0400, CPER \u03c3=0.0159, \u03c1=0.077. Min-variance weights: AVAX-USD=0.116, CPER=0.884.", "question": "Assets: AVAX-USD, CPER\nAVAX-USD: annualized_mean_return=0.5292, daily_std=0.0400\nCPER: annualized_mean_return=0.6300, daily_std=0.0159\nMinimum required portfolio return (annualized): 0.6265\nMarket regime: bull\n\nCompute portfolio weights (w_AVAX-USD, w_CPER) 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_CPER=X.XXXX", "answer": "w_AVAX-USD=0.0347, w_CPER=0.9653", "answer_numeric": 0.0347, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000252 - 0.000049) / (0.001599 + 0.000252 - 0.000098)\n Unconstrained: w_AVAX-USD=0.1157\n After long-only clamp: w_AVAX-USD=0.1157, w_CPER=0.8843.", "metadata": {"weights": {"AVAX-USD": 0.0347, "CPER": 0.9653}, "sigma_1": 0.039983, "sigma_2": 0.015867, "covariance": 4.9e-05, "correlation": 0.0773, "has_text": true, "text_chars": 20, "mu_floor": 0.6265, "constraint_binding": true}} +{"id": "T4_all_20250319_0124", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLF", "LQD"], "decision_date": "2025-03-19", "context_summary": "XLF \u03c3=0.0113, LQD \u03c3=0.0038, \u03c1=0.115. Min-variance weights: XLF=0.071, LQD=0.929.", "question": "Assets: XLF, LQD\nXLF: annualized_mean_return=0.0000, daily_std=0.0113\nLQD: annualized_mean_return=0.1260, daily_std=0.0038\nMinimum required portfolio return (annualized): 0.1205\nMarket regime: bear\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=0.0437, w_LQD=0.9563", "answer_numeric": 0.0437, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000014 - 0.000005) / (0.000129 + 0.000014 - 0.000010)\n Unconstrained: w_XLF=0.0710\n After long-only clamp: w_XLF=0.0710, w_LQD=0.9290.", "metadata": {"weights": {"XLF": 0.0437, "LQD": 0.9563}, "sigma_1": 0.011346, "sigma_2": 0.003798, "covariance": 5e-06, "correlation": 0.1152, "has_text": true, "text_chars": 3020, "mu_floor": 0.1205, "constraint_binding": true}} +{"id": "T4_all_20250709_0132", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BNDX"], "decision_date": "2025-07-09", "context_summary": "EWJ \u03c3=0.0113, BNDX \u03c3=0.0022, \u03c1=-0.030. Min-variance weights: EWJ=0.040, BNDX=0.960.", "question": "Assets: EWJ, BNDX\nEWJ: annualized_mean_return=0.4536, daily_std=0.0113\nBNDX: annualized_mean_return=0.0756, daily_std=0.0022\nMinimum required portfolio return (annualized): 0.3171\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_BNDX) 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_BNDX=X.XXXX", "answer": "w_EWJ=0.6389, w_BNDX=0.3611", "answer_numeric": 0.6389, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000005 - -0.000001) / (0.000128 + 0.000005 - -0.000001)\n Unconstrained: w_EWJ=0.0399\n After long-only clamp: w_EWJ=0.0399, w_BNDX=0.9601.", "metadata": {"weights": {"EWJ": 0.6389, "BNDX": 0.3611}, "sigma_1": 0.011329, "sigma_2": 0.00215, "covariance": -1e-06, "correlation": -0.0305, "has_text": true, "text_chars": 3020, "mu_floor": 0.3171, "constraint_binding": true}} +{"id": "T4_all_20250120_0135", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "IYR"], "decision_date": "2025-01-20", "context_summary": "SOL-USD \u03c3=0.0471, IYR \u03c3=0.0110, \u03c1=0.336. Min-variance weights: SOL-USD=0.000, IYR=1.000.", "question": "Assets: SOL-USD, IYR\nSOL-USD: annualized_mean_return=0.5292, daily_std=0.0471\nIYR: annualized_mean_return=-0.1764, daily_std=0.0110\nMinimum required portfolio return (annualized): -0.1764\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=0.0000, 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 = (0.000121 - 0.000174) / (0.002218 + 0.000121 - 0.000348)\n Unconstrained: w_SOL-USD=-0.0266\n After long-only clamp: w_SOL-USD=0.0000, w_IYR=1.0000.", "metadata": {"weights": {"SOL-USD": 0.0, "IYR": 1.0}, "sigma_1": 0.0471, "sigma_2": 0.010994, "covariance": 0.000174, "correlation": 0.3358, "has_text": true, "text_chars": 20, "mu_floor": -0.1764, "constraint_binding": false}} +{"id": "T4_all_20251229_0138", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "SOYB"], "decision_date": "2025-12-29", "context_summary": "^VIX \u03c3=0.0804, SOYB \u03c3=0.0079, \u03c1=-0.036. Min-variance weights: ^VIX=0.013, SOYB=0.987.", "question": "Assets: ^VIX, SOYB\n^VIX: annualized_mean_return=-0.8064, daily_std=0.0804\nSOYB: annualized_mean_return=0.1764, daily_std=0.0079\nMinimum required portfolio return (annualized): 0.1694\nMarket regime: sideways\n\nCompute portfolio weights (w_^VIX, w_SOYB) 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_SOYB=X.XXXX", "answer": "w_^VIX=0.0071, w_SOYB=0.9929", "answer_numeric": 0.0071, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000062 - -0.000023) / (0.006462 + 0.000062 - -0.000046)\n Unconstrained: w_^VIX=0.0129\n After long-only clamp: w_^VIX=0.0129, w_SOYB=0.9871.", "metadata": {"weights": {"^VIX": 0.0071, "SOYB": 0.9929}, "sigma_1": 0.080389, "sigma_2": 0.007884, "covariance": -2.3e-05, "correlation": -0.0359, "has_text": true, "text_chars": 9045, "mu_floor": 0.1694, "constraint_binding": true}} +{"id": "T4_all_20250812_0141", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF", "TLH"], "decision_date": "2025-08-12", "context_summary": "XLF \u03c3=0.0084, TLH \u03c3=0.0061, \u03c1=-0.136. Min-variance weights: XLF=0.362, TLH=0.638.", "question": "Assets: XLF, TLH\nXLF: annualized_mean_return=0.0756, daily_std=0.0084\nTLH: annualized_mean_return=0.1764, daily_std=0.0061\nMinimum required portfolio return (annualized): 0.1398\nMarket regime: bull\n\nCompute portfolio weights (w_XLF, w_TLH) 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_TLH=X.XXXX", "answer": "w_XLF=0.3619, w_TLH=0.6381", "answer_numeric": 0.3619, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000037 - -0.000007) / (0.000070 + 0.000037 - -0.000014)\n Unconstrained: w_XLF=0.3617\n After long-only clamp: w_XLF=0.3617, w_TLH=0.6383.", "metadata": {"weights": {"XLF": 0.3619, "TLH": 0.6381}, "sigma_1": 0.008372, "sigma_2": 0.00606, "covariance": -7e-06, "correlation": -0.1364, "has_text": true, "text_chars": 9045, "mu_floor": 0.1398, "constraint_binding": false}} +{"id": "T4_all_20250915_0144", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLB", "VNQ"], "decision_date": "2025-09-15", "context_summary": "XLB \u03c3=0.0100, VNQ \u03c3=0.0090, \u03c1=0.709. Min-variance weights: XLB=0.319, VNQ=0.681.", "question": "Assets: XLB, VNQ\nXLB: annualized_mean_return=0.2268, daily_std=0.0100\nVNQ: annualized_mean_return=0.2016, daily_std=0.0090\nMinimum required portfolio return (annualized): 0.2140\nMarket regime: bull\n\nCompute portfolio weights (w_XLB, w_VNQ) 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_VNQ=X.XXXX", "answer": "w_XLB=0.4921, w_VNQ=0.5079", "answer_numeric": 0.4921, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000081 - 0.000064) / (0.000100 + 0.000081 - 0.000128)\n Unconstrained: w_XLB=0.3190\n After long-only clamp: w_XLB=0.3190, w_VNQ=0.6810.", "metadata": {"weights": {"XLB": 0.4921, "VNQ": 0.5079}, "sigma_1": 0.010007, "sigma_2": 0.008989, "covariance": 6.4e-05, "correlation": 0.7089, "has_text": true, "text_chars": 3020, "mu_floor": 0.214, "constraint_binding": true}} +{"id": "T4_all_20250819_0147", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY", "PPLT"], "decision_date": "2025-08-19", "context_summary": "SPY \u03c3=0.0063, PPLT \u03c3=0.0235, \u03c1=-0.049. Min-variance weights: SPY=0.923, PPLT=0.077.", "question": "Assets: SPY, PPLT\nSPY: annualized_mean_return=0.4284, daily_std=0.0063\nPPLT: annualized_mean_return=0.9828, daily_std=0.0235\nMinimum required portfolio return (annualized): 0.4561\nMarket regime: bull\n\nCompute portfolio weights (w_SPY, w_PPLT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SPY=X.XXXX, w_PPLT=X.XXXX", "answer": "w_SPY=0.9232, w_PPLT=0.0768", "answer_numeric": 0.9232, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000554 - -0.000007) / (0.000040 + 0.000554 - -0.000015)\n Unconstrained: w_SPY=0.9229\n After long-only clamp: w_SPY=0.9229, w_PPLT=0.0771.", "metadata": {"weights": {"SPY": 0.9232, "PPLT": 0.0768}, "sigma_1": 0.006296, "sigma_2": 0.023537, "covariance": -7e-06, "correlation": -0.049, "has_text": true, "text_chars": 3020, "mu_floor": 0.4561, "constraint_binding": false}} +{"id": "T4_all_20250130_0150", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "ACWI"], "decision_date": "2025-01-30", "context_summary": "BNB-USD \u03c3=0.0297, ACWI \u03c3=0.0077, \u03c1=-0.174. Min-variance weights: BNB-USD=0.097, ACWI=0.903.", "question": "Assets: BNB-USD, ACWI\nBNB-USD: annualized_mean_return=0.2016, daily_std=0.0297\nACWI: annualized_mean_return=0.1260, daily_std=0.0077\nMinimum required portfolio return (annualized): 0.1493\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_ACWI) 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_ACWI=X.XXXX", "answer": "w_BNB-USD=0.3082, w_ACWI=0.6918", "answer_numeric": 0.3082, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000059 - -0.000040) / (0.000881 + 0.000059 - -0.000079)\n Unconstrained: w_BNB-USD=0.0973\n After long-only clamp: w_BNB-USD=0.0973, w_ACWI=0.9027.", "metadata": {"weights": {"BNB-USD": 0.3082, "ACWI": 0.6918}, "sigma_1": 0.029674, "sigma_2": 0.007711, "covariance": -4e-05, "correlation": -0.1737, "has_text": true, "text_chars": 20, "mu_floor": 0.1493, "constraint_binding": true}} +{"id": "T4_all_20250630_0152", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "BNDX"], "decision_date": "2025-06-30", "context_summary": "ETH-USD \u03c3=0.0378, BNDX \u03c3=0.0023, \u03c1=0.120. Min-variance weights: ETH-USD=0.000, BNDX=1.000.", "question": "Assets: ETH-USD, BNDX\nETH-USD: annualized_mean_return=1.3608, daily_std=0.0378\nBNDX: annualized_mean_return=0.0756, daily_std=0.0023\nMinimum required portfolio return (annualized): 1.0887\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_BNDX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_BNDX=X.XXXX", "answer": "w_ETH-USD=0.7883, w_BNDX=0.2117", "answer_numeric": 0.7883, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000005 - 0.000010) / (0.001426 + 0.000005 - 0.000021)\n Unconstrained: w_ETH-USD=-0.0036\n After long-only clamp: w_ETH-USD=0.0000, w_BNDX=1.0000.", "metadata": {"weights": {"ETH-USD": 0.7883, "BNDX": 0.2117}, "sigma_1": 0.037767, "sigma_2": 0.002291, "covariance": 1e-05, "correlation": 0.1197, "has_text": true, "text_chars": 20, "mu_floor": 1.0887, "constraint_binding": true}} +{"id": "T4_all_20250307_0155", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "STIP"], "decision_date": "2025-03-07", "context_summary": "MATIC-USD \u03c3=0.0460, STIP \u03c3=0.0011, \u03c1=0.050. Min-variance weights: MATIC-USD=0.000, STIP=1.000.", "question": "Assets: MATIC-USD, STIP\nMATIC-USD: annualized_mean_return=-2.7468, daily_std=0.0460\nSTIP: annualized_mean_return=0.0756, daily_std=0.0011\nMinimum required portfolio return (annualized): -0.6490\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_STIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_STIP=X.XXXX", "answer": "w_MATIC-USD=0.0000, w_STIP=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000002) / (0.002118 + 0.000001 - 0.000005)\n Unconstrained: w_MATIC-USD=-0.0006\n After long-only clamp: w_MATIC-USD=0.0000, w_STIP=1.0000.", "metadata": {"weights": {"MATIC-USD": 0.0, "STIP": 1.0}, "sigma_1": 0.046022, "sigma_2": 0.001074, "covariance": 2e-06, "correlation": 0.0504, "has_text": true, "text_chars": 20, "mu_floor": -0.649, "constraint_binding": false}} +{"id": "T4_all_20250512_0157", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "IAU"], "decision_date": "2025-05-12", "context_summary": "ADA-USD \u03c3=0.0431, IAU \u03c3=0.0128, \u03c1=0.147. Min-variance weights: ADA-USD=0.045, IAU=0.955.", "question": "Assets: ADA-USD, IAU\nADA-USD: annualized_mean_return=0.6048, daily_std=0.0431\nIAU: annualized_mean_return=0.3528, daily_std=0.0128\nMinimum required portfolio return (annualized): 0.3582\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_IAU) 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_IAU=X.XXXX", "answer": "w_ADA-USD=0.0448, w_IAU=0.9552", "answer_numeric": 0.0448, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000164 - 0.000081) / (0.001860 + 0.000164 - 0.000162)\n Unconstrained: w_ADA-USD=0.0447\n After long-only clamp: w_ADA-USD=0.0447, w_IAU=0.9553.", "metadata": {"weights": {"ADA-USD": 0.0448, "IAU": 0.9552}, "sigma_1": 0.043123, "sigma_2": 0.012823, "covariance": 8.1e-05, "correlation": 0.1468, "has_text": true, "text_chars": 20, "mu_floor": 0.3582, "constraint_binding": false}} +{"id": "T4_all_20250530_0160", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "TLT"], "decision_date": "2025-05-30", "context_summary": "BNB-USD \u03c3=0.0201, TLT \u03c3=0.0089, \u03c1=0.020. Min-variance weights: BNB-USD=0.157, TLT=0.843.", "question": "Assets: BNB-USD, TLT\nBNB-USD: annualized_mean_return=0.5292, daily_std=0.0201\nTLT: annualized_mean_return=-0.1260, daily_std=0.0089\nMinimum required portfolio return (annualized): 0.1558\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_TLT) 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_TLT=X.XXXX", "answer": "w_BNB-USD=0.4301, w_TLT=0.5699", "answer_numeric": 0.4301, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000078 - 0.000004) / (0.000405 + 0.000078 - 0.000007)\n Unconstrained: w_BNB-USD=0.1569\n After long-only clamp: w_BNB-USD=0.1569, w_TLT=0.8431.", "metadata": {"weights": {"BNB-USD": 0.4301, "TLT": 0.5699}, "sigma_1": 0.020128, "sigma_2": 0.00885, "covariance": 4e-06, "correlation": 0.0203, "has_text": true, "text_chars": 20, "mu_floor": 0.1558, "constraint_binding": true}} +{"id": "T4_all_20250129_0163", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "SGOV"], "decision_date": "2025-01-29", "context_summary": "VEA \u03c3=0.0076, SGOV \u03c3=0.0002, \u03c1=-0.075. Min-variance weights: VEA=0.002, SGOV=0.998.", "question": "Assets: VEA, SGOV\nVEA: annualized_mean_return=-0.0000, daily_std=0.0076\nSGOV: annualized_mean_return=0.0756, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0536\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_SGOV=X.XXXX", "answer": "w_VEA=0.0004, 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 - -0.000000) / (0.000057 + 0.000000 - -0.000000)\n Unconstrained: w_VEA=0.0019\n After long-only clamp: w_VEA=0.0019, w_SGOV=0.9981.", "metadata": {"weights": {"VEA": 0.0004, "SGOV": 0.9996}, "sigma_1": 0.007575, "sigma_2": 0.000153, "covariance": -0.0, "correlation": -0.0747, "has_text": true, "text_chars": 9044, "mu_floor": 0.0536, "constraint_binding": false}} +{"id": "T4_all_20250402_0166", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EEM", "ICSH"], "decision_date": "2025-04-02", "context_summary": "EEM \u03c3=0.0104, ICSH \u03c3=0.0003, \u03c1=0.037. Min-variance weights: EEM=0.000, ICSH=1.000.", "question": "Assets: EEM, ICSH\nEEM: annualized_mean_return=0.2016, daily_std=0.0104\nICSH: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.1108\nMarket regime: bear\n\nCompute portfolio weights (w_EEM, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EEM=X.XXXX, w_ICSH=X.XXXX", "answer": "w_EEM=0.2794, w_ICSH=0.7206", "answer_numeric": 0.2794, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000109 + 0.000000 - 0.000000)\n Unconstrained: w_EEM=-0.0002\n After long-only clamp: w_EEM=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"EEM": 0.2794, "ICSH": 0.7206}, "sigma_1": 0.010421, "sigma_2": 0.000311, "covariance": 0.0, "correlation": 0.037, "has_text": true, "text_chars": 3020, "mu_floor": 0.1108, "constraint_binding": true}} +{"id": "T4_all_20251118_0169", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "XHB"], "decision_date": "2025-11-18", "context_summary": "BNB-USD \u03c3=0.0423, XHB \u03c3=0.0134, \u03c1=-0.016. Min-variance weights: BNB-USD=0.095, XHB=0.905.", "question": "Assets: BNB-USD, XHB\nBNB-USD: annualized_mean_return=-0.1008, daily_std=0.0423\nXHB: annualized_mean_return=-0.6048, daily_std=0.0134\nMinimum required portfolio return (annualized): -0.5674\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_XHB) 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_XHB=X.XXXX", "answer": "w_BNB-USD=0.0946, w_XHB=0.9054", "answer_numeric": 0.0946, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000179 - -0.000009) / (0.001791 + 0.000179 - -0.000018)\n Unconstrained: w_BNB-USD=0.0946\n After long-only clamp: w_BNB-USD=0.0946, w_XHB=0.9054.", "metadata": {"weights": {"BNB-USD": 0.0946, "XHB": 0.9054}, "sigma_1": 0.042318, "sigma_2": 0.013381, "covariance": -9e-06, "correlation": -0.0158, "has_text": true, "text_chars": 20, "mu_floor": -0.5674, "constraint_binding": false}} +{"id": "T4_all_20250609_0172", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BIL"], "decision_date": "2025-06-09", "context_summary": "EWJ \u03c3=0.0127, BIL \u03c3=0.0002, \u03c1=-0.147. Min-variance weights: EWJ=0.002, BIL=0.998.", "question": "Assets: EWJ, BIL\nEWJ: annualized_mean_return=0.2268, daily_std=0.0127\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0885\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=0.2160, w_BIL=0.7840", "answer_numeric": 0.216, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000162 + 0.000000 - -0.000001)\n Unconstrained: w_EWJ=0.0020\n After long-only clamp: w_EWJ=0.0020, w_BIL=0.9980.", "metadata": {"weights": {"EWJ": 0.216, "BIL": 0.784}, "sigma_1": 0.012729, "sigma_2": 0.000161, "covariance": -0.0, "correlation": -0.1469, "has_text": true, "text_chars": 9045, "mu_floor": 0.0885, "constraint_binding": true}} +{"id": "T4_all_20250909_0174", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XRP-USD", "TIP"], "decision_date": "2025-09-09", "context_summary": "XRP-USD \u03c3=0.0415, TIP \u03c3=0.0010, \u03c1=0.203. Min-variance weights: XRP-USD=0.000, TIP=1.000.", "question": "Assets: XRP-USD, TIP\nXRP-USD: annualized_mean_return=0.8568, daily_std=0.0415\nTIP: annualized_mean_return=0.1008, daily_std=0.0010\nMinimum required portfolio return (annualized): 0.4889\nMarket regime: bull\n\nCompute portfolio weights (w_XRP-USD, w_TIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_TIP=X.XXXX", "answer": "w_XRP-USD=0.5134, w_TIP=0.4866", "answer_numeric": 0.5134, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000009) / (0.001720 + 0.000001 - 0.000017)\n Unconstrained: w_XRP-USD=-0.0044\n After long-only clamp: w_XRP-USD=0.0000, w_TIP=1.0000.", "metadata": {"weights": {"XRP-USD": 0.5134, "TIP": 0.4866}, "sigma_1": 0.041467, "sigma_2": 0.001022, "covariance": 9e-06, "correlation": 0.2029, "has_text": true, "text_chars": 20, "mu_floor": 0.4889, "constraint_binding": true}} +{"id": "T4_all_20251231_0177", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "FXI"], "decision_date": "2025-12-31", "context_summary": "LINK-USD \u03c3=0.0393, FXI \u03c3=0.0114, \u03c1=-0.111. Min-variance weights: LINK-USD=0.102, FXI=0.898.", "question": "Assets: LINK-USD, FXI\nLINK-USD: annualized_mean_return=-1.1844, daily_std=0.0393\nFXI: annualized_mean_return=-0.2016, daily_std=0.0114\nMinimum required portfolio return (annualized): -0.5706\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_FXI) 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_FXI=X.XXXX", "answer": "w_LINK-USD=0.1017, w_FXI=0.8983", "answer_numeric": 0.1017, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000131 - -0.000050) / (0.001548 + 0.000131 - -0.000100)\n Unconstrained: w_LINK-USD=0.1017\n After long-only clamp: w_LINK-USD=0.1017, w_FXI=0.8983.", "metadata": {"weights": {"LINK-USD": 0.1017, "FXI": 0.8983}, "sigma_1": 0.03934, "sigma_2": 0.011439, "covariance": -5e-05, "correlation": -0.1112, "has_text": true, "text_chars": 20, "mu_floor": -0.5706, "constraint_binding": false}} +{"id": "T4_all_20251024_0180", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "BIL"], "decision_date": "2025-10-24", "context_summary": "VLUE \u03c3=0.0087, BIL \u03c3=0.0001, \u03c1=0.017. Min-variance weights: VLUE=0.000, BIL=1.000.", "question": "Assets: VLUE, BIL\nVLUE: annualized_mean_return=0.5040, daily_std=0.0087\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.1694\nMarket regime: bull\n\nCompute portfolio weights (w_VLUE, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VLUE=X.XXXX, w_BIL=X.XXXX", "answer": "w_VLUE=0.2623, w_BIL=0.7377", "answer_numeric": 0.2623, "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 - 0.000000)\n Unconstrained: w_VLUE=-0.0000\n After long-only clamp: w_VLUE=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"VLUE": 0.2623, "BIL": 0.7377}, "sigma_1": 0.008677, "sigma_2": 0.000139, "covariance": 0.0, "correlation": 0.0169, "has_text": true, "text_chars": 9044, "mu_floor": 0.1694, "constraint_binding": true}} +{"id": "T4_all_20251113_0183", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "HAUZ"], "decision_date": "2025-11-13", "context_summary": "VLUE \u03c3=0.0087, HAUZ \u03c3=0.0069, \u03c1=0.456. Min-variance weights: VLUE=0.299, HAUZ=0.701.", "question": "Assets: VLUE, HAUZ\nVLUE: annualized_mean_return=0.5292, daily_std=0.0087\nHAUZ: annualized_mean_return=0.0252, daily_std=0.0069\nMinimum required portfolio return (annualized): 0.1537\nMarket regime: sideways\n\nCompute portfolio weights (w_VLUE, w_HAUZ) 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_HAUZ=X.XXXX", "answer": "w_VLUE=0.3010, w_HAUZ=0.6990", "answer_numeric": 0.301, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000048 - 0.000027) / (0.000075 + 0.000048 - 0.000055)\n Unconstrained: w_VLUE=0.2993\n After long-only clamp: w_VLUE=0.2993, w_HAUZ=0.7007.", "metadata": {"weights": {"VLUE": 0.301, "HAUZ": 0.699}, "sigma_1": 0.008658, "sigma_2": 0.006903, "covariance": 2.7e-05, "correlation": 0.4564, "has_text": true, "text_chars": 9045, "mu_floor": 0.1537, "constraint_binding": false}} +{"id": "T4_all_20250528_0186", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "VCIT"], "decision_date": "2025-05-28", "context_summary": "EFA \u03c3=0.0115, VCIT \u03c3=0.0040, \u03c1=0.305. Min-variance weights: EFA=0.017, VCIT=0.983.", "question": "Assets: EFA, VCIT\nEFA: annualized_mean_return=0.3528, daily_std=0.0115\nVCIT: annualized_mean_return=0.0252, daily_std=0.0040\nMinimum required portfolio return (annualized): 0.1998\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=0.5330, w_VCIT=0.4670", "answer_numeric": 0.533, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000016 - 0.000014) / (0.000133 + 0.000016 - 0.000028)\n Unconstrained: w_EFA=0.0172\n After long-only clamp: w_EFA=0.0172, w_VCIT=0.9828.", "metadata": {"weights": {"EFA": 0.533, "VCIT": 0.467}, "sigma_1": 0.011521, "sigma_2": 0.004026, "covariance": 1.4e-05, "correlation": 0.3047, "has_text": true, "text_chars": 3020, "mu_floor": 0.1998, "constraint_binding": true}} +{"id": "T4_all_20250101_0189", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BIL"], "decision_date": "2025-01-01", "context_summary": "VLUE \u03c3=0.0085, BIL \u03c3=0.0002, \u03c1=0.212. Min-variance weights: VLUE=0.000, BIL=1.000.", "question": "Assets: VLUE, BIL\nVLUE: annualized_mean_return=-0.1008, daily_std=0.0085\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0396\nMarket regime: sideways\n\nCompute portfolio weights (w_VLUE, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VLUE=X.XXXX, w_BIL=X.XXXX", "answer": "w_VLUE=0.0003, w_BIL=0.9997", "answer_numeric": 0.0003, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000073 + 0.000000 - 0.000001)\n Unconstrained: w_VLUE=-0.0036\n After long-only clamp: w_VLUE=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"VLUE": 0.0003, "BIL": 0.9997}, "sigma_1": 0.008523, "sigma_2": 0.000157, "covariance": 0.0, "correlation": 0.2115, "has_text": true, "text_chars": 9045, "mu_floor": 0.0396, "constraint_binding": false}} +{"id": "T4_all_20251124_0191", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "IEF"], "decision_date": "2025-11-24", "context_summary": "ETH-USD \u03c3=0.0384, IEF \u03c3=0.0026, \u03c1=0.046. Min-variance weights: ETH-USD=0.002, IEF=0.999.", "question": "Assets: ETH-USD, IEF\nETH-USD: annualized_mean_return=-1.4616, daily_std=0.0384\nIEF: annualized_mean_return=0.0756, daily_std=0.0026\nMinimum required portfolio return (annualized): 0.0704\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=0.0011, w_IEF=0.9989", "answer_numeric": 0.0011, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000007 - 0.000005) / (0.001472 + 0.000007 - 0.000009)\n Unconstrained: w_ETH-USD=0.0015\n After long-only clamp: w_ETH-USD=0.0015, w_IEF=0.9985.", "metadata": {"weights": {"ETH-USD": 0.0011, "IEF": 0.9989}, "sigma_1": 0.038363, "sigma_2": 0.002585, "covariance": 5e-06, "correlation": 0.0458, "has_text": true, "text_chars": 20, "mu_floor": 0.0704, "constraint_binding": false}} +{"id": "T4_all_20251015_0194", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VEA", "ICSH"], "decision_date": "2025-10-15", "context_summary": "VEA \u03c3=0.0074, ICSH \u03c3=0.0003, \u03c1=-0.022. Min-variance weights: VEA=0.002, ICSH=0.998.", "question": "Assets: VEA, ICSH\nVEA: annualized_mean_return=0.2268, daily_std=0.0074\nICSH: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.1540\nMarket regime: bull\n\nCompute portfolio weights (w_VEA, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_ICSH=X.XXXX", "answer": "w_VEA=0.5185, w_ICSH=0.4815", "answer_numeric": 0.5185, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000055 + 0.000000 - -0.000000)\n Unconstrained: w_VEA=0.0020\n After long-only clamp: w_VEA=0.0020, w_ICSH=0.9980.", "metadata": {"weights": {"VEA": 0.5185, "ICSH": 0.4815}, "sigma_1": 0.007435, "sigma_2": 0.000261, "covariance": -0.0, "correlation": -0.0219, "has_text": true, "text_chars": 3020, "mu_floor": 0.154, "constraint_binding": true}} +{"id": "T4_all_20250613_0198", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "HAUZ"], "decision_date": "2025-06-13", "context_summary": "FXI \u03c3=0.0171, HAUZ \u03c3=0.0097, \u03c1=0.612. Min-variance weights: FXI=0.000, HAUZ=1.000.", "question": "Assets: FXI, HAUZ\nFXI: annualized_mean_return=0.0756, daily_std=0.0171\nHAUZ: annualized_mean_return=0.4284, daily_std=0.0097\nMinimum required portfolio return (annualized): 0.2485\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_HAUZ) 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_HAUZ=X.XXXX", "answer": "w_FXI=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 = (0.000094 - 0.000102) / (0.000293 + 0.000094 - 0.000203)\n Unconstrained: w_FXI=-0.0402\n After long-only clamp: w_FXI=0.0000, w_HAUZ=1.0000.", "metadata": {"weights": {"FXI": 0.0, "HAUZ": 1.0}, "sigma_1": 0.017116, "sigma_2": 0.009706, "covariance": 0.000102, "correlation": 0.6116, "has_text": true, "text_chars": 3020, "mu_floor": 0.2485, "constraint_binding": false}} +{"id": "T4_all_20250121_0201", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "PALL"], "decision_date": "2025-01-21", "context_summary": "BTC-USD \u03c3=0.0237, PALL \u03c3=0.0185, \u03c1=0.222. Min-variance weights: BTC-USD=0.344, PALL=0.656.", "question": "Assets: BTC-USD, PALL\nBTC-USD: annualized_mean_return=0.2268, daily_std=0.0237\nPALL: annualized_mean_return=-0.8820, daily_std=0.0185\nMinimum required portfolio return (annualized): -0.5833\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=0.3436, w_PALL=0.6564", "answer_numeric": 0.3436, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000341 - 0.000097) / (0.000562 + 0.000341 - 0.000194)\n Unconstrained: w_BTC-USD=0.3435\n After long-only clamp: w_BTC-USD=0.3435, w_PALL=0.6565.", "metadata": {"weights": {"BTC-USD": 0.3436, "PALL": 0.6564}, "sigma_1": 0.023716, "sigma_2": 0.018458, "covariance": 9.7e-05, "correlation": 0.2221, "has_text": true, "text_chars": 20, "mu_floor": -0.5833, "constraint_binding": false}} +{"id": "T4_all_20250926_0204", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD", "QQQ"], "decision_date": "2025-09-26", "context_summary": "LINK-USD \u03c3=0.0515, QQQ \u03c3=0.0069, \u03c1=-0.206. Min-variance weights: LINK-USD=0.043, QQQ=0.958.", "question": "Assets: LINK-USD, QQQ\nLINK-USD: annualized_mean_return=0.5040, daily_std=0.0515\nQQQ: annualized_mean_return=0.3528, daily_std=0.0069\nMinimum required portfolio return (annualized): 0.4662\nMarket regime: bull\n\nCompute portfolio weights (w_LINK-USD, w_QQQ) 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_QQQ=X.XXXX", "answer": "w_LINK-USD=0.7500, w_QQQ=0.2500", "answer_numeric": 0.75, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000048 - -0.000073) / (0.002652 + 0.000048 - -0.000147)\n Unconstrained: w_LINK-USD=0.0425\n After long-only clamp: w_LINK-USD=0.0425, w_QQQ=0.9575.", "metadata": {"weights": {"LINK-USD": 0.75, "QQQ": 0.25}, "sigma_1": 0.051494, "sigma_2": 0.006905, "covariance": -7.3e-05, "correlation": -0.2061, "has_text": true, "text_chars": 20, "mu_floor": 0.4662, "constraint_binding": true}} +{"id": "T4_all_20251204_0206", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ETH-USD"], "decision_date": "2025-12-04", "context_summary": "FXI \u03c3=0.0120, ETH-USD \u03c3=0.0396, \u03c1=0.018. Min-variance weights: FXI=0.920, ETH-USD=0.080.", "question": "Assets: FXI, ETH-USD\nFXI: annualized_mean_return=-0.0252, daily_std=0.0120\nETH-USD: annualized_mean_return=-1.2348, daily_std=0.0396\nMinimum required portfolio return (annualized): -0.0955\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_ETH-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_ETH-USD=X.XXXX", "answer": "w_FXI=0.9419, w_ETH-USD=0.0581", "answer_numeric": 0.9419, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001570 - 0.000009) / (0.000144 + 0.001570 - 0.000017)\n Unconstrained: w_FXI=0.9201\n After long-only clamp: w_FXI=0.9201, w_ETH-USD=0.0799.", "metadata": {"weights": {"FXI": 0.9419, "ETH-USD": 0.0581}, "sigma_1": 0.012011, "sigma_2": 0.039622, "covariance": 9e-06, "correlation": 0.0184, "has_text": true, "text_chars": 9045, "mu_floor": -0.0955, "constraint_binding": true}} +{"id": "T4_all_20250417_0208", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VTI", "ETH-USD"], "decision_date": "2025-04-17", "context_summary": "VTI \u03c3=0.0130, ETH-USD \u03c3=0.0494, \u03c1=0.147. Min-variance weights: VTI=0.969, ETH-USD=0.031.", "question": "Assets: VTI, ETH-USD\nVTI: annualized_mean_return=-0.6804, daily_std=0.0130\nETH-USD: annualized_mean_return=-1.9152, daily_std=0.0494\nMinimum required portfolio return (annualized): -0.6978\nMarket regime: bear\n\nCompute portfolio weights (w_VTI, w_ETH-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_ETH-USD=X.XXXX", "answer": "w_VTI=0.9859, w_ETH-USD=0.0141", "answer_numeric": 0.9859, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.002438 - 0.000094) / (0.000170 + 0.002438 - 0.000189)\n Unconstrained: w_VTI=0.9688\n After long-only clamp: w_VTI=0.9688, w_ETH-USD=0.0312.", "metadata": {"weights": {"VTI": 0.9859, "ETH-USD": 0.0141}, "sigma_1": 0.013036, "sigma_2": 0.049374, "covariance": 9.4e-05, "correlation": 0.1466, "has_text": true, "text_chars": 3020, "mu_floor": -0.6978, "constraint_binding": true}} +{"id": "T4_all_20251104_0210", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD", "SHV"], "decision_date": "2025-11-04", "context_summary": "ADA-USD \u03c3=0.0413, SHV \u03c3=0.0002, \u03c1=0.144. Min-variance weights: ADA-USD=0.000, SHV=1.000.", "question": "Assets: ADA-USD, SHV\nADA-USD: annualized_mean_return=-1.1340, daily_std=0.0413\nSHV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): -0.2178\nMarket regime: bull\n\nCompute portfolio weights (w_ADA-USD, w_SHV) 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_SHV=X.XXXX", "answer": "w_ADA-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) / (0.001710 + 0.000000 - 0.000002)\n Unconstrained: w_ADA-USD=-0.0005\n After long-only clamp: w_ADA-USD=0.0000, w_SHV=1.0000.", "metadata": {"weights": {"ADA-USD": 0.0, "SHV": 1.0}, "sigma_1": 0.041347, "sigma_2": 0.000157, "covariance": 1e-06, "correlation": 0.1437, "has_text": true, "text_chars": 20, "mu_floor": -0.2178, "constraint_binding": false}} +{"id": "T4_all_20250801_0212", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD", "JNK"], "decision_date": "2025-08-01", "context_summary": "SOL-USD \u03c3=0.0344, JNK \u03c3=0.0025, \u03c1=-0.044. Min-variance weights: SOL-USD=0.008, JNK=0.992.", "question": "Assets: SOL-USD, JNK\nSOL-USD: annualized_mean_return=0.5292, daily_std=0.0344\nJNK: annualized_mean_return=0.1512, daily_std=0.0025\nMinimum required portfolio return (annualized): 0.4380\nMarket regime: bull\n\nCompute portfolio weights (w_SOL-USD, w_JNK) 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_JNK=X.XXXX", "answer": "w_SOL-USD=0.7587, w_JNK=0.2413", "answer_numeric": 0.7587, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000006 - -0.000004) / (0.001180 + 0.000006 - -0.000008)\n Unconstrained: w_SOL-USD=0.0084\n After long-only clamp: w_SOL-USD=0.0084, w_JNK=0.9916.", "metadata": {"weights": {"SOL-USD": 0.7587, "JNK": 0.2413}, "sigma_1": 0.034356, "sigma_2": 0.002502, "covariance": -4e-06, "correlation": -0.0444, "has_text": true, "text_chars": 20, "mu_floor": 0.438, "constraint_binding": true}} +{"id": "T4_all_20251014_0214", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD", "REZ"], "decision_date": "2025-10-14", "context_summary": "BNB-USD \u03c3=0.0388, REZ \u03c3=0.0090, \u03c1=-0.016. Min-variance weights: BNB-USD=0.054, REZ=0.946.", "question": "Assets: BNB-USD, REZ\nBNB-USD: annualized_mean_return=1.9908, daily_std=0.0388\nREZ: annualized_mean_return=-0.0252, daily_std=0.0090\nMinimum required portfolio return (annualized): 1.3294\nMarket regime: bull\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=0.6719, w_REZ=0.3281", "answer_numeric": 0.6719, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000081 - -0.000006) / (0.001503 + 0.000081 - -0.000011)\n Unconstrained: w_BNB-USD=0.0541\n After long-only clamp: w_BNB-USD=0.0541, w_REZ=0.9459.", "metadata": {"weights": {"BNB-USD": 0.6719, "REZ": 0.3281}, "sigma_1": 0.038767, "sigma_2": 0.008976, "covariance": -6e-06, "correlation": -0.0164, "has_text": true, "text_chars": 20, "mu_floor": 1.3294, "constraint_binding": true}} +{"id": "T4_all_20250617_0216", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "ITB"], "decision_date": "2025-06-17", "context_summary": "ETH-USD \u03c3=0.0376, ITB \u03c3=0.0198, \u03c1=-0.033. Min-variance weights: ETH-USD=0.225, ITB=0.775.", "question": "Assets: ETH-USD, ITB\nETH-USD: annualized_mean_return=1.9404, daily_std=0.0376\nITB: annualized_mean_return=-0.2016, daily_std=0.0198\nMinimum required portfolio return (annualized): 1.2267\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_ITB) 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_ITB=X.XXXX", "answer": "w_ETH-USD=0.6668, w_ITB=0.3332", "answer_numeric": 0.6668, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000393 - -0.000025) / (0.001410 + 0.000393 - -0.000049)\n Unconstrained: w_ETH-USD=0.2254\n After long-only clamp: w_ETH-USD=0.2254, w_ITB=0.7746.", "metadata": {"weights": {"ETH-USD": 0.6668, "ITB": 0.3332}, "sigma_1": 0.037556, "sigma_2": 0.019823, "covariance": -2.5e-05, "correlation": -0.033, "has_text": true, "text_chars": 20, "mu_floor": 1.2267, "constraint_binding": true}} +{"id": "T4_all_20250522_0218", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "CSHI"], "decision_date": "2025-05-22", "context_summary": "XLB \u03c3=0.0147, CSHI \u03c3=0.0032, \u03c1=-0.151. Min-variance weights: XLB=0.072, CSHI=0.927.", "question": "Assets: XLB, CSHI\nXLB: annualized_mean_return=-0.1512, daily_std=0.0147\nCSHI: annualized_mean_return=-0.0504, daily_std=0.0032\nMinimum required portfolio return (annualized): -0.0542\nMarket regime: sideways\n\nCompute portfolio weights (w_XLB, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLB=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XLB=0.0377, w_CSHI=0.9623", "answer_numeric": 0.0377, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000010 - -0.000007) / (0.000216 + 0.000010 - -0.000014)\n Unconstrained: w_XLB=0.0725\n After long-only clamp: w_XLB=0.0725, w_CSHI=0.9275.", "metadata": {"weights": {"XLB": 0.0377, "CSHI": 0.9623}, "sigma_1": 0.0147, "sigma_2": 0.003214, "covariance": -7e-06, "correlation": -0.1509, "has_text": true, "text_chars": 3020, "mu_floor": -0.0542, "constraint_binding": true}} +{"id": "T4_all_20250314_0220", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EFA", "AVAX-USD"], "decision_date": "2025-03-14", "context_summary": "EFA \u03c3=0.0089, AVAX-USD \u03c3=0.0569, \u03c1=-0.031. Min-variance weights: EFA=0.972, AVAX-USD=0.028.", "question": "Assets: EFA, AVAX-USD\nEFA: annualized_mean_return=0.2268, daily_std=0.0089\nAVAX-USD: annualized_mean_return=-2.4192, daily_std=0.0569\nMinimum required portfolio return (annualized): 0.1938\nMarket regime: bear\n\nCompute portfolio weights (w_EFA, w_AVAX-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_AVAX-USD=X.XXXX", "answer": "w_EFA=0.9875, w_AVAX-USD=0.0125", "answer_numeric": 0.9875, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.003235 - -0.000016) / (0.000079 + 0.003235 - -0.000031)\n Unconstrained: w_EFA=0.9717\n After long-only clamp: w_EFA=0.9717, w_AVAX-USD=0.0283.", "metadata": {"weights": {"EFA": 0.9875, "AVAX-USD": 0.0125}, "sigma_1": 0.008891, "sigma_2": 0.056875, "covariance": -1.6e-05, "correlation": -0.0311, "has_text": true, "text_chars": 3020, "mu_floor": 0.1938, "constraint_binding": true}} +{"id": "T4_all_20250218_0222", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "IGOV"], "decision_date": "2025-02-18", "context_summary": "BNB-USD \u03c3=0.0271, IGOV \u03c3=0.0057, \u03c1=0.184. Min-variance weights: BNB-USD=0.006, IGOV=0.994.", "question": "Assets: BNB-USD, IGOV\nBNB-USD: annualized_mean_return=0.1008, daily_std=0.0271\nIGOV: annualized_mean_return=0.0756, daily_std=0.0057\nMinimum required portfolio return (annualized): 0.0947\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_IGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_IGOV=X.XXXX", "answer": "w_BNB-USD=0.7579, w_IGOV=0.2421", "answer_numeric": 0.7579, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000033 - 0.000029) / (0.000732 + 0.000033 - 0.000057)\n Unconstrained: w_BNB-USD=0.0061\n After long-only clamp: w_BNB-USD=0.0061, w_IGOV=0.9939.", "metadata": {"weights": {"BNB-USD": 0.7579, "IGOV": 0.2421}, "sigma_1": 0.027051, "sigma_2": 0.005741, "covariance": 2.9e-05, "correlation": 0.1842, "has_text": true, "text_chars": 20, "mu_floor": 0.0947, "constraint_binding": true}} +{"id": "T4_all_20250516_0225", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "INDS"], "decision_date": "2025-05-16", "context_summary": "AVAX-USD \u03c3=0.0496, INDS \u03c3=0.0148, \u03c1=-0.188. Min-variance weights: AVAX-USD=0.121, INDS=0.879.", "question": "Assets: AVAX-USD, INDS\nAVAX-USD: annualized_mean_return=1.3356, daily_std=0.0496\nINDS: annualized_mean_return=-0.0756, daily_std=0.0148\nMinimum required portfolio return (annualized): 0.0030\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_INDS) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_INDS=X.XXXX", "answer": "w_AVAX-USD=0.1212, w_INDS=0.8788", "answer_numeric": 0.1212, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000220 - -0.000138) / (0.002456 + 0.000220 - -0.000277)\n Unconstrained: w_AVAX-USD=0.1214\n After long-only clamp: w_AVAX-USD=0.1214, w_INDS=0.8786.", "metadata": {"weights": {"AVAX-USD": 0.1212, "INDS": 0.8788}, "sigma_1": 0.049561, "sigma_2": 0.014829, "covariance": -0.000138, "correlation": -0.1884, "has_text": true, "text_chars": 20, "mu_floor": 0.003, "constraint_binding": false}} +{"id": "T4_all_20250825_0228", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["USMV", "VNQI"], "decision_date": "2025-08-25", "context_summary": "USMV \u03c3=0.0055, VNQI \u03c3=0.0063, \u03c1=0.649. Min-variance weights: USMV=0.672, VNQI=0.328.", "question": "Assets: USMV, VNQI\nUSMV: annualized_mean_return=0.1008, daily_std=0.0055\nVNQI: annualized_mean_return=0.3780, daily_std=0.0063\nMinimum required portfolio return (annualized): 0.2452\nMarket regime: bull\n\nCompute portfolio weights (w_USMV, w_VNQI) 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_VNQI=X.XXXX", "answer": "w_USMV=0.4791, w_VNQI=0.5209", "answer_numeric": 0.4791, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000039 - 0.000023) / (0.000031 + 0.000039 - 0.000045)\n Unconstrained: w_USMV=0.6723\n After long-only clamp: w_USMV=0.6723, w_VNQI=0.3277.", "metadata": {"weights": {"USMV": 0.4791, "VNQI": 0.5209}, "sigma_1": 0.005547, "sigma_2": 0.006276, "covariance": 2.3e-05, "correlation": 0.6486, "has_text": true, "text_chars": 3020, "mu_floor": 0.2452, "constraint_binding": true}} +{"id": "T4_all_20250328_0230", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "CSHI"], "decision_date": "2025-03-28", "context_summary": "XRP-USD \u03c3=0.0647, CSHI \u03c3=0.0006, \u03c1=0.136. Min-variance weights: XRP-USD=0.000, CSHI=1.000.", "question": "Assets: XRP-USD, CSHI\nXRP-USD: annualized_mean_return=-0.6300, daily_std=0.0647\nCSHI: annualized_mean_return=0.0504, daily_std=0.0006\nMinimum required portfolio return (annualized): -0.1559\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XRP-USD=0.0000, w_CSHI=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000005) / (0.004187 + 0.000000 - 0.000011)\n Unconstrained: w_XRP-USD=-0.0012\n After long-only clamp: w_XRP-USD=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"XRP-USD": 0.0, "CSHI": 1.0}, "sigma_1": 0.064704, "sigma_2": 0.000608, "covariance": 5e-06, "correlation": 0.1362, "has_text": true, "text_chars": 20, "mu_floor": -0.1559, "constraint_binding": false}} +{"id": "T4_all_20250710_0233", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "UNG"], "decision_date": "2025-07-10", "context_summary": "IVV \u03c3=0.0095, UNG \u03c3=0.0337, \u03c1=-0.045. Min-variance weights: IVV=0.916, UNG=0.084.", "question": "Assets: IVV, UNG\nIVV: annualized_mean_return=0.7056, daily_std=0.0095\nUNG: annualized_mean_return=-0.5796, daily_std=0.0337\nMinimum required portfolio return (annualized): 0.2181\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_UNG) 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_UNG=X.XXXX", "answer": "w_IVV=0.9160, w_UNG=0.0840", "answer_numeric": 0.916, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001139 - -0.000015) / (0.000091 + 0.001139 - -0.000029)\n Unconstrained: w_IVV=0.9162\n After long-only clamp: w_IVV=0.9162, w_UNG=0.0838.", "metadata": {"weights": {"IVV": 0.916, "UNG": 0.084}, "sigma_1": 0.009531, "sigma_2": 0.033742, "covariance": -1.5e-05, "correlation": -0.0454, "has_text": true, "text_chars": 3020, "mu_floor": 0.2181, "constraint_binding": false}} +{"id": "T4_all_20251219_0235", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "HAUZ"], "decision_date": "2025-12-19", "context_summary": "VEA \u03c3=0.0073, HAUZ \u03c3=0.0068, \u03c1=0.788. Min-variance weights: VEA=0.310, HAUZ=0.690.", "question": "Assets: VEA, HAUZ\nVEA: annualized_mean_return=0.2016, daily_std=0.0073\nHAUZ: annualized_mean_return=0.0504, daily_std=0.0068\nMinimum required portfolio return (annualized): 0.0840\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_HAUZ) 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_HAUZ=X.XXXX", "answer": "w_VEA=0.3117, w_HAUZ=0.6883", "answer_numeric": 0.3117, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000046 - 0.000039) / (0.000054 + 0.000046 - 0.000078)\n Unconstrained: w_VEA=0.3105\n After long-only clamp: w_VEA=0.3105, w_HAUZ=0.6895.", "metadata": {"weights": {"VEA": 0.3117, "HAUZ": 0.6883}, "sigma_1": 0.007332, "sigma_2": 0.006759, "covariance": 3.9e-05, "correlation": 0.7882, "has_text": true, "text_chars": 9045, "mu_floor": 0.084, "constraint_binding": false}} +{"id": "T4_all_20250506_0238", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "VCIT"], "decision_date": "2025-05-06", "context_summary": "SOL-USD \u03c3=0.0454, VCIT \u03c3=0.0039, \u03c1=0.033. Min-variance weights: SOL-USD=0.005, VCIT=0.995.", "question": "Assets: SOL-USD, VCIT\nSOL-USD: annualized_mean_return=0.3528, daily_std=0.0454\nVCIT: annualized_mean_return=0.1008, daily_std=0.0039\nMinimum required portfolio return (annualized): 0.2351\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_VCIT) 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_VCIT=X.XXXX", "answer": "w_SOL-USD=0.5329, w_VCIT=0.4671", "answer_numeric": 0.5329, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000016 - 0.000006) / (0.002060 + 0.000016 - 0.000012)\n Unconstrained: w_SOL-USD=0.0046\n After long-only clamp: w_SOL-USD=0.0046, w_VCIT=0.9954.", "metadata": {"weights": {"SOL-USD": 0.5329, "VCIT": 0.4671}, "sigma_1": 0.045384, "sigma_2": 0.003946, "covariance": 6e-06, "correlation": 0.0335, "has_text": true, "text_chars": 20, "mu_floor": 0.2351, "constraint_binding": true}} +{"id": "T4_all_20250107_0241", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "XHB"], "decision_date": "2025-01-07", "context_summary": "FXI \u03c3=0.0191, XHB \u03c3=0.0140, \u03c1=0.316. Min-variance weights: FXI=0.286, XHB=0.714.", "question": "Assets: FXI, XHB\nFXI: annualized_mean_return=-0.3528, daily_std=0.0191\nXHB: annualized_mean_return=-0.6048, daily_std=0.0140\nMinimum required portfolio return (annualized): -0.5691\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_XHB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_FXI=X.XXXX, w_XHB=X.XXXX", "answer": "w_FXI=0.2852, w_XHB=0.7148", "answer_numeric": 0.2852, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000197 - 0.000085) / (0.000365 + 0.000197 - 0.000169)\n Unconstrained: w_FXI=0.2857\n After long-only clamp: w_FXI=0.2857, w_XHB=0.7143.", "metadata": {"weights": {"FXI": 0.2852, "XHB": 0.7148}, "sigma_1": 0.019105, "sigma_2": 0.014026, "covariance": 8.5e-05, "correlation": 0.3156, "has_text": true, "text_chars": 9045, "mu_floor": -0.5691, "constraint_binding": false}} +{"id": "T4_all_20250918_0244", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLK", "ICSH"], "decision_date": "2025-09-18", "context_summary": "XLK \u03c3=0.0085, ICSH \u03c3=0.0004, \u03c1=0.005. Min-variance weights: XLK=0.002, ICSH=0.999.", "question": "Assets: XLK, ICSH\nXLK: annualized_mean_return=0.4788, daily_std=0.0085\nICSH: annualized_mean_return=0.0756, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.3519\nMarket regime: bull\n\nCompute portfolio weights (w_XLK, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_ICSH=X.XXXX", "answer": "w_XLK=0.6853, w_ICSH=0.3147", "answer_numeric": 0.6853, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000073 + 0.000000 - 0.000000)\n Unconstrained: w_XLK=0.0015\n After long-only clamp: w_XLK=0.0015, w_ICSH=0.9985.", "metadata": {"weights": {"XLK": 0.6853, "ICSH": 0.3147}, "sigma_1": 0.008541, "sigma_2": 0.000356, "covariance": 0.0, "correlation": 0.005, "has_text": true, "text_chars": 3020, "mu_floor": 0.3519, "constraint_binding": true}} +{"id": "T4_all_20250306_0247", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "XHB"], "decision_date": "2025-03-06", "context_summary": "XRP-USD \u03c3=0.0675, XHB \u03c3=0.0148, \u03c1=-0.050. Min-variance weights: XRP-USD=0.055, XHB=0.945.", "question": "Assets: XRP-USD, XHB\nXRP-USD: annualized_mean_return=0.6300, daily_std=0.0675\nXHB: annualized_mean_return=-0.7056, daily_std=0.0148\nMinimum required portfolio return (annualized): -0.6536\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_XHB) 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_XHB=X.XXXX", "answer": "w_XRP-USD=0.0548, w_XHB=0.9452", "answer_numeric": 0.0548, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000218 - -0.000049) / (0.004554 + 0.000218 - -0.000099)\n Unconstrained: w_XRP-USD=0.0549\n After long-only clamp: w_XRP-USD=0.0549, w_XHB=0.9451.", "metadata": {"weights": {"XRP-USD": 0.0548, "XHB": 0.9452}, "sigma_1": 0.067483, "sigma_2": 0.01476, "covariance": -4.9e-05, "correlation": -0.0495, "has_text": true, "text_chars": 20, "mu_floor": -0.6536, "constraint_binding": false}} +{"id": "T4_all_20250401_0250", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VEA", "DBC"], "decision_date": "2025-04-01", "context_summary": "VEA \u03c3=0.0089, DBC \u03c3=0.0074, \u03c1=0.193. Min-variance weights: VEA=0.393, DBC=0.607.", "question": "Assets: VEA, DBC\nVEA: annualized_mean_return=0.2772, daily_std=0.0089\nDBC: annualized_mean_return=0.1260, daily_std=0.0074\nMinimum required portfolio return (annualized): 0.2587\nMarket regime: bear\n\nCompute portfolio weights (w_VEA, w_DBC) 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_DBC=X.XXXX", "answer": "w_VEA=0.8776, w_DBC=0.1224", "answer_numeric": 0.8776, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000055 - 0.000013) / (0.000078 + 0.000055 - 0.000025)\n Unconstrained: w_VEA=0.3934\n After long-only clamp: w_VEA=0.3934, w_DBC=0.6066.", "metadata": {"weights": {"VEA": 0.8776, "DBC": 0.1224}, "sigma_1": 0.00886, "sigma_2": 0.007442, "covariance": 1.3e-05, "correlation": 0.1929, "has_text": true, "text_chars": 3020, "mu_floor": 0.2587, "constraint_binding": true}} +{"id": "T4_all_20250407_0253", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ADA-USD", "SGOV"], "decision_date": "2025-04-07", "context_summary": "ADA-USD \u03c3=0.0593, SGOV \u03c3=0.0001, \u03c1=-0.160. Min-variance weights: ADA-USD=0.000, SGOV=1.000.", "question": "Assets: ADA-USD, SGOV\nADA-USD: annualized_mean_return=-1.6632, daily_std=0.0593\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.1647\nMarket regime: bear\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=0.0003, w_SGOV=0.9997", "answer_numeric": 0.0003, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.003515 + 0.000000 - -0.000002)\n Unconstrained: w_ADA-USD=0.0003\n After long-only clamp: w_ADA-USD=0.0003, w_SGOV=0.9997.", "metadata": {"weights": {"ADA-USD": 0.0003, "SGOV": 0.9997}, "sigma_1": 0.059288, "sigma_2": 0.000121, "covariance": -1e-06, "correlation": -0.1603, "has_text": true, "text_chars": 20, "mu_floor": -0.1647, "constraint_binding": false}} +{"id": "T4_all_20250514_0256", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "IGOV"], "decision_date": "2025-05-14", "context_summary": "BNB-USD \u03c3=0.0220, IGOV \u03c3=0.0066, \u03c1=0.094. Min-variance weights: BNB-USD=0.060, IGOV=0.940.", "question": "Assets: BNB-USD, IGOV\nBNB-USD: annualized_mean_return=0.5796, daily_std=0.0220\nIGOV: annualized_mean_return=0.1512, daily_std=0.0066\nMinimum required portfolio return (annualized): 0.3405\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_IGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BNB-USD=X.XXXX, w_IGOV=X.XXXX", "answer": "w_BNB-USD=0.4419, w_IGOV=0.5581", "answer_numeric": 0.4419, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000044 - 0.000014) / (0.000484 + 0.000044 - 0.000027)\n Unconstrained: w_BNB-USD=0.0602\n After long-only clamp: w_BNB-USD=0.0602, w_IGOV=0.9398.", "metadata": {"weights": {"BNB-USD": 0.4419, "IGOV": 0.5581}, "sigma_1": 0.021995, "sigma_2": 0.006619, "covariance": 1.4e-05, "correlation": 0.094, "has_text": true, "text_chars": 20, "mu_floor": 0.3405, "constraint_binding": true}} +{"id": "T4_all_20250527_0258", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "PALL"], "decision_date": "2025-05-27", "context_summary": "BNB-USD \u03c3=0.0205, PALL \u03c3=0.0150, \u03c1=-0.069. Min-variance weights: BNB-USD=0.356, PALL=0.644.", "question": "Assets: BNB-USD, PALL\nBNB-USD: annualized_mean_return=0.3024, daily_std=0.0205\nPALL: annualized_mean_return=0.3024, daily_std=0.0150\nMinimum required portfolio return (annualized): 0.3024\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_PALL) 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_PALL=X.XXXX", "answer": "w_BNB-USD=0.3563, w_PALL=0.6437", "answer_numeric": 0.3563, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000224 - -0.000021) / (0.000421 + 0.000224 - -0.000042)\n Unconstrained: w_BNB-USD=0.3564\n After long-only clamp: w_BNB-USD=0.3564, w_PALL=0.6436.", "metadata": {"weights": {"BNB-USD": 0.3563, "PALL": 0.6437}, "sigma_1": 0.02053, "sigma_2": 0.014965, "covariance": -2.1e-05, "correlation": -0.069, "has_text": true, "text_chars": 20, "mu_floor": 0.3024, "constraint_binding": false}} +{"id": "T4_all_20251028_0262", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD", "IGOV"], "decision_date": "2025-10-28", "context_summary": "DOT-USD \u03c3=0.0408, IGOV \u03c3=0.0046, \u03c1=-0.070. Min-variance weights: DOT-USD=0.020, IGOV=0.980.", "question": "Assets: DOT-USD, IGOV\nDOT-USD: annualized_mean_return=-0.3780, daily_std=0.0408\nIGOV: annualized_mean_return=0.0504, daily_std=0.0046\nMinimum required portfolio return (annualized): 0.0472\nMarket regime: bull\n\nCompute portfolio weights (w_DOT-USD, w_IGOV) 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_IGOV=X.XXXX", "answer": "w_DOT-USD=0.0075, w_IGOV=0.9925", "answer_numeric": 0.0075, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000021 - -0.000013) / (0.001664 + 0.000021 - -0.000026)\n Unconstrained: w_DOT-USD=0.0201\n After long-only clamp: w_DOT-USD=0.0201, w_IGOV=0.9799.", "metadata": {"weights": {"DOT-USD": 0.0075, "IGOV": 0.9925}, "sigma_1": 0.040791, "sigma_2": 0.004606, "covariance": -1.3e-05, "correlation": -0.0701, "has_text": true, "text_chars": 20, "mu_floor": 0.0472, "constraint_binding": true}} +{"id": "T4_all_20250414_0265", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EFA", "IGOV"], "decision_date": "2025-04-14", "context_summary": "EFA \u03c3=0.0115, IGOV \u03c3=0.0058, \u03c1=0.234. Min-variance weights: EFA=0.134, IGOV=0.866.", "question": "Assets: EFA, IGOV\nEFA: annualized_mean_return=0.1260, daily_std=0.0115\nIGOV: annualized_mean_return=0.3024, daily_std=0.0058\nMinimum required portfolio return (annualized): 0.2676\nMarket regime: bear\n\nCompute portfolio weights (w_EFA, w_IGOV) 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_IGOV=X.XXXX", "answer": "w_EFA=0.1321, w_IGOV=0.8679", "answer_numeric": 0.1321, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000034 - 0.000016) / (0.000133 + 0.000034 - 0.000031)\n Unconstrained: w_EFA=0.1340\n After long-only clamp: w_EFA=0.1340, w_IGOV=0.8660.", "metadata": {"weights": {"EFA": 0.1321, "IGOV": 0.8679}, "sigma_1": 0.011526, "sigma_2": 0.005812, "covariance": 1.6e-05, "correlation": 0.2335, "has_text": true, "text_chars": 3020, "mu_floor": 0.2676, "constraint_binding": false}} +{"id": "T4_all_20250115_0268", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "WEAT"], "decision_date": "2025-01-15", "context_summary": "XLI \u03c3=0.0090, WEAT \u03c3=0.0106, \u03c1=-0.129. Min-variance weights: XLI=0.574, WEAT=0.426.", "question": "Assets: XLI, WEAT\nXLI: annualized_mean_return=-0.1512, daily_std=0.0090\nWEAT: annualized_mean_return=-0.3780, daily_std=0.0106\nMinimum required portfolio return (annualized): -0.2116\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_WEAT) 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_WEAT=X.XXXX", "answer": "w_XLI=0.7337, w_WEAT=0.2663", "answer_numeric": 0.7337, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000113 - -0.000012) / (0.000080 + 0.000113 - -0.000025)\n Unconstrained: w_XLI=0.5744\n After long-only clamp: w_XLI=0.5744, w_WEAT=0.4256.", "metadata": {"weights": {"XLI": 0.7337, "WEAT": 0.2663}, "sigma_1": 0.008967, "sigma_2": 0.010621, "covariance": -1.2e-05, "correlation": -0.1287, "has_text": true, "text_chars": 9045, "mu_floor": -0.2116, "constraint_binding": true}} +{"id": "T4_all_20250827_0271", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD", "USO"], "decision_date": "2025-08-27", "context_summary": "BTC-USD \u03c3=0.0159, USO \u03c3=0.0202, \u03c1=-0.058. Min-variance weights: BTC-USD=0.610, USO=0.390.", "question": "Assets: BTC-USD, USO\nBTC-USD: annualized_mean_return=0.2016, daily_std=0.0159\nUSO: annualized_mean_return=0.2772, daily_std=0.0202\nMinimum required portfolio return (annualized): 0.2199\nMarket regime: bull\n\nCompute portfolio weights (w_BTC-USD, w_USO) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_USO=X.XXXX", "answer": "w_BTC-USD=0.6099, w_USO=0.3901", "answer_numeric": 0.6099, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000408 - -0.000019) / (0.000254 + 0.000408 - -0.000037)\n Unconstrained: w_BTC-USD=0.6100\n After long-only clamp: w_BTC-USD=0.6100, w_USO=0.3900.", "metadata": {"weights": {"BTC-USD": 0.6099, "USO": 0.3901}, "sigma_1": 0.015941, "sigma_2": 0.0202, "covariance": -1.9e-05, "correlation": -0.0577, "has_text": true, "text_chars": 20, "mu_floor": 0.2199, "constraint_binding": false}} +{"id": "T4_all_20250304_0273", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "XHB"], "decision_date": "2025-03-04", "context_summary": "XLV \u03c3=0.0081, XHB \u03c3=0.0144, \u03c1=0.452. Min-variance weights: XLV=0.922, XHB=0.078.", "question": "Assets: XLV, XHB\nXLV: annualized_mean_return=0.0756, daily_std=0.0081\nXHB: annualized_mean_return=-0.8568, daily_std=0.0144\nMinimum required portfolio return (annualized): -0.4223\nMarket regime: sideways\n\nCompute portfolio weights (w_XLV, w_XHB) 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_XHB=X.XXXX", "answer": "w_XLV=0.9246, w_XHB=0.0754", "answer_numeric": 0.9246, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000207 - 0.000053) / (0.000066 + 0.000207 - 0.000105)\n Unconstrained: w_XLV=0.9223\n After long-only clamp: w_XLV=0.9223, w_XHB=0.0777.", "metadata": {"weights": {"XLV": 0.9246, "XHB": 0.0754}, "sigma_1": 0.008095, "sigma_2": 0.014372, "covariance": 5.3e-05, "correlation": 0.4518, "has_text": true, "text_chars": 9045, "mu_floor": -0.4223, "constraint_binding": false}} +{"id": "T4_all_20251126_0275", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "SLV"], "decision_date": "2025-11-26", "context_summary": "XLV \u03c3=0.0087, SLV \u03c3=0.0194, \u03c1=-0.003. Min-variance weights: XLV=0.832, SLV=0.168.", "question": "Assets: XLV, SLV\nXLV: annualized_mean_return=0.6048, daily_std=0.0087\nSLV: annualized_mean_return=1.1340, daily_std=0.0194\nMinimum required portfolio return (annualized): 0.6874\nMarket regime: sideways\n\nCompute portfolio weights (w_XLV, w_SLV) 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_SLV=X.XXXX", "answer": "w_XLV=0.8325, w_SLV=0.1675", "answer_numeric": 0.8325, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000376 - -0.000000) / (0.000076 + 0.000376 - -0.000001)\n Unconstrained: w_XLV=0.8318\n After long-only clamp: w_XLV=0.8318, w_SLV=0.1682.", "metadata": {"weights": {"XLV": 0.8325, "SLV": 0.1675}, "sigma_1": 0.008695, "sigma_2": 0.019385, "covariance": -0.0, "correlation": -0.0028, "has_text": true, "text_chars": 9046, "mu_floor": 0.6874, "constraint_binding": false}} +{"id": "T4_all_20250818_0278", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD", "TIP"], "decision_date": "2025-08-18", "context_summary": "SOL-USD \u03c3=0.0367, TIP \u03c3=0.0010, \u03c1=0.104. Min-variance weights: SOL-USD=0.000, TIP=1.000.", "question": "Assets: SOL-USD, TIP\nSOL-USD: annualized_mean_return=1.2852, daily_std=0.0367\nTIP: annualized_mean_return=0.0756, daily_std=0.0010\nMinimum required portfolio return (annualized): 0.9255\nMarket regime: bull\n\nCompute portfolio weights (w_SOL-USD, w_TIP) 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_TIP=X.XXXX", "answer": "w_SOL-USD=0.7026, w_TIP=0.2974", "answer_numeric": 0.7026, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000004) / (0.001346 + 0.000001 - 0.000008)\n Unconstrained: w_SOL-USD=-0.0021\n After long-only clamp: w_SOL-USD=0.0000, w_TIP=1.0000.", "metadata": {"weights": {"SOL-USD": 0.7026, "TIP": 0.2974}, "sigma_1": 0.036687, "sigma_2": 0.001029, "covariance": 4e-06, "correlation": 0.1039, "has_text": true, "text_chars": 20, "mu_floor": 0.9255, "constraint_binding": true}} +{"id": "T4_all_20250320_0281", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "SHY"], "decision_date": "2025-03-20", "context_summary": "SOL-USD \u03c3=0.0596, SHY \u03c3=0.0008, \u03c1=-0.065. Min-variance weights: SOL-USD=0.001, SHY=0.999.", "question": "Assets: SOL-USD, SHY\nSOL-USD: annualized_mean_return=-2.2932, daily_std=0.0596\nSHY: annualized_mean_return=0.0756, daily_std=0.0008\nMinimum required portfolio return (annualized): -1.0965\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_SHY) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_SOL-USD=X.XXXX, w_SHY=X.XXXX", "answer": "w_SOL-USD=0.0010, w_SHY=0.9990", "answer_numeric": 0.001, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - -0.000003) / (0.003556 + 0.000001 - -0.000006)\n Unconstrained: w_SOL-USD=0.0011\n After long-only clamp: w_SOL-USD=0.0011, w_SHY=0.9989.", "metadata": {"weights": {"SOL-USD": 0.001, "SHY": 0.999}, "sigma_1": 0.059631, "sigma_2": 0.000832, "covariance": -3e-06, "correlation": -0.0647, "has_text": true, "text_chars": 20, "mu_floor": -1.0965, "constraint_binding": false}} +{"id": "T4_all_20250616_0283", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "USMV"], "decision_date": "2025-06-16", "context_summary": "XRP-USD \u03c3=0.0285, USMV \u03c3=0.0091, \u03c1=-0.248. Min-variance weights: XRP-USD=0.143, USMV=0.857.", "question": "Assets: XRP-USD, USMV\nXRP-USD: annualized_mean_return=0.2772, daily_std=0.0285\nUSMV: annualized_mean_return=0.0252, daily_std=0.0091\nMinimum required portfolio return (annualized): 0.0423\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_USMV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_USMV=X.XXXX", "answer": "w_XRP-USD=0.1433, w_USMV=0.8567", "answer_numeric": 0.1433, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000082 - -0.000064) / (0.000811 + 0.000082 - -0.000128)\n Unconstrained: w_XRP-USD=0.1434\n After long-only clamp: w_XRP-USD=0.1434, w_USMV=0.8566.", "metadata": {"weights": {"XRP-USD": 0.1433, "USMV": 0.8567}, "sigma_1": 0.028475, "sigma_2": 0.009075, "covariance": -6.4e-05, "correlation": -0.2479, "has_text": true, "text_chars": 20, "mu_floor": 0.0423, "constraint_binding": false}} +{"id": "T4_all_20250610_0285", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BIL"], "decision_date": "2025-06-10", "context_summary": "VEA \u03c3=0.0104, BIL \u03c3=0.0002, \u03c1=-0.140. Min-variance weights: VEA=0.002, BIL=0.998.", "question": "Assets: VEA, BIL\nVEA: annualized_mean_return=0.3780, daily_std=0.0104\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_VEA=X.XXXX, w_BIL=X.XXXX", "answer": "w_VEA=0.0002, w_BIL=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000109 + 0.000000 - -0.000000)\n Unconstrained: w_VEA=0.0024\n After long-only clamp: w_VEA=0.0024, w_BIL=0.9976.", "metadata": {"weights": {"VEA": 0.0002, "BIL": 0.9998}, "sigma_1": 0.010424, "sigma_2": 0.00016, "covariance": -0.0, "correlation": -0.1402, "has_text": true, "text_chars": 3020, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20250704_0287", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "PDBC"], "decision_date": "2025-07-04", "context_summary": "VTI \u03c3=0.0113, PDBC \u03c3=0.0104, \u03c1=-0.204. Min-variance weights: VTI=0.467, PDBC=0.533.", "question": "Assets: VTI, PDBC\nVTI: annualized_mean_return=0.6552, daily_std=0.0113\nPDBC: annualized_mean_return=0.3024, daily_std=0.0104\nMinimum required portfolio return (annualized): 0.4255\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_PDBC) 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_PDBC=X.XXXX", "answer": "w_VTI=0.4665, w_PDBC=0.5335", "answer_numeric": 0.4665, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000108 - -0.000024) / (0.000127 + 0.000108 - -0.000048)\n Unconstrained: w_VTI=0.4665\n After long-only clamp: w_VTI=0.4665, w_PDBC=0.5335.", "metadata": {"weights": {"VTI": 0.4665, "PDBC": 0.5335}, "sigma_1": 0.011264, "sigma_2": 0.01039, "covariance": -2.4e-05, "correlation": -0.2038, "has_text": true, "text_chars": 3020, "mu_floor": 0.4255, "constraint_binding": false}} +{"id": "T4_all_20251225_0290", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "TLH"], "decision_date": "2025-12-25", "context_summary": "XLE \u03c3=0.0112, TLH \u03c3=0.0042, \u03c1=-0.127. Min-variance weights: XLE=0.150, TLH=0.850.", "question": "Assets: XLE, TLH\nXLE: annualized_mean_return=0.0000, daily_std=0.0112\nTLH: annualized_mean_return=-0.0000, daily_std=0.0042\nMinimum required portfolio return (annualized): -0.0000\nMarket regime: sideways\n\nCompute portfolio weights (w_XLE, w_TLH) 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_TLH=X.XXXX", "answer": "w_XLE=0.1505, w_TLH=0.8495", "answer_numeric": 0.1505, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000017 - -0.000006) / (0.000125 + 0.000017 - -0.000012)\n Unconstrained: w_XLE=0.1500\n After long-only clamp: w_XLE=0.1500, w_TLH=0.8500.", "metadata": {"weights": {"XLE": 0.1505, "TLH": 0.8495}, "sigma_1": 0.011196, "sigma_2": 0.004156, "covariance": -6e-06, "correlation": -0.1266, "has_text": true, "text_chars": 9045, "mu_floor": -0.0, "constraint_binding": false}} +{"id": "T4_all_20250701_0293", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "ICSH"], "decision_date": "2025-07-01", "context_summary": "AVAX-USD \u03c3=0.0442, ICSH \u03c3=0.0002, \u03c1=-0.001. Min-variance weights: AVAX-USD=0.000, ICSH=1.000.", "question": "Assets: AVAX-USD, ICSH\nAVAX-USD: annualized_mean_return=-0.5292, daily_std=0.0442\nICSH: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): -0.2270\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_ICSH=X.XXXX", "answer": "w_AVAX-USD=0.0000, 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) / (0.001955 + 0.000000 - -0.000000)\n Unconstrained: w_AVAX-USD=0.0000\n After long-only clamp: w_AVAX-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"AVAX-USD": 0.0, "ICSH": 1.0}, "sigma_1": 0.044214, "sigma_2": 0.000231, "covariance": -0.0, "correlation": -0.0005, "has_text": true, "text_chars": 20, "mu_floor": -0.227, "constraint_binding": false}} +{"id": "T4_all_20250214_0296", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "VNQ"], "decision_date": "2025-02-14", "context_summary": "ADA-USD \u03c3=0.0484, VNQ \u03c3=0.0104, \u03c1=0.256. Min-variance weights: ADA-USD=0.000, VNQ=1.000.", "question": "Assets: ADA-USD, VNQ\nADA-USD: annualized_mean_return=-0.9828, daily_std=0.0484\nVNQ: annualized_mean_return=0.0000, daily_std=0.0104\nMinimum required portfolio return (annualized): -0.3057\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ADA-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_ADA-USD=0.0000, w_VNQ=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000109 - 0.000129) / (0.002340 + 0.000109 - 0.000259)\n Unconstrained: w_ADA-USD=-0.0093\n After long-only clamp: w_ADA-USD=0.0000, w_VNQ=1.0000.", "metadata": {"weights": {"ADA-USD": 0.0, "VNQ": 1.0}, "sigma_1": 0.048379, "sigma_2": 0.010437, "covariance": 0.000129, "correlation": 0.2562, "has_text": true, "text_chars": 20, "mu_floor": -0.3057, "constraint_binding": false}} +{"id": "T4_all_20250910_0299", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD", "CSHI"], "decision_date": "2025-09-10", "context_summary": "AVAX-USD \u03c3=0.0405, CSHI \u03c3=0.0005, \u03c1=0.237. Min-variance weights: AVAX-USD=0.000, CSHI=1.000.", "question": "Assets: AVAX-USD, CSHI\nAVAX-USD: annualized_mean_return=1.1592, daily_std=0.0405\nCSHI: annualized_mean_return=0.0504, daily_std=0.0005\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: bull\n\nCompute portfolio weights (w_AVAX-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_AVAX-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_AVAX-USD=0.0000, w_CSHI=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000005) / (0.001637 + 0.000000 - 0.000010)\n Unconstrained: w_AVAX-USD=-0.0030\n After long-only clamp: w_AVAX-USD=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"AVAX-USD": 0.0, "CSHI": 1.0}, "sigma_1": 0.040465, "sigma_2": 0.000535, "covariance": 5e-06, "correlation": 0.2371, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20251003_0302", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLK", "CSHI"], "decision_date": "2025-10-03", "context_summary": "XLK \u03c3=0.0085, CSHI \u03c3=0.0004, \u03c1=-0.083. Min-variance weights: XLK=0.007, CSHI=0.993.", "question": "Assets: XLK, CSHI\nXLK: annualized_mean_return=0.4536, daily_std=0.0085\nCSHI: annualized_mean_return=0.0504, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.2889\nMarket regime: bull\n\nCompute portfolio weights (w_XLK, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XLK=0.5915, w_CSHI=0.4085", "answer_numeric": 0.5915, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000072 + 0.000000 - -0.000001)\n Unconstrained: w_XLK=0.0071\n After long-only clamp: w_XLK=0.0071, w_CSHI=0.9929.", "metadata": {"weights": {"XLK": 0.5915, "CSHI": 0.4085}, "sigma_1": 0.008456, "sigma_2": 0.000446, "covariance": -0.0, "correlation": -0.0831, "has_text": true, "text_chars": 3020, "mu_floor": 0.2889, "constraint_binding": true}} +{"id": "T4_all_20251201_0307", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "DBB"], "decision_date": "2025-12-01", "context_summary": "LINK-USD \u03c3=0.0475, DBB \u03c3=0.0086, \u03c1=0.197. Min-variance weights: LINK-USD=0.000, DBB=1.000.", "question": "Assets: LINK-USD, DBB\nLINK-USD: annualized_mean_return=-1.9152, daily_std=0.0475\nDBB: annualized_mean_return=0.5292, daily_std=0.0086\nMinimum required portfolio return (annualized): -0.2277\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=0.0000, w_DBB=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000075 - 0.000081) / (0.002255 + 0.000075 - 0.000161)\n Unconstrained: w_LINK-USD=-0.0028\n After long-only clamp: w_LINK-USD=0.0000, w_DBB=1.0000.", "metadata": {"weights": {"LINK-USD": 0.0, "DBB": 1.0}, "sigma_1": 0.047491, "sigma_2": 0.008635, "covariance": 8.1e-05, "correlation": 0.1969, "has_text": true, "text_chars": 20, "mu_floor": -0.2277, "constraint_binding": false}} +{"id": "T4_all_20250606_0310", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "SHY"], "decision_date": "2025-06-06", "context_summary": "DOT-USD \u03c3=0.0401, SHY \u03c3=0.0011, \u03c1=0.120. Min-variance weights: DOT-USD=0.000, SHY=1.000.", "question": "Assets: DOT-USD, SHY\nDOT-USD: annualized_mean_return=0.3780, daily_std=0.0401\nSHY: annualized_mean_return=0.0504, daily_std=0.0011\nMinimum required portfolio return (annualized): 0.2343\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_SHY) 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_SHY=X.XXXX", "answer": "w_DOT-USD=0.5614, w_SHY=0.4386", "answer_numeric": 0.5614, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000005) / (0.001607 + 0.000001 - 0.000010)\n Unconstrained: w_DOT-USD=-0.0025\n After long-only clamp: w_DOT-USD=0.0000, w_SHY=1.0000.", "metadata": {"weights": {"DOT-USD": 0.5614, "SHY": 0.4386}, "sigma_1": 0.040089, "sigma_2": 0.001066, "covariance": 5e-06, "correlation": 0.1205, "has_text": true, "text_chars": 20, "mu_floor": 0.2343, "constraint_binding": true}} +{"id": "T4_all_20250717_0312", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "HAUZ"], "decision_date": "2025-07-17", "context_summary": "FXI \u03c3=0.0125, HAUZ \u03c3=0.0070, \u03c1=0.172. Min-variance weights: FXI=0.192, HAUZ=0.808.", "question": "Assets: FXI, HAUZ\nFXI: annualized_mean_return=0.6804, daily_std=0.0125\nHAUZ: annualized_mean_return=0.3528, daily_std=0.0070\nMinimum required portfolio return (annualized): 0.6069\nMarket regime: bull\n\nCompute portfolio weights (w_FXI, w_HAUZ) 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_HAUZ=X.XXXX", "answer": "w_FXI=0.7756, w_HAUZ=0.2244", "answer_numeric": 0.7756, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000048 - 0.000015) / (0.000156 + 0.000048 - 0.000030)\n Unconstrained: w_FXI=0.1920\n After long-only clamp: w_FXI=0.1920, w_HAUZ=0.8080.", "metadata": {"weights": {"FXI": 0.7756, "HAUZ": 0.2244}, "sigma_1": 0.012492, "sigma_2": 0.00696, "covariance": 1.5e-05, "correlation": 0.1716, "has_text": true, "text_chars": 3020, "mu_floor": 0.6069, "constraint_binding": true}} +{"id": "T4_all_20250626_0315", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "SCHH"], "decision_date": "2025-06-26", "context_summary": "ETH-USD \u03c3=0.0378, SCHH \u03c3=0.0130, \u03c1=-0.046. Min-variance weights: ETH-USD=0.117, SCHH=0.883.", "question": "Assets: ETH-USD, SCHH\nETH-USD: annualized_mean_return=1.1592, daily_std=0.0378\nSCHH: annualized_mean_return=-0.0756, daily_std=0.0130\nMinimum required portfolio return (annualized): 0.0003\nMarket regime: sideways\n\nCompute portfolio weights (w_ETH-USD, w_SCHH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_SCHH=X.XXXX", "answer": "w_ETH-USD=0.1166, w_SCHH=0.8834", "answer_numeric": 0.1166, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000169 - -0.000022) / (0.001427 + 0.000169 - -0.000045)\n Unconstrained: w_ETH-USD=0.1168\n After long-only clamp: w_ETH-USD=0.1168, w_SCHH=0.8832.", "metadata": {"weights": {"ETH-USD": 0.1166, "SCHH": 0.8834}, "sigma_1": 0.037774, "sigma_2": 0.013011, "covariance": -2.2e-05, "correlation": -0.0456, "has_text": true, "text_chars": 20, "mu_floor": 0.0003, "constraint_binding": false}} +{"id": "T4_all_20250627_0318", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "TLH"], "decision_date": "2025-06-27", "context_summary": "ACWI \u03c3=0.0116, TLH \u03c3=0.0074, \u03c1=0.269. Min-variance weights: ACWI=0.223, TLH=0.777.", "question": "Assets: ACWI, TLH\nACWI: annualized_mean_return=0.3276, daily_std=0.0116\nTLH: annualized_mean_return=-0.0252, daily_std=0.0074\nMinimum required portfolio return (annualized): 0.1830\nMarket regime: sideways\n\nCompute portfolio weights (w_ACWI, w_TLH) 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_TLH=X.XXXX", "answer": "w_ACWI=0.5901, w_TLH=0.4099", "answer_numeric": 0.5901, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000055 - 0.000023) / (0.000135 + 0.000055 - 0.000047)\n Unconstrained: w_ACWI=0.2227\n After long-only clamp: w_ACWI=0.2227, w_TLH=0.7773.", "metadata": {"weights": {"ACWI": 0.5901, "TLH": 0.4099}, "sigma_1": 0.011625, "sigma_2": 0.007437, "covariance": 2.3e-05, "correlation": 0.269, "has_text": true, "text_chars": 3020, "mu_floor": 0.183, "constraint_binding": true}} +{"id": "T4_all_20250313_0320", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLK", "PPLT"], "decision_date": "2025-03-13", "context_summary": "XLK \u03c3=0.0161, PPLT \u03c3=0.0107, \u03c1=0.006. Min-variance weights: XLK=0.306, PPLT=0.694.", "question": "Assets: XLK, PPLT\nXLK: annualized_mean_return=-0.4788, daily_std=0.0161\nPPLT: annualized_mean_return=0.3276, daily_std=0.0107\nMinimum required portfolio return (annualized): 0.2379\nMarket regime: bear\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=0.1112, w_PPLT=0.8888", "answer_numeric": 0.1112, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000114 - 0.000001) / (0.000258 + 0.000114 - 0.000002)\n Unconstrained: w_XLK=0.3056\n After long-only clamp: w_XLK=0.3056, w_PPLT=0.6944.", "metadata": {"weights": {"XLK": 0.1112, "PPLT": 0.8888}, "sigma_1": 0.016062, "sigma_2": 0.010679, "covariance": 1e-06, "correlation": 0.0055, "has_text": true, "text_chars": 3020, "mu_floor": 0.2379, "constraint_binding": true}} +{"id": "T4_all_20250916_0323", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SOL-USD", "CPER"], "decision_date": "2025-09-16", "context_summary": "SOL-USD \u03c3=0.0408, CPER \u03c3=0.0130, \u03c1=-0.018. Min-variance weights: SOL-USD=0.096, CPER=0.904.", "question": "Assets: SOL-USD, CPER\nSOL-USD: annualized_mean_return=1.4112, daily_std=0.0408\nCPER: annualized_mean_return=0.3276, daily_std=0.0129\nMinimum required portfolio return (annualized): 0.3861\nMarket regime: bull\n\nCompute portfolio weights (w_SOL-USD, w_CPER) 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_CPER=X.XXXX", "answer": "w_SOL-USD=0.0959, w_CPER=0.9041", "answer_numeric": 0.0959, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000168 - -0.000010) / (0.001666 + 0.000168 - -0.000019)\n Unconstrained: w_SOL-USD=0.0957\n After long-only clamp: w_SOL-USD=0.0957, w_CPER=0.9043.", "metadata": {"weights": {"SOL-USD": 0.0959, "CPER": 0.9041}, "sigma_1": 0.040811, "sigma_2": 0.01295, "covariance": -1e-05, "correlation": -0.0181, "has_text": true, "text_chars": 20, "mu_floor": 0.3861, "constraint_binding": false}} +{"id": "T4_all_20250625_0326", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "IAU"], "decision_date": "2025-06-25", "context_summary": "DOT-USD \u03c3=0.0391, IAU \u03c3=0.0145, \u03c1=0.033. Min-variance weights: DOT-USD=0.113, IAU=0.887.", "question": "Assets: DOT-USD, IAU\nDOT-USD: annualized_mean_return=-0.7056, daily_std=0.0391\nIAU: annualized_mean_return=0.1764, daily_std=0.0145\nMinimum required portfolio return (annualized): 0.1185\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_IAU) 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_IAU=X.XXXX", "answer": "w_DOT-USD=0.0656, w_IAU=0.9344", "answer_numeric": 0.0656, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000210 - 0.000019) / (0.001527 + 0.000210 - 0.000038)\n Unconstrained: w_DOT-USD=0.1125\n After long-only clamp: w_DOT-USD=0.1125, w_IAU=0.8875.", "metadata": {"weights": {"DOT-USD": 0.0656, "IAU": 0.9344}, "sigma_1": 0.039079, "sigma_2": 0.014497, "covariance": 1.9e-05, "correlation": 0.0334, "has_text": true, "text_chars": 20, "mu_floor": 0.1185, "constraint_binding": true}} +{"id": "T4_all_20250821_0329", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD", "HYG"], "decision_date": "2025-08-21", "context_summary": "BTC-USD \u03c3=0.0153, HYG \u03c3=0.0017, \u03c1=0.084. Min-variance weights: BTC-USD=0.003, HYG=0.997.", "question": "Assets: BTC-USD, HYG\nBTC-USD: annualized_mean_return=0.5040, daily_std=0.0153\nHYG: annualized_mean_return=0.1260, daily_std=0.0017\nMinimum required portfolio return (annualized): 0.1269\nMarket regime: bull\n\nCompute portfolio weights (w_BTC-USD, w_HYG) 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_HYG=X.XXXX", "answer": "w_BTC-USD=0.0032, w_HYG=0.9968", "answer_numeric": 0.0032, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000003 - 0.000002) / (0.000235 + 0.000003 - 0.000004)\n Unconstrained: w_BTC-USD=0.0027\n After long-only clamp: w_BTC-USD=0.0027, w_HYG=0.9973.", "metadata": {"weights": {"BTC-USD": 0.0032, "HYG": 0.9968}, "sigma_1": 0.015328, "sigma_2": 0.001661, "covariance": 2e-06, "correlation": 0.0837, "has_text": true, "text_chars": 20, "mu_floor": 0.1269, "constraint_binding": false}} +{"id": "T4_all_20250707_0331", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "LQD"], "decision_date": "2025-07-07", "context_summary": "QUAL \u03c3=0.0111, LQD \u03c3=0.0042, \u03c1=-0.273. Min-variance weights: QUAL=0.185, LQD=0.815.", "question": "Assets: QUAL, LQD\nQUAL: annualized_mean_return=0.5040, daily_std=0.0111\nLQD: annualized_mean_return=0.2016, daily_std=0.0042\nMinimum required portfolio return (annualized): 0.2415\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_LQD) 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_LQD=X.XXXX", "answer": "w_QUAL=0.1860, w_LQD=0.8140", "answer_numeric": 0.186, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000018 - -0.000013) / (0.000122 + 0.000018 - -0.000026)\n Unconstrained: w_QUAL=0.1851\n After long-only clamp: w_QUAL=0.1851, w_LQD=0.8149.", "metadata": {"weights": {"QUAL": 0.186, "LQD": 0.814}, "sigma_1": 0.011059, "sigma_2": 0.004232, "covariance": -1.3e-05, "correlation": -0.2726, "has_text": true, "text_chars": 3020, "mu_floor": 0.2415, "constraint_binding": false}} +{"id": "T4_all_20250624_0333", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "CSHI"], "decision_date": "2025-06-24", "context_summary": "LINK-USD \u03c3=0.0407, CSHI \u03c3=0.0008, \u03c1=0.141. Min-variance weights: LINK-USD=0.000, CSHI=1.000.", "question": "Assets: LINK-USD, CSHI\nLINK-USD: annualized_mean_return=-0.4536, daily_std=0.0407\nCSHI: annualized_mean_return=0.0504, daily_std=0.0008\nMinimum required portfolio return (annualized): -0.1309\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_CSHI=X.XXXX", "answer": "w_LINK-USD=0.0000, w_CSHI=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - 0.000004) / (0.001654 + 0.000001 - 0.000009)\n Unconstrained: w_LINK-USD=-0.0023\n After long-only clamp: w_LINK-USD=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"LINK-USD": 0.0, "CSHI": 1.0}, "sigma_1": 0.040665, "sigma_2": 0.000759, "covariance": 4e-06, "correlation": 0.1415, "has_text": true, "text_chars": 20, "mu_floor": -0.1309, "constraint_binding": false}} +{"id": "T4_all_20251016_0336", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VTI", "MORT"], "decision_date": "2025-10-16", "context_summary": "VTI \u03c3=0.0070, MORT \u03c3=0.0099, \u03c1=0.419. Min-variance weights: VTI=0.780, MORT=0.220.", "question": "Assets: VTI, MORT\nVTI: annualized_mean_return=0.2520, daily_std=0.0070\nMORT: annualized_mean_return=0.1008, daily_std=0.0099\nMinimum required portfolio return (annualized): 0.2386\nMarket regime: bull\n\nCompute portfolio weights (w_VTI, w_MORT) 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_MORT=X.XXXX", "answer": "w_VTI=0.9114, w_MORT=0.0886", "answer_numeric": 0.9114, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000099 - 0.000029) / (0.000049 + 0.000099 - 0.000058)\n Unconstrained: w_VTI=0.7802\n After long-only clamp: w_VTI=0.7802, w_MORT=0.2198.", "metadata": {"weights": {"VTI": 0.9114, "MORT": 0.0886}, "sigma_1": 0.00697, "sigma_2": 0.009928, "covariance": 2.9e-05, "correlation": 0.419, "has_text": true, "text_chars": 3020, "mu_floor": 0.2386, "constraint_binding": true}} +{"id": "T4_all_20251211_0339", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "CSHI"], "decision_date": "2025-12-11", "context_summary": "SOL-USD \u03c3=0.0413, CSHI \u03c3=0.0007, \u03c1=0.072. Min-variance weights: SOL-USD=0.000, CSHI=1.000.", "question": "Assets: SOL-USD, CSHI\nSOL-USD: annualized_mean_return=-0.9072, daily_std=0.0413\nCSHI: annualized_mean_return=0.0504, daily_std=0.0007\nMinimum required portfolio return (annualized): 0.0403\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_CSHI) 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_CSHI=X.XXXX", "answer": "w_SOL-USD=0.0000, w_CSHI=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000002) / (0.001704 + 0.000000 - 0.000004)\n Unconstrained: w_SOL-USD=-0.0009\n After long-only clamp: w_SOL-USD=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"SOL-USD": 0.0, "CSHI": 1.0}, "sigma_1": 0.041285, "sigma_2": 0.000667, "covariance": 2e-06, "correlation": 0.0718, "has_text": true, "text_chars": 20, "mu_floor": 0.0403, "constraint_binding": false}} +{"id": "T4_all_20250724_0342", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "PPLT"], "decision_date": "2025-07-24", "context_summary": "VLUE \u03c3=0.0085, PPLT \u03c3=0.0235, \u03c1=0.004. Min-variance weights: VLUE=0.884, PPLT=0.116.", "question": "Assets: VLUE, PPLT\nVLUE: annualized_mean_return=0.6048, daily_std=0.0085\nPPLT: annualized_mean_return=1.6128, daily_std=0.0235\nMinimum required portfolio return (annualized): 0.9338\nMarket regime: bull\n\nCompute portfolio weights (w_VLUE, w_PPLT) 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_PPLT=X.XXXX", "answer": "w_VLUE=0.6736, w_PPLT=0.3264", "answer_numeric": 0.6736, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000552 - 0.000001) / (0.000073 + 0.000552 - 0.000001)\n Unconstrained: w_VLUE=0.8843\n After long-only clamp: w_VLUE=0.8843, w_PPLT=0.1157.", "metadata": {"weights": {"VLUE": 0.6736, "PPLT": 0.3264}, "sigma_1": 0.008534, "sigma_2": 0.023491, "covariance": 1e-06, "correlation": 0.0035, "has_text": true, "text_chars": 3020, "mu_floor": 0.9338, "constraint_binding": true}} +{"id": "T4_all_20250404_0345", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VLUE", "VNQ"], "decision_date": "2025-04-04", "context_summary": "VLUE \u03c3=0.0101, VNQ \u03c3=0.0114, \u03c1=0.727. Min-variance weights: VLUE=0.715, VNQ=0.285.", "question": "Assets: VLUE, VNQ\nVLUE: annualized_mean_return=-0.1260, daily_std=0.0101\nVNQ: annualized_mean_return=0.0504, daily_std=0.0114\nMinimum required portfolio return (annualized): -0.0955\nMarket regime: bear\n\nCompute portfolio weights (w_VLUE, w_VNQ) 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_VNQ=X.XXXX", "answer": "w_VLUE=0.7143, w_VNQ=0.2857", "answer_numeric": 0.7143, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000129 - 0.000083) / (0.000101 + 0.000129 - 0.000166)\n Unconstrained: w_VLUE=0.7149\n After long-only clamp: w_VLUE=0.7149, w_VNQ=0.2851.", "metadata": {"weights": {"VLUE": 0.7143, "VNQ": 0.2857}, "sigma_1": 0.010067, "sigma_2": 0.011352, "covariance": 8.3e-05, "correlation": 0.727, "has_text": true, "text_chars": 3020, "mu_floor": -0.0955, "constraint_binding": false}} +{"id": "T4_all_20251001_0348", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["USMV", "BIL"], "decision_date": "2025-10-01", "context_summary": "USMV \u03c3=0.0051, BIL \u03c3=0.0001, \u03c1=-0.018. Min-variance weights: USMV=0.001, BIL=0.999.", "question": "Assets: USMV, BIL\nUSMV: annualized_mean_return=0.0756, daily_std=0.0051\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0666\nMarket regime: bull\n\nCompute portfolio weights (w_USMV, w_BIL) 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_BIL=X.XXXX", "answer": "w_USMV=0.6429, w_BIL=0.3571", "answer_numeric": 0.6429, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000026 + 0.000000 - -0.000000)\n Unconstrained: w_USMV=0.0014\n After long-only clamp: w_USMV=0.0014, w_BIL=0.9986.", "metadata": {"weights": {"USMV": 0.6429, "BIL": 0.3571}, "sigma_1": 0.005147, "sigma_2": 0.000148, "covariance": -0.0, "correlation": -0.0183, "has_text": true, "text_chars": 3020, "mu_floor": 0.0666, "constraint_binding": true}} +{"id": "T4_all_20251128_0350", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "VCIT"], "decision_date": "2025-11-28", "context_summary": "EFA \u03c3=0.0072, VCIT \u03c3=0.0020, \u03c1=0.153. Min-variance weights: EFA=0.035, VCIT=0.965.", "question": "Assets: EFA, VCIT\nEFA: annualized_mean_return=0.1764, daily_std=0.0072\nVCIT: annualized_mean_return=0.1008, daily_std=0.0020\nMinimum required portfolio return (annualized): 0.1212\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=0.2698, w_VCIT=0.7302", "answer_numeric": 0.2698, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000004 - 0.000002) / (0.000052 + 0.000004 - 0.000004)\n Unconstrained: w_EFA=0.0349\n After long-only clamp: w_EFA=0.0349, w_VCIT=0.9651.", "metadata": {"weights": {"EFA": 0.2698, "VCIT": 0.7302}, "sigma_1": 0.007218, "sigma_2": 0.002004, "covariance": 2e-06, "correlation": 0.153, "has_text": true, "text_chars": 9046, "mu_floor": 0.1212, "constraint_binding": true}} +{"id": "T4_all_20250807_0353", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLU", "SCHH"], "decision_date": "2025-08-07", "context_summary": "XLU \u03c3=0.0089, SCHH \u03c3=0.0091, \u03c1=0.595. Min-variance weights: XLU=0.530, SCHH=0.470.", "question": "Assets: XLU, SCHH\nXLU: annualized_mean_return=0.3024, daily_std=0.0089\nSCHH: annualized_mean_return=-0.0000, daily_std=0.0091\nMinimum required portfolio return (annualized): 0.0745\nMarket regime: bull\n\nCompute portfolio weights (w_XLU, w_SCHH) 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_SCHH=X.XXXX", "answer": "w_XLU=0.5299, w_SCHH=0.4701", "answer_numeric": 0.5299, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000083 - 0.000048) / (0.000079 + 0.000083 - 0.000097)\n Unconstrained: w_XLU=0.5303\n After long-only clamp: w_XLU=0.5303, w_SCHH=0.4697.", "metadata": {"weights": {"XLU": 0.5299, "SCHH": 0.4701}, "sigma_1": 0.008903, "sigma_2": 0.009124, "covariance": 4.8e-05, "correlation": 0.5953, "has_text": true, "text_chars": 9045, "mu_floor": 0.0745, "constraint_binding": false}} +{"id": "T4_all_20250311_0356", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ADA-USD", "CORN"], "decision_date": "2025-03-11", "context_summary": "ADA-USD \u03c3=0.0603, CORN \u03c3=0.0116, \u03c1=-0.227. Min-variance weights: ADA-USD=0.072, CORN=0.928.", "question": "Assets: ADA-USD, CORN\nADA-USD: annualized_mean_return=-1.8396, daily_std=0.0603\nCORN: annualized_mean_return=0.2016, daily_std=0.0116\nMinimum required portfolio return (annualized): 0.1152\nMarket regime: sideways\n\nCompute portfolio weights (w_ADA-USD, w_CORN) 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_CORN=X.XXXX", "answer": "w_ADA-USD=0.0423, w_CORN=0.9577", "answer_numeric": 0.0423, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000135 - -0.000159) / (0.003641 + 0.000135 - -0.000318)\n Unconstrained: w_ADA-USD=0.0719\n After long-only clamp: w_ADA-USD=0.0719, w_CORN=0.9281.", "metadata": {"weights": {"ADA-USD": 0.0423, "CORN": 0.9577}, "sigma_1": 0.060342, "sigma_2": 0.01163, "covariance": -0.000159, "correlation": -0.2266, "has_text": true, "text_chars": 20, "mu_floor": 0.1152, "constraint_binding": true}} +{"id": "T4_all_20250708_0359", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "UNG"], "decision_date": "2025-07-08", "context_summary": "IVV \u03c3=0.0110, UNG \u03c3=0.0334, \u03c1=-0.016. Min-variance weights: IVV=0.898, UNG=0.102.", "question": "Assets: IVV, UNG\nIVV: annualized_mean_return=0.6552, daily_std=0.0110\nUNG: annualized_mean_return=-0.4284, daily_std=0.0333\nMinimum required portfolio return (annualized): 0.2769\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_UNG) 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_UNG=X.XXXX", "answer": "w_IVV=0.8983, w_UNG=0.1017", "answer_numeric": 0.8983, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001112 - -0.000006) / (0.000121 + 0.001112 - -0.000012)\n Unconstrained: w_IVV=0.8984\n After long-only clamp: w_IVV=0.8984, w_UNG=0.1016.", "metadata": {"weights": {"IVV": 0.8983, "UNG": 0.1017}, "sigma_1": 0.010982, "sigma_2": 0.03335, "covariance": -6e-06, "correlation": -0.0158, "has_text": true, "text_chars": 3020, "mu_floor": 0.2769, "constraint_binding": false}} +{"id": "T4_all_20250729_0361", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EEM", "SCHH"], "decision_date": "2025-07-29", "context_summary": "EEM \u03c3=0.0081, SCHH \u03c3=0.0086, \u03c1=0.258. Min-variance weights: EEM=0.538, SCHH=0.462.", "question": "Assets: EEM, SCHH\nEEM: annualized_mean_return=0.5292, daily_std=0.0081\nSCHH: annualized_mean_return=0.0756, daily_std=0.0086\nMinimum required portfolio return (annualized): 0.1800\nMarket regime: bull\n\nCompute portfolio weights (w_EEM, w_SCHH) 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_SCHH=X.XXXX", "answer": "w_EEM=0.5380, w_SCHH=0.4620", "answer_numeric": 0.538, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000074 - 0.000018) / (0.000066 + 0.000074 - 0.000036)\n Unconstrained: w_EEM=0.5380\n After long-only clamp: w_EEM=0.5380, w_SCHH=0.4620.", "metadata": {"weights": {"EEM": 0.538, "SCHH": 0.462}, "sigma_1": 0.008113, "sigma_2": 0.008584, "covariance": 1.8e-05, "correlation": 0.2576, "has_text": true, "text_chars": 3020, "mu_floor": 0.18, "constraint_binding": false}} +{"id": "T4_all_20250409_0364", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ETH-USD", "VLUE"], "decision_date": "2025-04-09", "context_summary": "ETH-USD \u03c3=0.0447, VLUE \u03c3=0.0112, \u03c1=0.176. Min-variance weights: ETH-USD=0.019, VLUE=0.981.", "question": "Assets: ETH-USD, VLUE\nETH-USD: annualized_mean_return=-2.1420, daily_std=0.0447\nVLUE: annualized_mean_return=-0.2772, daily_std=0.0112\nMinimum required portfolio return (annualized): -0.2857\nMarket regime: bear\n\nCompute portfolio weights (w_ETH-USD, w_VLUE) 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_VLUE=X.XXXX", "answer": "w_ETH-USD=0.0046, w_VLUE=0.9954", "answer_numeric": 0.0046, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000126 - 0.000088) / (0.001994 + 0.000126 - 0.000176)\n Unconstrained: w_ETH-USD=0.0194\n After long-only clamp: w_ETH-USD=0.0194, w_VLUE=0.9806.", "metadata": {"weights": {"ETH-USD": 0.0046, "VLUE": 0.9954}, "sigma_1": 0.044655, "sigma_2": 0.011207, "covariance": 8.8e-05, "correlation": 0.1756, "has_text": true, "text_chars": 20, "mu_floor": -0.2857, "constraint_binding": true}} +{"id": "T4_all_20251007_0367", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM", "SGOV"], "decision_date": "2025-10-07", "context_summary": "MTUM \u03c3=0.0068, SGOV \u03c3=0.0002, \u03c1=-0.035. Min-variance weights: MTUM=0.002, SGOV=0.999.", "question": "Assets: MTUM, SGOV\nMTUM: annualized_mean_return=0.3276, daily_std=0.0068\nSGOV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0505\nMarket regime: bull\n\nCompute portfolio weights (w_MTUM, w_SGOV) 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_SGOV=X.XXXX", "answer": "w_MTUM=0.0006, w_SGOV=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) / (0.000046 + 0.000000 - -0.000000)\n Unconstrained: w_MTUM=0.0015\n After long-only clamp: w_MTUM=0.0015, w_SGOV=0.9985.", "metadata": {"weights": {"MTUM": 0.0006, "SGOV": 0.9994}, "sigma_1": 0.006814, "sigma_2": 0.000171, "covariance": -0.0, "correlation": -0.0352, "has_text": true, "text_chars": 3020, "mu_floor": 0.0505, "constraint_binding": false}} +{"id": "T4_all_20251127_0370", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["AVAX-USD", "FXI"], "decision_date": "2025-11-27", "context_summary": "AVAX-USD \u03c3=0.0461, FXI \u03c3=0.0125, \u03c1=-0.167. Min-variance weights: AVAX-USD=0.102, FXI=0.898.", "question": "Assets: AVAX-USD, FXI\nAVAX-USD: annualized_mean_return=-2.0412, daily_std=0.0461\nFXI: annualized_mean_return=0.1008, daily_std=0.0125\nMinimum required portfolio return (annualized): 0.0068\nMarket regime: sideways\n\nCompute portfolio weights (w_AVAX-USD, w_FXI) 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_FXI=X.XXXX", "answer": "w_AVAX-USD=0.0439, w_FXI=0.9561", "answer_numeric": 0.0439, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000156 - -0.000096) / (0.002123 + 0.000156 - -0.000192)\n Unconstrained: w_AVAX-USD=0.1021\n After long-only clamp: w_AVAX-USD=0.1021, w_FXI=0.8979.", "metadata": {"weights": {"AVAX-USD": 0.0439, "FXI": 0.9561}, "sigma_1": 0.046072, "sigma_2": 0.012496, "covariance": -9.6e-05, "correlation": -0.1671, "has_text": true, "text_chars": 20, "mu_floor": 0.0068, "constraint_binding": true}} +{"id": "T4_all_20250128_0372", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "CSHI"], "decision_date": "2025-01-28", "context_summary": "FXI \u03c3=0.0179, CSHI \u03c3=0.0004, \u03c1=0.125. Min-variance weights: FXI=0.000, CSHI=1.000.", "question": "Assets: FXI, CSHI\nFXI: annualized_mean_return=-0.1008, daily_std=0.0179\nCSHI: annualized_mean_return=0.0756, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.0070\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_CSHI) 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_CSHI=X.XXXX", "answer": "w_FXI=0.0000, w_CSHI=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.000320 + 0.000000 - 0.000002)\n Unconstrained: w_FXI=-0.0022\n After long-only clamp: w_FXI=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"FXI": 0.0, "CSHI": 1.0}, "sigma_1": 0.017882, "sigma_2": 0.000368, "covariance": 1e-06, "correlation": 0.1252, "has_text": true, "text_chars": 9044, "mu_floor": 0.007, "constraint_binding": false}} +{"id": "T4_all_20250123_0377", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "BIL"], "decision_date": "2025-01-23", "context_summary": "BNB-USD \u03c3=0.0306, BIL \u03c3=0.0002, \u03c1=0.022. Min-variance weights: BNB-USD=0.000, BIL=1.000.", "question": "Assets: BNB-USD, BIL\nBNB-USD: annualized_mean_return=0.3780, daily_std=0.0306\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_BIL) 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_BIL=X.XXXX", "answer": "w_BNB-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) / (0.000933 + 0.000000 - 0.000000)\n Unconstrained: w_BNB-USD=-0.0001\n After long-only clamp: w_BNB-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"BNB-USD": 0.0, "BIL": 1.0}, "sigma_1": 0.03055, "sigma_2": 0.000152, "covariance": 0.0, "correlation": 0.0219, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20250416_0379", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLF", "CSHI"], "decision_date": "2025-04-16", "context_summary": "XLF \u03c3=0.0135, CSHI \u03c3=0.0032, \u03c1=-0.066. Min-variance weights: XLF=0.064, CSHI=0.936.", "question": "Assets: XLF, CSHI\nXLF: annualized_mean_return=-0.1764, daily_std=0.0135\nCSHI: annualized_mean_return=-0.0504, daily_std=0.0032\nMinimum required portfolio return (annualized): -0.1228\nMarket regime: bear\n\nCompute portfolio weights (w_XLF, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_CSHI=X.XXXX", "answer": "w_XLF=0.0653, w_CSHI=0.9347", "answer_numeric": 0.0653, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000010 - -0.000003) / (0.000183 + 0.000010 - -0.000006)\n Unconstrained: w_XLF=0.0644\n After long-only clamp: w_XLF=0.0644, w_CSHI=0.9356.", "metadata": {"weights": {"XLF": 0.0653, "CSHI": 0.9347}, "sigma_1": 0.013522, "sigma_2": 0.003158, "covariance": -3e-06, "correlation": -0.0657, "has_text": true, "text_chars": 3020, "mu_floor": -0.1228, "constraint_binding": false}} +{"id": "T4_all_20250102_0382", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "VNQ"], "decision_date": "2025-01-02", "context_summary": "XRP-USD \u03c3=0.0742, VNQ \u03c3=0.0101, \u03c1=-0.017. Min-variance weights: XRP-USD=0.020, VNQ=0.980.", "question": "Assets: XRP-USD, VNQ\nXRP-USD: annualized_mean_return=7.1064, daily_std=0.0742\nVNQ: annualized_mean_return=-0.2016, daily_std=0.0101\nMinimum required portfolio return (annualized): 5.5237\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_VNQ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XRP-USD=X.XXXX, w_VNQ=X.XXXX", "answer": "w_XRP-USD=0.7834, w_VNQ=0.2166", "answer_numeric": 0.7834, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000101 - -0.000013) / (0.005508 + 0.000101 - -0.000025)\n Unconstrained: w_XRP-USD=0.0202\n After long-only clamp: w_XRP-USD=0.0202, w_VNQ=0.9798.", "metadata": {"weights": {"XRP-USD": 0.7834, "VNQ": 0.2166}, "sigma_1": 0.074213, "sigma_2": 0.010052, "covariance": -1.3e-05, "correlation": -0.017, "has_text": true, "text_chars": 20, "mu_floor": 5.5237, "constraint_binding": true}} +{"id": "T4_all_20250305_0385", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "GLD"], "decision_date": "2025-03-05", "context_summary": "XLRE \u03c3=0.0106, GLD \u03c3=0.0087, \u03c1=0.280. Min-variance weights: XLRE=0.363, GLD=0.637.", "question": "Assets: XLRE, GLD\nXLRE: annualized_mean_return=-0.0504, daily_std=0.0106\nGLD: annualized_mean_return=0.2520, daily_std=0.0087\nMinimum required portfolio return (annualized): 0.0436\nMarket regime: sideways\n\nCompute portfolio weights (w_XLRE, w_GLD) 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_GLD=X.XXXX", "answer": "w_XLRE=0.3629, w_GLD=0.6371", "answer_numeric": 0.3629, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000075 - 0.000026) / (0.000113 + 0.000075 - 0.000052)\n Unconstrained: w_XLRE=0.3632\n After long-only clamp: w_XLRE=0.3632, w_GLD=0.6368.", "metadata": {"weights": {"XLRE": 0.3629, "GLD": 0.6371}, "sigma_1": 0.010616, "sigma_2": 0.008682, "covariance": 2.6e-05, "correlation": 0.28, "has_text": true, "text_chars": 9045, "mu_floor": 0.0436, "constraint_binding": false}} +{"id": "T4_all_20250220_0387", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "SGOV"], "decision_date": "2025-02-20", "context_summary": "ETH-USD \u03c3=0.0313, SGOV \u03c3=0.0001, \u03c1=0.003. Min-variance weights: ETH-USD=0.000, SGOV=1.000.", "question": "Assets: ETH-USD, SGOV\nETH-USD: annualized_mean_return=-0.7308, daily_std=0.0313\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.2367\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) / (0.000978 + 0.000000 - 0.000000)\n Unconstrained: w_ETH-USD=0.0000\n After long-only clamp: w_ETH-USD=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"ETH-USD": 0.0, "SGOV": 1.0}, "sigma_1": 0.031278, "sigma_2": 0.000136, "covariance": 0.0, "correlation": 0.0026, "has_text": true, "text_chars": 20, "mu_floor": -0.2367, "constraint_binding": false}} +{"id": "T4_all_20250213_0389", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "CPER"], "decision_date": "2025-02-13", "context_summary": "LINK-USD \u03c3=0.0493, CPER \u03c3=0.0114, \u03c1=0.049. Min-variance weights: LINK-USD=0.041, CPER=0.959.", "question": "Assets: LINK-USD, CPER\nLINK-USD: annualized_mean_return=-1.4364, daily_std=0.0493\nCPER: annualized_mean_return=0.4788, daily_std=0.0114\nMinimum required portfolio return (annualized): 0.2553\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_CPER) 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_CPER=X.XXXX", "answer": "w_LINK-USD=0.0412, w_CPER=0.9588", "answer_numeric": 0.0412, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000130 - 0.000027) / (0.002434 + 0.000130 - 0.000055)\n Unconstrained: w_LINK-USD=0.0411\n After long-only clamp: w_LINK-USD=0.0411, w_CPER=0.9589.", "metadata": {"weights": {"LINK-USD": 0.0412, "CPER": 0.9588}, "sigma_1": 0.049335, "sigma_2": 0.011422, "covariance": 2.7e-05, "correlation": 0.0486, "has_text": true, "text_chars": 20, "mu_floor": 0.2553, "constraint_binding": false}} +{"id": "T4_all_20251023_0392", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM", "SGOV"], "decision_date": "2025-10-23", "context_summary": "MTUM \u03c3=0.0076, SGOV \u03c3=0.0002, \u03c1=0.180. Min-variance weights: MTUM=0.000, SGOV=1.000.", "question": "Assets: MTUM, SGOV\nMTUM: annualized_mean_return=0.1764, daily_std=0.0076\nSGOV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.1459\nMarket regime: bull\n\nCompute portfolio weights (w_MTUM, w_SGOV) 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_SGOV=X.XXXX", "answer": "w_MTUM=0.7579, w_SGOV=0.2421", "answer_numeric": 0.7579, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000058 + 0.000000 - 0.000000)\n Unconstrained: w_MTUM=-0.0035\n After long-only clamp: w_MTUM=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"MTUM": 0.7579, "SGOV": 0.2421}, "sigma_1": 0.007637, "sigma_2": 0.000169, "covariance": 0.0, "correlation": 0.18, "has_text": true, "text_chars": 9045, "mu_floor": 0.1459, "constraint_binding": true}} +{"id": "T4_all_20251013_0395", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "IEF"], "decision_date": "2025-10-13", "context_summary": "VTI \u03c3=0.0067, IEF \u03c3=0.0030, \u03c1=-0.092. Min-variance weights: VTI=0.186, IEF=0.814.", "question": "Assets: VTI, IEF\nVTI: annualized_mean_return=0.1764, daily_std=0.0067\nIEF: annualized_mean_return=0.1260, daily_std=0.0030\nMinimum required portfolio return (annualized): 0.1307\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_IEF) 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_IEF=X.XXXX", "answer": "w_VTI=0.1882, w_IEF=0.8118", "answer_numeric": 0.1882, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000009 - -0.000002) / (0.000045 + 0.000009 - -0.000004)\n Unconstrained: w_VTI=0.1863\n After long-only clamp: w_VTI=0.1863, w_IEF=0.8137.", "metadata": {"weights": {"VTI": 0.1882, "IEF": 0.8118}, "sigma_1": 0.00668, "sigma_2": 0.002968, "covariance": -2e-06, "correlation": -0.0919, "has_text": true, "text_chars": 3020, "mu_floor": 0.1307, "constraint_binding": false}} +{"id": "T4_all_20250122_0399", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "UNG"], "decision_date": "2025-01-22", "context_summary": "BTC-USD \u03c3=0.0242, UNG \u03c3=0.0482, \u03c1=0.222. Min-variance weights: BTC-USD=0.863, UNG=0.137.", "question": "Assets: BTC-USD, UNG\nBTC-USD: annualized_mean_return=0.3780, daily_std=0.0242\nUNG: annualized_mean_return=0.5796, daily_std=0.0482\nMinimum required portfolio return (annualized): 0.3973\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=0.8630, w_UNG=0.1370", "answer_numeric": 0.863, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.002326 - 0.000260) / (0.000588 + 0.002326 - 0.000519)\n Unconstrained: w_BTC-USD=0.8629\n After long-only clamp: w_BTC-USD=0.8629, w_UNG=0.1371.", "metadata": {"weights": {"BTC-USD": 0.863, "UNG": 0.137}, "sigma_1": 0.024248, "sigma_2": 0.048232, "covariance": 0.00026, "correlation": 0.2219, "has_text": true, "text_chars": 20, "mu_floor": 0.3973, "constraint_binding": false}} +{"id": "T4_all_20250806_0402", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLP", "BNDX"], "decision_date": "2025-08-06", "context_summary": "XLP \u03c3=0.0071, BNDX \u03c3=0.0019, \u03c1=-0.130. Min-variance weights: XLP=0.095, BNDX=0.905.", "question": "Assets: XLP, BNDX\nXLP: annualized_mean_return=-0.0252, daily_std=0.0071\nBNDX: annualized_mean_return=0.1260, daily_std=0.0019\nMinimum required portfolio return (annualized): 0.1202\nMarket regime: bull\n\nCompute portfolio weights (w_XLP, w_BNDX) 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_BNDX=X.XXXX", "answer": "w_XLP=0.0384, w_BNDX=0.9616", "answer_numeric": 0.0384, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000004 - -0.000002) / (0.000051 + 0.000004 - -0.000004)\n Unconstrained: w_XLP=0.0945\n After long-only clamp: w_XLP=0.0945, w_BNDX=0.9055.", "metadata": {"weights": {"XLP": 0.0384, "BNDX": 0.9616}, "sigma_1": 0.007117, "sigma_2": 0.001922, "covariance": -2e-06, "correlation": -0.1301, "has_text": true, "text_chars": 9045, "mu_floor": 0.1202, "constraint_binding": true}} +{"id": "T4_all_20250901_0405", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "XHB"], "decision_date": "2025-09-01", "context_summary": "IWM \u03c3=0.0114, XHB \u03c3=0.0177, \u03c1=0.710. Min-variance weights: IWM=1.000, XHB=0.000.", "question": "Assets: IWM, XHB\nIWM: annualized_mean_return=0.5040, daily_std=0.0114\nXHB: annualized_mean_return=0.6804, daily_std=0.0177\nMinimum required portfolio return (annualized): 0.5040\nMarket regime: bull\n\nCompute portfolio weights (w_IWM, w_XHB) 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_XHB=X.XXXX", "answer": "w_IWM=1.0000, w_XHB=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000313 - 0.000143) / (0.000130 + 0.000313 - 0.000287)\n Unconstrained: w_IWM=1.0825\n After long-only clamp: w_IWM=1.0000, w_XHB=0.0000.", "metadata": {"weights": {"IWM": 1.0, "XHB": 0.0}, "sigma_1": 0.011422, "sigma_2": 0.017695, "covariance": 0.000143, "correlation": 0.7095, "has_text": true, "text_chars": 9045, "mu_floor": 0.504, "constraint_binding": false}} +{"id": "T4_all_20250929_0408", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLI", "VNQI"], "decision_date": "2025-09-29", "context_summary": "XLI \u03c3=0.0070, VNQI \u03c3=0.0067, \u03c1=0.448. Min-variance weights: XLI=0.463, VNQI=0.537.", "question": "Assets: XLI, VNQI\nXLI: annualized_mean_return=0.1512, daily_std=0.0070\nVNQI: annualized_mean_return=0.0756, daily_std=0.0067\nMinimum required portfolio return (annualized): 0.1426\nMarket regime: bull\n\nCompute portfolio weights (w_XLI, w_VNQI) 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_VNQI=X.XXXX", "answer": "w_XLI=0.8862, w_VNQI=0.1138", "answer_numeric": 0.8862, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000045 - 0.000021) / (0.000049 + 0.000045 - 0.000042)\n Unconstrained: w_XLI=0.4634\n After long-only clamp: w_XLI=0.4634, w_VNQI=0.5366.", "metadata": {"weights": {"XLI": 0.8862, "VNQI": 0.1138}, "sigma_1": 0.007011, "sigma_2": 0.006733, "covariance": 2.1e-05, "correlation": 0.4477, "has_text": true, "text_chars": 3020, "mu_floor": 0.1426, "constraint_binding": true}} +{"id": "T4_all_20250509_0412", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "SGOV"], "decision_date": "2025-05-09", "context_summary": "FXI \u03c3=0.0200, SGOV \u03c3=0.0001, \u03c1=0.119. Min-variance weights: FXI=0.000, SGOV=1.000.", "question": "Assets: FXI, SGOV\nFXI: annualized_mean_return=0.4284, daily_std=0.0200\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.2788\nMarket regime: sideways\n\nCompute portfolio weights (w_FXI, w_SGOV) 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_SGOV=X.XXXX", "answer": "w_FXI=0.6042, w_SGOV=0.3958", "answer_numeric": 0.6042, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000399 + 0.000000 - 0.000001)\n Unconstrained: w_FXI=-0.0008\n After long-only clamp: w_FXI=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"FXI": 0.6042, "SGOV": 0.3958}, "sigma_1": 0.019974, "sigma_2": 0.000144, "covariance": 0.0, "correlation": 0.1187, "has_text": true, "text_chars": 9045, "mu_floor": 0.2788, "constraint_binding": true}} +{"id": "T4_all_20251114_0415", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "SCHH"], "decision_date": "2025-11-14", "context_summary": "XLI \u03c3=0.0079, SCHH \u03c3=0.0081, \u03c1=0.408. Min-variance weights: XLI=0.520, SCHH=0.480.", "question": "Assets: XLI, SCHH\nXLI: annualized_mean_return=0.0504, daily_std=0.0079\nSCHH: annualized_mean_return=0.0000, daily_std=0.0081\nMinimum required portfolio return (annualized): 0.0157\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_SCHH) 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_SCHH=X.XXXX", "answer": "w_XLI=0.5195, w_SCHH=0.4805", "answer_numeric": 0.5195, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000066 - 0.000026) / (0.000063 + 0.000066 - 0.000053)\n Unconstrained: w_XLI=0.5197\n After long-only clamp: w_XLI=0.5197, w_SCHH=0.4803.", "metadata": {"weights": {"XLI": 0.5195, "SCHH": 0.4805}, "sigma_1": 0.007943, "sigma_2": 0.00813, "covariance": 2.6e-05, "correlation": 0.4084, "has_text": true, "text_chars": 9045, "mu_floor": 0.0157, "constraint_binding": false}} +{"id": "T4_all_20251202_0417", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "WEAT"], "decision_date": "2025-12-02", "context_summary": "BTC-USD \u03c3=0.0226, WEAT \u03c3=0.0112, \u03c1=0.080. Min-variance weights: BTC-USD=0.176, WEAT=0.824.", "question": "Assets: BTC-USD, WEAT\nBTC-USD: annualized_mean_return=-1.3356, daily_std=0.0226\nWEAT: annualized_mean_return=0.0504, daily_std=0.0112\nMinimum required portfolio return (annualized): -0.5615\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_WEAT) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_WEAT=X.XXXX", "answer": "w_BTC-USD=0.1764, w_WEAT=0.8236", "answer_numeric": 0.1764, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000125 - 0.000020) / (0.000509 + 0.000125 - 0.000040)\n Unconstrained: w_BTC-USD=0.1762\n After long-only clamp: w_BTC-USD=0.1762, w_WEAT=0.8238.", "metadata": {"weights": {"BTC-USD": 0.1764, "WEAT": 0.8236}, "sigma_1": 0.022568, "sigma_2": 0.011172, "covariance": 2e-05, "correlation": 0.0801, "has_text": true, "text_chars": 20, "mu_floor": -0.5615, "constraint_binding": false}} +{"id": "T4_all_20250312_0420", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "ICSH"], "decision_date": "2025-03-12", "context_summary": "SOL-USD \u03c3=0.0641, ICSH \u03c3=0.0003, \u03c1=0.004. Min-variance weights: SOL-USD=0.000, ICSH=1.000.", "question": "Assets: SOL-USD, ICSH\nSOL-USD: annualized_mean_return=-1.1844, daily_std=0.0641\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_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 - 0.000000) / (0.004115 + 0.000000 - 0.000000)\n Unconstrained: w_SOL-USD=-0.0000\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": 0.06415, "sigma_2": 0.000251, "covariance": 0.0, "correlation": 0.0043, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": true}} +{"id": "T4_all_20250722_0423", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD", "UNG"], "decision_date": "2025-07-22", "context_summary": "BTC-USD \u03c3=0.0160, UNG \u03c3=0.0339, \u03c1=0.163. Min-variance weights: BTC-USD=0.864, UNG=0.136.", "question": "Assets: BTC-USD, UNG\nBTC-USD: annualized_mean_return=0.2520, daily_std=0.0160\nUNG: annualized_mean_return=-0.4032, daily_std=0.0339\nMinimum required portfolio return (annualized): 0.0242\nMarket regime: bull\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=0.8635, w_UNG=0.1365", "answer_numeric": 0.8635, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001151 - 0.000088) / (0.000256 + 0.001151 - 0.000177)\n Unconstrained: w_BTC-USD=0.8637\n After long-only clamp: w_BTC-USD=0.8637, w_UNG=0.1363.", "metadata": {"weights": {"BTC-USD": 0.8635, "UNG": 0.1365}, "sigma_1": 0.015999, "sigma_2": 0.033922, "covariance": 8.8e-05, "correlation": 0.1628, "has_text": true, "text_chars": 20, "mu_floor": 0.0242, "constraint_binding": false}} +{"id": "T4_all_20251125_0426", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "CPER"], "decision_date": "2025-11-25", "context_summary": "XLB \u03c3=0.0095, CPER \u03c3=0.0141, \u03c1=0.120. Min-variance weights: XLB=0.713, CPER=0.287.", "question": "Assets: XLB, CPER\nXLB: annualized_mean_return=-0.2520, daily_std=0.0095\nCPER: annualized_mean_return=0.3780, daily_std=0.0141\nMinimum required portfolio return (annualized): 0.1099\nMarket regime: sideways\n\nCompute portfolio weights (w_XLB, w_CPER) 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_CPER=X.XXXX", "answer": "w_XLB=0.4256, w_CPER=0.5744", "answer_numeric": 0.4256, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000198 - 0.000016) / (0.000090 + 0.000198 - 0.000032)\n Unconstrained: w_XLB=0.7125\n After long-only clamp: w_XLB=0.7125, w_CPER=0.2875.", "metadata": {"weights": {"XLB": 0.4256, "CPER": 0.5744}, "sigma_1": 0.009464, "sigma_2": 0.014082, "covariance": 1.6e-05, "correlation": 0.1201, "has_text": true, "text_chars": 9046, "mu_floor": 0.1099, "constraint_binding": true}} +{"id": "T4_all_20251119_0429", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "AVAX-USD"], "decision_date": "2025-11-19", "context_summary": "VTI \u03c3=0.0074, AVAX-USD \u03c3=0.0468, \u03c1=0.043. Min-variance weights: VTI=0.982, AVAX-USD=0.018.", "question": "Assets: VTI, AVAX-USD\nVTI: annualized_mean_return=0.1008, daily_std=0.0074\nAVAX-USD: annualized_mean_return=-2.7972, daily_std=0.0468\nMinimum required portfolio return (annualized): -0.4849\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_AVAX-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_AVAX-USD=X.XXXX", "answer": "w_VTI=0.9821, w_AVAX-USD=0.0179", "answer_numeric": 0.9821, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.002186 - 0.000015) / (0.000054 + 0.002186 - 0.000030)\n Unconstrained: w_VTI=0.9821\n After long-only clamp: w_VTI=0.9821, w_AVAX-USD=0.0179.", "metadata": {"weights": {"VTI": 0.9821, "AVAX-USD": 0.0179}, "sigma_1": 0.00738, "sigma_2": 0.046759, "covariance": 1.5e-05, "correlation": 0.0432, "has_text": true, "text_chars": 9045, "mu_floor": -0.4849, "constraint_binding": false}} +{"id": "T4_all_20250715_0432", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "IEF"], "decision_date": "2025-07-15", "context_summary": "VLUE \u03c3=0.0095, IEF \u03c3=0.0037, \u03c1=-0.076. Min-variance weights: VLUE=0.152, IEF=0.848.", "question": "Assets: VLUE, IEF\nVLUE: annualized_mean_return=0.6300, daily_std=0.0095\nIEF: annualized_mean_return=0.0504, daily_std=0.0037\nMinimum required portfolio return (annualized): 0.4533\nMarket regime: bull\n\nCompute portfolio weights (w_VLUE, w_IEF) 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_IEF=X.XXXX", "answer": "w_VLUE=0.6951, w_IEF=0.3049", "answer_numeric": 0.6951, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000014 - -0.000003) / (0.000090 + 0.000014 - -0.000005)\n Unconstrained: w_VLUE=0.1521\n After long-only clamp: w_VLUE=0.1521, w_IEF=0.8479.", "metadata": {"weights": {"VLUE": 0.6951, "IEF": 0.3049}, "sigma_1": 0.009467, "sigma_2": 0.003726, "covariance": -3e-06, "correlation": -0.0756, "has_text": true, "text_chars": 3020, "mu_floor": 0.4533, "constraint_binding": true}} +{"id": "T4_all_20250718_0435", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD", "XHB"], "decision_date": "2025-07-18", "context_summary": "DOT-USD \u03c3=0.0344, XHB \u03c3=0.0172, \u03c1=-0.230. Min-variance weights: DOT-USD=0.246, XHB=0.754.", "question": "Assets: DOT-USD, XHB\nDOT-USD: annualized_mean_return=-0.3528, daily_std=0.0344\nXHB: annualized_mean_return=0.6300, daily_std=0.0172\nMinimum required portfolio return (annualized): 0.3482\nMarket regime: bull\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=0.2459, w_XHB=0.7541", "answer_numeric": 0.2459, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000295 - -0.000136) / (0.001185 + 0.000295 - -0.000272)\n Unconstrained: w_DOT-USD=0.2459\n After long-only clamp: w_DOT-USD=0.2459, w_XHB=0.7541.", "metadata": {"weights": {"DOT-USD": 0.2459, "XHB": 0.7541}, "sigma_1": 0.034426, "sigma_2": 0.017168, "covariance": -0.000136, "correlation": -0.2305, "has_text": true, "text_chars": 20, "mu_floor": 0.3482, "constraint_binding": false}} +{"id": "T4_all_20250820_0438", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VTI", "CSHI"], "decision_date": "2025-08-20", "context_summary": "VTI \u03c3=0.0065, CSHI \u03c3=0.0006, \u03c1=-0.045. Min-variance weights: VTI=0.013, CSHI=0.987.", "question": "Assets: VTI, CSHI\nVTI: annualized_mean_return=0.4032, daily_std=0.0065\nCSHI: annualized_mean_return=0.0504, daily_std=0.0006\nMinimum required portfolio return (annualized): 0.1556\nMarket regime: bull\n\nCompute portfolio weights (w_VTI, w_CSHI) 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_CSHI=X.XXXX", "answer": "w_VTI=0.2982, w_CSHI=0.7018", "answer_numeric": 0.2982, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000043 + 0.000000 - -0.000000)\n Unconstrained: w_VTI=0.0128\n After long-only clamp: w_VTI=0.0128, w_CSHI=0.9872.", "metadata": {"weights": {"VTI": 0.2982, "CSHI": 0.7018}, "sigma_1": 0.00654, "sigma_2": 0.000614, "covariance": -0.0, "correlation": -0.0454, "has_text": true, "text_chars": 3020, "mu_floor": 0.1556, "constraint_binding": true}} +{"id": "T4_all_20250805_0440", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLB", "BNDX"], "decision_date": "2025-08-05", "context_summary": "XLB \u03c3=0.0101, BNDX \u03c3=0.0019, \u03c1=-0.124. Min-variance weights: XLB=0.056, BNDX=0.944.", "question": "Assets: XLB, BNDX\nXLB: annualized_mean_return=0.2520, daily_std=0.0101\nBNDX: annualized_mean_return=0.1008, daily_std=0.0019\nMinimum required portfolio return (annualized): 0.1992\nMarket regime: bull\n\nCompute portfolio weights (w_XLB, w_BNDX) 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_BNDX=X.XXXX", "answer": "w_XLB=0.6508, w_BNDX=0.3492", "answer_numeric": 0.6508, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000004 - -0.000002) / (0.000102 + 0.000004 - -0.000005)\n Unconstrained: w_XLB=0.0563\n After long-only clamp: w_XLB=0.0563, w_BNDX=0.9437.", "metadata": {"weights": {"XLB": 0.6508, "BNDX": 0.3492}, "sigma_1": 0.010078, "sigma_2": 0.001944, "covariance": -2e-06, "correlation": -0.1235, "has_text": true, "text_chars": 9044, "mu_floor": 0.1992, "constraint_binding": true}} +{"id": "T4_all_20251224_0442", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "PDBC"], "decision_date": "2025-12-24", "context_summary": "VTI \u03c3=0.0083, PDBC \u03c3=0.0082, \u03c1=0.200. Min-variance weights: VTI=0.497, PDBC=0.503.", "question": "Assets: VTI, PDBC\nVTI: annualized_mean_return=0.1512, daily_std=0.0083\nPDBC: annualized_mean_return=0.2268, daily_std=0.0082\nMinimum required portfolio return (annualized): 0.2115\nMarket regime: sideways\n\nCompute portfolio weights (w_VTI, w_PDBC) 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_PDBC=X.XXXX", "answer": "w_VTI=0.2024, w_PDBC=0.7976", "answer_numeric": 0.2024, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000068 - 0.000014) / (0.000068 + 0.000068 - 0.000027)\n Unconstrained: w_VTI=0.4966\n After long-only clamp: w_VTI=0.4966, w_PDBC=0.5034.", "metadata": {"weights": {"VTI": 0.2024, "PDBC": 0.7976}, "sigma_1": 0.008276, "sigma_2": 0.008232, "covariance": 1.4e-05, "correlation": 0.2004, "has_text": true, "text_chars": 9045, "mu_floor": 0.2115, "constraint_binding": true}} +{"id": "T4_all_20250106_0445", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "VNQI"], "decision_date": "2025-01-06", "context_summary": "VTI \u03c3=0.0082, VNQI \u03c3=0.0079, \u03c1=0.373. Min-variance weights: VTI=0.469, VNQI=0.531.", "question": "Assets: VTI, VNQI\nVTI: annualized_mean_return=0.1512, daily_std=0.0082\nVNQI: annualized_mean_return=-0.3780, daily_std=0.0079\nMinimum required portfolio return (annualized): -0.2678\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=0.4694, w_VNQI=0.5306", "answer_numeric": 0.4694, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000062 - 0.000024) / (0.000067 + 0.000062 - 0.000048)\n Unconstrained: w_VTI=0.4692\n After long-only clamp: w_VTI=0.4692, w_VNQI=0.5308.", "metadata": {"weights": {"VTI": 0.4694, "VNQI": 0.5306}, "sigma_1": 0.008207, "sigma_2": 0.007896, "covariance": 2.4e-05, "correlation": 0.3732, "has_text": true, "text_chars": 9045, "mu_floor": -0.2678, "constraint_binding": false}} +{"id": "T4_all_20251222_0448", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BIL"], "decision_date": "2025-12-22", "context_summary": "VTI \u03c3=0.0083, BIL \u03c3=0.0001, \u03c1=-0.002. Min-variance weights: VTI=0.000, BIL=1.000.", "question": "Assets: VTI, BIL\nVTI: annualized_mean_return=0.1512, daily_std=0.0083\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0949\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=0.4415, w_BIL=0.5585", "answer_numeric": 0.4415, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000068 + 0.000000 - -0.000000)\n Unconstrained: w_VTI=0.0003\n After long-only clamp: w_VTI=0.0003, w_BIL=0.9997.", "metadata": {"weights": {"VTI": 0.4415, "BIL": 0.5585}, "sigma_1": 0.008265, "sigma_2": 0.000134, "covariance": -0.0, "correlation": -0.0022, "has_text": true, "text_chars": 9045, "mu_floor": 0.0949, "constraint_binding": true}} +{"id": "T4_all_20251217_0450", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "XHB"], "decision_date": "2025-12-17", "context_summary": "XLF \u03c3=0.0088, XHB \u03c3=0.0145, \u03c1=0.628. Min-variance weights: XLF=1.000, XHB=0.000.", "question": "Assets: XLF, XHB\nXLF: annualized_mean_return=0.0504, daily_std=0.0088\nXHB: annualized_mean_return=-0.1512, daily_std=0.0145\nMinimum required portfolio return (annualized): -0.0489\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_XHB) 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_XHB=X.XXXX", "answer": "w_XLF=1.0000, w_XHB=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000211 - 0.000080) / (0.000077 + 0.000211 - 0.000161)\n Unconstrained: w_XLF=1.0219\n After long-only clamp: w_XLF=1.0000, w_XHB=0.0000.", "metadata": {"weights": {"XLF": 1.0, "XHB": 0.0}, "sigma_1": 0.008803, "sigma_2": 0.014536, "covariance": 8e-05, "correlation": 0.6275, "has_text": true, "text_chars": 9045, "mu_floor": -0.0489, "constraint_binding": false}} +{"id": "T4_all_20251117_0453", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "IGOV"], "decision_date": "2025-11-17", "context_summary": "LINK-USD \u03c3=0.0487, IGOV \u03c3=0.0040, \u03c1=0.139. Min-variance weights: LINK-USD=0.000, IGOV=1.000.", "question": "Assets: LINK-USD, IGOV\nLINK-USD: annualized_mean_return=-1.9152, daily_std=0.0487\nIGOV: annualized_mean_return=0.0252, daily_std=0.0040\nMinimum required portfolio return (annualized): -0.4187\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_IGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_LINK-USD=X.XXXX, w_IGOV=X.XXXX", "answer": "w_LINK-USD=0.0000, w_IGOV=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000016 - 0.000027) / (0.002371 + 0.000016 - 0.000054)\n Unconstrained: w_LINK-USD=-0.0047\n After long-only clamp: w_LINK-USD=0.0000, w_IGOV=1.0000.", "metadata": {"weights": {"LINK-USD": 0.0, "IGOV": 1.0}, "sigma_1": 0.048697, "sigma_2": 0.003999, "covariance": 2.7e-05, "correlation": 0.1388, "has_text": true, "text_chars": 20, "mu_floor": -0.4187, "constraint_binding": false}} +{"id": "T4_all_20250410_0456", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["AVAX-USD", "MORT"], "decision_date": "2025-04-10", "context_summary": "AVAX-USD \u03c3=0.0591, MORT \u03c3=0.0144, \u03c1=0.197. Min-variance weights: AVAX-USD=0.012, MORT=0.988.", "question": "Assets: AVAX-USD, MORT\nAVAX-USD: annualized_mean_return=-0.7560, daily_std=0.0591\nMORT: annualized_mean_return=-0.0756, daily_std=0.0144\nMinimum required portfolio return (annualized): -0.0786\nMarket regime: bear\n\nCompute portfolio weights (w_AVAX-USD, w_MORT) 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_MORT=X.XXXX", "answer": "w_AVAX-USD=0.0044, w_MORT=0.9956", "answer_numeric": 0.0044, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000208 - 0.000168) / (0.003496 + 0.000208 - 0.000336)\n Unconstrained: w_AVAX-USD=0.0120\n After long-only clamp: w_AVAX-USD=0.0120, w_MORT=0.9880.", "metadata": {"weights": {"AVAX-USD": 0.0044, "MORT": 0.9956}, "sigma_1": 0.059126, "sigma_2": 0.014438, "covariance": 0.000168, "correlation": 0.1969, "has_text": true, "text_chars": 20, "mu_floor": -0.0786, "constraint_binding": true}} +{"id": "T4_all_20251010_0459", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QQQ", "PALL"], "decision_date": "2025-10-10", "context_summary": "QQQ \u03c3=0.0069, PALL \u03c3=0.0211, \u03c1=0.027. Min-variance weights: QQQ=0.910, PALL=0.090.", "question": "Assets: QQQ, PALL\nQQQ: annualized_mean_return=0.3780, daily_std=0.0069\nPALL: annualized_mean_return=0.3528, daily_std=0.0211\nMinimum required portfolio return (annualized): 0.3740\nMarket regime: bull\n\nCompute portfolio weights (w_QQQ, w_PALL) 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_PALL=X.XXXX", "answer": "w_QQQ=0.9097, w_PALL=0.0903", "answer_numeric": 0.9097, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000447 - 0.000004) / (0.000048 + 0.000447 - 0.000008)\n Unconstrained: w_QQQ=0.9097\n After long-only clamp: w_QQQ=0.9097, w_PALL=0.0903.", "metadata": {"weights": {"QQQ": 0.9097, "PALL": 0.0903}, "sigma_1": 0.006925, "sigma_2": 0.021142, "covariance": 4e-06, "correlation": 0.0273, "has_text": true, "text_chars": 3020, "mu_floor": 0.374, "constraint_binding": false}} +{"id": "T4_all_20250808_0462", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLB", "CPER"], "decision_date": "2025-08-08", "context_summary": "XLB \u03c3=0.0097, CPER \u03c3=0.0160, \u03c1=0.323. Min-variance weights: XLB=0.824, CPER=0.176.", "question": "Assets: XLB, CPER\nXLB: annualized_mean_return=0.1008, daily_std=0.0097\nCPER: annualized_mean_return=0.5796, daily_std=0.0160\nMinimum required portfolio return (annualized): 0.3948\nMarket regime: bull\n\nCompute portfolio weights (w_XLB, w_CPER) 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_CPER=X.XXXX", "answer": "w_XLB=0.3860, w_CPER=0.6140", "answer_numeric": 0.386, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000255 - 0.000050) / (0.000094 + 0.000255 - 0.000100)\n Unconstrained: w_XLB=0.8239\n After long-only clamp: w_XLB=0.8239, w_CPER=0.1761.", "metadata": {"weights": {"XLB": 0.386, "CPER": 0.614}, "sigma_1": 0.009683, "sigma_2": 0.01596, "covariance": 5e-05, "correlation": 0.3235, "has_text": true, "text_chars": 9045, "mu_floor": 0.3948, "constraint_binding": true}} +{"id": "T4_all_20251120_0465", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "TIP"], "decision_date": "2025-11-20", "context_summary": "EWJ \u03c3=0.0101, TIP \u03c3=0.0008, \u03c1=-0.066. Min-variance weights: EWJ=0.011, TIP=0.989.", "question": "Assets: EWJ, TIP\nEWJ: annualized_mean_return=0.1260, daily_std=0.0101\nTIP: annualized_mean_return=0.0000, daily_std=0.0008\nMinimum required portfolio return (annualized): 0.0015\nMarket regime: sideways\n\nCompute portfolio weights (w_EWJ, w_TIP) 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_TIP=X.XXXX", "answer": "w_EWJ=0.0152, w_TIP=0.9848", "answer_numeric": 0.0152, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - -0.000001) / (0.000102 + 0.000001 - -0.000001)\n Unconstrained: w_EWJ=0.0107\n After long-only clamp: w_EWJ=0.0107, w_TIP=0.9893.", "metadata": {"weights": {"EWJ": 0.0152, "TIP": 0.9848}, "sigma_1": 0.010087, "sigma_2": 0.000768, "covariance": -1e-06, "correlation": -0.0663, "has_text": true, "text_chars": 9046, "mu_floor": 0.0015, "constraint_binding": false}} +{"id": "T4_all_20250903_0467", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "ETH-USD"], "decision_date": "2025-09-03", "context_summary": "QUAL \u03c3=0.0066, ETH-USD \u03c3=0.0389, \u03c1=-0.078. Min-variance weights: QUAL=0.960, ETH-USD=0.040.", "question": "Assets: QUAL, ETH-USD\nQUAL: annualized_mean_return=0.2016, daily_std=0.0066\nETH-USD: annualized_mean_return=2.4948, daily_std=0.0389\nMinimum required portfolio return (annualized): 0.2584\nMarket regime: bull\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=0.9602, w_ETH-USD=0.0398", "answer_numeric": 0.9602, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001511 - -0.000020) / (0.000043 + 0.001511 - -0.000040)\n Unconstrained: w_QUAL=0.9603\n After long-only clamp: w_QUAL=0.9603, w_ETH-USD=0.0397.", "metadata": {"weights": {"QUAL": 0.9602, "ETH-USD": 0.0398}, "sigma_1": 0.00659, "sigma_2": 0.038873, "covariance": -2e-05, "correlation": -0.0777, "has_text": true, "text_chars": 3020, "mu_floor": 0.2584, "constraint_binding": false}} +{"id": "T4_all_20250919_0470", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD", "ITB"], "decision_date": "2025-09-19", "context_summary": "BNB-USD \u03c3=0.0229, ITB \u03c3=0.0189, \u03c1=-0.031. Min-variance weights: BNB-USD=0.409, ITB=0.591.", "question": "Assets: BNB-USD, ITB\nBNB-USD: annualized_mean_return=1.1592, daily_std=0.0229\nITB: annualized_mean_return=0.6300, daily_std=0.0189\nMinimum required portfolio return (annualized): 1.0148\nMarket regime: bull\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=0.7271, w_ITB=0.2729", "answer_numeric": 0.7271, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000357 - -0.000014) / (0.000523 + 0.000357 - -0.000027)\n Unconstrained: w_BNB-USD=0.4088\n After long-only clamp: w_BNB-USD=0.4088, w_ITB=0.5912.", "metadata": {"weights": {"BNB-USD": 0.7271, "ITB": 0.2729}, "sigma_1": 0.022864, "sigma_2": 0.018902, "covariance": -1.4e-05, "correlation": -0.0312, "has_text": true, "text_chars": 20, "mu_floor": 1.0148, "constraint_binding": true}} +{"id": "T4_all_20250623_0473", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "SGOV"], "decision_date": "2025-06-23", "context_summary": "QUAL \u03c3=0.0129, SGOV \u03c3=0.0001, \u03c1=-0.165. Min-variance weights: QUAL=0.002, SGOV=0.998.", "question": "Assets: QUAL, SGOV\nQUAL: annualized_mean_return=-0.0756, daily_std=0.0129\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0047\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_SGOV) 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_SGOV=X.XXXX", "answer": "w_QUAL=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) / (0.000168 + 0.000000 - -0.000001)\n Unconstrained: w_QUAL=0.0018\n After long-only clamp: w_QUAL=0.0018, w_SGOV=0.9982.", "metadata": {"weights": {"QUAL": 0.0001, "SGOV": 0.9999}, "sigma_1": 0.012946, "sigma_2": 0.000132, "covariance": -0.0, "correlation": -0.1645, "has_text": true, "text_chars": 3020, "mu_floor": 0.0047, "constraint_binding": false}} +{"id": "T4_all_20251230_0476", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XRP-USD", "SGOV"], "decision_date": "2025-12-30", "context_summary": "XRP-USD \u03c3=0.0338, SGOV \u03c3=0.0001, \u03c1=0.102. Min-variance weights: XRP-USD=0.000, SGOV=1.000.", "question": "Assets: XRP-USD, SGOV\nXRP-USD: annualized_mean_return=-1.0080, daily_std=0.0338\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_XRP-USD, w_SGOV) 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_SGOV=X.XXXX", "answer": "w_XRP-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) / (0.001146 + 0.000000 - 0.000001)\n Unconstrained: w_XRP-USD=-0.0004\n After long-only clamp: w_XRP-USD=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"XRP-USD": -0.0, "SGOV": 1.0}, "sigma_1": 0.033849, "sigma_2": 0.00012, "covariance": 0.0, "correlation": 0.1024, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": true}} +{"id": "T4_all_20250714_0481", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EFA", "SOL-USD"], "decision_date": "2025-07-14", "context_summary": "EFA \u03c3=0.0073, SOL-USD \u03c3=0.0321, \u03c1=-0.254. Min-variance weights: EFA=0.906, SOL-USD=0.094.", "question": "Assets: EFA, SOL-USD\nEFA: annualized_mean_return=0.5292, daily_std=0.0073\nSOL-USD: annualized_mean_return=-0.2520, daily_std=0.0321\nMinimum required portfolio return (annualized): 0.1250\nMarket regime: bull\n\nCompute portfolio weights (w_EFA, w_SOL-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EFA=X.XXXX, w_SOL-USD=X.XXXX", "answer": "w_EFA=0.9058, w_SOL-USD=0.0942", "answer_numeric": 0.9058, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001033 - -0.000060) / (0.000054 + 0.001033 - -0.000120)\n Unconstrained: w_EFA=0.9059\n After long-only clamp: w_EFA=0.9059, w_SOL-USD=0.0941.", "metadata": {"weights": {"EFA": 0.9058, "SOL-USD": 0.0942}, "sigma_1": 0.007331, "sigma_2": 0.032145, "covariance": -6e-05, "correlation": -0.2538, "has_text": true, "text_chars": 3020, "mu_floor": 0.125, "constraint_binding": false}} +{"id": "T4_all_20251203_0483", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "CSHI"], "decision_date": "2025-12-03", "context_summary": "IVV \u03c3=0.0078, CSHI \u03c3=0.0007, \u03c1=-0.028. Min-variance weights: IVV=0.010, CSHI=0.990.", "question": "Assets: IVV, CSHI\nIVV: annualized_mean_return=0.2268, daily_std=0.0078\nCSHI: annualized_mean_return=0.0504, daily_std=0.0007\nMinimum required portfolio return (annualized): 0.0517\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_CSHI) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IVV=X.XXXX, w_CSHI=X.XXXX", "answer": "w_IVV=0.0079, w_CSHI=0.9921", "answer_numeric": 0.0079, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000060 + 0.000000 - -0.000000)\n Unconstrained: w_IVV=0.0103\n After long-only clamp: w_IVV=0.0103, w_CSHI=0.9897.", "metadata": {"weights": {"IVV": 0.0079, "CSHI": 0.9921}, "sigma_1": 0.007756, "sigma_2": 0.00069, "covariance": -0.0, "correlation": -0.0284, "has_text": true, "text_chars": 9046, "mu_floor": 0.0517, "constraint_binding": false}} +{"id": "T4_all_20250612_0486", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BIL"], "decision_date": "2025-06-12", "context_summary": "VTI \u03c3=0.0134, BIL \u03c3=0.0002, \u03c1=-0.245. Min-variance weights: VTI=0.003, BIL=0.997.", "question": "Assets: VTI, BIL\nVTI: annualized_mean_return=0.1764, daily_std=0.0134\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.1208\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=0.5587, w_BIL=0.4413", "answer_numeric": 0.5587, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.000179 + 0.000000 - -0.000001)\n Unconstrained: w_VTI=0.0031\n After long-only clamp: w_VTI=0.0031, w_BIL=0.9969.", "metadata": {"weights": {"VTI": 0.5587, "BIL": 0.4413}, "sigma_1": 0.013362, "sigma_2": 0.00016, "covariance": -1e-06, "correlation": -0.2453, "has_text": true, "text_chars": 3020, "mu_floor": 0.1208, "constraint_binding": true}} +{"id": "T4_all_20250814_0489", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF", "IAU"], "decision_date": "2025-08-14", "context_summary": "XLF \u03c3=0.0085, IAU \u03c3=0.0098, \u03c1=-0.092. Min-variance weights: XLF=0.569, IAU=0.431.", "question": "Assets: XLF, IAU\nXLF: annualized_mean_return=0.1008, daily_std=0.0085\nIAU: annualized_mean_return=0.1008, daily_std=0.0098\nMinimum required portfolio return (annualized): 0.1008\nMarket regime: bull\n\nCompute portfolio weights (w_XLF, w_IAU) 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_IAU=X.XXXX", "answer": "w_XLF=0.5685, w_IAU=0.4315", "answer_numeric": 0.5685, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000097 - -0.000008) / (0.000072 + 0.000097 - -0.000015)\n Unconstrained: w_XLF=0.5688\n After long-only clamp: w_XLF=0.5688, w_IAU=0.4312.", "metadata": {"weights": {"XLF": 0.5685, "IAU": 0.4315}, "sigma_1": 0.008465, "sigma_2": 0.009847, "covariance": -8e-06, "correlation": -0.0916, "has_text": true, "text_chars": 3020, "mu_floor": 0.1008, "constraint_binding": false}} +{"id": "T4_all_20250618_0492", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "CORN"], "decision_date": "2025-06-18", "context_summary": "EEM \u03c3=0.0124, CORN \u03c3=0.0086, \u03c1=-0.073. Min-variance weights: EEM=0.338, CORN=0.662.", "question": "Assets: EEM, CORN\nEEM: annualized_mean_return=0.2016, daily_std=0.0124\nCORN: annualized_mean_return=-0.1512, daily_std=0.0086\nMinimum required portfolio return (annualized): 0.1189\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_CORN) 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_CORN=X.XXXX", "answer": "w_EEM=0.7656, w_CORN=0.2344", "answer_numeric": 0.7656, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000074 - -0.000008) / (0.000153 + 0.000074 - -0.000016)\n Unconstrained: w_EEM=0.3377\n After long-only clamp: w_EEM=0.3377, w_CORN=0.6623.", "metadata": {"weights": {"EEM": 0.7656, "CORN": 0.2344}, "sigma_1": 0.012385, "sigma_2": 0.008624, "covariance": -8e-06, "correlation": -0.0733, "has_text": true, "text_chars": 3020, "mu_floor": 0.1189, "constraint_binding": true}} +{"id": "T4_all_20250513_0494", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ICSH"], "decision_date": "2025-05-13", "context_summary": "XLK \u03c3=0.0206, ICSH \u03c3=0.0004, \u03c1=0.072. Min-variance weights: XLK=0.000, ICSH=1.000.", "question": "Assets: XLK, ICSH\nXLK: annualized_mean_return=-0.3528, daily_std=0.0206\nICSH: annualized_mean_return=0.0756, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.0472\nMarket regime: sideways\n\nCompute portfolio weights (w_XLK, w_ICSH) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLK=X.XXXX, w_ICSH=X.XXXX", "answer": "w_XLK=0.0000, w_ICSH=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.000423 + 0.000000 - 0.000001)\n Unconstrained: w_XLK=-0.0010\n After long-only clamp: w_XLK=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"XLK": 0.0, "ICSH": 1.0}, "sigma_1": 0.020574, "sigma_2": 0.000364, "covariance": 1e-06, "correlation": 0.0716, "has_text": true, "text_chars": 3020, "mu_floor": 0.0472, "constraint_binding": false}} +{"id": "T4_all_20250429_0497", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ADA-USD", "ICSH"], "decision_date": "2025-04-29", "context_summary": "ADA-USD \u03c3=0.0589, ICSH \u03c3=0.0004, \u03c1=0.078. Min-variance weights: ADA-USD=0.000, ICSH=1.000.", "question": "Assets: ADA-USD, ICSH\nADA-USD: annualized_mean_return=-0.2520, daily_std=0.0589\nICSH: annualized_mean_return=0.0756, daily_std=0.0004\nMinimum required portfolio return (annualized): -0.0364\nMarket regime: bear\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 - 0.000002) / (0.003475 + 0.000000 - 0.000003)\n Unconstrained: w_ADA-USD=-0.0004\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": 0.058946, "sigma_2": 0.000355, "covariance": 2e-06, "correlation": 0.0785, "has_text": true, "text_chars": 20, "mu_floor": -0.0364, "constraint_binding": false}} +{"id": "T4_all_20250822_0500", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD", "SOYB"], "decision_date": "2025-08-22", "context_summary": "BNB-USD \u03c3=0.0197, SOYB \u03c3=0.0092, \u03c1=-0.001. Min-variance weights: BNB-USD=0.180, SOYB=0.820.", "question": "Assets: BNB-USD, SOYB\nBNB-USD: annualized_mean_return=1.3608, daily_std=0.0197\nSOYB: annualized_mean_return=0.1260, daily_std=0.0092\nMinimum required portfolio return (annualized): 0.8962\nMarket regime: bull\n\nCompute portfolio weights (w_BNB-USD, w_SOYB) 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_SOYB=X.XXXX", "answer": "w_BNB-USD=0.6237, w_SOYB=0.3763", "answer_numeric": 0.6237, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000085 - -0.000000) / (0.000386 + 0.000085 - -0.000000)\n Unconstrained: w_BNB-USD=0.1799\n After long-only clamp: w_BNB-USD=0.1799, w_SOYB=0.8201.", "metadata": {"weights": {"BNB-USD": 0.6237, "SOYB": 0.3763}, "sigma_1": 0.019655, "sigma_2": 0.0092, "covariance": -0.0, "correlation": -0.0008, "has_text": true, "text_chars": 20, "mu_floor": 0.8962, "constraint_binding": true}} +{"id": "T4_all_20250922_0503", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["AVAX-USD", "VCIT"], "decision_date": "2025-09-22", "context_summary": "AVAX-USD \u03c3=0.0445, VCIT \u03c3=0.0025, \u03c1=0.238. Min-variance weights: AVAX-USD=0.000, VCIT=1.000.", "question": "Assets: AVAX-USD, VCIT\nAVAX-USD: annualized_mean_return=1.6128, daily_std=0.0445\nVCIT: annualized_mean_return=0.1008, daily_std=0.0025\nMinimum required portfolio return (annualized): 0.1008\nMarket regime: bull\n\nCompute portfolio weights (w_AVAX-USD, w_VCIT) 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_VCIT=X.XXXX", "answer": "w_AVAX-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 = (0.000006 - 0.000027) / (0.001984 + 0.000006 - 0.000053)\n Unconstrained: w_AVAX-USD=-0.0105\n After long-only clamp: w_AVAX-USD=0.0000, w_VCIT=1.0000.", "metadata": {"weights": {"AVAX-USD": 0.0, "VCIT": 1.0}, "sigma_1": 0.044538, "sigma_2": 0.002496, "covariance": 2.7e-05, "correlation": 0.2384, "has_text": true, "text_chars": 20, "mu_floor": 0.1008, "constraint_binding": false}} +{"id": "T4_all_20250912_0508", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ADA-USD", "BIL"], "decision_date": "2025-09-12", "context_summary": "ADA-USD \u03c3=0.0383, BIL \u03c3=0.0001, \u03c1=0.038. Min-variance weights: ADA-USD=0.000, BIL=1.000.", "question": "Assets: ADA-USD, BIL\nADA-USD: annualized_mean_return=1.0080, daily_std=0.0383\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.5575\nMarket regime: bull\n\nCompute portfolio weights (w_ADA-USD, w_BIL) 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_BIL=X.XXXX", "answer": "w_ADA-USD=0.5296, w_BIL=0.4704", "answer_numeric": 0.5296, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.001470 + 0.000000 - 0.000000)\n Unconstrained: w_ADA-USD=-0.0001\n After long-only clamp: w_ADA-USD=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"ADA-USD": 0.5296, "BIL": 0.4704}, "sigma_1": 0.03834, "sigma_2": 0.000147, "covariance": 0.0, "correlation": 0.0384, "has_text": true, "text_chars": 20, "mu_floor": 0.5575, "constraint_binding": true}} +{"id": "T4_all_20250114_0512", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "VNQ"], "decision_date": "2025-01-14", "context_summary": "LINK-USD \u03c3=0.0626, VNQ \u03c3=0.0106, \u03c1=0.028. Min-variance weights: LINK-USD=0.024, VNQ=0.977.", "question": "Assets: LINK-USD, VNQ\nLINK-USD: annualized_mean_return=1.5372, daily_std=0.0626\nVNQ: annualized_mean_return=-0.3780, daily_std=0.0106\nMinimum required portfolio return (annualized): 1.1460\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_VNQ) 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_VNQ=X.XXXX", "answer": "w_LINK-USD=0.7957, w_VNQ=0.2043", "answer_numeric": 0.7957, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000113 - 0.000019) / (0.003915 + 0.000113 - 0.000037)\n Unconstrained: w_LINK-USD=0.0235\n After long-only clamp: w_LINK-USD=0.0235, w_VNQ=0.9765.", "metadata": {"weights": {"LINK-USD": 0.7957, "VNQ": 0.2043}, "sigma_1": 0.062571, "sigma_2": 0.010613, "covariance": 1.9e-05, "correlation": 0.0282, "has_text": true, "text_chars": 20, "mu_floor": 1.146, "constraint_binding": true}} +{"id": "T4_all_20250911_0514", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EEM", "SCHH"], "decision_date": "2025-09-11", "context_summary": "EEM \u03c3=0.0075, SCHH \u03c3=0.0087, \u03c1=0.332. Min-variance weights: EEM=0.608, SCHH=0.392.", "question": "Assets: EEM, SCHH\nEEM: annualized_mean_return=0.4284, daily_std=0.0075\nSCHH: annualized_mean_return=0.0756, daily_std=0.0087\nMinimum required portfolio return (annualized): 0.3302\nMarket regime: bull\n\nCompute portfolio weights (w_EEM, w_SCHH) 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_SCHH=X.XXXX", "answer": "w_EEM=0.7217, w_SCHH=0.2783", "answer_numeric": 0.7217, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000075 - 0.000022) / (0.000056 + 0.000075 - 0.000043)\n Unconstrained: w_EEM=0.6077\n After long-only clamp: w_EEM=0.6077, w_SCHH=0.3923.", "metadata": {"weights": {"EEM": 0.7217, "SCHH": 0.2783}, "sigma_1": 0.007492, "sigma_2": 0.008667, "covariance": 2.2e-05, "correlation": 0.3316, "has_text": true, "text_chars": 3020, "mu_floor": 0.3302, "constraint_binding": true}} +{"id": "T4_all_20250605_0517", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "PDBC"], "decision_date": "2025-06-05", "context_summary": "EFA \u03c3=0.0107, PDBC \u03c3=0.0109, \u03c1=0.158. Min-variance weights: EFA=0.512, PDBC=0.488.", "question": "Assets: EFA, PDBC\nEFA: annualized_mean_return=0.3024, daily_std=0.0107\nPDBC: annualized_mean_return=-0.1260, daily_std=0.0109\nMinimum required portfolio return (annualized): 0.0305\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_PDBC) 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_PDBC=X.XXXX", "answer": "w_EFA=0.5119, w_PDBC=0.4881", "answer_numeric": 0.5119, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000119 - 0.000019) / (0.000115 + 0.000119 - 0.000037)\n Unconstrained: w_EFA=0.5118\n After long-only clamp: w_EFA=0.5118, w_PDBC=0.4882.", "metadata": {"weights": {"EFA": 0.5119, "PDBC": 0.4881}, "sigma_1": 0.010702, "sigma_2": 0.010917, "covariance": 1.9e-05, "correlation": 0.1584, "has_text": true, "text_chars": 3020, "mu_floor": 0.0305, "constraint_binding": false}} +{"id": "T4_all_20250902_0519", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["DOT-USD", "SOYB"], "decision_date": "2025-09-02", "context_summary": "DOT-USD \u03c3=0.0389, SOYB \u03c3=0.0090, \u03c1=-0.077. Min-variance weights: DOT-USD=0.066, SOYB=0.934.", "question": "Assets: DOT-USD, SOYB\nDOT-USD: annualized_mean_return=0.3780, daily_std=0.0389\nSOYB: annualized_mean_return=0.1512, daily_std=0.0090\nMinimum required portfolio return (annualized): 0.1649\nMarket regime: bull\n\nCompute portfolio weights (w_DOT-USD, w_SOYB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_DOT-USD=X.XXXX, w_SOYB=X.XXXX", "answer": "w_DOT-USD=0.0655, w_SOYB=0.9345", "answer_numeric": 0.0655, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000081 - -0.000027) / (0.001517 + 0.000081 - -0.000054)\n Unconstrained: w_DOT-USD=0.0655\n After long-only clamp: w_DOT-USD=0.0655, w_SOYB=0.9345.", "metadata": {"weights": {"DOT-USD": 0.0655, "SOYB": 0.9345}, "sigma_1": 0.038943, "sigma_2": 0.009009, "covariance": -2.7e-05, "correlation": -0.077, "has_text": true, "text_chars": 20, "mu_floor": 0.1649, "constraint_binding": false}} +{"id": "T4_all_20250829_0521", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QQQ", "XHB"], "decision_date": "2025-08-29", "context_summary": "QQQ \u03c3=0.0074, XHB \u03c3=0.0177, \u03c1=0.244. Min-variance weights: QQQ=0.924, XHB=0.076.", "question": "Assets: QQQ, XHB\nQQQ: annualized_mean_return=0.3780, daily_std=0.0074\nXHB: annualized_mean_return=0.7560, daily_std=0.0177\nMinimum required portfolio return (annualized): 0.3979\nMarket regime: bull\n\nCompute portfolio weights (w_QQQ, w_XHB) 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_XHB=X.XXXX", "answer": "w_QQQ=0.9235, w_XHB=0.0765", "answer_numeric": 0.9235, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000315 - 0.000032) / (0.000055 + 0.000315 - 0.000064)\n Unconstrained: w_QQQ=0.9240\n After long-only clamp: w_QQQ=0.9240, w_XHB=0.0760.", "metadata": {"weights": {"QQQ": 0.9235, "XHB": 0.0765}, "sigma_1": 0.007444, "sigma_2": 0.017734, "covariance": 3.2e-05, "correlation": 0.2439, "has_text": true, "text_chars": 3020, "mu_floor": 0.3979, "constraint_binding": false}} +{"id": "T4_all_20250116_0524", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "HAUZ"], "decision_date": "2025-01-16", "context_summary": "^VIX \u03c3=0.0778, HAUZ \u03c3=0.0091, \u03c1=-0.394. Min-variance weights: ^VIX=0.054, HAUZ=0.946.", "question": "Assets: ^VIX, HAUZ\n^VIX: annualized_mean_return=-1.4112, daily_std=0.0778\nHAUZ: annualized_mean_return=-0.5040, daily_std=0.0091\nMinimum required portfolio return (annualized): -0.5318\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=0.0306, w_HAUZ=0.9694", "answer_numeric": 0.0306, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000083 - -0.000280) / (0.006046 + 0.000083 - -0.000560)\n Unconstrained: w_^VIX=0.0543\n After long-only clamp: w_^VIX=0.0543, w_HAUZ=0.9457.", "metadata": {"weights": {"^VIX": 0.0306, "HAUZ": 0.9694}, "sigma_1": 0.077759, "sigma_2": 0.009132, "covariance": -0.00028, "correlation": -0.3944, "has_text": true, "text_chars": 9045, "mu_floor": -0.5318, "constraint_binding": true}} +{"id": "T4_all_20250117_0526", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "VCIT"], "decision_date": "2025-01-17", "context_summary": "USMV \u03c3=0.0066, VCIT \u03c3=0.0035, \u03c1=0.216. Min-variance weights: USMV=0.162, VCIT=0.838.", "question": "Assets: USMV, VCIT\nUSMV: annualized_mean_return=-0.1260, daily_std=0.0066\nVCIT: annualized_mean_return=0.0000, daily_std=0.0035\nMinimum required portfolio return (annualized): -0.0075\nMarket regime: sideways\n\nCompute portfolio weights (w_USMV, w_VCIT) 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_VCIT=X.XXXX", "answer": "w_USMV=0.0595, w_VCIT=0.9405", "answer_numeric": 0.0595, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000012 - 0.000005) / (0.000043 + 0.000012 - 0.000010)\n Unconstrained: w_USMV=0.1623\n After long-only clamp: w_USMV=0.1623, w_VCIT=0.8377.", "metadata": {"weights": {"USMV": 0.0595, "VCIT": 0.9405}, "sigma_1": 0.006565, "sigma_2": 0.003517, "covariance": 5e-06, "correlation": 0.2161, "has_text": true, "text_chars": 9045, "mu_floor": -0.0075, "constraint_binding": true}} +{"id": "T4_all_20251212_0529", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "IYR"], "decision_date": "2025-12-12", "context_summary": "EFA \u03c3=0.0071, IYR \u03c3=0.0079, \u03c1=0.530. Min-variance weights: EFA=0.616, IYR=0.384.", "question": "Assets: EFA, IYR\nEFA: annualized_mean_return=0.1764, daily_std=0.0071\nIYR: annualized_mean_return=-0.0756, daily_std=0.0079\nMinimum required portfolio return (annualized): 0.0303\nMarket regime: sideways\n\nCompute portfolio weights (w_EFA, w_IYR) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_EFA=X.XXXX, w_IYR=X.XXXX", "answer": "w_EFA=0.6174, w_IYR=0.3826", "answer_numeric": 0.6174, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000062 - 0.000030) / (0.000050 + 0.000062 - 0.000059)\n Unconstrained: w_EFA=0.6157\n After long-only clamp: w_EFA=0.6157, w_IYR=0.3843.", "metadata": {"weights": {"EFA": 0.6174, "IYR": 0.3826}, "sigma_1": 0.007077, "sigma_2": 0.0079, "covariance": 3e-05, "correlation": 0.5298, "has_text": true, "text_chars": 9045, "mu_floor": 0.0303, "constraint_binding": false}} +{"id": "T4_all_20250331_0532", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["MATIC-USD", "TLH"], "decision_date": "2025-03-31", "context_summary": "MATIC-USD \u03c3=0.0447, TLH \u03c3=0.0063, \u03c1=0.005. Min-variance weights: MATIC-USD=0.019, TLH=0.981.", "question": "Assets: MATIC-USD, TLH\nMATIC-USD: annualized_mean_return=-2.4444, daily_std=0.0447\nTLH: annualized_mean_return=0.2268, daily_std=0.0063\nMinimum required portfolio return (annualized): 0.1913\nMarket regime: bear\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=0.0133, w_TLH=0.9867", "answer_numeric": 0.0133, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000040 - 0.000002) / (0.001998 + 0.000040 - 0.000003)\n Unconstrained: w_MATIC-USD=0.0189\n After long-only clamp: w_MATIC-USD=0.0189, w_TLH=0.9811.", "metadata": {"weights": {"MATIC-USD": 0.0133, "TLH": 0.9867}, "sigma_1": 0.044696, "sigma_2": 0.006327, "covariance": 2e-06, "correlation": 0.0055, "has_text": true, "text_chars": 20, "mu_floor": 0.1913, "constraint_binding": true}} +{"id": "T4_all_20250925_0534", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLB", "BIL"], "decision_date": "2025-09-25", "context_summary": "XLB \u03c3=0.0099, BIL \u03c3=0.0001, \u03c1=0.081. Min-variance weights: XLB=0.000, BIL=1.000.", "question": "Assets: XLB, BIL\nXLB: annualized_mean_return=0.0756, daily_std=0.0099\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0593\nMarket regime: bull\n\nCompute portfolio weights (w_XLB, w_BIL) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLB=X.XXXX, w_BIL=X.XXXX", "answer": "w_XLB=0.3532, w_BIL=0.6468", "answer_numeric": 0.3532, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000097 + 0.000000 - 0.000000)\n Unconstrained: w_XLB=-0.0010\n After long-only clamp: w_XLB=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"XLB": 0.3532, "BIL": 0.6468}, "sigma_1": 0.00986, "sigma_2": 0.000146, "covariance": 0.0, "correlation": 0.0809, "has_text": true, "text_chars": 3020, "mu_floor": 0.0593, "constraint_binding": true}} +{"id": "T4_all_20250403_0536", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["MATIC-USD", "SGOV"], "decision_date": "2025-04-03", "context_summary": "MATIC-USD \u03c3=0.0447, SGOV \u03c3=0.0001, \u03c1=-0.101. Min-variance weights: MATIC-USD=0.000, SGOV=1.000.", "question": "Assets: MATIC-USD, SGOV\nMATIC-USD: annualized_mean_return=-2.4444, daily_std=0.0447\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0494\nMarket regime: bear\n\nCompute portfolio weights (w_MATIC-USD, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_SGOV=X.XXXX", "answer": "w_MATIC-USD=0.0004, 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) / (0.001998 + 0.000000 - -0.000001)\n Unconstrained: w_MATIC-USD=0.0003\n After long-only clamp: w_MATIC-USD=0.0003, w_SGOV=0.9997.", "metadata": {"weights": {"MATIC-USD": 0.0004, "SGOV": 0.9996}, "sigma_1": 0.044696, "sigma_2": 0.000123, "covariance": -1e-06, "correlation": -0.1014, "has_text": true, "text_chars": 20, "mu_floor": 0.0494, "constraint_binding": true}} +{"id": "T4_all_20250217_0539", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "XHB"], "decision_date": "2025-02-17", "context_summary": "XLY \u03c3=0.0115, XHB \u03c3=0.0147, \u03c1=0.526. Min-variance weights: XLY=0.751, XHB=0.249.", "question": "Assets: XLY, XHB\nXLY: annualized_mean_return=0.3024, daily_std=0.0115\nXHB: annualized_mean_return=-0.3024, daily_std=0.0147\nMinimum required portfolio return (annualized): -0.0504\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=0.7521, w_XHB=0.2479", "answer_numeric": 0.7521, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000217 - 0.000089) / (0.000131 + 0.000217 - 0.000177)\n Unconstrained: w_XLY=0.7510\n After long-only clamp: w_XLY=0.7510, w_XHB=0.2490.", "metadata": {"weights": {"XLY": 0.7521, "XHB": 0.2479}, "sigma_1": 0.011451, "sigma_2": 0.014724, "covariance": 8.9e-05, "correlation": 0.5257, "has_text": true, "text_chars": 9045, "mu_floor": -0.0504, "constraint_binding": false}} +{"id": "T4_all_20251103_0542", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "LQD"], "decision_date": "2025-11-03", "context_summary": "FXI \u03c3=0.0134, LQD \u03c3=0.0031, \u03c1=0.104. Min-variance weights: FXI=0.030, LQD=0.970.", "question": "Assets: FXI, LQD\nFXI: annualized_mean_return=0.2520, daily_std=0.0134\nLQD: annualized_mean_return=0.0756, daily_std=0.0031\nMinimum required portfolio return (annualized): 0.1180\nMarket regime: bull\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=0.2404, w_LQD=0.7596", "answer_numeric": 0.2404, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000010 - 0.000004) / (0.000180 + 0.000010 - 0.000009)\n Unconstrained: w_FXI=0.0302\n After long-only clamp: w_FXI=0.0302, w_LQD=0.9698.", "metadata": {"weights": {"FXI": 0.2404, "LQD": 0.7596}, "sigma_1": 0.013424, "sigma_2": 0.003143, "covariance": 4e-06, "correlation": 0.1043, "has_text": true, "text_chars": 9046, "mu_floor": 0.118, "constraint_binding": true}} +{"id": "T4_all_20250310_0545", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ITB"], "decision_date": "2025-03-10", "context_summary": "IWM \u03c3=0.0113, ITB \u03c3=0.0158, \u03c1=0.608. Min-variance weights: IWM=0.882, ITB=0.118.", "question": "Assets: IWM, ITB\nIWM: annualized_mean_return=-0.5796, daily_std=0.0113\nITB: annualized_mean_return=-0.7056, daily_std=0.0158\nMinimum required portfolio return (annualized): -0.6365\nMarket regime: sideways\n\nCompute portfolio weights (w_IWM, w_ITB) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_ITB=X.XXXX", "answer": "w_IWM=0.8801, w_ITB=0.1199", "answer_numeric": 0.8801, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000250 - 0.000108) / (0.000127 + 0.000250 - 0.000217)\n Unconstrained: w_IWM=0.8824\n After long-only clamp: w_IWM=0.8824, w_ITB=0.1176.", "metadata": {"weights": {"IWM": 0.8801, "ITB": 0.1199}, "sigma_1": 0.011283, "sigma_2": 0.015803, "covariance": 0.000108, "correlation": 0.6083, "has_text": true, "text_chars": 9045, "mu_floor": -0.6365, "constraint_binding": false}} +{"id": "T4_all_20250619_0548", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ETH-USD", "MORT"], "decision_date": "2025-06-19", "context_summary": "ETH-USD \u03c3=0.0376, MORT \u03c3=0.0170, \u03c1=0.103. Min-variance weights: ETH-USD=0.142, MORT=0.858.", "question": "Assets: ETH-USD, MORT\nETH-USD: annualized_mean_return=1.8396, daily_std=0.0376\nMORT: annualized_mean_return=-0.1764, daily_std=0.0170\nMinimum required portfolio return (annualized): 0.6149\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=0.3925, w_MORT=0.6075", "answer_numeric": 0.3925, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000290 - 0.000066) / (0.001416 + 0.000290 - 0.000132)\n Unconstrained: w_ETH-USD=0.1423\n After long-only clamp: w_ETH-USD=0.1423, w_MORT=0.8577.", "metadata": {"weights": {"ETH-USD": 0.3925, "MORT": 0.6075}, "sigma_1": 0.037624, "sigma_2": 0.017032, "covariance": 6.6e-05, "correlation": 0.1033, "has_text": true, "text_chars": 20, "mu_floor": 0.6149, "constraint_binding": true}} +{"id": "T4_all_20250620_0550", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BNDX"], "decision_date": "2025-06-20", "context_summary": "VEA \u03c3=0.0103, BNDX \u03c3=0.0024, \u03c1=0.068. Min-variance weights: VEA=0.037, BNDX=0.963.", "question": "Assets: VEA, BNDX\nVEA: annualized_mean_return=0.2520, daily_std=0.0103\nBNDX: annualized_mean_return=0.1260, daily_std=0.0024\nMinimum required portfolio return (annualized): 0.1561\nMarket regime: sideways\n\nCompute portfolio weights (w_VEA, w_BNDX) 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_BNDX=X.XXXX", "answer": "w_VEA=0.2389, w_BNDX=0.7611", "answer_numeric": 0.2389, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000006 - 0.000002) / (0.000106 + 0.000006 - 0.000003)\n Unconstrained: w_VEA=0.0366\n After long-only clamp: w_VEA=0.0366, w_BNDX=0.9634.", "metadata": {"weights": {"VEA": 0.2389, "BNDX": 0.7611}, "sigma_1": 0.010318, "sigma_2": 0.002374, "covariance": 2e-06, "correlation": 0.0676, "has_text": true, "text_chars": 3020, "mu_floor": 0.1561, "constraint_binding": true}} +{"id": "T4_all_20251110_0553", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "PPLT"], "decision_date": "2025-11-10", "context_summary": "XLV \u03c3=0.0078, PPLT \u03c3=0.0191, \u03c1=-0.073. Min-variance weights: XLV=0.840, PPLT=0.160.", "question": "Assets: XLV, PPLT\nXLV: annualized_mean_return=0.3528, daily_std=0.0078\nPPLT: annualized_mean_return=0.7056, daily_std=0.0191\nMinimum required portfolio return (annualized): 0.3787\nMarket regime: sideways\n\nCompute portfolio weights (w_XLV, w_PPLT) 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_PPLT=X.XXXX", "answer": "w_XLV=0.8398, w_PPLT=0.1602", "answer_numeric": 0.8398, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000366 - -0.000011) / (0.000061 + 0.000366 - -0.000022)\n Unconstrained: w_XLV=0.8399\n After long-only clamp: w_XLV=0.8399, w_PPLT=0.1601.", "metadata": {"weights": {"XLV": 0.8398, "PPLT": 0.1602}, "sigma_1": 0.007804, "sigma_2": 0.019129, "covariance": -1.1e-05, "correlation": -0.073, "has_text": true, "text_chars": 9045, "mu_floor": 0.3787, "constraint_binding": false}} +{"id": "T4_all_20250519_0556", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "SHV"], "decision_date": "2025-05-19", "context_summary": "XLY \u03c3=0.0188, SHV \u03c3=0.0001, \u03c1=0.000. Min-variance weights: XLY=0.000, SHV=1.000.", "question": "Assets: XLY, SHV\nXLY: annualized_mean_return=-0.3528, daily_std=0.0187\nSHV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: sideways\n\nCompute portfolio weights (w_XLY, w_SHV) 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_SHV=X.XXXX", "answer": "w_XLY=-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) / (0.000352 + 0.000000 - 0.000000)\n Unconstrained: w_XLY=0.0000\n After long-only clamp: w_XLY=0.0000, w_SHV=1.0000.", "metadata": {"weights": {"XLY": -0.0, "SHV": 1.0}, "sigma_1": 0.01875, "sigma_2": 0.000128, "covariance": 0.0, "correlation": 0.0002, "has_text": true, "text_chars": 3020, "mu_floor": 0.0504, "constraint_binding": true}} +{"id": "T4_all_20250505_0558", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "HAUZ"], "decision_date": "2025-05-05", "context_summary": "BNB-USD \u03c3=0.0229, HAUZ \u03c3=0.0102, \u03c1=0.031. Min-variance weights: BNB-USD=0.157, HAUZ=0.844.", "question": "Assets: BNB-USD, HAUZ\nBNB-USD: annualized_mean_return=-0.0252, daily_std=0.0229\nHAUZ: annualized_mean_return=0.3276, daily_std=0.0102\nMinimum required portfolio return (annualized): 0.2861\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_HAUZ) 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_HAUZ=X.XXXX", "answer": "w_BNB-USD=0.1176, w_HAUZ=0.8824", "answer_numeric": 0.1176, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000103 - 0.000007) / (0.000525 + 0.000103 - 0.000015)\n Unconstrained: w_BNB-USD=0.1565\n After long-only clamp: w_BNB-USD=0.1565, w_HAUZ=0.8435.", "metadata": {"weights": {"BNB-USD": 0.1176, "HAUZ": 0.8824}, "sigma_1": 0.022913, "sigma_2": 0.010166, "covariance": 7e-06, "correlation": 0.0313, "has_text": true, "text_chars": 20, "mu_floor": 0.2861, "constraint_binding": true}} +{"id": "T4_all_20250113_0561", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "TLH"], "decision_date": "2025-01-13", "context_summary": "XLK \u03c3=0.0123, TLH \u03c3=0.0068, \u03c1=-0.139. Min-variance weights: XLK=0.259, TLH=0.741.", "question": "Assets: XLK, TLH\nXLK: annualized_mean_return=-0.0756, daily_std=0.0123\nTLH: annualized_mean_return=-0.2016, daily_std=0.0068\nMinimum required portfolio return (annualized): -0.1748\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=0.2601, w_TLH=0.7399", "answer_numeric": 0.2601, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000046 - -0.000012) / (0.000152 + 0.000046 - -0.000023)\n Unconstrained: w_XLK=0.2593\n After long-only clamp: w_XLK=0.2593, w_TLH=0.7407.", "metadata": {"weights": {"XLK": 0.2601, "TLH": 0.7399}, "sigma_1": 0.012343, "sigma_2": 0.006765, "covariance": -1.2e-05, "correlation": -0.1395, "has_text": true, "text_chars": 9045, "mu_floor": -0.1748, "constraint_binding": false}} +{"id": "T4_all_20250415_0563", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XRP-USD", "BIL"], "decision_date": "2025-04-15", "context_summary": "XRP-USD \u03c3=0.0677, BIL \u03c3=0.0001, \u03c1=-0.155. Min-variance weights: XRP-USD=0.000, BIL=1.000.", "question": "Assets: XRP-USD, BIL\nXRP-USD: annualized_mean_return=-0.2772, daily_std=0.0677\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): -0.0475\nMarket regime: bear\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=0.0002, w_BIL=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000001) / (0.004577 + 0.000000 - -0.000003)\n Unconstrained: w_XRP-USD=0.0003\n After long-only clamp: w_XRP-USD=0.0003, w_BIL=0.9997.", "metadata": {"weights": {"XRP-USD": 0.0002, "BIL": 0.9998}, "sigma_1": 0.067653, "sigma_2": 0.000128, "covariance": -1e-06, "correlation": -0.1549, "has_text": true, "text_chars": 20, "mu_floor": -0.0475, "constraint_binding": false}} +{"id": "T4_all_20251022_0565", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "USO"], "decision_date": "2025-10-22", "context_summary": "QUAL \u03c3=0.0068, USO \u03c3=0.0148, \u03c1=0.176. Min-variance weights: QUAL=0.876, USO=0.124.", "question": "Assets: QUAL, USO\nQUAL: annualized_mean_return=0.2268, daily_std=0.0068\nUSO: annualized_mean_return=-0.6552, daily_std=0.0148\nMinimum required portfolio return (annualized): -0.2264\nMarket regime: bull\n\nCompute portfolio weights (w_QUAL, w_USO) 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_USO=X.XXXX", "answer": "w_QUAL=0.8773, w_USO=0.1227", "answer_numeric": 0.8773, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000220 - 0.000018) / (0.000046 + 0.000220 - 0.000035)\n Unconstrained: w_QUAL=0.8764\n After long-only clamp: w_QUAL=0.8764, w_USO=0.1236.", "metadata": {"weights": {"QUAL": 0.8773, "USO": 0.1227}, "sigma_1": 0.006798, "sigma_2": 0.014823, "covariance": 1.8e-05, "correlation": 0.176, "has_text": true, "text_chars": 3020, "mu_floor": -0.2264, "constraint_binding": false}} +{"id": "T4_all_20250813_0567", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD", "STIP"], "decision_date": "2025-08-13", "context_summary": "ETH-USD \u03c3=0.0331, STIP \u03c3=0.0010, \u03c1=-0.269. Min-variance weights: ETH-USD=0.009, STIP=0.991.", "question": "Assets: ETH-USD, STIP\nETH-USD: annualized_mean_return=2.5704, daily_std=0.0331\nSTIP: annualized_mean_return=0.0756, daily_std=0.0010\nMinimum required portfolio return (annualized): 0.0931\nMarket regime: bull\n\nCompute portfolio weights (w_ETH-USD, w_STIP) 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_STIP=X.XXXX", "answer": "w_ETH-USD=0.0090, w_STIP=0.9910", "answer_numeric": 0.009, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - -0.000009) / (0.001092 + 0.000001 - -0.000018)\n Unconstrained: w_ETH-USD=0.0090\n After long-only clamp: w_ETH-USD=0.0090, w_STIP=0.9910.", "metadata": {"weights": {"ETH-USD": 0.009, "STIP": 0.991}, "sigma_1": 0.033053, "sigma_2": 0.001009, "covariance": -9e-06, "correlation": -0.2693, "has_text": true, "text_chars": 20, "mu_floor": 0.0931, "constraint_binding": false}} +{"id": "T4_all_20250207_0570", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "SGOV"], "decision_date": "2025-02-07", "context_summary": "XLB \u03c3=0.0087, SGOV \u03c3=0.0001, \u03c1=-0.018. Min-variance weights: XLB=0.001, SGOV=0.999.", "question": "Assets: XLB, SGOV\nXLB: annualized_mean_return=-0.2520, daily_std=0.0087\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0503\nMarket regime: sideways\n\nCompute portfolio weights (w_XLB, w_SGOV) 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_SGOV=X.XXXX", "answer": "w_XLB=0.0003, w_SGOV=0.9997", "answer_numeric": 0.0003, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000076 + 0.000000 - -0.000000)\n Unconstrained: w_XLB=0.0006\n After long-only clamp: w_XLB=0.0006, w_SGOV=0.9994.", "metadata": {"weights": {"XLB": 0.0003, "SGOV": 0.9997}, "sigma_1": 0.008718, "sigma_2": 0.000143, "covariance": -0.0, "correlation": -0.0176, "has_text": true, "text_chars": 9047, "mu_floor": 0.0503, "constraint_binding": true}} +{"id": "T4_all_20250423_0573", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VLUE", "DBC"], "decision_date": "2025-04-23", "context_summary": "VLUE \u03c3=0.0131, DBC \u03c3=0.0099, \u03c1=0.648. Min-variance weights: VLUE=0.142, DBC=0.858.", "question": "Assets: VLUE, DBC\nVLUE: annualized_mean_return=-0.4788, daily_std=0.0131\nDBC: annualized_mean_return=-0.1260, daily_std=0.0099\nMinimum required portfolio return (annualized): -0.3471\nMarket regime: bear\n\nCompute portfolio weights (w_VLUE, w_DBC) 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_DBC=X.XXXX", "answer": "w_VLUE=0.1414, w_DBC=0.8586", "answer_numeric": 0.1414, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000098 - 0.000084) / (0.000171 + 0.000098 - 0.000168)\n Unconstrained: w_VLUE=0.1419\n After long-only clamp: w_VLUE=0.1419, w_DBC=0.8581.", "metadata": {"weights": {"VLUE": 0.1414, "DBC": 0.8586}, "sigma_1": 0.013072, "sigma_2": 0.009915, "covariance": 8.4e-05, "correlation": 0.6475, "has_text": true, "text_chars": 3020, "mu_floor": -0.3471, "constraint_binding": false}} +{"id": "T4_all_20250408_0575", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLF", "CPER"], "decision_date": "2025-04-08", "context_summary": "XLF \u03c3=0.0129, CPER \u03c3=0.0168, \u03c1=0.290. Min-variance weights: XLF=0.678, CPER=0.322.", "question": "Assets: XLF, CPER\nXLF: annualized_mean_return=-0.1764, daily_std=0.0129\nCPER: annualized_mean_return=-0.2520, daily_std=0.0168\nMinimum required portfolio return (annualized): -0.2189\nMarket regime: bear\n\nCompute portfolio weights (w_XLF, w_CPER) 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_CPER=X.XXXX", "answer": "w_XLF=0.6783, w_CPER=0.3217", "answer_numeric": 0.6783, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000282 - 0.000063) / (0.000167 + 0.000282 - 0.000126)\n Unconstrained: w_XLF=0.6783\n After long-only clamp: w_XLF=0.6783, w_CPER=0.3217.", "metadata": {"weights": {"XLF": 0.6783, "CPER": 0.3217}, "sigma_1": 0.012917, "sigma_2": 0.016791, "covariance": 6.3e-05, "correlation": 0.2903, "has_text": true, "text_chars": 3020, "mu_floor": -0.2189, "constraint_binding": false}} +{"id": "T4_all_20250204_0577", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "TLT"], "decision_date": "2025-02-04", "context_summary": "QUAL \u03c3=0.0077, TLT \u03c3=0.0078, \u03c1=-0.101. Min-variance weights: QUAL=0.507, TLT=0.493.", "question": "Assets: QUAL, TLT\nQUAL: annualized_mean_return=0.1512, daily_std=0.0077\nTLT: annualized_mean_return=-0.0756, daily_std=0.0078\nMinimum required portfolio return (annualized): 0.0165\nMarket regime: sideways\n\nCompute portfolio weights (w_QUAL, w_TLT) 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_TLT=X.XXXX", "answer": "w_QUAL=0.5069, w_TLT=0.4931", "answer_numeric": 0.5069, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000060 - -0.000006) / (0.000059 + 0.000060 - -0.000012)\n Unconstrained: w_QUAL=0.5069\n After long-only clamp: w_QUAL=0.5069, w_TLT=0.4931.", "metadata": {"weights": {"QUAL": 0.5069, "TLT": 0.4931}, "sigma_1": 0.007661, "sigma_2": 0.007778, "covariance": -6e-06, "correlation": -0.1011, "has_text": true, "text_chars": 9044, "mu_floor": 0.0165, "constraint_binding": false}} +{"id": "T4_all_20250730_0580", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD", "LQD"], "decision_date": "2025-07-30", "context_summary": "ETH-USD \u03c3=0.0313, LQD \u03c3=0.0039, \u03c1=-0.130. Min-variance weights: ETH-USD=0.030, LQD=0.970.", "question": "Assets: ETH-USD, LQD\nETH-USD: annualized_mean_return=1.8396, daily_std=0.0313\nLQD: annualized_mean_return=0.1260, daily_std=0.0039\nMinimum required portfolio return (annualized): 0.8779\nMarket regime: bull\n\nCompute portfolio weights (w_ETH-USD, w_LQD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_ETH-USD=X.XXXX, w_LQD=X.XXXX", "answer": "w_ETH-USD=0.4388, w_LQD=0.5612", "answer_numeric": 0.4388, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000015 - -0.000016) / (0.000982 + 0.000015 - -0.000032)\n Unconstrained: w_ETH-USD=0.0299\n After long-only clamp: w_ETH-USD=0.0299, w_LQD=0.9701.", "metadata": {"weights": {"ETH-USD": 0.4388, "LQD": 0.5612}, "sigma_1": 0.03134, "sigma_2": 0.00387, "covariance": -1.6e-05, "correlation": -0.1303, "has_text": true, "text_chars": 20, "mu_floor": 0.8779, "constraint_binding": true}} +{"id": "T4_all_20250124_0583", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "DBB"], "decision_date": "2025-01-24", "context_summary": "IVV \u03c3=0.0085, DBB \u03c3=0.0093, \u03c1=-0.117. Min-variance weights: IVV=0.541, DBB=0.459.", "question": "Assets: IVV, DBB\nIVV: annualized_mean_return=0.2268, daily_std=0.0085\nDBB: annualized_mean_return=-0.1008, daily_std=0.0093\nMinimum required portfolio return (annualized): 0.0199\nMarket regime: sideways\n\nCompute portfolio weights (w_IVV, w_DBB) 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_DBB=X.XXXX", "answer": "w_IVV=0.5414, w_DBB=0.4586", "answer_numeric": 0.5414, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000087 - -0.000009) / (0.000072 + 0.000087 - -0.000019)\n Unconstrained: w_IVV=0.5413\n After long-only clamp: w_IVV=0.5413, w_DBB=0.4587.", "metadata": {"weights": {"IVV": 0.5414, "DBB": 0.4586}, "sigma_1": 0.008514, "sigma_2": 0.009339, "covariance": -9e-06, "correlation": -0.1174, "has_text": true, "text_chars": 9044, "mu_floor": 0.0199, "constraint_binding": false}} +{"id": "T4_all_20250702_0586", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SOL-USD", "XLI"], "decision_date": "2025-07-02", "context_summary": "SOL-USD \u03c3=0.0360, XLI \u03c3=0.0117, \u03c1=0.038. Min-variance weights: SOL-USD=0.086, XLI=0.914.", "question": "Assets: SOL-USD, XLI\nSOL-USD: annualized_mean_return=0.1260, daily_std=0.0360\nXLI: annualized_mean_return=0.6048, daily_std=0.0117\nMinimum required portfolio return (annualized): 0.5916\nMarket regime: sideways\n\nCompute portfolio weights (w_SOL-USD, w_XLI) 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_XLI=X.XXXX", "answer": "w_SOL-USD=0.0276, w_XLI=0.9724", "answer_numeric": 0.0276, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000137 - 0.000016) / (0.001295 + 0.000137 - 0.000032)\n Unconstrained: w_SOL-USD=0.0862\n After long-only clamp: w_SOL-USD=0.0862, w_XLI=0.9138.", "metadata": {"weights": {"SOL-USD": 0.0276, "XLI": 0.9724}, "sigma_1": 0.035981, "sigma_2": 0.011683, "covariance": 1.6e-05, "correlation": 0.0377, "has_text": true, "text_chars": 20, "mu_floor": 0.5916, "constraint_binding": true}} +{"id": "T4_all_20250210_0587", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BIL"], "decision_date": "2025-02-10", "context_summary": "EEM \u03c3=0.0086, BIL \u03c3=0.0002, \u03c1=0.116. Min-variance weights: EEM=0.000, BIL=1.000.", "question": "Assets: EEM, BIL\nEEM: annualized_mean_return=-0.0756, daily_std=0.0086\nBIL: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): -0.0180\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_BIL) 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_BIL=X.XXXX", "answer": "w_EEM=0.0003, w_BIL=0.9997", "answer_numeric": 0.0003, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000000) / (0.000074 + 0.000000 - 0.000000)\n Unconstrained: w_EEM=-0.0018\n After long-only clamp: w_EEM=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"EEM": 0.0003, "BIL": 0.9997}, "sigma_1": 0.008601, "sigma_2": 0.000157, "covariance": 0.0, "correlation": 0.1162, "has_text": true, "text_chars": 9046, "mu_floor": -0.018, "constraint_binding": false}} +{"id": "T4_all_20251215_0590", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "REZ"], "decision_date": "2025-12-15", "context_summary": "DOT-USD \u03c3=0.0492, REZ \u03c3=0.0085, \u03c1=0.063. Min-variance weights: DOT-USD=0.019, REZ=0.981.", "question": "Assets: DOT-USD, REZ\nDOT-USD: annualized_mean_return=-1.6884, daily_std=0.0492\nREZ: annualized_mean_return=-0.0000, daily_std=0.0085\nMinimum required portfolio return (annualized): -0.0173\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_REZ) 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_REZ=X.XXXX", "answer": "w_DOT-USD=0.0102, w_REZ=0.9898", "answer_numeric": 0.0102, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000073 - 0.000026) / (0.002425 + 0.000073 - 0.000053)\n Unconstrained: w_DOT-USD=0.0190\n After long-only clamp: w_DOT-USD=0.0190, w_REZ=0.9810.", "metadata": {"weights": {"DOT-USD": 0.0102, "REZ": 0.9898}, "sigma_1": 0.049241, "sigma_2": 0.008533, "covariance": 2.6e-05, "correlation": 0.0628, "has_text": true, "text_chars": 20, "mu_floor": -0.0173, "constraint_binding": true}} +{"id": "T4_all_20250811_0593", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI", "VNQ"], "decision_date": "2025-08-11", "context_summary": "ACWI \u03c3=0.0061, VNQ \u03c3=0.0091, \u03c1=0.545. Min-variance weights: ACWI=0.874, VNQ=0.126.", "question": "Assets: ACWI, VNQ\nACWI: annualized_mean_return=0.3276, daily_std=0.0061\nVNQ: annualized_mean_return=0.0756, daily_std=0.0091\nMinimum required portfolio return (annualized): 0.1957\nMarket regime: bull\n\nCompute portfolio weights (w_ACWI, w_VNQ) 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_VNQ=X.XXXX", "answer": "w_ACWI=0.8703, w_VNQ=0.1297", "answer_numeric": 0.8703, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000082 - 0.000030) / (0.000038 + 0.000082 - 0.000061)\n Unconstrained: w_ACWI=0.8742\n After long-only clamp: w_ACWI=0.8742, w_VNQ=0.1258.", "metadata": {"weights": {"ACWI": 0.8703, "VNQ": 0.1297}, "sigma_1": 0.006143, "sigma_2": 0.00905, "covariance": 3e-05, "correlation": 0.5453, "has_text": true, "text_chars": 3020, "mu_floor": 0.1957, "constraint_binding": false}} +{"id": "T4_all_20250411_0595", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VLUE", "SOL-USD"], "decision_date": "2025-04-11", "context_summary": "VLUE \u03c3=0.0126, SOL-USD \u03c3=0.0633, \u03c1=0.253. Min-variance weights: VLUE=1.000, SOL-USD=0.000.", "question": "Assets: VLUE, SOL-USD\nVLUE: annualized_mean_return=-0.3780, daily_std=0.0126\nSOL-USD: annualized_mean_return=-1.8900, daily_std=0.0633\nMinimum required portfolio return (annualized): -0.9949\nMarket regime: bear\n\nCompute portfolio weights (w_VLUE, w_SOL-USD) 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_SOL-USD=X.XXXX", "answer": "w_VLUE=1.0000, w_SOL-USD=0.0000", "answer_numeric": 1.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.004004 - 0.000201) / (0.000158 + 0.004004 - 0.000402)\n Unconstrained: w_VLUE=1.0115\n After long-only clamp: w_VLUE=1.0000, w_SOL-USD=0.0000.", "metadata": {"weights": {"VLUE": 1.0, "SOL-USD": 0.0}, "sigma_1": 0.012563, "sigma_2": 0.063279, "covariance": 0.000201, "correlation": 0.2529, "has_text": true, "text_chars": 3020, "mu_floor": -0.9949, "constraint_binding": false}} +{"id": "T4_all_20251029_0598", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BTC-USD", "VNQ"], "decision_date": "2025-10-29", "context_summary": "BTC-USD \u03c3=0.0178, VNQ \u03c3=0.0079, \u03c1=-0.067. Min-variance weights: BTC-USD=0.181, VNQ=0.819.", "question": "Assets: BTC-USD, VNQ\nBTC-USD: annualized_mean_return=0.2016, daily_std=0.0178\nVNQ: annualized_mean_return=0.1008, daily_std=0.0079\nMinimum required portfolio return (annualized): 0.1830\nMarket regime: bull\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=0.8155, w_VNQ=0.1845", "answer_numeric": 0.8155, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000063 - -0.000009) / (0.000316 + 0.000063 - -0.000019)\n Unconstrained: w_BTC-USD=0.1814\n After long-only clamp: w_BTC-USD=0.1814, w_VNQ=0.8186.", "metadata": {"weights": {"BTC-USD": 0.8155, "VNQ": 0.1845}, "sigma_1": 0.017775, "sigma_2": 0.007916, "covariance": -9e-06, "correlation": -0.0672, "has_text": true, "text_chars": 20, "mu_floor": 0.183, "constraint_binding": true}} +{"id": "T4_all_20250501_0601", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VTI", "ICSH"], "decision_date": "2025-05-01", "context_summary": "VTI \u03c3=0.0141, ICSH \u03c3=0.0004, \u03c1=0.158. Min-variance weights: VTI=0.000, ICSH=1.000.", "question": "Assets: VTI, ICSH\nVTI: annualized_mean_return=-0.4032, daily_std=0.0141\nICSH: annualized_mean_return=0.0756, daily_std=0.0004\nMinimum required portfolio return (annualized): 0.0384\nMarket regime: bear\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=0.0000, w_ICSH=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.000200 + 0.000000 - 0.000002)\n Unconstrained: w_VTI=-0.0034\n After long-only clamp: w_VTI=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"VTI": 0.0, "ICSH": 1.0}, "sigma_1": 0.014148, "sigma_2": 0.000356, "covariance": 1e-06, "correlation": 0.1582, "has_text": true, "text_chars": 9045, "mu_floor": 0.0384, "constraint_binding": false}} +{"id": "T4_all_20250127_0604", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "ICSH"], "decision_date": "2025-01-27", "context_summary": "BNB-USD \u03c3=0.0294, ICSH \u03c3=0.0003, \u03c1=0.064. Min-variance weights: BNB-USD=0.000, ICSH=1.000.", "question": "Assets: BNB-USD, ICSH\nBNB-USD: annualized_mean_return=0.2520, daily_std=0.0294\nICSH: annualized_mean_return=0.0504, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.1008\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=0.2500, w_ICSH=0.7500", "answer_numeric": 0.25, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000001) / (0.000864 + 0.000000 - 0.000001)\n Unconstrained: w_BNB-USD=-0.0005\n After long-only clamp: w_BNB-USD=0.0000, w_ICSH=1.0000.", "metadata": {"weights": {"BNB-USD": 0.25, "ICSH": 0.75}, "sigma_1": 0.029389, "sigma_2": 0.000289, "covariance": 1e-06, "correlation": 0.0637, "has_text": true, "text_chars": 20, "mu_floor": 0.1008, "constraint_binding": true}} +{"id": "T4_all_20250508_0607", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BNB-USD", "CPER"], "decision_date": "2025-05-08", "context_summary": "BNB-USD \u03c3=0.0231, CPER \u03c3=0.0189, \u03c1=-0.196. Min-variance weights: BNB-USD=0.416, CPER=0.584.", "question": "Assets: BNB-USD, CPER\nBNB-USD: annualized_mean_return=0.1512, daily_std=0.0231\nCPER: annualized_mean_return=-0.2016, daily_std=0.0189\nMinimum required portfolio return (annualized): -0.1265\nMarket regime: sideways\n\nCompute portfolio weights (w_BNB-USD, w_CPER) 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_CPER=X.XXXX", "answer": "w_BNB-USD=0.4165, w_CPER=0.5835", "answer_numeric": 0.4165, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000355 - -0.000085) / (0.000532 + 0.000355 - -0.000171)\n Unconstrained: w_BNB-USD=0.4165\n After long-only clamp: w_BNB-USD=0.4165, w_CPER=0.5835.", "metadata": {"weights": {"BNB-USD": 0.4165, "CPER": 0.5835}, "sigma_1": 0.023065, "sigma_2": 0.018852, "covariance": -8.5e-05, "correlation": -0.1963, "has_text": true, "text_chars": 20, "mu_floor": -0.1265, "constraint_binding": false}} +{"id": "T4_all_20250428_0609", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["AVAX-USD", "LQD"], "decision_date": "2025-04-28", "context_summary": "AVAX-USD \u03c3=0.0582, LQD \u03c3=0.0052, \u03c1=0.057. Min-variance weights: AVAX-USD=0.003, LQD=0.997.", "question": "Assets: AVAX-USD, LQD\nAVAX-USD: annualized_mean_return=0.4284, daily_std=0.0582\nLQD: annualized_mean_return=0.1008, daily_std=0.0052\nMinimum required portfolio return (annualized): 0.1017\nMarket regime: bear\n\nCompute portfolio weights (w_AVAX-USD, w_LQD) 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_LQD=X.XXXX", "answer": "w_AVAX-USD=0.0031, w_LQD=0.9969", "answer_numeric": 0.0031, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000027 - 0.000017) / (0.003389 + 0.000027 - 0.000035)\n Unconstrained: w_AVAX-USD=0.0030\n After long-only clamp: w_AVAX-USD=0.0030, w_LQD=0.9970.", "metadata": {"weights": {"AVAX-USD": 0.0031, "LQD": 0.9969}, "sigma_1": 0.058216, "sigma_2": 0.005236, "covariance": 1.7e-05, "correlation": 0.0566, "has_text": true, "text_chars": 20, "mu_floor": 0.1017, "constraint_binding": false}} +{"id": "T4_all_20250828_0611", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLI", "LINK-USD"], "decision_date": "2025-08-28", "context_summary": "XLI \u03c3=0.0069, LINK-USD \u03c3=0.0510, \u03c1=0.044. Min-variance weights: XLI=0.988, LINK-USD=0.012.", "question": "Assets: XLI, LINK-USD\nXLI: annualized_mean_return=0.3024, daily_std=0.0069\nLINK-USD: annualized_mean_return=2.7468, daily_std=0.0510\nMinimum required portfolio return (annualized): 0.3156\nMarket regime: bull\n\nCompute portfolio weights (w_XLI, w_LINK-USD) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLI=X.XXXX, w_LINK-USD=X.XXXX", "answer": "w_XLI=0.9879, w_LINK-USD=0.0121", "answer_numeric": 0.9879, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.002598 - 0.000016) / (0.000048 + 0.002598 - 0.000031)\n Unconstrained: w_XLI=0.9878\n After long-only clamp: w_XLI=0.9878, w_LINK-USD=0.0122.", "metadata": {"weights": {"XLI": 0.9879, "LINK-USD": 0.0121}, "sigma_1": 0.006902, "sigma_2": 0.050969, "covariance": 1.6e-05, "correlation": 0.0444, "has_text": true, "text_chars": 9046, "mu_floor": 0.3156, "constraint_binding": false}} +{"id": "T4_all_20251210_0614", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "CSHI"], "decision_date": "2025-12-10", "context_summary": "BTC-USD \u03c3=0.0228, CSHI \u03c3=0.0007, \u03c1=0.155. Min-variance weights: BTC-USD=0.000, CSHI=1.000.", "question": "Assets: BTC-USD, CSHI\nBTC-USD: annualized_mean_return=-0.7812, daily_std=0.0228\nCSHI: annualized_mean_return=0.0504, daily_std=0.0007\nMinimum required portfolio return (annualized): -0.1564\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_CSHI) 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_CSHI=X.XXXX", "answer": "w_BTC-USD=0.0000, w_CSHI=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000002) / (0.000518 + 0.000000 - 0.000005)\n Unconstrained: w_BTC-USD=-0.0038\n After long-only clamp: w_BTC-USD=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"BTC-USD": 0.0, "CSHI": 1.0}, "sigma_1": 0.022766, "sigma_2": 0.000675, "covariance": 2e-06, "correlation": 0.1553, "has_text": true, "text_chars": 20, "mu_floor": -0.1564, "constraint_binding": false}} +{"id": "T4_all_20251002_0617", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "DBC"], "decision_date": "2025-10-02", "context_summary": "QUAL \u03c3=0.0058, DBC \u03c3=0.0069, \u03c1=-0.097. Min-variance weights: QUAL=0.583, DBC=0.417.", "question": "Assets: QUAL, DBC\nQUAL: annualized_mean_return=0.2772, daily_std=0.0058\nDBC: annualized_mean_return=0.0504, daily_std=0.0069\nMinimum required portfolio return (annualized): 0.1491\nMarket regime: bull\n\nCompute portfolio weights (w_QUAL, w_DBC) 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_DBC=X.XXXX", "answer": "w_QUAL=0.5831, w_DBC=0.4169", "answer_numeric": 0.5831, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000048 - -0.000004) / (0.000033 + 0.000048 - -0.000008)\n Unconstrained: w_QUAL=0.5833\n After long-only clamp: w_QUAL=0.5833, w_DBC=0.4167.", "metadata": {"weights": {"QUAL": 0.5831, "DBC": 0.4169}, "sigma_1": 0.005767, "sigma_2": 0.006936, "covariance": -4e-06, "correlation": -0.0969, "has_text": true, "text_chars": 3020, "mu_floor": 0.1491, "constraint_binding": false}} +{"id": "T4_all_20250526_0620", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "USO"], "decision_date": "2025-05-26", "context_summary": "USMV \u03c3=0.0097, USO \u03c3=0.0222, \u03c1=0.385. Min-variance weights: USMV=0.975, USO=0.025.", "question": "Assets: USMV, USO\nUSMV: annualized_mean_return=0.0000, daily_std=0.0097\nUSO: annualized_mean_return=-0.4032, daily_std=0.0222\nMinimum required portfolio return (annualized): -0.0034\nMarket regime: sideways\n\nCompute portfolio weights (w_USMV, w_USO) 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_USO=X.XXXX", "answer": "w_USMV=0.9916, w_USO=0.0084", "answer_numeric": 0.9916, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000493 - 0.000083) / (0.000093 + 0.000493 - 0.000165)\n Unconstrained: w_USMV=0.9745\n After long-only clamp: w_USMV=0.9745, w_USO=0.0255.", "metadata": {"weights": {"USMV": 0.9916, "USO": 0.0084}, "sigma_1": 0.009657, "sigma_2": 0.022206, "covariance": 8.3e-05, "correlation": 0.3847, "has_text": true, "text_chars": 3020, "mu_floor": -0.0034, "constraint_binding": true}} +{"id": "T4_all_20250731_0623", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "VNQI"], "decision_date": "2025-07-31", "context_summary": "IWM \u03c3=0.0113, VNQI \u03c3=0.0063, \u03c1=0.423. Min-variance weights: IWM=0.086, VNQI=0.914.", "question": "Assets: IWM, VNQI\nIWM: annualized_mean_return=0.4284, daily_std=0.0113\nVNQI: annualized_mean_return=0.2016, daily_std=0.0063\nMinimum required portfolio return (annualized): 0.2189\nMarket regime: bull\n\nCompute portfolio weights (w_IWM, w_VNQI) 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_VNQI=X.XXXX", "answer": "w_IWM=0.0856, w_VNQI=0.9144", "answer_numeric": 0.0856, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000039 - 0.000030) / (0.000128 + 0.000039 - 0.000060)\n Unconstrained: w_IWM=0.0855\n After long-only clamp: w_IWM=0.0855, w_VNQI=0.9145.", "metadata": {"weights": {"IWM": 0.0856, "VNQI": 0.9144}, "sigma_1": 0.011322, "sigma_2": 0.00626, "covariance": 3e-05, "correlation": 0.4234, "has_text": true, "text_chars": 9046, "mu_floor": 0.2189, "constraint_binding": false}} +{"id": "T4_all_20250515_0626", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "REZ"], "decision_date": "2025-05-15", "context_summary": "XLF \u03c3=0.0150, REZ \u03c3=0.0132, \u03c1=0.656. Min-variance weights: XLF=0.325, REZ=0.675.", "question": "Assets: XLF, REZ\nXLF: annualized_mean_return=-0.0252, daily_std=0.0150\nREZ: annualized_mean_return=-0.1008, daily_std=0.0132\nMinimum required portfolio return (annualized): -0.0646\nMarket regime: sideways\n\nCompute portfolio weights (w_XLF, w_REZ) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLF=X.XXXX, w_REZ=X.XXXX", "answer": "w_XLF=0.4788, w_REZ=0.5212", "answer_numeric": 0.4788, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000175 - 0.000130) / (0.000224 + 0.000175 - 0.000259)\n Unconstrained: w_XLF=0.3245\n After long-only clamp: w_XLF=0.3245, w_REZ=0.6755.", "metadata": {"weights": {"XLF": 0.4788, "REZ": 0.5212}, "sigma_1": 0.014954, "sigma_2": 0.013221, "covariance": 0.00013, "correlation": 0.6558, "has_text": true, "text_chars": 3020, "mu_floor": -0.0646, "constraint_binding": true}} +{"id": "T4_all_20250815_0629", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "SGOV"], "decision_date": "2025-08-15", "context_summary": "IWM \u03c3=0.0117, SGOV \u03c3=0.0002, \u03c1=-0.042. Min-variance weights: IWM=0.001, SGOV=0.999.", "question": "Assets: IWM, SGOV\nIWM: annualized_mean_return=0.3780, daily_std=0.0117\nSGOV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: bull\n\nCompute portfolio weights (w_IWM, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_SGOV=X.XXXX", "answer": "w_IWM=0.0002, w_SGOV=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000137 + 0.000000 - -0.000000)\n Unconstrained: w_IWM=0.0008\n After long-only clamp: w_IWM=0.0008, w_SGOV=0.9992.", "metadata": {"weights": {"IWM": 0.0002, "SGOV": 0.9998}, "sigma_1": 0.011701, "sigma_2": 0.00016, "covariance": -0.0, "correlation": -0.0421, "has_text": true, "text_chars": 3020, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20250905_0632", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE", "WEAT"], "decision_date": "2025-09-05", "context_summary": "XLRE \u03c3=0.0087, WEAT \u03c3=0.0137, \u03c1=0.041. Min-variance weights: XLRE=0.719, WEAT=0.281.", "question": "Assets: XLRE, WEAT\nXLRE: annualized_mean_return=0.0252, daily_std=0.0087\nWEAT: annualized_mean_return=-0.1008, daily_std=0.0137\nMinimum required portfolio return (annualized): 0.0115\nMarket regime: bull\n\nCompute portfolio weights (w_XLRE, w_WEAT) 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_WEAT=X.XXXX", "answer": "w_XLRE=0.8913, w_WEAT=0.1087", "answer_numeric": 0.8913, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000187 - 0.000005) / (0.000076 + 0.000187 - 0.000010)\n Unconstrained: w_XLRE=0.7185\n After long-only clamp: w_XLRE=0.7185, w_WEAT=0.2815.", "metadata": {"weights": {"XLRE": 0.8913, "WEAT": 0.1087}, "sigma_1": 0.008744, "sigma_2": 0.013689, "covariance": 5e-06, "correlation": 0.0414, "has_text": true, "text_chars": 3020, "mu_floor": 0.0115, "constraint_binding": true}} +{"id": "T4_all_20250418_0634", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VTI", "BIL"], "decision_date": "2025-04-18", "context_summary": "VTI \u03c3=0.0130, BIL \u03c3=0.0001, \u03c1=0.055. Min-variance weights: VTI=0.000, BIL=1.000.", "question": "Assets: VTI, BIL\nVTI: annualized_mean_return=-0.6804, daily_std=0.0130\nBIL: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0503\nMarket regime: bear\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) / (0.000169 + 0.000000 - 0.000000)\n Unconstrained: w_VTI=-0.0005\n After long-only clamp: w_VTI=0.0000, w_BIL=1.0000.", "metadata": {"weights": {"VTI": 0.0001, "BIL": 0.9999}, "sigma_1": 0.013014, "sigma_2": 0.00013, "covariance": 0.0, "correlation": 0.0553, "has_text": true, "text_chars": 3020, "mu_floor": 0.0503, "constraint_binding": true}} +{"id": "T4_all_20250904_0637", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD", "ICSH"], "decision_date": "2025-09-04", "context_summary": "LINK-USD \u03c3=0.0517, ICSH \u03c3=0.0003, \u03c1=-0.113. Min-variance weights: LINK-USD=0.001, ICSH=0.999.", "question": "Assets: LINK-USD, ICSH\nLINK-USD: annualized_mean_return=2.7972, daily_std=0.0517\nICSH: annualized_mean_return=0.0756, daily_std=0.0003\nMinimum required portfolio return (annualized): 0.0775\nMarket regime: bull\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=0.0008, w_ICSH=0.9992", "answer_numeric": 0.0008, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000002) / (0.002677 + 0.000000 - -0.000004)\n Unconstrained: w_LINK-USD=0.0008\n After long-only clamp: w_LINK-USD=0.0008, w_ICSH=0.9992.", "metadata": {"weights": {"LINK-USD": 0.0008, "ICSH": 0.9992}, "sigma_1": 0.05174, "sigma_2": 0.000348, "covariance": -2e-06, "correlation": -0.1134, "has_text": true, "text_chars": 20, "mu_floor": 0.0775, "constraint_binding": false}} +{"id": "T4_all_20250703_0640", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "BNDX"], "decision_date": "2025-07-03", "context_summary": "BTC-USD \u03c3=0.0179, BNDX \u03c3=0.0022, \u03c1=0.056. Min-variance weights: BTC-USD=0.008, BNDX=0.992.", "question": "Assets: BTC-USD, BNDX\nBTC-USD: annualized_mean_return=0.5796, daily_std=0.0179\nBNDX: annualized_mean_return=0.1008, daily_std=0.0022\nMinimum required portfolio return (annualized): 0.3827\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_BNDX) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_BTC-USD=X.XXXX, w_BNDX=X.XXXX", "answer": "w_BTC-USD=0.5888, w_BNDX=0.4112", "answer_numeric": 0.5888, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000005 - 0.000002) / (0.000321 + 0.000005 - 0.000004)\n Unconstrained: w_BTC-USD=0.0079\n After long-only clamp: w_BTC-USD=0.0079, w_BNDX=0.9921.", "metadata": {"weights": {"BTC-USD": 0.5888, "BNDX": 0.4112}, "sigma_1": 0.017919, "sigma_2": 0.002176, "covariance": 2e-06, "correlation": 0.0563, "has_text": true, "text_chars": 20, "mu_floor": 0.3827, "constraint_binding": true}} +{"id": "T4_all_20251006_0642", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLY", "STIP"], "decision_date": "2025-10-06", "context_summary": "XLY \u03c3=0.0095, STIP \u03c3=0.0010, \u03c1=-0.010. Min-variance weights: XLY=0.013, STIP=0.987.", "question": "Assets: XLY, STIP\nXLY: annualized_mean_return=0.3024, daily_std=0.0095\nSTIP: annualized_mean_return=0.0504, daily_std=0.0010\nMinimum required portfolio return (annualized): 0.2021\nMarket regime: bull\n\nCompute portfolio weights (w_XLY, w_STIP) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_XLY=X.XXXX, w_STIP=X.XXXX", "answer": "w_XLY=0.6020, w_STIP=0.3980", "answer_numeric": 0.602, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - -0.000000) / (0.000090 + 0.000001 - -0.000000)\n Unconstrained: w_XLY=0.0128\n After long-only clamp: w_XLY=0.0128, w_STIP=0.9872.", "metadata": {"weights": {"XLY": 0.602, "STIP": 0.398}, "sigma_1": 0.009508, "sigma_2": 0.001034, "covariance": -0.0, "correlation": -0.0104, "has_text": true, "text_chars": 3020, "mu_floor": 0.2021, "constraint_binding": true}} +{"id": "T4_all_20250205_0646", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MATIC-USD", "PDBC"], "decision_date": "2025-02-05", "context_summary": "MATIC-USD \u03c3=0.0493, PDBC \u03c3=0.0074, \u03c1=-0.072. Min-variance weights: MATIC-USD=0.032, PDBC=0.968.", "question": "Assets: MATIC-USD, PDBC\nMATIC-USD: annualized_mean_return=-3.1248, daily_std=0.0493\nPDBC: annualized_mean_return=0.2268, daily_std=0.0074\nMinimum required portfolio return (annualized): 0.1966\nMarket regime: sideways\n\nCompute portfolio weights (w_MATIC-USD, w_PDBC) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_MATIC-USD=X.XXXX, w_PDBC=X.XXXX", "answer": "w_MATIC-USD=0.0090, w_PDBC=0.9910", "answer_numeric": 0.009, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000054 - -0.000026) / (0.002432 + 0.000054 - -0.000052)\n Unconstrained: w_MATIC-USD=0.0316\n After long-only clamp: w_MATIC-USD=0.0316, w_PDBC=0.9684.", "metadata": {"weights": {"MATIC-USD": 0.009, "PDBC": 0.991}, "sigma_1": 0.049319, "sigma_2": 0.007351, "covariance": -2.6e-05, "correlation": -0.072, "has_text": true, "text_chars": 20, "mu_floor": 0.1966, "constraint_binding": true}} +{"id": "T4_all_20250103_0649", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["BTC-USD", "STIP"], "decision_date": "2025-01-03", "context_summary": "BTC-USD \u03c3=0.0286, STIP \u03c3=0.0010, \u03c1=-0.344. Min-variance weights: BTC-USD=0.013, STIP=0.987.", "question": "Assets: BTC-USD, STIP\nBTC-USD: annualized_mean_return=1.5372, daily_std=0.0286\nSTIP: annualized_mean_return=0.0252, daily_std=0.0010\nMinimum required portfolio return (annualized): 0.0439\nMarket regime: sideways\n\nCompute portfolio weights (w_BTC-USD, w_STIP) 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_STIP=X.XXXX", "answer": "w_BTC-USD=0.0130, w_STIP=0.9870", "answer_numeric": 0.013, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000001 - -0.000010) / (0.000819 + 0.000001 - -0.000019)\n Unconstrained: w_BTC-USD=0.0126\n After long-only clamp: w_BTC-USD=0.0126, w_STIP=0.9874.", "metadata": {"weights": {"BTC-USD": 0.013, "STIP": 0.987}, "sigma_1": 0.02861, "sigma_2": 0.000974, "covariance": -1e-05, "correlation": -0.344, "has_text": true, "text_chars": 20, "mu_floor": 0.0439, "constraint_binding": false}} +{"id": "T4_all_20250723_0651", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "SGOV"], "decision_date": "2025-07-23", "context_summary": "IWM \u03c3=0.0113, SGOV \u03c3=0.0001, \u03c1=-0.061. Min-variance weights: IWM=0.001, SGOV=0.999.", "question": "Assets: IWM, SGOV\nIWM: annualized_mean_return=0.6048, daily_std=0.0113\nSGOV: annualized_mean_return=0.0504, daily_std=0.0001\nMinimum required portfolio return (annualized): 0.0505\nMarket regime: bull\n\nCompute portfolio weights (w_IWM, w_SGOV) that minimize portfolio variance while satisfying the minimum return constraint. Constraints: all weights >= 0, weights sum to 1. Report as: w_IWM=X.XXXX, w_SGOV=X.XXXX", "answer": "w_IWM=0.0002, w_SGOV=0.9998", "answer_numeric": 0.0002, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - -0.000000) / (0.000127 + 0.000000 - -0.000000)\n Unconstrained: w_IWM=0.0010\n After long-only clamp: w_IWM=0.0010, w_SGOV=0.9990.", "metadata": {"weights": {"IWM": 0.0002, "SGOV": 0.9998}, "sigma_1": 0.01129, "sigma_2": 0.000148, "covariance": -0.0, "correlation": -0.0607, "has_text": true, "text_chars": 3020, "mu_floor": 0.0505, "constraint_binding": false}} +{"id": "T4_all_20250211_0654", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "SCHH"], "decision_date": "2025-02-11", "context_summary": "EEM \u03c3=0.0087, SCHH \u03c3=0.0104, \u03c1=0.385. Min-variance weights: EEM=0.646, SCHH=0.354.", "question": "Assets: EEM, SCHH\nEEM: annualized_mean_return=0.0252, daily_std=0.0087\nSCHH: annualized_mean_return=-0.1008, daily_std=0.0104\nMinimum required portfolio return (annualized): 0.0037\nMarket regime: sideways\n\nCompute portfolio weights (w_EEM, w_SCHH) 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_SCHH=X.XXXX", "answer": "w_EEM=0.8294, w_SCHH=0.1706", "answer_numeric": 0.8294, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000109 - 0.000035) / (0.000075 + 0.000109 - 0.000070)\n Unconstrained: w_EEM=0.6459\n After long-only clamp: w_EEM=0.6459, w_SCHH=0.3541.", "metadata": {"weights": {"EEM": 0.8294, "SCHH": 0.1706}, "sigma_1": 0.008687, "sigma_2": 0.010435, "covariance": 3.5e-05, "correlation": 0.3851, "has_text": true, "text_chars": 9046, "mu_floor": 0.0037, "constraint_binding": true}} +{"id": "T4_all_20250321_0657", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "TLH"], "decision_date": "2025-03-21", "context_summary": "LINK-USD \u03c3=0.0568, TLH \u03c3=0.0061, \u03c1=-0.145. Min-variance weights: LINK-USD=0.026, TLH=0.974.", "question": "Assets: LINK-USD, TLH\nLINK-USD: annualized_mean_return=-1.8144, daily_std=0.0568\nTLH: annualized_mean_return=0.2268, daily_std=0.0061\nMinimum required portfolio return (annualized): -0.4249\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_TLH) 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_TLH=X.XXXX", "answer": "w_LINK-USD=0.0259, w_TLH=0.9741", "answer_numeric": 0.0259, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000037 - -0.000050) / (0.003230 + 0.000037 - -0.000101)\n Unconstrained: w_LINK-USD=0.0260\n After long-only clamp: w_LINK-USD=0.0260, w_TLH=0.9740.", "metadata": {"weights": {"LINK-USD": 0.0259, "TLH": 0.9741}, "sigma_1": 0.056833, "sigma_2": 0.006105, "covariance": -5e-05, "correlation": -0.145, "has_text": true, "text_chars": 20, "mu_floor": -0.4249, "constraint_binding": false}} +{"id": "T4_all_20250110_0659", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["LINK-USD", "CPER"], "decision_date": "2025-01-10", "context_summary": "LINK-USD \u03c3=0.0635, CPER \u03c3=0.0123, \u03c1=-0.085. Min-variance weights: LINK-USD=0.050, CPER=0.950.", "question": "Assets: LINK-USD, CPER\nLINK-USD: annualized_mean_return=1.2096, daily_std=0.0635\nCPER: annualized_mean_return=-0.0252, daily_std=0.0123\nMinimum required portfolio return (annualized): 0.0251\nMarket regime: sideways\n\nCompute portfolio weights (w_LINK-USD, w_CPER) 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_CPER=X.XXXX", "answer": "w_LINK-USD=0.0501, w_CPER=0.9499", "answer_numeric": 0.0501, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000150 - -0.000066) / (0.004035 + 0.000150 - -0.000132)\n Unconstrained: w_LINK-USD=0.0502\n After long-only clamp: w_LINK-USD=0.0502, w_CPER=0.9498.", "metadata": {"weights": {"LINK-USD": 0.0501, "CPER": 0.9499}, "sigma_1": 0.06352, "sigma_2": 0.012264, "covariance": -6.6e-05, "correlation": -0.0849, "has_text": true, "text_chars": 20, "mu_floor": 0.0251, "constraint_binding": false}} +{"id": "T4_all_20250728_0662", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["BNB-USD", "XLP"], "decision_date": "2025-07-28", "context_summary": "BNB-USD \u03c3=0.0166, XLP \u03c3=0.0069, \u03c1=0.129. Min-variance weights: BNB-USD=0.111, XLP=0.889.", "question": "Assets: BNB-USD, XLP\nBNB-USD: annualized_mean_return=0.8820, daily_std=0.0166\nXLP: annualized_mean_return=0.0504, daily_std=0.0069\nMinimum required portfolio return (annualized): 0.3195\nMarket regime: bull\n\nCompute portfolio weights (w_BNB-USD, w_XLP) 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_XLP=X.XXXX", "answer": "w_BNB-USD=0.3236, w_XLP=0.6764", "answer_numeric": 0.3236, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000048 - 0.000015) / (0.000277 + 0.000048 - 0.000030)\n Unconstrained: w_BNB-USD=0.1110\n After long-only clamp: w_BNB-USD=0.1110, w_XLP=0.8890.", "metadata": {"weights": {"BNB-USD": 0.3236, "XLP": 0.6764}, "sigma_1": 0.016649, "sigma_2": 0.006894, "covariance": 1.5e-05, "correlation": 0.1286, "has_text": true, "text_chars": 20, "mu_floor": 0.3195, "constraint_binding": true}} +{"id": "T4_all_20250611_0665", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "DOT-USD"], "decision_date": "2025-06-11", "context_summary": "XLB \u03c3=0.0139, DOT-USD \u03c3=0.0378, \u03c1=0.117. Min-variance weights: XLB=0.911, DOT-USD=0.088.", "question": "Assets: XLB, DOT-USD\nXLB: annualized_mean_return=0.1260, daily_std=0.0139\nDOT-USD: annualized_mean_return=0.9576, daily_std=0.0378\nMinimum required portfolio return (annualized): 0.1569\nMarket regime: sideways\n\nCompute portfolio weights (w_XLB, w_DOT-USD) 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_DOT-USD=X.XXXX", "answer": "w_XLB=0.9117, w_DOT-USD=0.0883", "answer_numeric": 0.9117, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.001426 - 0.000062) / (0.000194 + 0.001426 - 0.000123)\n Unconstrained: w_XLB=0.9115\n After long-only clamp: w_XLB=0.9115, w_DOT-USD=0.0885.", "metadata": {"weights": {"XLB": 0.9117, "DOT-USD": 0.0883}, "sigma_1": 0.013933, "sigma_2": 0.037762, "covariance": 6.2e-05, "correlation": 0.1171, "has_text": true, "text_chars": 3020, "mu_floor": 0.1569, "constraint_binding": false}} +{"id": "T4_all_20250930_0667", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ETH-USD", "SGOV"], "decision_date": "2025-09-30", "context_summary": "ETH-USD \u03c3=0.0388, SGOV \u03c3=0.0002, \u03c1=0.051. Min-variance weights: ETH-USD=0.000, SGOV=1.000.", "question": "Assets: ETH-USD, SGOV\nETH-USD: annualized_mean_return=0.7308, daily_std=0.0388\nSGOV: annualized_mean_return=0.0504, daily_std=0.0002\nMinimum required portfolio return (annualized): 0.0504\nMarket regime: bull\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) / (0.001503 + 0.000000 - 0.000001)\n Unconstrained: w_ETH-USD=-0.0002\n After long-only clamp: w_ETH-USD=0.0000, w_SGOV=1.0000.", "metadata": {"weights": {"ETH-USD": 0.0, "SGOV": 1.0}, "sigma_1": 0.038764, "sigma_2": 0.000166, "covariance": 0.0, "correlation": 0.0508, "has_text": true, "text_chars": 20, "mu_floor": 0.0504, "constraint_binding": false}} +{"id": "T4_all_20250507_0670", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "VNQI"], "decision_date": "2025-05-07", "context_summary": "XLI \u03c3=0.0136, VNQI \u03c3=0.0093, \u03c1=0.599. Min-variance weights: XLI=0.090, VNQI=0.910.", "question": "Assets: XLI, VNQI\nXLI: annualized_mean_return=-0.1008, daily_std=0.0136\nVNQI: annualized_mean_return=0.3276, daily_std=0.0093\nMinimum required portfolio return (annualized): 0.3195\nMarket regime: sideways\n\nCompute portfolio weights (w_XLI, w_VNQI) 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_VNQI=X.XXXX", "answer": "w_XLI=0.0189, w_VNQI=0.9811", "answer_numeric": 0.0189, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000086 - 0.000075) / (0.000184 + 0.000086 - 0.000151)\n Unconstrained: w_XLI=0.0900\n After long-only clamp: w_XLI=0.0900, w_VNQI=0.9100.", "metadata": {"weights": {"XLI": 0.0189, "VNQI": 0.9811}, "sigma_1": 0.013558, "sigma_2": 0.00928, "covariance": 7.5e-05, "correlation": 0.5992, "has_text": true, "text_chars": 3020, "mu_floor": 0.3195, "constraint_binding": true}} +{"id": "T4_all_20250325_0673", "template": "T4", "complexity": 2, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["DOT-USD", "CSHI"], "decision_date": "2025-03-25", "context_summary": "DOT-USD \u03c3=0.0454, CSHI \u03c3=0.0006, \u03c1=0.174. Min-variance weights: DOT-USD=0.000, CSHI=1.000.", "question": "Assets: DOT-USD, CSHI\nDOT-USD: annualized_mean_return=-1.0836, daily_std=0.0454\nCSHI: annualized_mean_return=0.0504, daily_std=0.0006\nMinimum required portfolio return (annualized): -0.2324\nMarket regime: sideways\n\nCompute portfolio weights (w_DOT-USD, w_CSHI) 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_CSHI=X.XXXX", "answer": "w_DOT-USD=0.0000, w_CSHI=1.0000", "answer_numeric": 0.0, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000000 - 0.000005) / (0.002061 + 0.000000 - 0.000010)\n Unconstrained: w_DOT-USD=-0.0022\n After long-only clamp: w_DOT-USD=0.0000, w_CSHI=1.0000.", "metadata": {"weights": {"DOT-USD": 0.0, "CSHI": 1.0}, "sigma_1": 0.045403, "sigma_2": 0.000604, "covariance": 5e-06, "correlation": 0.1742, "has_text": true, "text_chars": 20, "mu_floor": -0.2324, "constraint_binding": false}} +{"id": "T4_all_20251021_0675", "template": "T4", "complexity": 2, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["LINK-USD", "BNO"], "decision_date": "2025-10-21", "context_summary": "LINK-USD \u03c3=0.0472, BNO \u03c3=0.0146, \u03c1=0.052. Min-variance weights: LINK-USD=0.074, BNO=0.925.", "question": "Assets: LINK-USD, BNO\nLINK-USD: annualized_mean_return=-0.8064, daily_std=0.0472\nBNO: annualized_mean_return=-0.4536, daily_std=0.0146\nMinimum required portfolio return (annualized): -0.5313\nMarket regime: bull\n\nCompute portfolio weights (w_LINK-USD, w_BNO) 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_BNO=X.XXXX", "answer": "w_LINK-USD=0.0744, w_BNO=0.9256", "answer_numeric": 0.0744, "explanation": "Analytic min-variance formula:\n w1* = (\u03c32\u00b2 - \u03c312) / (\u03c31\u00b2 + \u03c32\u00b2 - 2\u03c312)\n = (0.000212 - 0.000036) / (0.002225 + 0.000212 - 0.000072)\n Unconstrained: w_LINK-USD=0.0745\n After long-only clamp: w_LINK-USD=0.0745, w_BNO=0.9255.", "metadata": {"weights": {"LINK-USD": 0.0744, "BNO": 0.9256}, "sigma_1": 0.047174, "sigma_2": 0.014561, "covariance": 3.6e-05, "correlation": 0.0521, "has_text": true, "text_chars": 20, "mu_floor": -0.5313, "constraint_binding": false}} +{"id": "T5_all_20251226_0001", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "XRP-USD", "IGOV", "REZ"], "decision_date": "2025-12-26", "context_summary": "4-asset optimization. Max-Sharpe: 0.185. Portfolio: return=7.38%, vol=18.26%. Weights: w_QQQ=1.0000, w_XRP-USD=0.0000, w_IGOV=0.0000, w_REZ=0.0000.", "question": "Assets: QQQ, XRP-USD, IGOV, REZ\nAnnualized mean returns: QQQ:0.0738, XRP-USD:-2.1648, IGOV:-0.0114, REZ:-0.0626\nCovariance matrix (annualized):\n[[0.033336, 0.056593, 0.001731, -0.002864], [0.056593, 0.387307, 0.002656, -0.000389], [0.001731, 0.002656, 0.002677, 0.001857], [-0.002864, -0.000389, 0.001857, 0.020961]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=1.0000, w_XRP-USD=0.0000, w_IGOV=0.0000, w_REZ=0.0000", "answer_numeric": 0.1849496297925387, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=1.0000, w_XRP-USD=0.0000, w_IGOV=0.0000, w_REZ=0.0000\nPortfolio annualized return: 7.38%, volatility: 18.26%\nSharpe ratio: (0.0738 - 0.0400) / 0.1826 = 0.1849", "metadata": {"weights": {"QQQ": 1.0, "XRP-USD": 0.0, "IGOV": 0.0, "REZ": 0.0}, "sharpe_ratio": 0.1849, "portfolio_return": 0.073769, "portfolio_vol": 0.182582, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251027_0003", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLE", "BTC-USD", "REZ", "GLD"], "decision_date": "2025-10-27", "context_summary": "4-asset optimization. Max-Sharpe: 7.307. Portfolio: return=128.96%, vol=17.10%. Weights: w_XLE=0.0408, w_BTC-USD=0.0000, w_REZ=0.0139, w_GLD=0.9453.", "question": "Assets: XLE, BTC-USD, REZ, GLD\nAnnualized mean returns: XLE:-0.0275, BTC-USD:-0.4041, REZ:0.0860, GLD:1.3642\nCovariance matrix (annualized):\n[[0.032443, 0.015183, 0.00166, -0.003098], [0.015183, 0.104165, -0.005615, 0.003206], [0.00166, -0.005615, 0.014375, 0.000856], [-0.003098, 0.003206, 0.000856, 0.032911]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0408, w_BTC-USD=0.0000, w_REZ=0.0139, w_GLD=0.9453", "answer_numeric": 7.306508079828266, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0408, w_BTC-USD=0.0000, w_REZ=0.0139, w_GLD=0.9453\nPortfolio annualized return: 128.96%, volatility: 17.10%\nSharpe ratio: (1.2896 - 0.0400) / 0.1710 = 7.3065", "metadata": {"weights": {"XLE": 0.0408, "BTC-USD": 0.0, "REZ": 0.0139, "GLD": 0.9453}, "sharpe_ratio": 7.3065, "portfolio_return": 1.289619, "portfolio_vol": 0.171028, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20251209_0006", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BTC-USD", "VNQ", "CSHI"], "decision_date": "2025-12-09", "context_summary": "4-asset optimization. Max-Sharpe: 1.291. Portfolio: return=5.49%, vol=1.15%. Weights: w_XLF=0.0000, w_BTC-USD=0.0000, w_VNQ=0.0000, w_CSHI=1.0000.", "question": "Assets: XLF, BTC-USD, VNQ, CSHI\nAnnualized mean returns: XLF:0.0184, BTC-USD:-2.4667, VNQ:0.0043, CSHI:0.0549\nCovariance matrix (annualized):\n[[0.024178, 0.031554, 0.014326, 0.00054], [0.031554, 0.171106, 0.015982, 0.001341], [0.014326, 0.015982, 0.019973, 0.000463], [0.00054, 0.001341, 0.000463, 0.000133]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_BTC-USD=0.0000, w_VNQ=0.0000, w_CSHI=1.0000", "answer_numeric": 1.2906173596365569, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_BTC-USD=0.0000, w_VNQ=0.0000, w_CSHI=1.0000\nPortfolio annualized return: 5.49%, volatility: 1.15%\nSharpe ratio: (0.0549 - 0.0400) / 0.0115 = 1.2906", "metadata": {"weights": {"XLF": 0.0, "BTC-USD": 0.0, "VNQ": 0.0, "CSHI": 1.0}, "sharpe_ratio": 1.2906, "portfolio_return": 0.054907, "portfolio_vol": 0.01155, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250716_0008", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "SOL-USD", "ICSH", "DBB"], "decision_date": "2025-07-16", "context_summary": "4-asset optimization. Max-Sharpe: 4.315. Portfolio: return=5.37%, vol=0.32%. Weights: w_QUAL=0.0000, w_SOL-USD=0.0000, w_ICSH=0.9974, w_DBB=0.0026.", "question": "Assets: QUAL, SOL-USD, ICSH, DBB\nAnnualized mean returns: QUAL:0.1384, SOL-USD:-0.7355, ICSH:0.0533, DBB:0.2040\nCovariance matrix (annualized):\n[[0.014461, 0.0159, 0.000142, 0.00558], [0.0159, 0.299291, 0.000413, 0.020013], [0.000142, 0.000413, 1e-05, 8.1e-05], [0.00558, 0.020013, 8.1e-05, 0.015187]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0000, w_SOL-USD=0.0000, w_ICSH=0.9974, w_DBB=0.0026", "answer_numeric": 4.315059985460373, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_SOL-USD=0.0000, w_ICSH=0.9974, w_DBB=0.0026\nPortfolio annualized return: 5.37%, volatility: 0.32%\nSharpe ratio: (0.0537 - 0.0400) / 0.0032 = 4.3151", "metadata": {"weights": {"QUAL": 0.0, "SOL-USD": 0.0, "ICSH": 0.9974, "DBB": 0.0026}, "sharpe_ratio": 4.3151, "portfolio_return": 0.053658, "portfolio_vol": 0.003165, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250424_0011", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLV", "BTC-USD", "SHY", "PPLT"], "decision_date": "2025-04-24", "context_summary": "4-asset optimization. Max-Sharpe: 1.800. Portfolio: return=6.73%, vol=1.51%. Weights: w_XLV=0.0000, w_BTC-USD=0.0134, w_SHY=0.9842, w_PPLT=0.0024.", "question": "Assets: XLV, BTC-USD, SHY, PPLT\nAnnualized mean returns: XLV:-0.3790, BTC-USD:0.2376, SHY:0.0651, PPLT:-0.0016\nCovariance matrix (annualized):\n[[0.034805, 0.023514, -8.9e-05, 0.008974], [0.023514, 0.293137, -0.002342, 0.013667], [-8.9e-05, -0.002342, 0.000248, -0.000618], [0.008974, 0.013667, -0.000618, 0.031301]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_BTC-USD=0.0134, w_SHY=0.9842, w_PPLT=0.0024", "answer_numeric": 1.7999091048296258, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_BTC-USD=0.0134, w_SHY=0.9842, w_PPLT=0.0024\nPortfolio annualized return: 6.73%, volatility: 1.51%\nSharpe ratio: (0.0673 - 0.0400) / 0.0151 = 1.7999", "metadata": {"weights": {"XLV": 0.0, "BTC-USD": 0.0134, "SHY": 0.9842, "PPLT": 0.0024}, "sharpe_ratio": 1.7999, "portfolio_return": 0.06726, "portfolio_vol": 0.015145, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20250711_0014", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "ETH-USD", "HAUZ", "TLT"], "decision_date": "2025-07-11", "context_summary": "4-asset optimization. Max-Sharpe: 3.854. Portfolio: return=49.12%, vol=11.71%. Weights: w_XLV=0.0000, w_ETH-USD=0.1098, w_HAUZ=0.8902, w_TLT=0.0000.", "question": "Assets: XLV, ETH-USD, HAUZ, TLT\nAnnualized mean returns: XLV:0.2025, ETH-USD:1.4916, HAUZ:0.3678, TLT:0.0491\nCovariance matrix (annualized):\n[[0.03041, -0.009272, 0.007789, 0.007123], [-0.009272, 0.347793, 0.006634, -0.001526], [0.007789, 0.006634, 0.010368, 0.004981], [0.007123, -0.001526, 0.004981, 0.015645]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_ETH-USD=0.1098, w_HAUZ=0.8902, w_TLT=0.0000", "answer_numeric": 3.8537530310262165, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_ETH-USD=0.1098, w_HAUZ=0.8902, w_TLT=0.0000\nPortfolio annualized return: 49.12%, volatility: 11.71%\nSharpe ratio: (0.4912 - 0.0400) / 0.1171 = 3.8538", "metadata": {"weights": {"XLV": 0.0, "ETH-USD": 0.1098, "HAUZ": 0.8902, "TLT": 0.0}, "sharpe_ratio": 3.8538, "portfolio_return": 0.491199, "portfolio_vol": 0.117081, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250421_0017", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["QUAL", "BNB-USD", "DBA", "SHY"], "decision_date": "2025-04-21", "context_summary": "4-asset optimization. Max-Sharpe: 2.973. Portfolio: return=8.31%, vol=1.45%. Weights: w_QUAL=0.0000, w_BNB-USD=0.0145, w_DBA=0.0000, w_SHY=0.9855.", "question": "Assets: QUAL, BNB-USD, DBA, SHY\nAnnualized mean returns: QUAL:-0.9987, BNB-USD:0.0295, DBA:-0.3068, SHY:0.0839\nCovariance matrix (annualized):\n[[0.052062, 0.028894, 0.016178, -0.001395], [0.028894, 0.175141, 0.031483, -0.002622], [0.016178, 0.031483, 0.029163, -0.000593], [-0.001395, -0.002622, -0.000593, 0.000255]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0000, w_BNB-USD=0.0145, w_DBA=0.0000, w_SHY=0.9855", "answer_numeric": 2.9734884638518, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_BNB-USD=0.0145, w_DBA=0.0000, w_SHY=0.9855\nPortfolio annualized return: 8.31%, volatility: 1.45%\nSharpe ratio: (0.0831 - 0.0400) / 0.0145 = 2.9735", "metadata": {"weights": {"QUAL": 0.0, "BNB-USD": 0.0145, "DBA": 0.0, "SHY": 0.9855}, "sharpe_ratio": 2.9735, "portfolio_return": 0.083076, "portfolio_vol": 0.014487, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250425_0020", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VTI", "SOL-USD", "INDS", "ICSH"], "decision_date": "2025-04-25", "context_summary": "4-asset optimization. Max-Sharpe: 0.713. Portfolio: return=4.42%, vol=0.58%. Weights: w_VTI=0.0000, w_SOL-USD=0.0001, w_INDS=0.0000, w_ICSH=0.9999.", "question": "Assets: VTI, SOL-USD, INDS, ICSH\nAnnualized mean returns: VTI:-0.6349, SOL-USD:0.1577, INDS:-0.3244, ICSH:0.0442\nCovariance matrix (annualized):\n[[0.066641, 0.12064, 0.044325, 0.000255], [0.12064, 0.953645, 0.050971, 0.000914], [0.044325, 0.050971, 0.072114, 0.000509], [0.000255, 0.000914, 0.000509, 3.4e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_SOL-USD=0.0001, w_INDS=0.0000, w_ICSH=0.9999", "answer_numeric": 0.7132656761946217, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_SOL-USD=0.0001, w_INDS=0.0000, w_ICSH=0.9999\nPortfolio annualized return: 4.42%, volatility: 0.58%\nSharpe ratio: (0.0442 - 0.0400) / 0.0058 = 0.7133", "metadata": {"weights": {"VTI": 0.0, "SOL-USD": 0.0001, "INDS": 0.0, "ICSH": 0.9999}, "sharpe_ratio": 0.7133, "portfolio_return": 0.044158, "portfolio_vol": 0.005829, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20250521_0023", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "AVAX-USD", "CSHI", "HAUZ"], "decision_date": "2025-05-21", "context_summary": "4-asset optimization. Max-Sharpe: 3.369. Portfolio: return=84.08%, vol=23.77%. Weights: w_XLY=0.0000, w_AVAX-USD=0.2140, w_CSHI=0.0000, w_HAUZ=0.7860.", "question": "Assets: XLY, AVAX-USD, CSHI, HAUZ\nAnnualized mean returns: XLY:0.2160, AVAX-USD:2.2293, CSHI:0.0567, HAUZ:0.4628\nCovariance matrix (annualized):\n[[0.095587, 0.102193, 0.008622, 0.021448], [0.102193, 0.632046, 0.015149, 0.024377], [0.008622, 0.015149, 0.002094, 0.004964], [0.021448, 0.024377, 0.004964, 0.031302]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_AVAX-USD=0.2140, w_CSHI=0.0000, w_HAUZ=0.7860", "answer_numeric": 3.3694111440005425, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_AVAX-USD=0.2140, w_CSHI=0.0000, w_HAUZ=0.7860\nPortfolio annualized return: 84.08%, volatility: 23.77%\nSharpe ratio: (0.8408 - 0.0400) / 0.2377 = 3.3694", "metadata": {"weights": {"XLY": 0.0, "AVAX-USD": 0.214, "CSHI": 0.0, "HAUZ": 0.786}, "sharpe_ratio": 3.3694, "portfolio_return": 0.840808, "portfolio_vol": 0.23767, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250131_0025", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BTC-USD", "BIL", "TLT"], "decision_date": "2025-01-31", "context_summary": "4-asset optimization. Max-Sharpe: 2.856. Portfolio: return=4.85%, vol=0.30%. Weights: w_EEM=0.0000, w_BTC-USD=0.0039, w_BIL=0.9961, w_TLT=0.0000.", "question": "Assets: EEM, BTC-USD, BIL, TLT\nAnnualized mean returns: EEM:0.0982, BTC-USD:0.8574, BIL:0.0453, TLT:-0.3360\nCovariance matrix (annualized):\n[[0.021059, 0.0196, -6e-06, 0.002904], [0.0196, 0.175614, 0.00016, 0.020782], [-6e-06, 0.00016, 5e-06, -1e-05], [0.002904, 0.020782, -1e-05, 0.013858]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0039, w_BIL=0.9961, w_TLT=0.0000", "answer_numeric": 2.8558840407461576, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_BTC-USD=0.0039, w_BIL=0.9961, w_TLT=0.0000\nPortfolio annualized return: 4.85%, volatility: 0.30%\nSharpe ratio: (0.0485 - 0.0400) / 0.0030 = 2.8559", "metadata": {"weights": {"EEM": 0.0, "BTC-USD": 0.0039, "BIL": 0.9961, "TLT": 0.0}, "sharpe_ratio": 2.8559, "portfolio_return": 0.048506, "portfolio_vol": 0.002978, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250228_0027", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "ADA-USD", "WEAT", "SCHH"], "decision_date": "2025-02-28", "context_summary": "4-asset optimization. Max-Sharpe: 2.832. Portfolio: return=39.86%, vol=12.66%. Weights: w_^VIX=0.0977, w_ADA-USD=0.0368, w_WEAT=0.2599, w_SCHH=0.6055.", "question": "Assets: ^VIX, ADA-USD, WEAT, SCHH\nAnnualized mean returns: ^VIX:1.7718, ADA-USD:-0.0455, WEAT:0.1724, SCHH:0.3011\nCovariance matrix (annualized):\n[[1.233037, -0.273164, -0.051388, -0.032387], [-0.273164, 0.609242, -0.030297, 0.0137], [-0.051388, -0.030297, 0.060578, -0.006086], [-0.032387, 0.0137, -0.006086, 0.026293]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0977, w_ADA-USD=0.0368, w_WEAT=0.2599, w_SCHH=0.6055", "answer_numeric": 2.831598953762345, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0977, w_ADA-USD=0.0368, w_WEAT=0.2599, w_SCHH=0.6055\nPortfolio annualized return: 39.86%, volatility: 12.66%\nSharpe ratio: (0.3986 - 0.0400) / 0.1266 = 2.8316", "metadata": {"weights": {"^VIX": 0.0977, "ADA-USD": 0.0368, "WEAT": 0.2599, "SCHH": 0.6055}, "sharpe_ratio": 2.8316, "portfolio_return": 0.398611, "portfolio_vol": 0.126646, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250327_0030", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BTC-USD", "REZ", "TIP"], "decision_date": "2025-03-27", "context_summary": "4-asset optimization. Max-Sharpe: 4.289. Portfolio: return=11.57%, vol=1.76%. Weights: w_QQQ=0.0000, w_BTC-USD=0.0000, w_REZ=0.0293, w_TIP=0.9707.", "question": "Assets: QQQ, BTC-USD, REZ, TIP\nAnnualized mean returns: QQQ:-0.5269, BTC-USD:-0.7827, REZ:0.3127, TIP:0.1097\nCovariance matrix (annualized):\n[[0.055376, 0.040133, 0.004306, -0.00083], [0.040133, 0.200807, -0.007299, -0.00227], [0.004306, -0.007299, 0.031706, 0.000198], [-0.00083, -0.00227, 0.000198, 0.00029]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.0000, w_BTC-USD=0.0000, w_REZ=0.0293, w_TIP=0.9707", "answer_numeric": 4.2886351155679545, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0000, w_BTC-USD=0.0000, w_REZ=0.0293, w_TIP=0.9707\nPortfolio annualized return: 11.57%, volatility: 1.76%\nSharpe ratio: (0.1157 - 0.0400) / 0.0176 = 4.2886", "metadata": {"weights": {"QQQ": 0.0, "BTC-USD": 0.0, "REZ": 0.0293, "TIP": 0.9707}, "sharpe_ratio": 4.2886, "portfolio_return": 0.115675, "portfolio_vol": 0.017645, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250225_0031", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "XRP-USD", "TLH", "HAUZ"], "decision_date": "2025-02-25", "context_summary": "4-asset optimization. Max-Sharpe: 3.173. Portfolio: return=50.42%, vol=14.63%. Weights: w_XLE=0.4400, w_XRP-USD=0.1082, w_TLH=0.4518, w_HAUZ=0.0000.", "question": "Assets: XLE, XRP-USD, TLH, HAUZ\nAnnualized mean returns: XLE:0.4823, XRP-USD:1.8937, TLH:0.1926, HAUZ:0.1219\nCovariance matrix (annualized):\n[[0.037964, 0.030567, 0.000842, 0.004445], [0.030567, 0.589699, 0.018107, 0.021043], [0.000842, 0.018107, 0.010411, 0.007005], [0.004445, 0.021043, 0.007005, 0.013359]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.4400, w_XRP-USD=0.1082, w_TLH=0.4518, w_HAUZ=0.0000", "answer_numeric": 3.173111341989282, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.4400, w_XRP-USD=0.1082, w_TLH=0.4518, w_HAUZ=0.0000\nPortfolio annualized return: 50.42%, volatility: 14.63%\nSharpe ratio: (0.5042 - 0.0400) / 0.1463 = 3.1731", "metadata": {"weights": {"XLE": 0.44, "XRP-USD": 0.1082, "TLH": 0.4518, "HAUZ": 0.0}, "sharpe_ratio": 3.1731, "portfolio_return": 0.504199, "portfolio_vol": 0.146291, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250725_0034", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLI", "AVAX-USD", "ICSH", "SLV"], "decision_date": "2025-07-25", "context_summary": "4-asset optimization. Max-Sharpe: 7.121. Portfolio: return=9.80%, vol=0.81%. Weights: w_XLI=0.0500, w_AVAX-USD=0.0000, w_ICSH=0.9274, w_SLV=0.0226.", "question": "Assets: XLI, AVAX-USD, ICSH, SLV\nAnnualized mean returns: XLI:0.5470, AVAX-USD:-0.5441, ICSH:0.0531, SLV:0.9486\nCovariance matrix (annualized):\n[[0.011185, 0.014038, 0.000138, -0.004757], [0.014038, 0.462482, 0.000449, 0.016533], [0.000138, 0.000449, 1e-05, -3.5e-05], [-0.004757, 0.016533, -3.5e-05, 0.058041]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0500, w_AVAX-USD=0.0000, w_ICSH=0.9274, w_SLV=0.0226", "answer_numeric": 7.120513691834653, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0500, w_AVAX-USD=0.0000, w_ICSH=0.9274, w_SLV=0.0226\nPortfolio annualized return: 9.80%, volatility: 0.81%\nSharpe ratio: (0.0980 - 0.0400) / 0.0081 = 7.1205", "metadata": {"weights": {"XLI": 0.05, "AVAX-USD": 0.0, "ICSH": 0.9274, "SLV": 0.0226}, "sharpe_ratio": 7.1205, "portfolio_return": 0.098006, "portfolio_vol": 0.008146, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9047}} +{"id": "T5_all_20250917_0037", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI", "BTC-USD", "VNQ", "PALL"], "decision_date": "2025-09-17", "context_summary": "4-asset optimization. Max-Sharpe: 3.112. Portfolio: return=33.82%, vol=9.58%. Weights: w_ACWI=1.0000, w_BTC-USD=0.0000, w_VNQ=0.0000, w_PALL=0.0000.", "question": "Assets: ACWI, BTC-USD, VNQ, PALL\nAnnualized mean returns: ACWI:0.3382, BTC-USD:-0.1265, VNQ:0.1613, PALL:-0.3407\nCovariance matrix (annualized):\n[[0.009181, 0.014145, 0.00595, -0.001496], [0.014145, 0.073814, 0.010085, 0.021845], [0.00595, 0.010085, 0.022038, 0.004585], [-0.001496, 0.021845, 0.004585, 0.087786]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=1.0000, w_BTC-USD=0.0000, w_VNQ=0.0000, w_PALL=0.0000", "answer_numeric": 3.112100182643105, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=1.0000, w_BTC-USD=0.0000, w_VNQ=0.0000, w_PALL=0.0000\nPortfolio annualized return: 33.82%, volatility: 9.58%\nSharpe ratio: (0.3382 - 0.0400) / 0.0958 = 3.1121", "metadata": {"weights": {"ACWI": 1.0, "BTC-USD": 0.0, "VNQ": 0.0, "PALL": 0.0}, "sharpe_ratio": 3.1121, "portfolio_return": 0.338197, "portfolio_vol": 0.095819, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250221_0039", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "SOL-USD", "PPLT", "IEF"], "decision_date": "2025-02-21", "context_summary": "4-asset optimization. Max-Sharpe: 2.727. Portfolio: return=48.76%, vol=16.42%. Weights: w_XLK=0.0000, w_SOL-USD=0.1939, w_PPLT=0.6759, w_IEF=0.1302.", "question": "Assets: XLK, SOL-USD, PPLT, IEF\nAnnualized mean returns: XLK:0.2069, SOL-USD:1.2084, PPLT:0.3632, IEF:0.0607\nCovariance matrix (annualized):\n[[0.047442, 0.026975, 0.008665, 0.00167], [0.026975, 0.374212, -0.004914, 0.008557], [0.008665, -0.004914, 0.030452, -0.001328], [0.00167, 0.008557, -0.001328, 0.003709]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_SOL-USD=0.1939, w_PPLT=0.6759, w_IEF=0.1302", "answer_numeric": 2.726766514897271, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0000, w_SOL-USD=0.1939, w_PPLT=0.6759, w_IEF=0.1302\nPortfolio annualized return: 48.76%, volatility: 16.42%\nSharpe ratio: (0.4876 - 0.0400) / 0.1642 = 2.7268", "metadata": {"weights": {"XLK": 0.0, "SOL-USD": 0.1939, "PPLT": 0.6759, "IEF": 0.1302}, "sharpe_ratio": 2.7268, "portfolio_return": 0.48763, "portfolio_vol": 0.164162, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20250317_0041", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY", "ETH-USD", "HAUZ", "UNG"], "decision_date": "2025-03-17", "context_summary": "4-asset optimization. Max-Sharpe: 2.619. Portfolio: return=37.60%, vol=12.83%. Weights: w_SPY=0.0000, w_ETH-USD=0.0000, w_HAUZ=0.8896, w_UNG=0.1104.", "question": "Assets: SPY, ETH-USD, HAUZ, UNG\nAnnualized mean returns: SPY:-0.3269, ETH-USD:-2.9067, HAUZ:0.2966, UNG:1.0156\nCovariance matrix (annualized):\n[[0.026696, 0.038493, 0.009212, -0.013491], [0.038493, 0.420296, 0.017986, -0.047047], [0.009212, 0.017986, 0.014109, 0.000191], [-0.013491, -0.047047, 0.000191, 0.431363]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.0000, w_ETH-USD=0.0000, w_HAUZ=0.8896, w_UNG=0.1104", "answer_numeric": 2.618701748059456, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.0000, w_ETH-USD=0.0000, w_HAUZ=0.8896, w_UNG=0.1104\nPortfolio annualized return: 37.60%, volatility: 12.83%\nSharpe ratio: (0.3760 - 0.0400) / 0.1283 = 2.6187", "metadata": {"weights": {"SPY": 0.0, "ETH-USD": 0.0, "HAUZ": 0.8896, "UNG": 0.1104}, "sharpe_ratio": 2.6187, "portfolio_return": 0.375995, "portfolio_vol": 0.128306, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250324_0043", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "XRP-USD", "EMB", "CSHI"], "decision_date": "2025-03-24", "context_summary": "4-asset optimization. Max-Sharpe: 1.333. Portfolio: return=10.94%, vol=5.21%. Weights: w_XLU=0.0000, w_XRP-USD=0.0000, w_EMB=1.0000, w_CSHI=0.0000.", "question": "Assets: XLU, XRP-USD, EMB, CSHI\nAnnualized mean returns: XLU:0.0337, XRP-USD:-1.1689, EMB:0.1094, CSHI:0.0408\nCovariance matrix (annualized):\n[[0.028096, -0.018999, 0.002915, 0.000505], [-0.018999, 0.743566, 0.003946, 0.000637], [0.002915, 0.003946, 0.002711, 5.1e-05], [0.000505, 0.000637, 5.1e-05, 0.000111]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_EMB=1.0000, w_CSHI=0.0000", "answer_numeric": 1.3333877410389687, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_XRP-USD=0.0000, w_EMB=1.0000, w_CSHI=0.0000\nPortfolio annualized return: 10.94%, volatility: 5.21%\nSharpe ratio: (0.1094 - 0.0400) / 0.0521 = 1.3334", "metadata": {"weights": {"XLU": 0.0, "XRP-USD": 0.0, "EMB": 1.0, "CSHI": 0.0}, "sharpe_ratio": 1.3334, "portfolio_return": 0.109425, "portfolio_vol": 0.052066, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250206_0046", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "AVAX-USD", "DBB", "IYR"], "decision_date": "2025-02-06", "context_summary": "4-asset optimization. Max-Sharpe: -1.462. Portfolio: return=-130.01%, vol=91.65%. Weights: w_XLP=0.0000, w_AVAX-USD=1.0000, w_DBB=0.0000, w_IYR=0.0000.", "question": "Assets: XLP, AVAX-USD, DBB, IYR\nAnnualized mean returns: XLP:-0.2492, AVAX-USD:-1.3001, DBB:-0.1124, IYR:-0.1220\nCovariance matrix (annualized):\n[[0.014331, 0.017408, 0.003529, 0.0152], [0.017408, 0.839975, 0.011004, 0.045695], [0.003529, 0.011004, 0.01308, 0.002605], [0.0152, 0.045695, 0.002605, 0.037684]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_AVAX-USD=1.0000, w_DBB=0.0000, w_IYR=0.0000", "answer_numeric": -1.4621518510684992, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_AVAX-USD=1.0000, w_DBB=0.0000, w_IYR=0.0000\nPortfolio annualized return: -130.01%, volatility: 91.65%\nSharpe ratio: (-1.3001 - 0.0400) / 0.9165 = -1.4622", "metadata": {"weights": {"XLP": 0.0, "AVAX-USD": 1.0, "DBB": 0.0, "IYR": 0.0}, "sharpe_ratio": -1.4622, "portfolio_return": -1.300065, "portfolio_vol": 0.916502, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9047}} +{"id": "T5_all_20251111_0049", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLB", "ETH-USD", "USO", "EMB"], "decision_date": "2025-11-11", "context_summary": "4-asset optimization. Max-Sharpe: 1.281. Portfolio: return=9.62%, vol=4.39%. Weights: w_XLB=0.0000, w_ETH-USD=0.0000, w_USO=0.0000, w_EMB=1.0000.", "question": "Assets: XLB, ETH-USD, USO, EMB\nAnnualized mean returns: XLB:-0.3721, ETH-USD:-2.5340, USO:-0.0784, EMB:0.0962\nCovariance matrix (annualized):\n[[0.019825, 0.040093, 0.002791, 0.002101], [0.040093, 0.363113, 0.037515, 0.006099], [0.002791, 0.037515, 0.063417, 0.001369], [0.002101, 0.006099, 0.001369, 0.001925]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_ETH-USD=0.0000, w_USO=0.0000, w_EMB=1.0000", "answer_numeric": 1.2812444344313616, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_ETH-USD=0.0000, w_USO=0.0000, w_EMB=1.0000\nPortfolio annualized return: 9.62%, volatility: 4.39%\nSharpe ratio: (0.0962 - 0.0400) / 0.0439 = 1.2812", "metadata": {"weights": {"XLB": 0.0, "ETH-USD": 0.0, "USO": 0.0, "EMB": 1.0}, "sharpe_ratio": 1.2812, "portfolio_return": 0.096207, "portfolio_vol": 0.043869, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250203_0051", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BNB-USD", "DBC", "HYG"], "decision_date": "2025-02-03", "context_summary": "4-asset optimization. Max-Sharpe: 2.273. Portfolio: return=30.86%, vol=11.82%. Weights: w_EEM=0.0000, w_BNB-USD=0.0543, w_DBC=0.9457, w_HYG=0.0000.", "question": "Assets: EEM, BNB-USD, DBC, HYG\nAnnualized mean returns: EEM:-0.0288, BNB-USD:0.2841, DBC:0.3101, HYG:0.0255\nCovariance matrix (annualized):\n[[0.022944, 0.005923, 0.002002, 0.00377], [0.005923, 0.171107, 0.003604, 0.006011], [0.002002, 0.003604, 0.014645, 0.000679], [0.00377, 0.006011, 0.000679, 0.002481]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0543, w_DBC=0.9457, w_HYG=0.0000", "answer_numeric": 2.2727160502034365, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_BNB-USD=0.0543, w_DBC=0.9457, w_HYG=0.0000\nPortfolio annualized return: 30.86%, volatility: 11.82%\nSharpe ratio: (0.3086 - 0.0400) / 0.1182 = 2.2727", "metadata": {"weights": {"EEM": 0.0, "BNB-USD": 0.0543, "DBC": 0.9457, "HYG": 0.0}, "sharpe_ratio": 2.2727, "portfolio_return": 0.308647, "portfolio_vol": 0.118205, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20251008_0053", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "LINK-USD", "IAU", "TLH"], "decision_date": "2025-10-08", "context_summary": "4-asset optimization. Max-Sharpe: 8.105. Portfolio: return=70.38%, vol=8.19%. Weights: w_QUAL=0.4331, w_LINK-USD=0.0000, w_IAU=0.5669, w_TLH=0.0000.", "question": "Assets: QUAL, LINK-USD, IAU, TLH\nAnnualized mean returns: QUAL:0.3426, LINK-USD:0.0175, IAU:0.9798, TLH:0.1579\nCovariance matrix (annualized):\n[[0.006643, 0.02811, 0.000318, 0.001389], [0.02811, 0.677939, 0.027178, 0.006196], [0.000318, 0.027178, 0.016509, 0.0015], [0.001389, 0.006196, 0.0015, 0.005883]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.4331, w_LINK-USD=0.0000, w_IAU=0.5669, w_TLH=0.0000", "answer_numeric": 8.10467052783718, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.4331, w_LINK-USD=0.0000, w_IAU=0.5669, w_TLH=0.0000\nPortfolio annualized return: 70.38%, volatility: 8.19%\nSharpe ratio: (0.7038 - 0.0400) / 0.0819 = 8.1047", "metadata": {"weights": {"QUAL": 0.4331, "LINK-USD": 0.0, "IAU": 0.5669, "TLH": 0.0}, "sharpe_ratio": 8.1047, "portfolio_return": 0.703798, "portfolio_vol": 0.081903, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250108_0055", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BNB-USD", "UNG", "ICSH"], "decision_date": "2025-01-08", "context_summary": "4-asset optimization. Max-Sharpe: 2.779. Portfolio: return=6.16%, vol=0.78%. Weights: w_VEA=0.0000, w_BNB-USD=0.0047, w_UNG=0.0070, w_ICSH=0.9883.", "question": "Assets: VEA, BNB-USD, UNG, ICSH\nAnnualized mean returns: VEA:-0.1583, BNB-USD:0.6323, UNG:1.3467, ICSH:0.0498\nCovariance matrix (annualized):\n[[0.011778, 0.029108, -0.004568, 0.000236], [0.029108, 0.354755, -0.041302, 0.000287], [-0.004568, -0.041302, 0.564367, -0.000114], [0.000236, 0.000287, -0.000114, 2.7e-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_BNB-USD=0.0047, w_UNG=0.0070, w_ICSH=0.9883", "answer_numeric": 2.7785945019499247, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_BNB-USD=0.0047, w_UNG=0.0070, w_ICSH=0.9883\nPortfolio annualized return: 6.16%, volatility: 0.78%\nSharpe ratio: (0.0616 - 0.0400) / 0.0078 = 2.7786", "metadata": {"weights": {"VEA": 0.0, "BNB-USD": 0.0047, "UNG": 0.007, "ICSH": 0.9883}, "sharpe_ratio": 2.7786, "portfolio_return": 0.061639, "portfolio_vol": 0.007788, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250212_0058", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "AVAX-USD", "CSHI", "TIP"], "decision_date": "2025-02-12", "context_summary": "4-asset optimization. Max-Sharpe: 2.320. Portfolio: return=5.54%, vol=0.66%. Weights: w_EEM=0.0000, w_AVAX-USD=0.0000, w_CSHI=0.7602, w_TIP=0.2398.", "question": "Assets: EEM, AVAX-USD, CSHI, TIP\nAnnualized mean returns: EEM:0.0383, AVAX-USD:-1.5666, CSHI:0.0512, TIP:0.0686\nCovariance matrix (annualized):\n[[0.02149, 0.048485, 0.000463, 0.000686], [0.048485, 0.59301, 0.002392, 0.004366], [0.000463, 0.002392, 3.4e-05, 2.6e-05], [0.000686, 0.004366, 2.6e-05, 0.00026]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_AVAX-USD=0.0000, w_CSHI=0.7602, w_TIP=0.2398", "answer_numeric": 2.31994780822039, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_AVAX-USD=0.0000, w_CSHI=0.7602, w_TIP=0.2398\nPortfolio annualized return: 5.54%, volatility: 0.66%\nSharpe ratio: (0.0554 - 0.0400) / 0.0066 = 2.3199", "metadata": {"weights": {"EEM": 0.0, "AVAX-USD": 0.0, "CSHI": 0.7602, "TIP": 0.2398}, "sharpe_ratio": 2.3199, "portfolio_return": 0.055409, "portfolio_vol": 0.006642, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20251105_0059", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "LINK-USD", "EMB", "DBC"], "decision_date": "2025-11-05", "context_summary": "4-asset optimization. Max-Sharpe: 2.759. Portfolio: return=19.40%, vol=5.58%. Weights: w_XLV=0.2681, w_LINK-USD=0.0000, w_EMB=0.5114, w_DBC=0.2205.", "question": "Assets: XLV, LINK-USD, EMB, DBC\nAnnualized mean returns: XLV:0.2967, LINK-USD:-2.8145, EMB:0.1211, DBC:0.2384\nCovariance matrix (annualized):\n[[0.01784, 0.034779, 0.001396, -0.001363], [0.034779, 0.680033, 0.013233, 0.039005], [0.001396, 0.013233, 0.002044, 0.001006], [-0.001363, 0.039005, 0.001006, 0.017541]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2681, w_LINK-USD=0.0000, w_EMB=0.5114, w_DBC=0.2205", "answer_numeric": 2.758660611225617, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.2681, w_LINK-USD=0.0000, w_EMB=0.5114, w_DBC=0.2205\nPortfolio annualized return: 19.40%, volatility: 5.58%\nSharpe ratio: (0.1940 - 0.0400) / 0.0558 = 2.7587", "metadata": {"weights": {"XLV": 0.2681, "LINK-USD": 0.0, "EMB": 0.5114, "DBC": 0.2205}, "sharpe_ratio": 2.7587, "portfolio_return": 0.194042, "portfolio_vol": 0.055839, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251106_0061", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "AVAX-USD", "BIL", "IGOV"], "decision_date": "2025-11-06", "context_summary": "4-asset optimization. Max-Sharpe: 0.749. Portfolio: return=93.85%, vol=119.89%. Weights: w_^VIX=1.0000, w_AVAX-USD=0.0000, w_BIL=0.0000, w_IGOV=0.0000.", "question": "Assets: ^VIX, AVAX-USD, BIL, IGOV\nAnnualized mean returns: ^VIX:0.9385, AVAX-USD:-2.4897, BIL:0.0367, IGOV:-0.0980\nCovariance matrix (annualized):\n[[1.437473, -0.415861, -5.8e-05, 0.025022], [-0.415861, 0.800384, -8.7e-05, -0.003596], [-5.8e-05, -8.7e-05, 3e-06, 1e-06], [0.025022, -0.003596, 1e-06, 0.003693]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_AVAX-USD=0.0000, w_BIL=0.0000, w_IGOV=0.0000", "answer_numeric": 0.749436402364531, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=1.0000, w_AVAX-USD=0.0000, w_BIL=0.0000, w_IGOV=0.0000\nPortfolio annualized return: 93.85%, volatility: 119.89%\nSharpe ratio: (0.9385 - 0.0400) / 1.1989 = 0.7494", "metadata": {"weights": {"^VIX": 1.0, "AVAX-USD": 0.0, "BIL": 0.0, "IGOV": 0.0}, "sharpe_ratio": 0.7494, "portfolio_return": 0.938534, "portfolio_vol": 1.198947, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250318_0063", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DOT-USD", "HAUZ", "CORN"], "decision_date": "2025-03-18", "context_summary": "4-asset optimization. Max-Sharpe: 2.600. Portfolio: return=32.00%, vol=10.77%. Weights: w_XLP=0.2496, w_DOT-USD=0.0000, w_HAUZ=0.7504, w_CORN=0.0000.", "question": "Assets: XLP, DOT-USD, HAUZ, CORN\nAnnualized mean returns: XLP:0.2743, DOT-USD:-0.3393, HAUZ:0.3351, CORN:-0.0904\nCovariance matrix (annualized):\n[[0.024089, 0.003015, 0.004924, 0.001217], [0.003015, 0.530774, 0.012052, 0.028948], [0.004924, 0.012052, 0.014656, 0.00328], [0.001217, 0.028948, 0.00328, 0.030779]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2496, w_DOT-USD=0.0000, w_HAUZ=0.7504, w_CORN=0.0000", "answer_numeric": 2.599616407019362, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.2496, w_DOT-USD=0.0000, w_HAUZ=0.7504, w_CORN=0.0000\nPortfolio annualized return: 32.00%, volatility: 10.77%\nSharpe ratio: (0.3200 - 0.0400) / 0.1077 = 2.5996", "metadata": {"weights": {"XLP": 0.2496, "DOT-USD": 0.0, "HAUZ": 0.7504, "CORN": 0.0}, "sharpe_ratio": 2.5996, "portfolio_return": 0.319968, "portfolio_vol": 0.107696, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251121_0065", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "ADA-USD", "SLV", "HYG"], "decision_date": "2025-11-21", "context_summary": "4-asset optimization. Max-Sharpe: 3.412. Portfolio: return=119.83%, vol=33.95%. Weights: w_MTUM=0.0000, w_ADA-USD=0.0000, w_SLV=1.0000, w_HYG=0.0000.", "question": "Assets: MTUM, ADA-USD, SLV, HYG\nAnnualized mean returns: MTUM:-0.4352, ADA-USD:-4.2966, SLV:1.1983, HYG:-0.0256\nCovariance matrix (annualized):\n[[0.022129, 0.06464, 0.012714, 0.003753], [0.06464, 0.547082, 0.051142, 0.014546], [0.012714, 0.051142, 0.115267, 0.001262], [0.003753, 0.014546, 0.001262, 0.001327]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0000, w_ADA-USD=0.0000, w_SLV=1.0000, w_HYG=0.0000", "answer_numeric": 3.4116437914600652, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0000, w_ADA-USD=0.0000, w_SLV=1.0000, w_HYG=0.0000\nPortfolio annualized return: 119.83%, volatility: 33.95%\nSharpe ratio: (1.1983 - 0.0400) / 0.3395 = 3.4116", "metadata": {"weights": {"MTUM": 0.0, "ADA-USD": 0.0, "SLV": 1.0, "HYG": 0.0}, "sharpe_ratio": 3.4116, "portfolio_return": 1.198285, "portfolio_vol": 0.339509, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250326_0067", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ETH-USD", "VNQI", "DBC"], "decision_date": "2025-03-26", "context_summary": "4-asset optimization. Max-Sharpe: 1.242. Portfolio: return=17.52%, vol=10.88%. Weights: w_QUAL=0.0000, w_ETH-USD=0.0000, w_VNQI=1.0000, w_DBC=0.0000.", "question": "Assets: QUAL, ETH-USD, VNQI, DBC\nAnnualized mean returns: QUAL:-0.3033, ETH-USD:-2.4971, VNQI:0.1752, DBC:-0.0051\nCovariance matrix (annualized):\n[[0.024598, 0.038766, 0.01071, 0.006894], [0.038766, 0.426526, 0.019056, 0.019085], [0.01071, 0.019056, 0.011833, 0.002572], [0.006894, 0.019085, 0.002572, 0.012124]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0000, w_VNQI=1.0000, w_DBC=0.0000", "answer_numeric": 1.242437492996186, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_ETH-USD=0.0000, w_VNQI=1.0000, w_DBC=0.0000\nPortfolio annualized return: 17.52%, volatility: 10.88%\nSharpe ratio: (0.1752 - 0.0400) / 0.1088 = 1.2424", "metadata": {"weights": {"QUAL": 0.0, "ETH-USD": 0.0, "VNQI": 1.0, "DBC": 0.0}, "sharpe_ratio": 1.2424, "portfolio_return": 0.175151, "portfolio_vol": 0.108779, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250529_0069", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "DOT-USD", "WEAT", "CSHI"], "decision_date": "2025-05-29", "context_summary": "4-asset optimization. Max-Sharpe: 1.863. Portfolio: return=122.54%, vol=63.63%. Weights: w_FXI=0.0000, w_DOT-USD=1.0000, w_WEAT=0.0000, w_CSHI=0.0000.", "question": "Assets: FXI, DOT-USD, WEAT, CSHI\nAnnualized mean returns: FXI:0.2166, DOT-USD:1.2254, WEAT:-0.1303, CSHI:0.0632\nCovariance matrix (annualized):\n[[0.090353, 0.063296, 0.015265, 0.008662], [0.063296, 0.404858, -0.003872, 0.010802], [0.015265, -0.003872, 0.036535, 0.002441], [0.008662, 0.010802, 0.002441, 0.002101]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_DOT-USD=1.0000, w_WEAT=0.0000, w_CSHI=0.0000", "answer_numeric": 1.8630515433403454, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_DOT-USD=1.0000, w_WEAT=0.0000, w_CSHI=0.0000\nPortfolio annualized return: 122.54%, volatility: 63.63%\nSharpe ratio: (1.2254 - 0.0400) / 0.6363 = 1.8631", "metadata": {"weights": {"FXI": 0.0, "DOT-USD": 1.0, "WEAT": 0.0, "CSHI": 0.0}, "sharpe_ratio": 1.8631, "portfolio_return": 1.225431, "portfolio_vol": 0.636284, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20251205_0071", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "SOL-USD", "TIP", "ICSH"], "decision_date": "2025-12-05", "context_summary": "4-asset optimization. Max-Sharpe: 0.539. Portfolio: return=4.23%, vol=0.42%. Weights: w_QUAL=0.0254, w_SOL-USD=0.0000, w_TIP=0.0000, w_ICSH=0.9746.", "question": "Assets: QUAL, SOL-USD, TIP, ICSH\nAnnualized mean returns: QUAL:0.0832, SOL-USD:-3.1309, TIP:0.0195, ICSH:0.0412\nCovariance matrix (annualized):\n[[0.015993, 0.053957, -0.000217, -7.1e-05], [0.053957, 0.616487, -0.001537, -0.000204], [-0.000217, -0.001537, 0.00017, 1.4e-05], [-7.1e-05, -0.000204, 1.4e-05, 1.1e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0254, w_SOL-USD=0.0000, w_TIP=0.0000, w_ICSH=0.9746", "answer_numeric": 0.5387967555403124, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0254, w_SOL-USD=0.0000, w_TIP=0.0000, w_ICSH=0.9746\nPortfolio annualized return: 4.23%, volatility: 0.42%\nSharpe ratio: (0.0423 - 0.0400) / 0.0042 = 0.5388", "metadata": {"weights": {"QUAL": 0.0254, "SOL-USD": 0.0, "TIP": 0.0, "ICSH": 0.9746}, "sharpe_ratio": 0.5388, "portfolio_return": 0.042258, "portfolio_vol": 0.004191, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251031_0074", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "ADA-USD", "ICSH", "DBC"], "decision_date": "2025-10-31", "context_summary": "4-asset optimization. Max-Sharpe: -1.906. Portfolio: return=-36.25%, vol=21.12%. Weights: w_IWM=0.2500, w_ADA-USD=0.2500, w_ICSH=0.2500, w_DBC=0.2500.", "question": "Assets: IWM, ADA-USD, ICSH, DBC\nAnnualized mean returns: IWM:0.2530, ADA-USD:-1.8883, ICSH:0.0431, DBC:0.1424\nCovariance matrix (annualized):\n[[0.033532, 0.065425, -2.6e-05, 0.003105], [0.065425, 0.450166, -0.000178, 0.037097], [-2.6e-05, -0.000178, 1.4e-05, -0.000149], [0.003105, 0.037097, -0.000149, 0.019097]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.2500, w_ADA-USD=0.2500, w_ICSH=0.2500, w_DBC=0.2500", "answer_numeric": -1.9060815791236372, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.2500, w_ADA-USD=0.2500, w_ICSH=0.2500, w_DBC=0.2500\nPortfolio annualized return: -36.25%, volatility: 21.12%\nSharpe ratio: (-0.3625 - 0.0400) / 0.2112 = -1.9061", "metadata": {"weights": {"IWM": 0.25, "ADA-USD": 0.25, "ICSH": 0.25, "DBC": 0.25}, "sharpe_ratio": -1.9061, "portfolio_return": -0.362472, "portfolio_vol": 0.211151, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9047}} +{"id": "T5_all_20250422_0076", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["QQQ", "BTC-USD", "IAU", "ICSH"], "decision_date": "2025-04-22", "context_summary": "4-asset optimization. Max-Sharpe: 4.271. Portfolio: return=10.70%, vol=1.57%. Weights: w_QQQ=0.0000, w_BTC-USD=0.0000, w_IAU=0.0860, w_ICSH=0.9140.", "question": "Assets: QQQ, BTC-USD, IAU, ICSH\nAnnualized mean returns: QQQ:-1.5392, BTC-USD:-0.3275, IAU:0.7774, ICSH:0.0439\nCovariance matrix (annualized):\n[[0.093322, 0.078618, 0.003627, 2.4e-05], [0.078618, 0.27454, 0.00916, 0.000281], [0.003627, 0.00916, 0.033731, -0.000213], [2.4e-05, 0.000281, -0.000213, 3.6e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.0000, w_BTC-USD=0.0000, w_IAU=0.0860, w_ICSH=0.9140", "answer_numeric": 4.27148857061246, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0000, w_BTC-USD=0.0000, w_IAU=0.0860, w_ICSH=0.9140\nPortfolio annualized return: 10.70%, volatility: 1.57%\nSharpe ratio: (0.1070 - 0.0400) / 0.0157 = 4.2715", "metadata": {"weights": {"QQQ": 0.0, "BTC-USD": 0.0, "IAU": 0.086, "ICSH": 0.914}, "sharpe_ratio": 4.2715, "portfolio_return": 0.106953, "portfolio_vol": 0.015674, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250603_0079", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ADA-USD", "SGOV", "IYR"], "decision_date": "2025-06-03", "context_summary": "4-asset optimization. Max-Sharpe: 2.385. Portfolio: return=4.96%, vol=0.40%. Weights: w_IVV=0.0058, w_ADA-USD=0.0034, w_SGOV=0.9908, w_IYR=0.0000.", "question": "Assets: IVV, ADA-USD, SGOV, IYR\nAnnualized mean returns: IVV:0.3700, ADA-USD:1.3101, SGOV:0.0434, IYR:0.0126\nCovariance matrix (annualized):\n[[0.051072, 0.057652, 6.6e-05, 0.038248], [0.057652, 0.479354, 0.000197, 0.025294], [6.6e-05, 0.000197, 5e-06, 9.6e-05], [0.038248, 0.025294, 9.6e-05, 0.050976]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0058, w_ADA-USD=0.0034, w_SGOV=0.9908, w_IYR=0.0000", "answer_numeric": 2.3851674261769698, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0058, w_ADA-USD=0.0034, w_SGOV=0.9908, w_IYR=0.0000\nPortfolio annualized return: 4.96%, volatility: 0.40%\nSharpe ratio: (0.0496 - 0.0400) / 0.0040 = 2.3852", "metadata": {"weights": {"IVV": 0.0058, "ADA-USD": 0.0034, "SGOV": 0.9908, "IYR": 0.0}, "sharpe_ratio": 2.3852, "portfolio_return": 0.049601, "portfolio_vol": 0.004025, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250430_0081", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["IWM", "SOL-USD", "BNDX", "CSHI"], "decision_date": "2025-04-30", "context_summary": "4-asset optimization. Max-Sharpe: 0.744. Portfolio: return=69.85%, vol=88.48%. Weights: w_IWM=0.0000, w_SOL-USD=1.0000, w_BNDX=0.0000, w_CSHI=0.0000.", "question": "Assets: IWM, SOL-USD, BNDX, CSHI\nAnnualized mean returns: IWM:-0.5602, SOL-USD:0.6985, BNDX:0.0294, CSHI:0.0346\nCovariance matrix (annualized):\n[[0.081038, 0.143785, -0.001655, 0.009019], [0.143785, 0.782943, -0.002121, 0.011838], [-0.001655, -0.002121, 0.001644, -0.000473], [0.009019, 0.011838, -0.000473, 0.002106]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0000, w_SOL-USD=1.0000, w_BNDX=0.0000, w_CSHI=0.0000", "answer_numeric": 0.7441875706851494, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_SOL-USD=1.0000, w_BNDX=0.0000, w_CSHI=0.0000\nPortfolio annualized return: 69.85%, volatility: 88.48%\nSharpe ratio: (0.6985 - 0.0400) / 0.8848 = 0.7442", "metadata": {"weights": {"IWM": 0.0, "SOL-USD": 1.0, "BNDX": 0.0, "CSHI": 0.0}, "sharpe_ratio": 0.7442, "portfolio_return": 0.698487, "portfolio_vol": 0.88484, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250303_0085", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "MATIC-USD", "ITB", "ICSH"], "decision_date": "2025-03-03", "context_summary": "4-asset optimization. Max-Sharpe: -1.280. Portfolio: return=-23.34%, vol=21.35%. Weights: w_EEM=0.2500, w_MATIC-USD=0.2500, w_ITB=0.2500, w_ICSH=0.2500.", "question": "Assets: EEM, MATIC-USD, ITB, ICSH\nAnnualized mean returns: EEM:0.2113, MATIC-USD:-0.9450, ITB:-0.2570, ICSH:0.0573\nCovariance matrix (annualized):\n[[0.023475, 0.033078, 0.01179, 5.3e-05], [0.033078, 0.482683, 0.031737, 0.000121], [0.01179, 0.031737, 0.069131, 0.000176], [5.3e-05, 0.000121, 0.000176, 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_EEM=0.2500, w_MATIC-USD=0.2500, w_ITB=0.2500, w_ICSH=0.2500", "answer_numeric": -1.280494504803509, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.2500, w_MATIC-USD=0.2500, w_ITB=0.2500, w_ICSH=0.2500\nPortfolio annualized return: -23.34%, volatility: 21.35%\nSharpe ratio: (-0.2334 - 0.0400) / 0.2135 = -1.2805", "metadata": {"weights": {"EEM": 0.25, "MATIC-USD": 0.25, "ITB": 0.25, "ICSH": 0.25}, "sharpe_ratio": -1.2805, "portfolio_return": -0.233366, "portfolio_vol": 0.213485, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251017_0087", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI", "SOL-USD", "INDS", "BIL"], "decision_date": "2025-10-17", "context_summary": "4-asset optimization. Max-Sharpe: 2.896. Portfolio: return=52.02%, vol=16.58%. Weights: w_ACWI=0.0000, w_SOL-USD=0.0000, w_INDS=1.0000, w_BIL=0.0000.", "question": "Assets: ACWI, SOL-USD, INDS, BIL\nAnnualized mean returns: ACWI:0.2030, SOL-USD:-0.0744, INDS:0.5202, BIL:0.0392\nCovariance matrix (annualized):\n[[0.011718, 0.055546, 0.009505, -2.6e-05], [0.055546, 0.691818, 0.031699, 0.000214], [0.009505, 0.031699, 0.027497, 1.8e-05], [-2.6e-05, 0.000214, 1.8e-05, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.0000, w_SOL-USD=0.0000, w_INDS=1.0000, w_BIL=0.0000", "answer_numeric": 2.8957824513285053, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0000, w_SOL-USD=0.0000, w_INDS=1.0000, w_BIL=0.0000\nPortfolio annualized return: 52.02%, volatility: 16.58%\nSharpe ratio: (0.5202 - 0.0400) / 0.1658 = 2.8958", "metadata": {"weights": {"ACWI": 0.0, "SOL-USD": 0.0, "INDS": 1.0, "BIL": 0.0}, "sharpe_ratio": 2.8958, "portfolio_return": 0.520186, "portfolio_vol": 0.165823, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251009_0089", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QQQ", "ETH-USD", "ICSH", "XHB"], "decision_date": "2025-10-09", "context_summary": "4-asset optimization. Max-Sharpe: 4.219. Portfolio: return=6.36%, vol=0.56%. Weights: w_QQQ=0.0413, w_ETH-USD=0.0000, w_ICSH=0.9587, w_XHB=0.0000.", "question": "Assets: QQQ, ETH-USD, ICSH, XHB\nAnnualized mean returns: QQQ:0.3803, ETH-USD:0.6951, ICSH:0.0500, XHB:-0.0190\nCovariance matrix (annualized):\n[[0.010448, 0.036125, 2.1e-05, 0.01028], [0.036125, 0.478384, 0.000464, 0.081014], [2.1e-05, 0.000464, 1.3e-05, 0.000323], [0.01028, 0.081014, 0.000323, 0.072189]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.0413, w_ETH-USD=0.0000, w_ICSH=0.9587, w_XHB=0.0000", "answer_numeric": 4.219185029831726, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0413, w_ETH-USD=0.0000, w_ICSH=0.9587, w_XHB=0.0000\nPortfolio annualized return: 6.36%, volatility: 0.56%\nSharpe ratio: (0.0636 - 0.0400) / 0.0056 = 4.2192", "metadata": {"weights": {"QQQ": 0.0413, "ETH-USD": 0.0, "ICSH": 0.9587, "XHB": 0.0}, "sharpe_ratio": 4.2192, "portfolio_return": 0.063648, "portfolio_vol": 0.005605, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250602_0091", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "BNB-USD", "ICSH", "IYR"], "decision_date": "2025-06-02", "context_summary": "4-asset optimization. Max-Sharpe: 3.763. Portfolio: return=12.66%, vol=2.30%. Weights: w_XLY=0.0000, w_BNB-USD=0.0699, w_ICSH=0.9301, w_IYR=0.0000.", "question": "Assets: XLY, BNB-USD, ICSH, IYR\nAnnualized mean returns: XLY:-0.0264, BNB-USD:1.2233, ICSH:0.0442, IYR:-0.1865\nCovariance matrix (annualized):\n[[0.089447, 0.023042, 0.000365, 0.053099], [0.023042, 0.10399, -3e-05, 0.01076], [0.000365, -3e-05, 3e-05, 0.000563], [0.053099, 0.01076, 0.000563, 0.057073]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BNB-USD=0.0699, w_ICSH=0.9301, w_IYR=0.0000", "answer_numeric": 3.762698085173215, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_BNB-USD=0.0699, w_ICSH=0.9301, w_IYR=0.0000\nPortfolio annualized return: 12.66%, volatility: 2.30%\nSharpe ratio: (0.1266 - 0.0400) / 0.0230 = 3.7627", "metadata": {"weights": {"XLY": 0.0, "BNB-USD": 0.0699, "ICSH": 0.9301, "IYR": 0.0}, "sharpe_ratio": 3.7627, "portfolio_return": 0.126594, "portfolio_vol": 0.023014, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250523_0093", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BTC-USD", "DBA", "ICSH"], "decision_date": "2025-05-23", "context_summary": "4-asset optimization. Max-Sharpe: 5.349. Portfolio: return=26.20%, vol=4.15%. Weights: w_QUAL=0.0000, w_BTC-USD=0.1063, w_DBA=0.0000, w_ICSH=0.8937.", "question": "Assets: QUAL, BTC-USD, DBA, ICSH\nAnnualized mean returns: QUAL:-0.0132, BTC-USD:2.1079, DBA:0.1845, ICSH:0.0424\nCovariance matrix (annualized):\n[[0.0543, 0.031848, 0.017118, 0.000183], [0.031848, 0.15151, 0.025192, -6.9e-05], [0.017118, 0.025192, 0.025369, 6.8e-05], [0.000183, -6.9e-05, 6.8e-05, 2.9e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0000, w_BTC-USD=0.1063, w_DBA=0.0000, w_ICSH=0.8937", "answer_numeric": 5.349003110771317, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_BTC-USD=0.1063, w_DBA=0.0000, w_ICSH=0.8937\nPortfolio annualized return: 26.20%, volatility: 4.15%\nSharpe ratio: (0.2620 - 0.0400) / 0.0415 = 5.3490", "metadata": {"weights": {"QUAL": 0.0, "BTC-USD": 0.1063, "DBA": 0.0, "ICSH": 0.8937}, "sharpe_ratio": 5.349, "portfolio_return": 0.261985, "portfolio_vol": 0.0415, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251216_0095", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "BTC-USD", "INDS", "BIL"], "decision_date": "2025-12-16", "context_summary": "4-asset optimization. Max-Sharpe: -1.576. Portfolio: return=-16.91%, vol=13.27%. Weights: w_XLU=0.0000, w_BTC-USD=0.0000, w_INDS=1.0000, w_BIL=0.0000.", "question": "Assets: XLU, BTC-USD, INDS, BIL\nAnnualized mean returns: XLU:-0.3758, BTC-USD:-1.8014, INDS:-0.1691, BIL:0.0392\nCovariance matrix (annualized):\n[[0.016103, 0.015459, 0.007656, 1.3e-05], [0.015459, 0.15357, 0.017239, 5.1e-05], [0.007656, 0.017239, 0.017602, 8e-06], [1.3e-05, 5.1e-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_XLU=0.0000, w_BTC-USD=0.0000, w_INDS=1.0000, w_BIL=0.0000", "answer_numeric": -1.576109019309817, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_BTC-USD=0.0000, w_INDS=1.0000, w_BIL=0.0000\nPortfolio annualized return: -16.91%, volatility: 13.27%\nSharpe ratio: (-0.1691 - 0.0400) / 0.1327 = -1.5761", "metadata": {"weights": {"XLU": 0.0, "BTC-USD": 0.0, "INDS": 1.0, "BIL": 0.0}, "sharpe_ratio": -1.5761, "portfolio_return": -0.169107, "portfolio_vol": 0.132673, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250109_0097", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "SOL-USD", "SGOV", "SOYB"], "decision_date": "2025-01-09", "context_summary": "4-asset optimization. Max-Sharpe: 2.311. Portfolio: return=4.52%, vol=0.22%. Weights: w_XLE=0.0000, w_SOL-USD=0.0000, w_SGOV=1.0000, w_SOYB=0.0000.", "question": "Assets: XLE, SOL-USD, SGOV, SOYB\nAnnualized mean returns: XLE:-0.3440, SOL-USD:-0.0550, SGOV:0.0452, SOYB:-0.2774\nCovariance matrix (annualized):\n[[0.027554, 0.053614, -6e-06, 0.006835], [0.053614, 0.475731, -5.5e-05, 0.002003], [-6e-06, -5.5e-05, 5e-06, 1.1e-05], [0.006835, 0.002003, 1.1e-05, 0.022421]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_SOL-USD=0.0000, w_SGOV=1.0000, w_SOYB=0.0000", "answer_numeric": 2.310595590838717, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_SOL-USD=0.0000, w_SGOV=1.0000, w_SOYB=0.0000\nPortfolio annualized return: 4.52%, volatility: 0.22%\nSharpe ratio: (0.0452 - 0.0400) / 0.0022 = 2.3106", "metadata": {"weights": {"XLE": 0.0, "SOL-USD": 0.0, "SGOV": 1.0, "SOYB": 0.0}, "sharpe_ratio": 2.3106, "portfolio_return": 0.045181, "portfolio_vol": 0.002242, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250924_0101", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLB", "DOT-USD", "PALL", "SGOV"], "decision_date": "2025-09-24", "context_summary": "4-asset optimization. Max-Sharpe: -0.899. Portfolio: return=-14.59%, vol=20.67%. Weights: w_XLB=0.2500, w_DOT-USD=0.2500, w_PALL=0.2500, w_SGOV=0.2500.", "question": "Assets: XLB, DOT-USD, PALL, SGOV\nAnnualized mean returns: XLB:-0.1252, DOT-USD:-0.5504, PALL:0.0492, SGOV:0.0429\nCovariance matrix (annualized):\n[[0.022167, 0.045308, 0.003185, 2.9e-05], [0.045308, 0.445293, 0.012879, -9e-05], [0.003185, 0.012879, 0.093743, -7.1e-05], [2.9e-05, -9e-05, -7.1e-05, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.2500, w_DOT-USD=0.2500, w_PALL=0.2500, w_SGOV=0.2500", "answer_numeric": -0.8991124492626059, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.2500, w_DOT-USD=0.2500, w_PALL=0.2500, w_SGOV=0.2500\nPortfolio annualized return: -14.59%, volatility: 20.67%\nSharpe ratio: (-0.1459 - 0.0400) / 0.2067 = -0.8991", "metadata": {"weights": {"XLB": 0.25, "DOT-USD": 0.25, "PALL": 0.25, "SGOV": 0.25}, "sharpe_ratio": -0.8991, "portfolio_return": -0.145859, "portfolio_vol": 0.206714, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250319_0104", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["^VIX", "ETH-USD", "ITB", "LQD"], "decision_date": "2025-03-19", "context_summary": "4-asset optimization. Max-Sharpe: 2.233. Portfolio: return=21.46%, vol=7.82%. Weights: w_^VIX=0.0389, w_ETH-USD=0.0000, w_ITB=0.0000, w_LQD=0.9611.", "question": "Assets: ^VIX, ETH-USD, ITB, LQD\nAnnualized mean returns: ^VIX:1.9316, ETH-USD:-2.8125, ITB:-0.8075, LQD:0.1452\nCovariance matrix (annualized):\n[[1.569982, -0.314957, -0.074797, 0.005399], [-0.314957, 0.398186, 0.027801, -0.008481], [-0.074797, 0.027801, 0.063607, 0.006252], [0.005399, -0.008481, 0.006252, 0.00361]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0389, w_ETH-USD=0.0000, w_ITB=0.0000, w_LQD=0.9611", "answer_numeric": 2.233427866698444, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0389, w_ETH-USD=0.0000, w_ITB=0.0000, w_LQD=0.9611\nPortfolio annualized return: 21.46%, volatility: 7.82%\nSharpe ratio: (0.2146 - 0.0400) / 0.0782 = 2.2334", "metadata": {"weights": {"^VIX": 0.0389, "ETH-USD": 0.0, "ITB": 0.0, "LQD": 0.9611}, "sharpe_ratio": 2.2334, "portfolio_return": 0.214573, "portfolio_vol": 0.078164, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250804_0105", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI", "BTC-USD", "STIP", "BIL"], "decision_date": "2025-08-04", "context_summary": "4-asset optimization. Max-Sharpe: 4.032. Portfolio: return=5.44%, vol=0.36%. Weights: w_ACWI=0.0313, w_BTC-USD=0.0004, w_STIP=0.1605, w_BIL=0.8078.", "question": "Assets: ACWI, BTC-USD, STIP, BIL\nAnnualized mean returns: ACWI:0.2051, BTC-USD:0.4450, STIP:0.0782, BIL:0.0437\nCovariance matrix (annualized):\n[[0.009017, 0.011688, -0.000652, -4.4e-05], [0.011688, 0.084429, -0.000408, 3.5e-05], [-0.000652, -0.000408, 0.000313, 5e-06], [-4.4e-05, 3.5e-05, 5e-06, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.0313, w_BTC-USD=0.0004, w_STIP=0.1605, w_BIL=0.8078", "answer_numeric": 4.032072676919991, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0313, w_BTC-USD=0.0004, w_STIP=0.1605, w_BIL=0.8078\nPortfolio annualized return: 5.44%, volatility: 0.36%\nSharpe ratio: (0.0544 - 0.0400) / 0.0036 = 4.0321", "metadata": {"weights": {"ACWI": 0.0313, "BTC-USD": 0.0004, "STIP": 0.1605, "BIL": 0.8078}, "sharpe_ratio": 4.0321, "portfolio_return": 0.054421, "portfolio_vol": 0.003577, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250826_0108", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLE", "BTC-USD", "TLH", "ICSH"], "decision_date": "2025-08-26", "context_summary": "4-asset optimization. Max-Sharpe: 3.252. Portfolio: return=5.34%, vol=0.41%. Weights: w_XLE=0.0132, w_BTC-USD=0.0000, w_TLH=0.0000, w_ICSH=0.9868.", "question": "Assets: XLE, BTC-USD, TLH, ICSH\nAnnualized mean returns: XLE:0.1850, BTC-USD:0.0224, TLH:0.0140, ICSH:0.0516\nCovariance matrix (annualized):\n[[0.025114, 0.015596, -0.000915, -0.000149], [0.015596, 0.081576, 0.003476, -9e-05], [-0.000915, 0.003476, 0.007801, 0.000147], [-0.000149, -9e-05, 0.000147, 1.7e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0132, w_BTC-USD=0.0000, w_TLH=0.0000, w_ICSH=0.9868", "answer_numeric": 3.2524204068366327, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0132, w_BTC-USD=0.0000, w_TLH=0.0000, w_ICSH=0.9868\nPortfolio annualized return: 5.34%, volatility: 0.41%\nSharpe ratio: (0.0534 - 0.0400) / 0.0041 = 3.2524", "metadata": {"weights": {"XLE": 0.0132, "BTC-USD": 0.0, "TLH": 0.0, "ICSH": 0.9868}, "sharpe_ratio": 3.2524, "portfolio_return": 0.05339, "portfolio_vol": 0.004117, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251030_0111", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EFA", "AVAX-USD", "IEF", "VNQI"], "decision_date": "2025-10-30", "context_summary": "4-asset optimization. Max-Sharpe: 2.101. Portfolio: return=15.67%, vol=5.55%. Weights: w_EFA=0.4682, w_AVAX-USD=0.0000, w_IEF=0.5318, w_VNQI=0.0000.", "question": "Assets: EFA, AVAX-USD, IEF, VNQI\nAnnualized mean returns: EFA:0.2341, AVAX-USD:-1.0669, IEF:0.0886, VNQI:0.0721\nCovariance matrix (annualized):\n[[0.010264, 0.036257, 0.000614, 0.007919], [0.036257, 0.734868, -0.009664, 0.017999], [0.000614, -0.009664, 0.001875, 0.001568], [0.007919, 0.017999, 0.001568, 0.010072]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.4682, w_AVAX-USD=0.0000, w_IEF=0.5318, w_VNQI=0.0000", "answer_numeric": 2.10114820715846, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.4682, w_AVAX-USD=0.0000, w_IEF=0.5318, w_VNQI=0.0000\nPortfolio annualized return: 15.67%, volatility: 5.55%\nSharpe ratio: (0.1567 - 0.0400) / 0.0555 = 2.1011", "metadata": {"weights": {"EFA": 0.4682, "AVAX-USD": 0.0, "IEF": 0.5318, "VNQI": 0.0}, "sharpe_ratio": 2.1011, "portfolio_return": 0.156716, "portfolio_vol": 0.055549, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20250709_0114", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "AVAX-USD", "VNQ", "BIL"], "decision_date": "2025-07-09", "context_summary": "4-asset optimization. Max-Sharpe: -1.986. Portfolio: return=-34.67%, vol=19.47%. Weights: w_IVV=0.2500, w_AVAX-USD=0.2500, w_VNQ=0.2500, w_BIL=0.2500.", "question": "Assets: IVV, AVAX-USD, VNQ, BIL\nAnnualized mean returns: IVV:0.5911, AVAX-USD:-2.0911, VNQ:0.0707, BIL:0.0425\nCovariance matrix (annualized):\n[[0.015876, 0.025684, 0.010577, -5.4e-05], [0.025684, 0.497235, -1.3e-05, 1.7e-05], [0.010577, -1.3e-05, 0.021232, 8e-06], [-5.4e-05, 1.7e-05, 8e-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_IVV=0.2500, w_AVAX-USD=0.2500, w_VNQ=0.2500, w_BIL=0.2500", "answer_numeric": -1.985774014210514, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.2500, w_AVAX-USD=0.2500, w_VNQ=0.2500, w_BIL=0.2500\nPortfolio annualized return: -34.67%, volatility: 19.47%\nSharpe ratio: (-0.3467 - 0.0400) / 0.1947 = -1.9858", "metadata": {"weights": {"IVV": 0.25, "AVAX-USD": 0.25, "VNQ": 0.25, "BIL": 0.25}, "sharpe_ratio": -1.9858, "portfolio_return": -0.346712, "portfolio_vol": 0.194741, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250120_0117", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ADA-USD", "SLV", "SCHP"], "decision_date": "2025-01-20", "context_summary": "4-asset optimization. Max-Sharpe: 2.478. Portfolio: return=263.68%, vol=104.79%. Weights: w_EFA=0.0000, w_ADA-USD=1.0000, w_SLV=0.0000, w_SCHP=0.0000.", "question": "Assets: EFA, ADA-USD, SLV, SCHP\nAnnualized mean returns: EFA:0.0501, ADA-USD:2.6368, SLV:-0.0893, SCHP:-0.0148\nCovariance matrix (annualized):\n[[0.01297, 0.035445, 0.011697, 0.00285], [0.035445, 1.098176, 0.059438, 0.008317], [0.011697, 0.059438, 0.055848, 0.002607], [0.00285, 0.008317, 0.002607, 0.001775]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_SLV=0.0000, w_SCHP=0.0000", "answer_numeric": 2.478024885832735, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_ADA-USD=1.0000, w_SLV=0.0000, w_SCHP=0.0000\nPortfolio annualized return: 263.68%, volatility: 104.79%\nSharpe ratio: (2.6368 - 0.0400) / 1.0479 = 2.4780", "metadata": {"weights": {"EFA": 0.0, "ADA-USD": 1.0, "SLV": 0.0, "SCHP": 0.0}, "sharpe_ratio": 2.478, "portfolio_return": 2.636818, "portfolio_vol": 1.047939, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251229_0119", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ETH-USD", "DBC", "ICSH"], "decision_date": "2025-12-29", "context_summary": "4-asset optimization. Max-Sharpe: 2.000. Portfolio: return=8.30%, vol=2.15%. Weights: w_XLP=0.1311, w_ETH-USD=0.0000, w_DBC=0.1277, w_ICSH=0.7412.", "question": "Assets: XLP, ETH-USD, DBC, ICSH\nAnnualized mean returns: XLP:0.1846, ETH-USD:-1.9166, DBC:0.2125, ICSH:0.0427\nCovariance matrix (annualized):\n[[0.01112, -0.008077, 0.000352, 7e-05], [-0.008077, 0.396146, 0.010188, 9e-06], [0.000352, 0.010188, 0.013729, 7.5e-05], [7e-05, 9e-06, 7.5e-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_XLP=0.1311, w_ETH-USD=0.0000, w_DBC=0.1277, w_ICSH=0.7412", "answer_numeric": 1.9998408270899937, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.1311, w_ETH-USD=0.0000, w_DBC=0.1277, w_ICSH=0.7412\nPortfolio annualized return: 8.30%, volatility: 2.15%\nSharpe ratio: (0.0830 - 0.0400) / 0.0215 = 1.9998", "metadata": {"weights": {"XLP": 0.1311, "ETH-USD": 0.0, "DBC": 0.1277, "ICSH": 0.7412}, "sharpe_ratio": 1.9998, "portfolio_return": 0.083001, "portfolio_vol": 0.021502, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250812_0122", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLE", "AVAX-USD", "PPLT", "ITB"], "decision_date": "2025-08-12", "context_summary": "4-asset optimization. Max-Sharpe: 1.853. Portfolio: return=52.02%, vol=25.92%. Weights: w_XLE=0.0000, w_AVAX-USD=0.0000, w_PPLT=0.2661, w_ITB=0.7339.", "question": "Assets: XLE, AVAX-USD, PPLT, ITB\nAnnualized mean returns: XLE:-0.1216, AVAX-USD:0.0571, PPLT:0.4250, ITB:0.5547\nCovariance matrix (annualized):\n[[0.031441, -0.019572, -0.003288, -0.000248], [-0.019572, 0.444837, 0.065673, 0.050733], [-0.003288, 0.065673, 0.152126, 0.018233], [-0.000248, 0.050733, 0.018233, 0.0915]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0000, w_AVAX-USD=0.0000, w_PPLT=0.2661, w_ITB=0.7339", "answer_numeric": 1.8528043658862334, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_AVAX-USD=0.0000, w_PPLT=0.2661, w_ITB=0.7339\nPortfolio annualized return: 52.02%, volatility: 25.92%\nSharpe ratio: (0.5202 - 0.0400) / 0.2592 = 1.8528", "metadata": {"weights": {"XLE": 0.0, "AVAX-USD": 0.0, "PPLT": 0.2661, "ITB": 0.7339}, "sharpe_ratio": 1.8528, "portfolio_return": 0.520222, "portfolio_vol": 0.259187, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250915_0125", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EFA", "SOL-USD", "SLV", "BIL"], "decision_date": "2025-09-15", "context_summary": "4-asset optimization. Max-Sharpe: 3.586. Portfolio: return=6.35%, vol=0.66%. Weights: w_EFA=0.0176, w_SOL-USD=0.0009, w_SLV=0.0221, w_BIL=0.9594.", "question": "Assets: EFA, SOL-USD, SLV, BIL\nAnnualized mean returns: EFA:0.3125, SOL-USD:1.7782, SLV:0.6861, BIL:0.0430\nCovariance matrix (annualized):\n[[0.016387, 0.035489, 0.007566, 1.1e-05], [0.035489, 0.589303, 0.086866, 0.000116], [0.007566, 0.086866, 0.041905, 4.7e-05], [1.1e-05, 0.000116, 4.7e-05, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0176, w_SOL-USD=0.0009, w_SLV=0.0221, w_BIL=0.9594", "answer_numeric": 3.5858087989699583, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0176, w_SOL-USD=0.0009, w_SLV=0.0221, w_BIL=0.9594\nPortfolio annualized return: 6.35%, volatility: 0.66%\nSharpe ratio: (0.0635 - 0.0400) / 0.0066 = 3.5858", "metadata": {"weights": {"EFA": 0.0176, "SOL-USD": 0.0009, "SLV": 0.0221, "BIL": 0.9594}, "sharpe_ratio": 3.5858, "portfolio_return": 0.063503, "portfolio_vol": 0.006555, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250819_0127", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE", "ADA-USD", "SGOV", "BNDX"], "decision_date": "2025-08-19", "context_summary": "4-asset optimization. Max-Sharpe: 4.079. Portfolio: return=5.42%, vol=0.35%. Weights: w_XLRE=0.0000, w_ADA-USD=0.0044, w_SGOV=0.9956, w_BNDX=0.0000.", "question": "Assets: XLRE, ADA-USD, SGOV, BNDX\nAnnualized mean returns: XLRE:-0.0783, ADA-USD:2.2361, SGOV:0.0446, BNDX:-0.0045\nCovariance matrix (annualized):\n[[0.021036, 0.035163, -1.9e-05, 0.00073], [0.035163, 0.485235, -0.000256, 0.00043], [-1.9e-05, -0.000256, 5e-06, 1e-06], [0.00073, 0.00043, 1e-06, 0.0008]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_ADA-USD=0.0044, w_SGOV=0.9956, w_BNDX=0.0000", "answer_numeric": 4.078505942056545, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_ADA-USD=0.0044, w_SGOV=0.9956, w_BNDX=0.0000\nPortfolio annualized return: 5.42%, volatility: 0.35%\nSharpe ratio: (0.0542 - 0.0400) / 0.0035 = 4.0785", "metadata": {"weights": {"XLRE": 0.0, "ADA-USD": 0.0044, "SGOV": 0.9956, "BNDX": 0.0}, "sharpe_ratio": 4.0785, "portfolio_return": 0.054187, "portfolio_vol": 0.003478, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250130_0130", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "XRP-USD", "SHY", "SCHH"], "decision_date": "2025-01-30", "context_summary": "4-asset optimization. Max-Sharpe: 2.068. Portfolio: return=198.49%, vol=94.04%. Weights: w_SPY=0.0000, w_XRP-USD=1.0000, w_SHY=0.0000, w_SCHH=0.0000.", "question": "Assets: SPY, XRP-USD, SHY, SCHH\nAnnualized mean returns: SPY:0.0322, XRP-USD:1.9849, SHY:0.0359, SCHH:-0.4837\nCovariance matrix (annualized):\n[[0.019606, 0.055359, 0.000672, 0.01111], [0.055359, 0.884336, 0.003571, 0.01938], [0.000672, 0.003571, 0.00015, 0.001044], [0.01111, 0.01938, 0.001044, 0.035356]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.0000, w_XRP-USD=1.0000, w_SHY=0.0000, w_SCHH=0.0000", "answer_numeric": 2.068142604936434, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.0000, w_XRP-USD=1.0000, w_SHY=0.0000, w_SCHH=0.0000\nPortfolio annualized return: 198.49%, volatility: 94.04%\nSharpe ratio: (1.9849 - 0.0400) / 0.9404 = 2.0681", "metadata": {"weights": {"SPY": 0.0, "XRP-USD": 1.0, "SHY": 0.0, "SCHH": 0.0}, "sharpe_ratio": 2.0681, "portfolio_return": 1.984864, "portfolio_vol": 0.940391, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250630_0132", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "SOL-USD", "SLV", "INDS"], "decision_date": "2025-06-30", "context_summary": "4-asset optimization. Max-Sharpe: 2.557. Portfolio: return=42.53%, vol=15.07%. Weights: w_^VIX=0.0000, w_SOL-USD=0.0000, w_SLV=0.5487, w_INDS=0.4513.", "question": "Assets: ^VIX, SOL-USD, SLV, INDS\nAnnualized mean returns: ^VIX:-2.6108, SOL-USD:-0.2223, SLV:0.6209, INDS:0.1874\nCovariance matrix (annualized):\n[[1.230334, -0.151141, 0.092145, -0.080598], [-0.151141, 0.395197, 0.005955, 0.010118], [0.092145, 0.005955, 0.064517, -0.002599], [-0.080598, 0.010118, -0.002599, 0.022412]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0000, w_SLV=0.5487, w_INDS=0.4513", "answer_numeric": 2.557165490898144, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0000, w_SOL-USD=0.0000, w_SLV=0.5487, w_INDS=0.4513\nPortfolio annualized return: 42.53%, volatility: 15.07%\nSharpe ratio: (0.4253 - 0.0400) / 0.1507 = 2.5572", "metadata": {"weights": {"^VIX": 0.0, "SOL-USD": 0.0, "SLV": 0.5487, "INDS": 0.4513}, "sharpe_ratio": 2.5572, "portfolio_return": 0.425306, "portfolio_vol": 0.150677, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250307_0134", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "DOT-USD", "VNQI", "JNK"], "decision_date": "2025-03-07", "context_summary": "4-asset optimization. Max-Sharpe: 0.782. Portfolio: return=8.11%, vol=5.26%. Weights: w_XLU=0.0000, w_DOT-USD=0.0000, w_VNQI=0.2051, w_JNK=0.7949.", "question": "Assets: XLU, DOT-USD, VNQI, JNK\nAnnualized mean returns: XLU:-0.0964, DOT-USD:-0.7411, VNQI:0.1253, JNK:0.0697\nCovariance matrix (annualized):\n[[0.034007, 0.035134, 0.009754, 0.003362], [0.035134, 0.605586, 0.019617, 0.005737], [0.009754, 0.019617, 0.014442, 0.003488], [0.003362, 0.005737, 0.003488, 0.001613]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_DOT-USD=0.0000, w_VNQI=0.2051, w_JNK=0.7949", "answer_numeric": 0.7822653858588215, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_DOT-USD=0.0000, w_VNQI=0.2051, w_JNK=0.7949\nPortfolio annualized return: 8.11%, volatility: 5.26%\nSharpe ratio: (0.0811 - 0.0400) / 0.0526 = 0.7823", "metadata": {"weights": {"XLU": 0.0, "DOT-USD": 0.0, "VNQI": 0.2051, "JNK": 0.7949}, "sharpe_ratio": 0.7823, "portfolio_return": 0.08113, "portfolio_vol": 0.052578, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250512_0136", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ETH-USD", "INDS", "IEF"], "decision_date": "2025-05-12", "context_summary": "4-asset optimization. Max-Sharpe: 3.142. Portfolio: return=79.40%, vol=24.00%. Weights: w_XLU=0.3013, w_ETH-USD=0.2932, w_INDS=0.0000, w_IEF=0.4055.", "question": "Assets: XLU, ETH-USD, INDS, IEF\nAnnualized mean returns: XLU:0.3556, ETH-USD:2.2775, INDS:-0.1040, IEF:0.0469\nCovariance matrix (annualized):\n[[0.035114, 0.044132, 0.036921, 0.001436], [0.044132, 0.547117, 0.086896, -0.007031], [0.036921, 0.086896, 0.07138, 0.000192], [0.001436, -0.007031, 0.000192, 0.005313]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.3013, w_ETH-USD=0.2932, w_INDS=0.0000, w_IEF=0.4055", "answer_numeric": 3.1421163358359117, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.3013, w_ETH-USD=0.2932, w_INDS=0.0000, w_IEF=0.4055\nPortfolio annualized return: 79.40%, volatility: 24.00%\nSharpe ratio: (0.7940 - 0.0400) / 0.2400 = 3.1421", "metadata": {"weights": {"XLU": 0.3013, "ETH-USD": 0.2932, "INDS": 0.0, "IEF": 0.4055}, "sharpe_ratio": 3.1421, "portfolio_return": 0.793969, "portfolio_vol": 0.239956, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250129_0140", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "SOL-USD", "ICSH", "GLD"], "decision_date": "2025-01-29", "context_summary": "4-asset optimization. Max-Sharpe: 2.927. Portfolio: return=5.81%, vol=0.62%. Weights: w_FXI=0.0037, w_SOL-USD=0.0000, w_ICSH=0.9731, w_GLD=0.0233.", "question": "Assets: FXI, SOL-USD, ICSH, GLD\nAnnualized mean returns: FXI:0.2610, SOL-USD:0.3112, ICSH:0.0524, GLD:0.2629\nCovariance matrix (annualized):\n[[0.068437, 0.012563, 0.000234, -0.000566], [0.012563, 0.446386, 0.000293, 0.017755], [0.000234, 0.000293, 2.5e-05, 5.5e-05], [-0.000566, 0.017755, 5.5e-05, 0.017999]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0037, w_SOL-USD=0.0000, w_ICSH=0.9731, w_GLD=0.0233", "answer_numeric": 2.9269283649228095, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0037, w_SOL-USD=0.0000, w_ICSH=0.9731, w_GLD=0.0233\nPortfolio annualized return: 5.81%, volatility: 0.62%\nSharpe ratio: (0.0581 - 0.0400) / 0.0062 = 2.9269", "metadata": {"weights": {"FXI": 0.0037, "SOL-USD": 0.0, "ICSH": 0.9731, "GLD": 0.0233}, "sharpe_ratio": 2.9269, "portfolio_return": 0.058075, "portfolio_vol": 0.006176, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20250402_0143", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLK", "AVAX-USD", "IYR", "SOYB"], "decision_date": "2025-04-02", "context_summary": "4-asset optimization. Max-Sharpe: 0.380. Portfolio: return=9.84%, vol=15.35%. Weights: w_XLK=0.0000, w_AVAX-USD=0.0000, w_IYR=1.0000, w_SOYB=0.0000.", "question": "Assets: XLK, AVAX-USD, IYR, SOYB\nAnnualized mean returns: XLK:-0.6246, AVAX-USD:-1.1396, IYR:0.0984, SOYB:-0.1054\nCovariance matrix (annualized):\n[[0.071407, 0.099138, 0.01896, 0.003333], [0.099138, 0.781754, 0.003679, 0.020847], [0.01896, 0.003679, 0.023563, -0.000729], [0.003333, 0.020847, -0.000729, 0.019253]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.0000, w_AVAX-USD=0.0000, w_IYR=1.0000, w_SOYB=0.0000", "answer_numeric": 0.38027044181976954, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0000, w_AVAX-USD=0.0000, w_IYR=1.0000, w_SOYB=0.0000\nPortfolio annualized return: 9.84%, volatility: 15.35%\nSharpe ratio: (0.0984 - 0.0400) / 0.1535 = 0.3803", "metadata": {"weights": {"XLK": 0.0, "AVAX-USD": 0.0, "IYR": 1.0, "SOYB": 0.0}, "sharpe_ratio": 0.3803, "portfolio_return": 0.098372, "portfolio_vol": 0.153501, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251118_0146", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "XRP-USD", "PPLT", "STIP"], "decision_date": "2025-11-18", "context_summary": "4-asset optimization. Max-Sharpe: 2.265. Portfolio: return=81.59%, vol=34.25%. Weights: w_EWJ=0.0000, w_XRP-USD=0.0000, w_PPLT=1.0000, w_STIP=0.0000.", "question": "Assets: EWJ, XRP-USD, PPLT, STIP\nAnnualized mean returns: EWJ:0.1161, XRP-USD:-2.9680, PPLT:0.8159, STIP:-0.0013\nCovariance matrix (annualized):\n[[0.026982, 0.050529, 0.014083, -0.000294], [0.050529, 0.462057, 0.045948, -0.001527], [0.014083, 0.045948, 0.117327, -0.000234], [-0.000294, -0.001527, -0.000234, 0.000184]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_XRP-USD=0.0000, w_PPLT=1.0000, w_STIP=0.0000", "answer_numeric": 2.265147254408175, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_XRP-USD=0.0000, w_PPLT=1.0000, w_STIP=0.0000\nPortfolio annualized return: 81.59%, volatility: 34.25%\nSharpe ratio: (0.8159 - 0.0400) / 0.3425 = 2.2651", "metadata": {"weights": {"EWJ": 0.0, "XRP-USD": 0.0, "PPLT": 1.0, "STIP": 0.0}, "sharpe_ratio": 2.2651, "portfolio_return": 0.815881, "portfolio_vol": 0.34253, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250609_0148", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "DOT-USD", "CPER", "BIL"], "decision_date": "2025-06-09", "context_summary": "4-asset optimization. Max-Sharpe: 2.804. Portfolio: return=6.37%, vol=0.84%. Weights: w_USMV=0.0329, w_DOT-USD=0.0006, w_CPER=0.0226, w_BIL=0.9439.", "question": "Assets: USMV, DOT-USD, CPER, BIL\nAnnualized mean returns: USMV:0.2670, DOT-USD:0.2754, CPER:0.6450, BIL:0.0425\nCovariance matrix (annualized):\n[[0.019256, 0.004487, 0.002042, -0.0], [0.004487, 0.395948, 0.008943, 0.000127], [0.002042, 0.008943, 0.072906, 0.000108], [-0.0, 0.000127, 0.000108, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0329, w_DOT-USD=0.0006, w_CPER=0.0226, w_BIL=0.9439", "answer_numeric": 2.804131167282982, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0329, w_DOT-USD=0.0006, w_CPER=0.0226, w_BIL=0.9439\nPortfolio annualized return: 6.37%, volatility: 0.84%\nSharpe ratio: (0.0637 - 0.0400) / 0.0084 = 2.8041", "metadata": {"weights": {"USMV": 0.0329, "DOT-USD": 0.0006, "CPER": 0.0226, "BIL": 0.9439}, "sharpe_ratio": 2.8041, "portfolio_return": 0.063661, "portfolio_vol": 0.008438, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250909_0150", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "ETH-USD", "CSHI", "DBB"], "decision_date": "2025-09-09", "context_summary": "4-asset optimization. Max-Sharpe: 2.645. Portfolio: return=66.98%, vol=23.81%. Weights: w_FXI=0.7113, w_ETH-USD=0.1934, w_CSHI=0.0000, w_DBB=0.0953.", "question": "Assets: FXI, ETH-USD, CSHI, DBB\nAnnualized mean returns: FXI:0.4728, ETH-USD:1.6363, CSHI:0.0462, DBB:0.1787\nCovariance matrix (annualized):\n[[0.035925, 0.065372, 0.00037, 0.007867], [0.065372, 0.487996, 0.001775, 0.028951], [0.00037, 0.001775, 7.2e-05, 0.00013], [0.007867, 0.028951, 0.00013, 0.013529]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.7113, w_ETH-USD=0.1934, w_CSHI=0.0000, w_DBB=0.0953", "answer_numeric": 2.645474667935624, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.7113, w_ETH-USD=0.1934, w_CSHI=0.0000, w_DBB=0.0953\nPortfolio annualized return: 66.98%, volatility: 23.81%\nSharpe ratio: (0.6698 - 0.0400) / 0.2381 = 2.6455", "metadata": {"weights": {"FXI": 0.7113, "ETH-USD": 0.1934, "CSHI": 0.0, "DBB": 0.0953}, "sharpe_ratio": 2.6455, "portfolio_return": 0.669823, "portfolio_vol": 0.238075, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251231_0153", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BNB-USD", "STIP", "CPER"], "decision_date": "2025-12-31", "context_summary": "4-asset optimization. Max-Sharpe: 2.756. Portfolio: return=46.55%, vol=15.44%. Weights: w_USMV=0.4284, w_BNB-USD=0.0000, w_STIP=0.0000, w_CPER=0.5716.", "question": "Assets: USMV, BNB-USD, STIP, CPER\nAnnualized mean returns: USMV:0.1446, BNB-USD:-1.6240, STIP:0.0199, CPER:0.7060\nCovariance matrix (annualized):\n[[0.00619, 0.0058, 0.000321, 0.005609], [0.0058, 0.227906, -0.000139, 0.029362], [0.000321, -0.000139, 0.000125, 0.000154], [0.005609, 0.029362, 0.000154, 0.061044]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.4284, w_BNB-USD=0.0000, w_STIP=0.0000, w_CPER=0.5716", "answer_numeric": 2.756387942186338, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.4284, w_BNB-USD=0.0000, w_STIP=0.0000, w_CPER=0.5716\nPortfolio annualized return: 46.55%, volatility: 15.44%\nSharpe ratio: (0.4655 - 0.0400) / 0.1544 = 2.7564", "metadata": {"weights": {"USMV": 0.4284, "BNB-USD": 0.0, "STIP": 0.0, "CPER": 0.5716}, "sharpe_ratio": 2.7564, "portfolio_return": 0.465504, "portfolio_vol": 0.15437, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251024_0156", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLK", "LINK-USD", "EMB", "SCHH"], "decision_date": "2025-10-24", "context_summary": "4-asset optimization. Max-Sharpe: 3.309. Portfolio: return=28.57%, vol=7.42%. Weights: w_XLK=0.3007, w_LINK-USD=0.0000, w_EMB=0.6993, w_SCHH=0.0000.", "question": "Assets: XLK, LINK-USD, EMB, SCHH\nAnnualized mean returns: XLK:0.5748, LINK-USD:-2.0582, EMB:0.1614, SCHH:0.0864\nCovariance matrix (annualized):\n[[0.030835, 0.085606, 0.003898, 0.003741], [0.085606, 0.668559, 0.013123, 0.007592], [0.003898, 0.013123, 0.002218, 0.002464], [0.003741, 0.007592, 0.002464, 0.012426]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.3007, w_LINK-USD=0.0000, w_EMB=0.6993, w_SCHH=0.0000", "answer_numeric": 3.3091631193374855, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.3007, w_LINK-USD=0.0000, w_EMB=0.6993, w_SCHH=0.0000\nPortfolio annualized return: 28.57%, volatility: 7.42%\nSharpe ratio: (0.2857 - 0.0400) / 0.0742 = 3.3092", "metadata": {"weights": {"XLK": 0.3007, "LINK-USD": 0.0, "EMB": 0.6993, "SCHH": 0.0}, "sharpe_ratio": 3.3092, "portfolio_return": 0.285672, "portfolio_vol": 0.07424, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20251113_0158", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "DOT-USD", "VCIT", "CPER"], "decision_date": "2025-11-13", "context_summary": "4-asset optimization. Max-Sharpe: 4.481. Portfolio: return=58.22%, vol=12.10%. Weights: w_XLV=0.7995, w_DOT-USD=0.0000, w_VCIT=0.0000, w_CPER=0.2005.", "question": "Assets: XLV, DOT-USD, VCIT, CPER\nAnnualized mean returns: XLV:0.5847, DOT-USD:-2.1615, VCIT:0.0180, CPER:0.5722\nCovariance matrix (annualized):\n[[0.017914, 0.022386, 0.001219, 0.001908], [0.022386, 0.929583, -0.002485, 0.082598], [0.001219, -0.002485, 0.000986, -6.9e-05], [0.001908, 0.082598, -6.9e-05, 0.06404]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.7995, w_DOT-USD=0.0000, w_VCIT=0.0000, w_CPER=0.2005", "answer_numeric": 4.4813799132075545, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.7995, w_DOT-USD=0.0000, w_VCIT=0.0000, w_CPER=0.2005\nPortfolio annualized return: 58.22%, volatility: 12.10%\nSharpe ratio: (0.5822 - 0.0400) / 0.1210 = 4.4814", "metadata": {"weights": {"XLV": 0.7995, "DOT-USD": 0.0, "VCIT": 0.0, "CPER": 0.2005}, "sharpe_ratio": 4.4814, "portfolio_return": 0.582168, "portfolio_vol": 0.120982, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250528_0161", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "BTC-USD", "SGOV", "USO"], "decision_date": "2025-05-28", "context_summary": "4-asset optimization. Max-Sharpe: 5.122. Portfolio: return=185.22%, vol=35.38%. Weights: w_EWJ=0.1573, w_BTC-USD=0.8427, w_SGOV=0.0000, w_USO=0.0000.", "question": "Assets: EWJ, BTC-USD, SGOV, USO\nAnnualized mean returns: EWJ:0.4476, BTC-USD:2.1144, SGOV:0.0414, USO:-0.6282\nCovariance matrix (annualized):\n[[0.049611, 0.024157, 4.2e-05, 0.046063], [0.024157, 0.165541, 0.0002, 0.066641], [4.2e-05, 0.0002, 5e-06, 0.00013], [0.046063, 0.066641, 0.00013, 0.169675]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.1573, w_BTC-USD=0.8427, w_SGOV=0.0000, w_USO=0.0000", "answer_numeric": 5.121711501072288, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.1573, w_BTC-USD=0.8427, w_SGOV=0.0000, w_USO=0.0000\nPortfolio annualized return: 185.22%, volatility: 35.38%\nSharpe ratio: (1.8522 - 0.0400) / 0.3538 = 5.1217", "metadata": {"weights": {"EWJ": 0.1573, "BTC-USD": 0.8427, "SGOV": 0.0, "USO": 0.0}, "sharpe_ratio": 5.1217, "portfolio_return": 1.852249, "portfolio_vol": 0.353837, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250101_0164", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ETH-USD", "CSHI", "CPER"], "decision_date": "2025-01-01", "context_summary": "4-asset optimization. Max-Sharpe: 3.468. Portfolio: return=6.43%, vol=0.70%. Weights: w_IWM=0.0000, w_ETH-USD=0.0051, w_CSHI=0.9949, w_CPER=0.0000.", "question": "Assets: IWM, ETH-USD, CSHI, CPER\nAnnualized mean returns: IWM:-0.0076, ETH-USD:1.8806, CSHI:0.0551, CPER:-0.4967\nCovariance matrix (annualized):\n[[0.040293, 0.077799, 0.000496, -0.002188], [0.077799, 0.497882, 0.001207, -0.018009], [0.000496, 0.001207, 2.4e-05, 6.8e-05], [-0.002188, -0.018009, 6.8e-05, 0.04341]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ETH-USD=0.0051, w_CSHI=0.9949, w_CPER=0.0000", "answer_numeric": 3.4682594193054497, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_ETH-USD=0.0051, w_CSHI=0.9949, w_CPER=0.0000\nPortfolio annualized return: 6.43%, volatility: 0.70%\nSharpe ratio: (0.0643 - 0.0400) / 0.0070 = 3.4683", "metadata": {"weights": {"IWM": 0.0, "ETH-USD": 0.0051, "CSHI": 0.9949, "CPER": 0.0}, "sharpe_ratio": 3.4683, "portfolio_return": 0.06431, "portfolio_vol": 0.007009, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251124_0167", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ETH-USD", "VNQI", "SHY"], "decision_date": "2025-11-24", "context_summary": "4-asset optimization. Max-Sharpe: 0.543. Portfolio: return=4.63%, vol=1.17%. Weights: w_EEM=0.0000, w_ETH-USD=0.0000, w_VNQI=0.0000, w_SHY=1.0000.", "question": "Assets: EEM, ETH-USD, VNQI, SHY\nAnnualized mean returns: EEM:0.0186, ETH-USD:-3.7577, VNQI:-0.0450, SHY:0.0463\nCovariance matrix (annualized):\n[[0.030056, 0.061775, 0.008003, -0.000209], [0.061775, 0.365543, 0.025521, -0.000329], [0.008003, 0.025521, 0.009632, 0.00028], [-0.000209, -0.000329, 0.00028, 0.000136]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_ETH-USD=0.0000, w_VNQI=0.0000, w_SHY=1.0000", "answer_numeric": 0.5428092730861593, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_ETH-USD=0.0000, w_VNQI=0.0000, w_SHY=1.0000\nPortfolio annualized return: 4.63%, volatility: 1.17%\nSharpe ratio: (0.0463 - 0.0400) / 0.0117 = 0.5428", "metadata": {"weights": {"EEM": 0.0, "ETH-USD": 0.0, "VNQI": 0.0, "SHY": 1.0}, "sharpe_ratio": 0.5428, "portfolio_return": 0.046338, "portfolio_vol": 0.011676, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20251015_0170", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLU", "ADA-USD", "BIL", "INDS"], "decision_date": "2025-10-15", "context_summary": "4-asset optimization. Max-Sharpe: 3.702. Portfolio: return=44.90%, vol=11.05%. Weights: w_XLU=0.7982, w_ADA-USD=0.0000, w_BIL=0.0000, w_INDS=0.2018.", "question": "Assets: XLU, ADA-USD, BIL, INDS\nAnnualized mean returns: XLU:0.4629, ADA-USD:-1.2896, BIL:0.0398, INDS:0.3941\nCovariance matrix (annualized):\n[[0.014211, 0.018397, 4.4e-05, 0.006317], [0.018397, 0.586304, 6.7e-05, 0.02892], [4.4e-05, 6.7e-05, 4e-06, 2.5e-05], [0.006317, 0.02892, 2.5e-05, 0.027368]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.7982, w_ADA-USD=0.0000, w_BIL=0.0000, w_INDS=0.2018", "answer_numeric": 3.70247971726866, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.7982, w_ADA-USD=0.0000, w_BIL=0.0000, w_INDS=0.2018\nPortfolio annualized return: 44.90%, volatility: 11.05%\nSharpe ratio: (0.4490 - 0.0400) / 0.1105 = 3.7025", "metadata": {"weights": {"XLU": 0.7982, "ADA-USD": 0.0, "BIL": 0.0, "INDS": 0.2018}, "sharpe_ratio": 3.7025, "portfolio_return": 0.449014, "portfolio_vol": 0.11047, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250227_0173", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "LINK-USD", "HAUZ", "BIL"], "decision_date": "2025-02-27", "context_summary": "4-asset optimization. Max-Sharpe: -0.338. Portfolio: return=-3.62%, vol=22.55%. Weights: w_XLI=0.2500, w_LINK-USD=0.2500, w_HAUZ=0.2500, w_BIL=0.2500.", "question": "Assets: XLI, LINK-USD, HAUZ, BIL\nAnnualized mean returns: XLI:0.0838, LINK-USD:-0.4606, HAUZ:0.1892, BIL:0.0428\nCovariance matrix (annualized):\n[[0.01802, 0.032985, 0.007286, -8.5e-05], [0.032985, 0.643928, 0.028858, 0.000222], [0.007286, 0.028858, 0.013614, -8.5e-05], [-8.5e-05, 0.000222, -8.5e-05, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.2500, w_LINK-USD=0.2500, w_HAUZ=0.2500, w_BIL=0.2500", "answer_numeric": -0.3379138243357051, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.2500, w_LINK-USD=0.2500, w_HAUZ=0.2500, w_BIL=0.2500\nPortfolio annualized return: -3.62%, volatility: 22.55%\nSharpe ratio: (-0.0362 - 0.0400) / 0.2255 = -0.3379", "metadata": {"weights": {"XLI": 0.25, "LINK-USD": 0.25, "HAUZ": 0.25, "BIL": 0.25}, "sharpe_ratio": -0.3379, "portfolio_return": -0.036215, "portfolio_vol": 0.225545, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250613_0175", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BTC-USD", "HAUZ", "UNG"], "decision_date": "2025-06-13", "context_summary": "4-asset optimization. Max-Sharpe: 7.313. Portfolio: return=74.49%, vol=9.64%. Weights: w_VTI=0.2179, w_BTC-USD=0.1417, w_HAUZ=0.6405, w_UNG=0.0000.", "question": "Assets: VTI, BTC-USD, HAUZ, UNG\nAnnualized mean returns: VTI:0.7210, BTC-USD:1.1475, HAUZ:0.6639, UNG:-0.7349\nCovariance matrix (annualized):\n[[0.028007, 0.00637, 0.003077, 0.015597], [0.00637, 0.114701, -0.004746, -0.001445], [0.003077, -0.004746, 0.012841, 0.01079], [0.015597, -0.001445, 0.01079, 0.311089]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2179, w_BTC-USD=0.1417, w_HAUZ=0.6405, w_UNG=0.0000", "answer_numeric": 7.3133389331752365, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.2179, w_BTC-USD=0.1417, w_HAUZ=0.6405, w_UNG=0.0000\nPortfolio annualized return: 74.49%, volatility: 9.64%\nSharpe ratio: (0.7449 - 0.0400) / 0.0964 = 7.3133", "metadata": {"weights": {"VTI": 0.2179, "BTC-USD": 0.1417, "HAUZ": 0.6405, "UNG": 0.0}, "sharpe_ratio": 7.3133, "portfolio_return": 0.744868, "portfolio_vol": 0.096381, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250121_0178", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ADA-USD", "JNK", "MORT"], "decision_date": "2025-01-21", "context_summary": "4-asset optimization. Max-Sharpe: 2.352. Portfolio: return=253.68%, vol=106.17%. Weights: w_ACWI=0.0000, w_ADA-USD=1.0000, w_JNK=0.0000, w_MORT=0.0000.", "question": "Assets: ACWI, ADA-USD, JNK, MORT\nAnnualized mean returns: ACWI:0.0363, ADA-USD:2.5368, JNK:0.0612, MORT:0.0520\nCovariance matrix (annualized):\n[[0.016396, 0.058067, 0.005288, 0.015742], [0.058067, 1.12713, 0.01807, 0.071542], [0.005288, 0.01807, 0.002678, 0.006585], [0.015742, 0.071542, 0.006585, 0.032753]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.0000, w_ADA-USD=1.0000, w_JNK=0.0000, w_MORT=0.0000", "answer_numeric": 2.3517700132572505, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0000, w_ADA-USD=1.0000, w_JNK=0.0000, w_MORT=0.0000\nPortfolio annualized return: 253.68%, volatility: 106.17%\nSharpe ratio: (2.5368 - 0.0400) / 1.0617 = 2.3518", "metadata": {"weights": {"ACWI": 0.0, "ADA-USD": 1.0, "JNK": 0.0, "MORT": 0.0}, "sharpe_ratio": 2.3518, "portfolio_return": 2.536789, "portfolio_vol": 1.061664, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250926_0181", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLE", "XRP-USD", "HYG", "CPER"], "decision_date": "2025-09-26", "context_summary": "4-asset optimization. Max-Sharpe: 2.253. Portfolio: return=13.12%, vol=4.05%. Weights: w_XLE=0.1854, w_XRP-USD=0.0000, w_HYG=0.8146, w_CPER=0.0000.", "question": "Assets: XLE, XRP-USD, HYG, CPER\nAnnualized mean returns: XLE:0.3162, XRP-USD:-0.3326, HYG:0.0891, CPER:-0.1063\nCovariance matrix (annualized):\n[[0.025304, 0.0086, 0.000332, 0.00561], [0.0086, 0.343512, 0.008128, 0.035111], [0.000332, 0.008128, 0.001007, 0.000843], [0.00561, 0.035111, 0.000843, 0.04232]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.1854, w_XRP-USD=0.0000, w_HYG=0.8146, w_CPER=0.0000", "answer_numeric": 2.252806350127016, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.1854, w_XRP-USD=0.0000, w_HYG=0.8146, w_CPER=0.0000\nPortfolio annualized return: 13.12%, volatility: 4.05%\nSharpe ratio: (0.1312 - 0.0400) / 0.0405 = 2.2528", "metadata": {"weights": {"XLE": 0.1854, "XRP-USD": 0.0, "HYG": 0.8146, "CPER": 0.0}, "sharpe_ratio": 2.2528, "portfolio_return": 0.13118, "portfolio_vol": 0.040474, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251204_0184", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "XRP-USD", "CSHI", "IYR"], "decision_date": "2025-12-04", "context_summary": "4-asset optimization. Max-Sharpe: -3.192. Portfolio: return=-67.18%, vol=22.30%. Weights: w_VTI=0.2500, w_XRP-USD=0.2500, w_CSHI=0.2500, w_IYR=0.2500.", "question": "Assets: VTI, XRP-USD, CSHI, IYR\nAnnualized mean returns: VTI:0.1186, XRP-USD:-2.7904, CSHI:0.0536, IYR:-0.0692\nCovariance matrix (annualized):\n[[0.021869, 0.073198, 0.000453, 0.008363], [0.073198, 0.538924, 0.001538, 0.023495], [0.000453, 0.001538, 0.000136, 0.000468], [0.008363, 0.023495, 0.000468, 0.019978]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2500, w_XRP-USD=0.2500, w_CSHI=0.2500, w_IYR=0.2500", "answer_numeric": -3.191542887503464, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.2500, w_XRP-USD=0.2500, w_CSHI=0.2500, w_IYR=0.2500\nPortfolio annualized return: -67.18%, volatility: 22.30%\nSharpe ratio: (-0.6718 - 0.0400) / 0.2230 = -3.1915", "metadata": {"weights": {"VTI": 0.25, "XRP-USD": 0.25, "CSHI": 0.25, "IYR": 0.25}, "sharpe_ratio": -3.1915, "portfolio_return": -0.671837, "portfolio_vol": 0.223038, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250417_0186", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLY", "MATIC-USD", "VNQI", "DBA"], "decision_date": "2025-04-17", "context_summary": "4-asset optimization. Max-Sharpe: 1.289. Portfolio: return=17.71%, vol=10.63%. Weights: w_XLY=0.0000, w_MATIC-USD=0.0000, w_VNQI=1.0000, w_DBA=0.0000.", "question": "Assets: XLY, MATIC-USD, VNQI, DBA\nAnnualized mean returns: XLY:-0.7233, MATIC-USD:-2.5661, VNQI:0.1771, DBA:-0.1953\nCovariance matrix (annualized):\n[[0.051131, 0.040958, 0.013613, 0.003178], [0.040958, 0.470231, 0.013715, 0.02163], [0.013613, 0.013715, 0.01131, 0.003], [0.003178, 0.02163, 0.003, 0.014927]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0000, w_MATIC-USD=0.0000, w_VNQI=1.0000, w_DBA=0.0000", "answer_numeric": 1.288796155712282, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_MATIC-USD=0.0000, w_VNQI=1.0000, w_DBA=0.0000\nPortfolio annualized return: 17.71%, volatility: 10.63%\nSharpe ratio: (0.1771 - 0.0400) / 0.1063 = 1.2888", "metadata": {"weights": {"XLY": 0.0, "MATIC-USD": 0.0, "VNQI": 1.0, "DBA": 0.0}, "sharpe_ratio": 1.2888, "portfolio_return": 0.177063, "portfolio_vol": 0.106349, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251104_0188", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IVV", "DOT-USD", "SCHH", "BIL"], "decision_date": "2025-11-04", "context_summary": "4-asset optimization. Max-Sharpe: 2.651. Portfolio: return=32.71%, vol=10.83%. Weights: w_IVV=1.0000, w_DOT-USD=0.0000, w_SCHH=0.0000, w_BIL=0.0000.", "question": "Assets: IVV, DOT-USD, SCHH, BIL\nAnnualized mean returns: IVV:0.3271, DOT-USD:-2.5548, SCHH:-0.0475, BIL:0.0383\nCovariance matrix (annualized):\n[[0.011732, 0.051065, 0.003949, -2e-05], [0.051065, 0.600529, 0.010358, 2.2e-05], [0.003949, 0.010358, 0.016132, -4.4e-05], [-2e-05, 2.2e-05, -4.4e-05, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=1.0000, w_DOT-USD=0.0000, w_SCHH=0.0000, w_BIL=0.0000", "answer_numeric": 2.651090783851893, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=1.0000, w_DOT-USD=0.0000, w_SCHH=0.0000, w_BIL=0.0000\nPortfolio annualized return: 32.71%, volatility: 10.83%\nSharpe ratio: (0.3271 - 0.0400) / 0.1083 = 2.6511", "metadata": {"weights": {"IVV": 1.0, "DOT-USD": 0.0, "SCHH": 0.0, "BIL": 0.0}, "sharpe_ratio": 2.6511, "portfolio_return": 0.327148, "portfolio_vol": 0.108313, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250801_0190", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE", "ETH-USD", "IAU", "VCIT"], "decision_date": "2025-08-01", "context_summary": "4-asset optimization. Max-Sharpe: 3.947. Portfolio: return=47.74%, vol=11.08%. Weights: w_XLRE=0.0000, w_ETH-USD=0.1784, w_IAU=0.0000, w_VCIT=0.8216.", "question": "Assets: XLRE, ETH-USD, IAU, VCIT\nAnnualized mean returns: XLRE:0.0078, ETH-USD:2.1305, IAU:-0.0157, VCIT:0.1184\nCovariance matrix (annualized):\n[[0.019014, 0.022154, 0.003306, 0.002262], [0.022154, 0.309365, 0.00355, 0.004268], [0.003306, 0.00355, 0.022568, 0.001592], [0.002262, 0.004268, 0.001592, 0.001751]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_ETH-USD=0.1784, w_IAU=0.0000, w_VCIT=0.8216", "answer_numeric": 3.946546558038116, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_ETH-USD=0.1784, w_IAU=0.0000, w_VCIT=0.8216\nPortfolio annualized return: 47.74%, volatility: 11.08%\nSharpe ratio: (0.4774 - 0.0400) / 0.1108 = 3.9465", "metadata": {"weights": {"XLRE": 0.0, "ETH-USD": 0.1784, "IAU": 0.0, "VCIT": 0.8216}, "sharpe_ratio": 3.9465, "portfolio_return": 0.477367, "portfolio_vol": 0.110823, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251014_0192", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ", "LINK-USD", "SHV", "SGOV"], "decision_date": "2025-10-14", "context_summary": "4-asset optimization. Max-Sharpe: 0.959. Portfolio: return=4.22%, vol=0.23%. Weights: w_EWJ=0.0046, w_LINK-USD=0.0000, w_SHV=0.3867, w_SGOV=0.6087.", "question": "Assets: EWJ, LINK-USD, SHV, SGOV\nAnnualized mean returns: EWJ:0.0835, LINK-USD:-1.0190, SHV:0.0421, SGOV:0.0420\nCovariance matrix (annualized):\n[[0.028548, 0.082711, 1e-05, -4.8e-05], [0.082711, 0.811249, -0.000318, -0.000465], [1e-05, -0.000318, 6e-06, 4e-06], [-4.8e-05, -0.000465, 4e-06, 6e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0046, w_LINK-USD=0.0000, w_SHV=0.3867, w_SGOV=0.6087", "answer_numeric": 0.959080509988788, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0046, w_LINK-USD=0.0000, w_SHV=0.3867, w_SGOV=0.6087\nPortfolio annualized return: 4.22%, volatility: 0.23%\nSharpe ratio: (0.0422 - 0.0400) / 0.0023 = 0.9591", "metadata": {"weights": {"EWJ": 0.0046, "LINK-USD": 0.0, "SHV": 0.3867, "SGOV": 0.6087}, "sharpe_ratio": 0.9591, "portfolio_return": 0.042226, "portfolio_vol": 0.002321, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250522_0195", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BTC-USD", "IAU", "ICSH"], "decision_date": "2025-05-22", "context_summary": "4-asset optimization. Max-Sharpe: 5.327. Portfolio: return=32.36%, vol=5.32%. Weights: w_XLB=0.0000, w_BTC-USD=0.1304, w_IAU=0.0568, w_ICSH=0.8128.", "question": "Assets: XLB, BTC-USD, IAU, ICSH\nAnnualized mean returns: XLB:-0.0055, BTC-USD:2.0490, IAU:0.3876, ICSH:0.0422\nCovariance matrix (annualized):\n[[0.064947, 0.046721, 0.000717, 0.000334], [0.046721, 0.154598, -0.000537, -7.3e-05], [0.000717, -0.000537, 0.060489, 0.000133], [0.000334, -7.3e-05, 0.000133, 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=0.0000, w_BTC-USD=0.1304, w_IAU=0.0568, w_ICSH=0.8128", "answer_numeric": 5.327326571696791, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_BTC-USD=0.1304, w_IAU=0.0568, w_ICSH=0.8128\nPortfolio annualized return: 32.36%, volatility: 5.32%\nSharpe ratio: (0.3236 - 0.0400) / 0.0532 = 5.3273", "metadata": {"weights": {"XLB": 0.0, "BTC-USD": 0.1304, "IAU": 0.0568, "ICSH": 0.8128}, "sharpe_ratio": 5.3273, "portfolio_return": 0.323558, "portfolio_vol": 0.053227, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250314_0198", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLY", "BTC-USD", "CPER", "BIL"], "decision_date": "2025-03-14", "context_summary": "4-asset optimization. Max-Sharpe: 3.422. Portfolio: return=5.22%, vol=0.36%. Weights: w_XLY=0.0000, w_BTC-USD=0.0000, w_CPER=0.0156, w_BIL=0.9844.", "question": "Assets: XLY, BTC-USD, CPER, BIL\nAnnualized mean returns: XLY:-0.8204, BTC-USD:-0.3902, CPER:0.7230, BIL:0.0416\nCovariance matrix (annualized):\n[[0.042634, 0.034003, 0.00633, -1.9e-05], [0.034003, 0.209074, 0.02767, -8e-06], [0.00633, 0.02767, 0.055084, -0.000148], [-1.9e-05, -8e-06, -0.000148, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\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_CPER=0.0156, w_BIL=0.9844", "answer_numeric": 3.422063617802894, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_BTC-USD=0.0000, w_CPER=0.0156, w_BIL=0.9844\nPortfolio annualized return: 5.22%, volatility: 0.36%\nSharpe ratio: (0.0522 - 0.0400) / 0.0036 = 3.4221", "metadata": {"weights": {"XLY": 0.0, "BTC-USD": 0.0, "CPER": 0.0156, "BIL": 0.9844}, "sharpe_ratio": 3.4221, "portfolio_return": 0.052244, "portfolio_vol": 0.003578, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250218_0201", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BNB-USD", "BIL", "LQD"], "decision_date": "2025-02-18", "context_summary": "4-asset optimization. Max-Sharpe: 4.547. Portfolio: return=5.34%, vol=0.30%. Weights: w_VTI=0.0111, w_BNB-USD=0.0040, w_BIL=0.9733, w_LQD=0.0116.", "question": "Assets: VTI, BNB-USD, BIL, LQD\nAnnualized mean returns: VTI:0.2949, BNB-USD:1.0342, BIL:0.0459, LQD:0.1176\nCovariance matrix (annualized):\n[[0.016437, -0.000997, -5.4e-05, 0.00345], [-0.000997, 0.191676, -5.7e-05, -0.005205], [-5.4e-05, -5.7e-05, 5e-06, -1.6e-05], [0.00345, -0.005205, -1.6e-05, 0.004193]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0111, w_BNB-USD=0.0040, w_BIL=0.9733, w_LQD=0.0116", "answer_numeric": 4.547071111159667, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0111, w_BNB-USD=0.0040, w_BIL=0.9733, w_LQD=0.0116\nPortfolio annualized return: 5.34%, volatility: 0.30%\nSharpe ratio: (0.0534 - 0.0400) / 0.0030 = 4.5471", "metadata": {"weights": {"VTI": 0.0111, "BNB-USD": 0.004, "BIL": 0.9733, "LQD": 0.0116}, "sharpe_ratio": 4.5471, "portfolio_return": 0.053431, "portfolio_vol": 0.002954, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250516_0204", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "SOL-USD", "JNK", "SLV"], "decision_date": "2025-05-16", "context_summary": "4-asset optimization. Max-Sharpe: 3.779. Portfolio: return=191.50%, vol=49.61%. Weights: w_MTUM=0.3797, w_SOL-USD=0.6203, w_JNK=0.0000, w_SLV=0.0000.", "question": "Assets: MTUM, SOL-USD, JNK, SLV\nAnnualized mean returns: MTUM:0.6562, SOL-USD:2.6856, JNK:0.0343, SLV:0.0277\nCovariance matrix (annualized):\n[[0.079325, 0.081843, 0.021665, 0.02181], [0.081843, 0.509755, 0.023573, 0.042667], [0.021665, 0.023573, 0.00876, 0.010328], [0.02181, 0.042667, 0.010328, 0.076004]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.3797, w_SOL-USD=0.6203, w_JNK=0.0000, w_SLV=0.0000", "answer_numeric": 3.7794744790848185, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.3797, w_SOL-USD=0.6203, w_JNK=0.0000, w_SLV=0.0000\nPortfolio annualized return: 191.50%, volatility: 49.61%\nSharpe ratio: (1.9150 - 0.0400) / 0.4961 = 3.7795", "metadata": {"weights": {"MTUM": 0.3797, "SOL-USD": 0.6203, "JNK": 0.0, "SLV": 0.0}, "sharpe_ratio": 3.7795, "portfolio_return": 1.914981, "portfolio_vol": 0.496096, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250328_0207", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "AVAX-USD", "CSHI", "HYG"], "decision_date": "2025-03-28", "context_summary": "4-asset optimization. Max-Sharpe: -0.029. Portfolio: return=3.97%, vol=1.03%. Weights: w_XLK=0.0000, w_AVAX-USD=0.0000, w_CSHI=1.0000, w_HYG=0.0000.", "question": "Assets: XLK, AVAX-USD, CSHI, HYG\nAnnualized mean returns: XLK:-0.6647, AVAX-USD:-1.1622, CSHI:0.0397, HYG:-0.0051\nCovariance matrix (annualized):\n[[0.079519, 0.08247, 0.001725, 0.007467], [0.08247, 0.743884, 0.003042, 0.006258], [0.001725, 0.003042, 0.000107, 0.000168], [0.007467, 0.006258, 0.000168, 0.001696]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_AVAX-USD=0.0000, w_CSHI=1.0000, w_HYG=0.0000", "answer_numeric": -0.028949014905300864, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.0000, w_AVAX-USD=0.0000, w_CSHI=1.0000, w_HYG=0.0000\nPortfolio annualized return: 3.97%, volatility: 1.03%\nSharpe ratio: (0.0397 - 0.0400) / 0.0103 = -0.0289", "metadata": {"weights": {"XLK": 0.0, "AVAX-USD": 0.0, "CSHI": 1.0, "HYG": 0.0}, "sharpe_ratio": -0.0289, "portfolio_return": 0.039701, "portfolio_vol": 0.010335, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250710_0210", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BNB-USD", "VNQ", "SGOV"], "decision_date": "2025-07-10", "context_summary": "4-asset optimization. Max-Sharpe: 4.470. Portfolio: return=5.53%, vol=0.34%. Weights: w_EEM=0.0272, w_BNB-USD=0.0000, w_VNQ=0.0000, w_SGOV=0.9728.", "question": "Assets: EEM, BNB-USD, VNQ, SGOV\nAnnualized mean returns: EEM:0.5179, BNB-USD:0.0915, VNQ:0.0738, SGOV:0.0423\nCovariance matrix (annualized):\n[[0.017067, 0.005084, 0.004431, -0.000103], [0.005084, 0.076652, -0.000423, -9e-05], [0.004431, -0.000423, 0.020689, -1.9e-05], [-0.000103, -9e-05, -1.9e-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_EEM=0.0272, w_BNB-USD=0.0000, w_VNQ=0.0000, w_SGOV=0.9728", "answer_numeric": 4.470307885233506, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0272, w_BNB-USD=0.0000, w_VNQ=0.0000, w_SGOV=0.9728\nPortfolio annualized return: 5.53%, volatility: 0.34%\nSharpe ratio: (0.0553 - 0.0400) / 0.0034 = 4.4703", "metadata": {"weights": {"EEM": 0.0272, "BNB-USD": 0.0, "VNQ": 0.0, "SGOV": 0.9728}, "sharpe_ratio": 4.4703, "portfolio_return": 0.055256, "portfolio_vol": 0.003413, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251219_0212", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "LINK-USD", "SHY", "ICSH"], "decision_date": "2025-12-19", "context_summary": "4-asset optimization. Max-Sharpe: 0.948. Portfolio: return=14.71%, vol=11.30%. Weights: w_QUAL=1.0000, w_LINK-USD=0.0000, w_SHY=0.0000, w_ICSH=0.0000.", "question": "Assets: QUAL, LINK-USD, SHY, ICSH\nAnnualized mean returns: QUAL:0.1471, LINK-USD:-2.1652, SHY:0.0320, ICSH:0.0389\nCovariance matrix (annualized):\n[[0.012772, 0.026492, 7.5e-05, 5.4e-05], [0.026492, 0.588689, -0.000192, 5.6e-05], [7.5e-05, -0.000192, 0.000104, 1.6e-05], [5.4e-05, 5.6e-05, 1.6e-05, 1.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=1.0000, w_LINK-USD=0.0000, w_SHY=0.0000, w_ICSH=0.0000", "answer_numeric": 0.9475536782746231, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=1.0000, w_LINK-USD=0.0000, w_SHY=0.0000, w_ICSH=0.0000\nPortfolio annualized return: 14.71%, volatility: 11.30%\nSharpe ratio: (0.1471 - 0.0400) / 0.1130 = 0.9476", "metadata": {"weights": {"QUAL": 1.0, "LINK-USD": 0.0, "SHY": 0.0, "ICSH": 0.0}, "sharpe_ratio": 0.9476, "portfolio_return": 0.147088, "portfolio_vol": 0.113015, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250107_0216", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "LINK-USD", "IGOV", "IYR"], "decision_date": "2025-01-07", "context_summary": "4-asset optimization. Max-Sharpe: 2.734. Portfolio: return=319.40%, vol=115.35%. Weights: w_IWM=0.0000, w_LINK-USD=1.0000, w_IGOV=0.0000, w_IYR=0.0000.", "question": "Assets: IWM, LINK-USD, IGOV, IYR\nAnnualized mean returns: IWM:-0.2604, LINK-USD:3.1940, IGOV:-0.2446, IYR:-0.2961\nCovariance matrix (annualized):\n[[0.031883, 0.070025, 0.006832, 0.018958], [0.070025, 1.330484, 0.006422, 0.056589], [0.006832, 0.006422, 0.006893, 0.00639], [0.018958, 0.056589, 0.00639, 0.026269]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_IGOV=0.0000, w_IYR=0.0000", "answer_numeric": 2.7344082927082876, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_LINK-USD=1.0000, w_IGOV=0.0000, w_IYR=0.0000\nPortfolio annualized return: 319.40%, volatility: 115.35%\nSharpe ratio: (3.1940 - 0.0400) / 1.1535 = 2.7344", "metadata": {"weights": {"IWM": 0.0, "LINK-USD": 1.0, "IGOV": 0.0, "IYR": 0.0}, "sharpe_ratio": 2.7344, "portfolio_return": 3.194047, "portfolio_vol": 1.153466, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250918_0219", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "SOL-USD", "IAU", "STIP"], "decision_date": "2025-09-18", "context_summary": "4-asset optimization. Max-Sharpe: 4.031. Portfolio: return=30.08%, vol=6.47%. Weights: w_FXI=0.1515, w_SOL-USD=0.0000, w_IAU=0.3287, w_STIP=0.5198.", "question": "Assets: FXI, SOL-USD, IAU, STIP\nAnnualized mean returns: FXI:0.5365, SOL-USD:1.7216, IAU:0.5435, STIP:0.0786\nCovariance matrix (annualized):\n[[0.03769, 0.068143, 0.006675, 0.000119], [0.068143, 0.585675, 0.045767, 0.004551], [0.006675, 0.045767, 0.019448, 0.001297], [0.000119, 0.004551, 0.001297, 0.000335]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.1515, w_SOL-USD=0.0000, w_IAU=0.3287, w_STIP=0.5198", "answer_numeric": 4.031495359315354, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.1515, w_SOL-USD=0.0000, w_IAU=0.3287, w_STIP=0.5198\nPortfolio annualized return: 30.08%, volatility: 6.47%\nSharpe ratio: (0.3008 - 0.0400) / 0.0647 = 4.0315", "metadata": {"weights": {"FXI": 0.1515, "SOL-USD": 0.0, "IAU": 0.3287, "STIP": 0.5198}, "sharpe_ratio": 4.0315, "portfolio_return": 0.300751, "portfolio_vol": 0.064679, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250306_0221", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ADA-USD", "SHV", "ICSH"], "decision_date": "2025-03-06", "context_summary": "4-asset optimization. Max-Sharpe: 3.975. Portfolio: return=5.46%, vol=0.37%. Weights: w_QQQ=0.0000, w_ADA-USD=0.0000, w_SHV=0.0000, w_ICSH=1.0000.", "question": "Assets: QQQ, ADA-USD, SHV, ICSH\nAnnualized mean returns: QQQ:-0.2046, ADA-USD:-1.4527, SHV:0.0423, ICSH:0.0546\nCovariance matrix (annualized):\n[[0.039745, 0.056084, -3e-06, -9e-06], [0.056084, 0.743925, -6.3e-05, -0.000141], [-3e-06, -6.3e-05, 4e-06, 2e-06], [-9e-06, -0.000141, 2e-06, 1.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.0000, w_ADA-USD=0.0000, w_SHV=0.0000, w_ICSH=1.0000", "answer_numeric": 3.9749508141402066, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0000, w_ADA-USD=0.0000, w_SHV=0.0000, w_ICSH=1.0000\nPortfolio annualized return: 5.46%, volatility: 0.37%\nSharpe ratio: (0.0546 - 0.0400) / 0.0037 = 3.9750", "metadata": {"weights": {"QQQ": 0.0, "ADA-USD": 0.0, "SHV": 0.0, "ICSH": 1.0}, "sharpe_ratio": 3.975, "portfolio_return": 0.05459, "portfolio_vol": 0.00367, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250401_0224", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY", "SOL-USD", "SGOV", "INDS"], "decision_date": "2025-04-01", "context_summary": "4-asset optimization. Max-Sharpe: -2.962. Portfolio: return=-70.78%, vol=25.25%. Weights: w_SPY=0.2500, w_SOL-USD=0.2500, w_SGOV=0.2500, w_INDS=0.2500.", "question": "Assets: SPY, SOL-USD, SGOV, INDS\nAnnualized mean returns: SPY:-0.4637, SOL-USD:-2.4363, SGOV:0.0420, INDS:0.0268\nCovariance matrix (annualized):\n[[0.029689, 0.07178, -5.6e-05, 0.011714], [0.07178, 0.810509, 0.000224, -0.006148], [-5.6e-05, 0.000224, 3e-06, -4.2e-05], [0.011714, -0.006148, -4.2e-05, 0.024847]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.2500, w_SOL-USD=0.2500, w_SGOV=0.2500, w_INDS=0.2500", "answer_numeric": -2.9618419899011674, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.2500, w_SOL-USD=0.2500, w_SGOV=0.2500, w_INDS=0.2500\nPortfolio annualized return: -70.78%, volatility: 25.25%\nSharpe ratio: (-0.7078 - 0.0400) / 0.2525 = -2.9618", "metadata": {"weights": {"SPY": 0.25, "SOL-USD": 0.25, "SGOV": 0.25, "INDS": 0.25}, "sharpe_ratio": -2.9618, "portfolio_return": -0.707825, "portfolio_vol": 0.252487, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250407_0226", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["QUAL", "MATIC-USD", "HAUZ", "SGOV"], "decision_date": "2025-04-07", "context_summary": "4-asset optimization. Max-Sharpe: 1.330. Portfolio: return=4.25%, vol=0.19%. Weights: w_QUAL=0.0000, w_MATIC-USD=0.0000, w_HAUZ=0.0001, w_SGOV=0.9999.", "question": "Assets: QUAL, MATIC-USD, HAUZ, SGOV\nAnnualized mean returns: QUAL:-0.4293, MATIC-USD:-2.2759, HAUZ:0.0343, SGOV:0.0425\nCovariance matrix (annualized):\n[[0.02667, 0.037379, 0.010654, -4.4e-05], [0.037379, 0.473125, 0.011126, -8.5e-05], [0.010654, 0.011126, 0.012663, -9e-06], [-4.4e-05, -8.5e-05, -9e-06, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0000, w_MATIC-USD=0.0000, w_HAUZ=0.0001, w_SGOV=0.9999", "answer_numeric": 1.3300311246840073, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_MATIC-USD=0.0000, w_HAUZ=0.0001, w_SGOV=0.9999\nPortfolio annualized return: 4.25%, volatility: 0.19%\nSharpe ratio: (0.0425 - 0.0400) / 0.0019 = 1.3300", "metadata": {"weights": {"QUAL": 0.0, "MATIC-USD": 0.0, "HAUZ": 0.0001, "SGOV": 0.9999}, "sharpe_ratio": 1.33, "portfolio_return": 0.042491, "portfolio_vol": 0.001873, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250514_0228", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "DOT-USD", "PPLT", "MORT"], "decision_date": "2025-05-14", "context_summary": "4-asset optimization. Max-Sharpe: 3.122. Portfolio: return=148.18%, vol=46.17%. Weights: w_XLI=0.2948, w_DOT-USD=0.7052, w_PPLT=0.0000, w_MORT=0.0000.", "question": "Assets: XLI, DOT-USD, PPLT, MORT\nAnnualized mean returns: XLI:0.4687, DOT-USD:1.9052, PPLT:-0.0038, MORT:-0.1854\nCovariance matrix (annualized):\n[[0.057679, 0.065796, 0.010021, 0.054473], [0.065796, 0.363632, 0.026457, 0.086063], [0.010021, 0.026457, 0.036609, 0.016002], [0.054473, 0.086063, 0.016002, 0.086743]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2948, w_DOT-USD=0.7052, w_PPLT=0.0000, w_MORT=0.0000", "answer_numeric": 3.122403747594569, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.2948, w_DOT-USD=0.7052, w_PPLT=0.0000, w_MORT=0.0000\nPortfolio annualized return: 148.18%, volatility: 46.17%\nSharpe ratio: (1.4818 - 0.0400) / 0.4617 = 3.1224", "metadata": {"weights": {"XLI": 0.2948, "DOT-USD": 0.7052, "PPLT": 0.0, "MORT": 0.0}, "sharpe_ratio": 3.1224, "portfolio_return": 1.481762, "portfolio_vol": 0.461747, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250527_0230", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "XRP-USD", "REZ", "USO"], "decision_date": "2025-05-27", "context_summary": "4-asset optimization. Max-Sharpe: 0.484. Portfolio: return=35.23%, vol=64.53%. Weights: w_VTI=0.0000, w_XRP-USD=1.0000, w_REZ=0.0000, w_USO=0.0000.", "question": "Assets: VTI, XRP-USD, REZ, USO\nAnnualized mean returns: VTI:-0.0092, XRP-USD:0.3523, REZ:-0.2583, USO:-0.6217\nCovariance matrix (annualized):\n[[0.059821, 0.060483, 0.036568, 0.05791], [0.060483, 0.416405, 0.018571, 0.102366], [0.036568, 0.018571, 0.056207, 0.048948], [0.05791, 0.102366, 0.048948, 0.169576]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_XRP-USD=1.0000, w_REZ=0.0000, w_USO=0.0000", "answer_numeric": 0.48396183258270375, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_XRP-USD=1.0000, w_REZ=0.0000, w_USO=0.0000\nPortfolio annualized return: 35.23%, volatility: 64.53%\nSharpe ratio: (0.3523 - 0.0400) / 0.6453 = 0.4840", "metadata": {"weights": {"VTI": 0.0, "XRP-USD": 1.0, "REZ": 0.0, "USO": 0.0}, "sharpe_ratio": 0.484, "portfolio_return": 0.352298, "portfolio_vol": 0.645295, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251112_0232", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VTI", "BTC-USD", "CSHI", "SOYB"], "decision_date": "2025-11-12", "context_summary": "4-asset optimization. Max-Sharpe: 2.082. Portfolio: return=10.89%, vol=3.31%. Weights: w_VTI=0.1049, w_BTC-USD=0.0000, w_CSHI=0.7197, w_SOYB=0.1754.", "question": "Assets: VTI, BTC-USD, CSHI, SOYB\nAnnualized mean returns: VTI:0.2245, BTC-USD:-1.3345, CSHI:0.0500, SOYB:0.2813\nCovariance matrix (annualized):\n[[0.015008, 0.027483, 0.000123, 0.007225], [0.027483, 0.122739, 0.000505, 0.020451], [0.000123, 0.000505, 0.000124, 0.00032], [0.007225, 0.020451, 0.00032, 0.01622]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.1049, w_BTC-USD=0.0000, w_CSHI=0.7197, w_SOYB=0.1754", "answer_numeric": 2.082228114230507, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.1049, w_BTC-USD=0.0000, w_CSHI=0.7197, w_SOYB=0.1754\nPortfolio annualized return: 10.89%, volatility: 3.31%\nSharpe ratio: (0.1089 - 0.0400) / 0.0331 = 2.0822", "metadata": {"weights": {"VTI": 0.1049, "BTC-USD": 0.0, "CSHI": 0.7197, "SOYB": 0.1754}, "sharpe_ratio": 2.0822, "portfolio_return": 0.108866, "portfolio_vol": 0.033073, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251028_0234", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EFA", "SOL-USD", "SGOV", "DBA"], "decision_date": "2025-10-28", "context_summary": "4-asset optimization. Max-Sharpe: 2.451. Portfolio: return=4.84%, vol=0.34%. Weights: w_EFA=0.0323, w_SOL-USD=0.0000, w_SGOV=0.9677, w_DBA=0.0000.", "question": "Assets: EFA, SOL-USD, SGOV, DBA\nAnnualized mean returns: EFA:0.2410, SOL-USD:-0.6618, SGOV:0.0420, DBA:-0.2752\nCovariance matrix (annualized):\n[[0.010528, 0.032882, -6e-05, 0.003908], [0.032882, 0.5307, -0.000412, 0.001502], [-6e-05, -0.000412, 5e-06, 3e-06], [0.003908, 0.001502, 3e-06, 0.011542]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0323, w_SOL-USD=0.0000, w_SGOV=0.9677, w_DBA=0.0000", "answer_numeric": 2.4513072310100967, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0323, w_SOL-USD=0.0000, w_SGOV=0.9677, w_DBA=0.0000\nPortfolio annualized return: 4.84%, volatility: 0.34%\nSharpe ratio: (0.0484 - 0.0400) / 0.0034 = 2.4513", "metadata": {"weights": {"EFA": 0.0323, "SOL-USD": 0.0, "SGOV": 0.9677, "DBA": 0.0}, "sharpe_ratio": 2.4513, "portfolio_return": 0.048434, "portfolio_vol": 0.003441, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20250414_0237", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLE", "SOL-USD", "HYG", "DBB"], "decision_date": "2025-04-14", "context_summary": "4-asset optimization. Max-Sharpe: -1.018. Portfolio: return=-96.24%, vol=98.50%. Weights: w_XLE=0.0000, w_SOL-USD=1.0000, w_HYG=0.0000, w_DBB=0.0000.", "question": "Assets: XLE, SOL-USD, HYG, DBB\nAnnualized mean returns: XLE:-0.2599, SOL-USD:-0.9624, HYG:-0.1969, DBB:-0.3568\nCovariance matrix (annualized):\n[[0.096532, 0.126966, 0.020634, 0.030146], [0.126966, 0.970232, 0.025888, 0.054677], [0.020634, 0.025888, 0.006639, 0.007899], [0.030146, 0.054677, 0.007899, 0.034978]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0000, w_SOL-USD=1.0000, w_HYG=0.0000, w_DBB=0.0000", "answer_numeric": -1.0176632811708561, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_SOL-USD=1.0000, w_HYG=0.0000, w_DBB=0.0000\nPortfolio annualized return: -96.24%, volatility: 98.50%\nSharpe ratio: (-0.9624 - 0.0400) / 0.9850 = -1.0177", "metadata": {"weights": {"XLE": 0.0, "SOL-USD": 1.0, "HYG": 0.0, "DBB": 0.0}, "sharpe_ratio": -1.0177, "portfolio_return": -0.962402, "portfolio_vol": 0.985004, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250219_0240", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "ETH-USD", "SHV", "SLV"], "decision_date": "2025-02-19", "context_summary": "4-asset optimization. Max-Sharpe: 5.053. Portfolio: return=5.26%, vol=0.25%. Weights: w_SPY=0.0002, w_ETH-USD=0.0000, w_SHV=0.9866, w_SLV=0.0132.", "question": "Assets: SPY, ETH-USD, SHV, SLV\nAnnualized mean returns: SPY:0.2304, ETH-USD:0.2679, SHV:0.0434, SLV:0.7361\nCovariance matrix (annualized):\n[[0.015843, 0.022284, -2.2e-05, 0.008536], [0.022284, 0.291935, 0.000199, 0.023747], [-2.2e-05, 0.000199, 4e-06, -0.000142], [0.008536, 0.023747, -0.000142, 0.036585]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.0002, w_ETH-USD=0.0000, w_SHV=0.9866, w_SLV=0.0132", "answer_numeric": 5.052740896886438, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.0002, w_ETH-USD=0.0000, w_SHV=0.9866, w_SLV=0.0132\nPortfolio annualized return: 5.26%, volatility: 0.25%\nSharpe ratio: (0.0526 - 0.0400) / 0.0025 = 5.0527", "metadata": {"weights": {"SPY": 0.0002, "ETH-USD": 0.0, "SHV": 0.9866, "SLV": 0.0132}, "sharpe_ratio": 5.0527, "portfolio_return": 0.052627, "portfolio_vol": 0.002499, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250115_0242", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "DOT-USD", "SGOV", "TLT"], "decision_date": "2025-01-15", "context_summary": "4-asset optimization. Max-Sharpe: 3.416. Portfolio: return=4.69%, vol=0.20%. Weights: w_XLI=0.0000, w_DOT-USD=0.0000, w_SGOV=1.0000, w_TLT=0.0000.", "question": "Assets: XLI, DOT-USD, SGOV, TLT\nAnnualized mean returns: XLI:-0.1932, DOT-USD:0.4358, SGOV:0.0469, TLT:-0.3201\nCovariance matrix (annualized):\n[[0.017931, 0.051093, 1.9e-05, 0.005983], [0.051093, 0.985768, 0.000347, 0.028507], [1.9e-05, 0.000347, 4e-06, -2.4e-05], [0.005983, 0.028507, -2.4e-05, 0.015455]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=0.0000, w_DOT-USD=0.0000, w_SGOV=1.0000, w_TLT=0.0000", "answer_numeric": 3.41647332677073, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=0.0000, w_DOT-USD=0.0000, w_SGOV=1.0000, w_TLT=0.0000\nPortfolio annualized return: 4.69%, volatility: 0.20%\nSharpe ratio: (0.0469 - 0.0400) / 0.0020 = 3.4165", "metadata": {"weights": {"XLI": 0.0, "DOT-USD": 0.0, "SGOV": 1.0, "TLT": 0.0}, "sharpe_ratio": 3.4165, "portfolio_return": 0.046903, "portfolio_vol": 0.00202, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250827_0244", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "BTC-USD", "LQD", "SGOV"], "decision_date": "2025-08-27", "context_summary": "4-asset optimization. Max-Sharpe: 2.456. Portfolio: return=5.66%, vol=0.68%. Weights: w_IWM=0.0296, w_BTC-USD=0.0000, w_LQD=0.0279, w_SGOV=0.9424.", "question": "Assets: IWM, BTC-USD, LQD, SGOV\nAnnualized mean returns: IWM:0.4924, BTC-USD:0.1087, LQD:0.1042, SGOV:0.0415\nCovariance matrix (annualized):\n[[0.038725, 0.033879, 0.003698, -4e-06], [0.033879, 0.082984, 0.004254, 7e-06], [0.003698, 0.004254, 0.003116, -2.1e-05], [-4e-06, 7e-06, -2.1e-05, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0296, w_BTC-USD=0.0000, w_LQD=0.0279, w_SGOV=0.9424", "answer_numeric": 2.45623237521411, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0296, w_BTC-USD=0.0000, w_LQD=0.0279, w_SGOV=0.9424\nPortfolio annualized return: 5.66%, volatility: 0.68%\nSharpe ratio: (0.0566 - 0.0400) / 0.0068 = 2.4562", "metadata": {"weights": {"IWM": 0.0296, "BTC-USD": 0.0, "LQD": 0.0279, "SGOV": 0.9424}, "sharpe_ratio": 2.4562, "portfolio_return": 0.056639, "portfolio_vol": 0.006774, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250304_0246", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "LINK-USD", "SHV", "UNG"], "decision_date": "2025-03-04", "context_summary": "4-asset optimization. Max-Sharpe: 5.482. Portfolio: return=6.32%, vol=0.42%. Weights: w_XLV=0.0267, w_LINK-USD=0.0000, w_SHV=0.9696, w_UNG=0.0037.", "question": "Assets: XLV, LINK-USD, SHV, UNG\nAnnualized mean returns: XLV:0.5389, LINK-USD:-1.5435, SHV:0.0434, UNG:1.8225\nCovariance matrix (annualized):\n[[0.016399, -0.00861, -2e-06, -0.014193], [-0.00861, 0.820715, 0.000348, -0.017465], [-2e-06, 0.000348, 4e-06, -0.000322], [-0.014193, -0.017465, -0.000322, 0.565408]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0267, w_LINK-USD=0.0000, w_SHV=0.9696, w_UNG=0.0037", "answer_numeric": 5.48228906975729, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0267, w_LINK-USD=0.0000, w_SHV=0.9696, w_UNG=0.0037\nPortfolio annualized return: 6.32%, volatility: 0.42%\nSharpe ratio: (0.0632 - 0.0400) / 0.0042 = 5.4823", "metadata": {"weights": {"XLV": 0.0267, "LINK-USD": 0.0, "SHV": 0.9696, "UNG": 0.0037}, "sharpe_ratio": 5.4823, "portfolio_return": 0.063168, "portfolio_vol": 0.004226, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251126_0248", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "LINK-USD", "SGOV", "BNO"], "decision_date": "2025-11-26", "context_summary": "4-asset optimization. Max-Sharpe: 0.551. Portfolio: return=11.85%, vol=14.24%. Weights: w_SPY=1.0000, w_LINK-USD=0.0000, w_SGOV=0.0000, w_BNO=0.0000.", "question": "Assets: SPY, LINK-USD, SGOV, BNO\nAnnualized mean returns: SPY:0.1185, LINK-USD:-3.7261, SGOV:0.0379, BNO:-0.5142\nCovariance matrix (annualized):\n[[0.020289, 0.066936, -5.1e-05, 0.00887], [0.066936, 0.704553, -0.000633, 0.057954], [-5.1e-05, -0.000633, 3e-06, -7e-05], [0.00887, 0.057954, -7e-05, 0.064893]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=1.0000, w_LINK-USD=0.0000, w_SGOV=0.0000, w_BNO=0.0000", "answer_numeric": 0.5510517231993851, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=1.0000, w_LINK-USD=0.0000, w_SGOV=0.0000, w_BNO=0.0000\nPortfolio annualized return: 11.85%, volatility: 14.24%\nSharpe ratio: (0.1185 - 0.0400) / 0.1424 = 0.5511", "metadata": {"weights": {"SPY": 1.0, "LINK-USD": 0.0, "SGOV": 0.0, "BNO": 0.0}, "sharpe_ratio": 0.5511, "portfolio_return": 0.118491, "portfolio_vol": 0.142439, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250818_0251", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY", "ETH-USD", "DBB", "CSHI"], "decision_date": "2025-08-18", "context_summary": "4-asset optimization. Max-Sharpe: 5.623. Portfolio: return=90.00%, vol=15.29%. Weights: w_SPY=0.8390, w_ETH-USD=0.1610, w_DBB=0.0000, w_CSHI=0.0000.", "question": "Assets: SPY, ETH-USD, DBB, CSHI\nAnnualized mean returns: SPY:0.4859, ETH-USD:3.0573, DBB:0.2347, CSHI:0.0490\nCovariance matrix (annualized):\n[[0.008677, 0.030101, 0.00539, 0.000245], [0.030101, 0.352783, 0.029215, 0.001295], [0.00539, 0.029215, 0.016233, -0.000129], [0.000245, 0.001295, -0.000129, 9.6e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.8390, w_ETH-USD=0.1610, w_DBB=0.0000, w_CSHI=0.0000", "answer_numeric": 5.623157901068176, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.8390, w_ETH-USD=0.1610, w_DBB=0.0000, w_CSHI=0.0000\nPortfolio annualized return: 90.00%, volatility: 15.29%\nSharpe ratio: (0.9000 - 0.0400) / 0.1529 = 5.6232", "metadata": {"weights": {"SPY": 0.839, "ETH-USD": 0.161, "DBB": 0.0, "CSHI": 0.0}, "sharpe_ratio": 5.6232, "portfolio_return": 0.89996, "portfolio_vol": 0.152932, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250320_0253", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "ETH-USD", "IEF", "BIL"], "decision_date": "2025-03-20", "context_summary": "4-asset optimization. Max-Sharpe: 2.721. Portfolio: return=20.38%, vol=6.02%. Weights: w_XLE=0.0000, w_ETH-USD=0.0000, w_IEF=1.0000, w_BIL=0.0000.", "question": "Assets: XLE, ETH-USD, IEF, BIL\nAnnualized mean returns: XLE:-0.0744, ETH-USD:-2.3457, IEF:0.2038, BIL:0.0399\nCovariance matrix (annualized):\n[[0.051905, 0.032767, 0.000288, -2.2e-05], [0.032767, 0.423685, -0.012104, -0.00015], [0.000288, -0.012104, 0.003625, 4e-06], [-2.2e-05, -0.00015, 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_XLE=0.0000, w_ETH-USD=0.0000, w_IEF=1.0000, w_BIL=0.0000", "answer_numeric": 2.7210899239787123, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_ETH-USD=0.0000, w_IEF=1.0000, w_BIL=0.0000\nPortfolio annualized return: 20.38%, volatility: 6.02%\nSharpe ratio: (0.2038 - 0.0400) / 0.0602 = 2.7211", "metadata": {"weights": {"XLE": 0.0, "ETH-USD": 0.0, "IEF": 1.0, "BIL": 0.0}, "sharpe_ratio": 2.7211, "portfolio_return": 0.203842, "portfolio_vol": 0.060212, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250616_0255", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "SOL-USD", "SHY", "CSHI"], "decision_date": "2025-06-16", "context_summary": "4-asset optimization. Max-Sharpe: 3.855. Portfolio: return=9.65%, vol=1.47%. Weights: w_XLU=0.0207, w_SOL-USD=0.0015, w_SHY=0.0000, w_CSHI=0.9778.", "question": "Assets: XLU, SOL-USD, SHY, CSHI\nAnnualized mean returns: XLU:0.3533, SOL-USD:0.5499, SHY:0.0169, CSHI:0.0904\nCovariance matrix (annualized):\n[[0.027033, -0.010993, 0.000653, 0.000663], [-0.010993, 0.356667, -0.002581, 0.001687], [0.000653, -0.002581, 0.000294, -1.2e-05], [0.000663, 0.001687, -1.2e-05, 0.00018]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0207, w_SOL-USD=0.0015, w_SHY=0.0000, w_CSHI=0.9778", "answer_numeric": 3.854598207024502, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0207, w_SOL-USD=0.0015, w_SHY=0.0000, w_CSHI=0.9778\nPortfolio annualized return: 9.65%, volatility: 1.47%\nSharpe ratio: (0.0965 - 0.0400) / 0.0147 = 3.8546", "metadata": {"weights": {"XLU": 0.0207, "SOL-USD": 0.0015, "SHY": 0.0, "CSHI": 0.9778}, "sharpe_ratio": 3.8546, "portfolio_return": 0.096533, "portfolio_vol": 0.014666, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250610_0257", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLK", "ADA-USD", "MORT", "SHY"], "decision_date": "2025-06-10", "context_summary": "4-asset optimization. Max-Sharpe: 5.209. Portfolio: return=121.14%, vol=22.49%. Weights: w_XLK=0.8848, w_ADA-USD=0.0000, w_MORT=0.1152, w_SHY=0.0000.", "question": "Assets: XLK, ADA-USD, MORT, SHY\nAnnualized mean returns: XLK:1.2650, ADA-USD:0.7948, MORT:0.7995, SHY:0.0169\nCovariance matrix (annualized):\n[[0.055764, 0.041765, 0.030764, -0.001147], [0.041765, 0.401593, 0.020849, -0.003988], [0.030764, 0.020849, 0.04832, 0.000418], [-0.001147, -0.003988, 0.000418, 0.000333]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.8848, w_ADA-USD=0.0000, w_MORT=0.1152, w_SHY=0.0000", "answer_numeric": 5.209184143165054, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.8848, w_ADA-USD=0.0000, w_MORT=0.1152, w_SHY=0.0000\nPortfolio annualized return: 121.14%, volatility: 22.49%\nSharpe ratio: (1.2114 - 0.0400) / 0.2249 = 5.2092", "metadata": {"weights": {"XLK": 0.8848, "ADA-USD": 0.0, "MORT": 0.1152, "SHY": 0.0}, "sharpe_ratio": 5.2092, "portfolio_return": 1.211402, "portfolio_vol": 0.224872, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250704_0258", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "BTC-USD", "JNK", "SOYB"], "decision_date": "2025-07-04", "context_summary": "4-asset optimization. Max-Sharpe: 4.441. Portfolio: return=22.94%, vol=4.26%. Weights: w_USMV=0.0000, w_BTC-USD=0.0545, w_JNK=0.9073, w_SOYB=0.0383.", "question": "Assets: USMV, BTC-USD, JNK, SOYB\nAnnualized mean returns: USMV:0.1064, BTC-USD:0.5320, JNK:0.2147, SOYB:0.1466\nCovariance matrix (annualized):\n[[0.01134, -0.007448, 0.002339, -0.00307], [-0.007448, 0.104588, -0.001019, -0.001248], [0.002339, -0.001019, 0.001896, 0.000322], [-0.00307, -0.001248, 0.000322, 0.02088]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BTC-USD=0.0545, w_JNK=0.9073, w_SOYB=0.0383", "answer_numeric": 4.441246803744113, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0000, w_BTC-USD=0.0545, w_JNK=0.9073, w_SOYB=0.0383\nPortfolio annualized return: 22.94%, volatility: 4.26%\nSharpe ratio: (0.2294 - 0.0400) / 0.0426 = 4.4412", "metadata": {"weights": {"USMV": 0.0, "BTC-USD": 0.0545, "JNK": 0.9073, "SOYB": 0.0383}, "sharpe_ratio": 4.4412, "portfolio_return": 0.229367, "portfolio_vol": 0.042638, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251225_0260", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "SOL-USD", "GLD", "IYR"], "decision_date": "2025-12-25", "context_summary": "4-asset optimization. Max-Sharpe: 3.082. Portfolio: return=54.29%, vol=16.32%. Weights: w_EEM=0.0000, w_SOL-USD=0.0000, w_GLD=1.0000, w_IYR=0.0000.", "question": "Assets: EEM, SOL-USD, GLD, IYR\nAnnualized mean returns: EEM:0.0107, SOL-USD:-2.4073, GLD:0.5429, IYR:-0.1834\nCovariance matrix (annualized):\n[[0.015502, 0.025504, 0.005096, 0.00102], [0.025504, 0.464799, 0.022479, 0.005404], [0.005096, 0.022479, 0.026625, 0.003815], [0.00102, 0.005404, 0.003815, 0.016888]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_SOL-USD=0.0000, w_GLD=1.0000, w_IYR=0.0000", "answer_numeric": 3.08214016116668, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_SOL-USD=0.0000, w_GLD=1.0000, w_IYR=0.0000\nPortfolio annualized return: 54.29%, volatility: 16.32%\nSharpe ratio: (0.5429 - 0.0400) / 0.1632 = 3.0821", "metadata": {"weights": {"EEM": 0.0, "SOL-USD": 0.0, "GLD": 1.0, "IYR": 0.0}, "sharpe_ratio": 3.0821, "portfolio_return": 0.542915, "portfolio_vol": 0.163171, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250701_0263", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BNB-USD", "CSHI", "JNK"], "decision_date": "2025-07-01", "context_summary": "4-asset optimization. Max-Sharpe: 5.649. Portfolio: return=12.63%, vol=1.53%. Weights: w_^VIX=0.0101, w_BNB-USD=0.0195, w_CSHI=0.5502, w_JNK=0.4202.", "question": "Assets: ^VIX, BNB-USD, CSHI, JNK\nAnnualized mean returns: ^VIX:-2.4289, BNB-USD:0.8170, CSHI:0.0683, JNK:0.2317\nCovariance matrix (annualized):\n[[1.237936, -0.083325, -0.00361, -0.037138], [-0.083325, 0.106473, 0.000481, 0.001442], [-0.00361, 0.000481, 0.000149, 5.2e-05], [-0.037138, 0.001442, 5.2e-05, 0.001994]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0101, w_BNB-USD=0.0195, w_CSHI=0.5502, w_JNK=0.4202", "answer_numeric": 5.648611639767989, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0101, w_BNB-USD=0.0195, w_CSHI=0.5502, w_JNK=0.4202\nPortfolio annualized return: 12.63%, volatility: 1.53%\nSharpe ratio: (0.1263 - 0.0400) / 0.0153 = 5.6486", "metadata": {"weights": {"^VIX": 0.0101, "BNB-USD": 0.0195, "CSHI": 0.5502, "JNK": 0.4202}, "sharpe_ratio": 5.6486, "portfolio_return": 0.126262, "portfolio_vol": 0.015271, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250214_0265", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "AVAX-USD", "CSHI", "XHB"], "decision_date": "2025-02-14", "context_summary": "4-asset optimization. Max-Sharpe: 1.501. Portfolio: return=4.87%, vol=0.58%. Weights: w_VTI=0.0000, w_AVAX-USD=0.0000, w_CSHI=1.0000, w_XHB=0.0000.", "question": "Assets: VTI, AVAX-USD, CSHI, XHB\nAnnualized mean returns: VTI:0.0611, AVAX-USD:-1.4710, CSHI:0.0487, XHB:-0.4207\nCovariance matrix (annualized):\n[[0.022144, 0.051218, 0.000455, 0.024468], [0.051218, 0.586145, 0.002141, 0.066358], [0.000455, 0.002141, 3.3e-05, 0.000401], [0.024468, 0.066358, 0.000401, 0.057503]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_AVAX-USD=0.0000, w_CSHI=1.0000, w_XHB=0.0000", "answer_numeric": 1.5006663070872637, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_AVAX-USD=0.0000, w_CSHI=1.0000, w_XHB=0.0000\nPortfolio annualized return: 4.87%, volatility: 0.58%\nSharpe ratio: (0.0487 - 0.0400) / 0.0058 = 1.5007", "metadata": {"weights": {"VTI": 0.0, "AVAX-USD": 0.0, "CSHI": 1.0, "XHB": 0.0}, "sharpe_ratio": 1.5007, "portfolio_return": 0.048681, "portfolio_vol": 0.005784, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250910_0268", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY", "DOT-USD", "SOYB", "MORT"], "decision_date": "2025-09-10", "context_summary": "4-asset optimization. Max-Sharpe: 2.578. Portfolio: return=27.88%, vol=9.26%. Weights: w_SPY=0.5920, w_DOT-USD=0.0000, w_SOYB=0.1413, w_MORT=0.2668.", "question": "Assets: SPY, DOT-USD, SOYB, MORT\nAnnualized mean returns: SPY:0.2578, DOT-USD:-0.6258, SOYB:0.1662, MORT:0.3849\nCovariance matrix (annualized):\n[[0.009274, 0.029267, 0.002458, 0.007445], [0.029267, 0.463018, 0.016456, 0.045501], [0.002458, 0.016456, 0.016068, 0.003029], [0.007445, 0.045501, 0.003029, 0.028326]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.5920, w_DOT-USD=0.0000, w_SOYB=0.1413, w_MORT=0.2668", "answer_numeric": 2.5780182521055113, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.5920, w_DOT-USD=0.0000, w_SOYB=0.1413, w_MORT=0.2668\nPortfolio annualized return: 27.88%, volatility: 9.26%\nSharpe ratio: (0.2788 - 0.0400) / 0.0926 = 2.5780", "metadata": {"weights": {"SPY": 0.592, "DOT-USD": 0.0, "SOYB": 0.1413, "MORT": 0.2668}, "sharpe_ratio": 2.578, "portfolio_return": 0.278759, "portfolio_vol": 0.092613, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251003_0270", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "SOL-USD", "ICSH", "SCHP"], "decision_date": "2025-10-03", "context_summary": "4-asset optimization. Max-Sharpe: 6.695. Portfolio: return=12.01%, vol=1.20%. Weights: w_VLUE=0.0963, w_SOL-USD=0.0000, w_ICSH=0.9037, w_SCHP=0.0000.", "question": "Assets: VLUE, SOL-USD, ICSH, SCHP\nAnnualized mean returns: VLUE:0.7893, SOL-USD:2.0483, ICSH:0.0488, SCHP:0.0899\nCovariance matrix (annualized):\n[[0.013506, 0.038137, 4.3e-05, 0.001299], [0.038137, 0.600402, 0.000341, 0.009236], [4.3e-05, 0.000341, 1.3e-05, 2.1e-05], [0.001299, 0.009236, 2.1e-05, 0.001049]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0963, w_SOL-USD=0.0000, w_ICSH=0.9037, w_SCHP=0.0000", "answer_numeric": 6.694846390270397, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0963, w_SOL-USD=0.0000, w_ICSH=0.9037, w_SCHP=0.0000\nPortfolio annualized return: 12.01%, volatility: 1.20%\nSharpe ratio: (0.1201 - 0.0400) / 0.0120 = 6.6948", "metadata": {"weights": {"VLUE": 0.0963, "SOL-USD": 0.0, "ICSH": 0.9037, "SCHP": 0.0}, "sharpe_ratio": 6.6948, "portfolio_return": 0.120109, "portfolio_vol": 0.011966, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250908_0272", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "SOL-USD", "VNQI", "DBB"], "decision_date": "2025-09-08", "context_summary": "4-asset optimization. Max-Sharpe: 1.957. Portfolio: return=44.57%, vol=20.74%. Weights: w_QUAL=0.1244, w_SOL-USD=0.2083, w_VNQI=0.1204, w_DBB=0.5468.", "question": "Assets: QUAL, SOL-USD, VNQI, DBB\nAnnualized mean returns: QUAL:0.1406, SOL-USD:1.4664, VNQI:0.1592, DBB:0.1894\nCovariance matrix (annualized):\n[[0.010087, 0.03358, 0.005894, 0.003115], [0.03358, 0.587627, 0.040099, 0.0361], [0.005894, 0.040099, 0.012249, 0.003785], [0.003115, 0.0361, 0.003785, 0.013652]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.1244, w_SOL-USD=0.2083, w_VNQI=0.1204, w_DBB=0.5468", "answer_numeric": 1.9565218853555753, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.1244, w_SOL-USD=0.2083, w_VNQI=0.1204, w_DBB=0.5468\nPortfolio annualized return: 44.57%, volatility: 20.74%\nSharpe ratio: (0.4457 - 0.0400) / 0.2074 = 1.9565", "metadata": {"weights": {"QUAL": 0.1244, "SOL-USD": 0.2083, "VNQI": 0.1204, "DBB": 0.5468}, "sharpe_ratio": 1.9565, "portfolio_return": 0.44572, "portfolio_vol": 0.207368, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251201_0274", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "LINK-USD", "USO", "CSHI"], "decision_date": "2025-12-01", "context_summary": "4-asset optimization. Max-Sharpe: 1.118. Portfolio: return=5.31%, vol=1.17%. Weights: w_XLY=0.0000, w_LINK-USD=0.0000, w_USO=0.0000, w_CSHI=1.0000.", "question": "Assets: XLY, LINK-USD, USO, CSHI\nAnnualized mean returns: XLY:-0.1205, LINK-USD:-3.9914, USO:-0.1406, CSHI:0.0531\nCovariance matrix (annualized):\n[[0.046721, 0.072722, 0.013629, 0.000396], [0.072722, 0.69822, 0.077015, 0.000682], [0.013629, 0.077015, 0.073082, 0.000432], [0.000396, 0.000682, 0.000432, 0.000136]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0000, w_LINK-USD=0.0000, w_USO=0.0000, w_CSHI=1.0000", "answer_numeric": 1.1178158429242984, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_LINK-USD=0.0000, w_USO=0.0000, w_CSHI=1.0000\nPortfolio annualized return: 5.31%, volatility: 1.17%\nSharpe ratio: (0.0531 - 0.0400) / 0.0117 = 1.1178", "metadata": {"weights": {"XLY": 0.0, "LINK-USD": 0.0, "USO": 0.0, "CSHI": 1.0}, "sharpe_ratio": 1.1178, "portfolio_return": 0.053057, "portfolio_vol": 0.011681, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250606_0277", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "BTC-USD", "BNO", "REZ"], "decision_date": "2025-06-06", "context_summary": "4-asset optimization. Max-Sharpe: 3.919. Portfolio: return=86.57%, vol=21.07%. Weights: w_ACWI=0.6835, w_BTC-USD=0.3165, w_BNO=0.0000, w_REZ=0.0000.", "question": "Assets: ACWI, BTC-USD, BNO, REZ\nAnnualized mean returns: ACWI:0.6248, BTC-USD:1.3860, BNO:0.1360, REZ:0.0698\nCovariance matrix (annualized):\n[[0.032247, 0.029714, 0.024508, 0.02594], [0.029714, 0.16448, 0.064686, 0.020566], [0.024508, 0.064686, 0.106753, 0.023772], [0.02594, 0.020566, 0.023772, 0.04694]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.6835, w_BTC-USD=0.3165, w_BNO=0.0000, w_REZ=0.0000", "answer_numeric": 3.918864076664411, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.6835, w_BTC-USD=0.3165, w_BNO=0.0000, w_REZ=0.0000\nPortfolio annualized return: 86.57%, volatility: 21.07%\nSharpe ratio: (0.8657 - 0.0400) / 0.2107 = 3.9189", "metadata": {"weights": {"ACWI": 0.6835, "BTC-USD": 0.3165, "BNO": 0.0, "REZ": 0.0}, "sharpe_ratio": 3.9189, "portfolio_return": 0.865732, "portfolio_vol": 0.210707, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250717_0280", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF", "XRP-USD", "VNQI", "PALL"], "decision_date": "2025-07-17", "context_summary": "4-asset optimization. Max-Sharpe: 4.948. Portfolio: return=70.32%, vol=13.41%. Weights: w_XLF=0.0000, w_XRP-USD=0.0274, w_VNQI=0.6931, w_PALL=0.2794.", "question": "Assets: XLF, XRP-USD, VNQI, PALL\nAnnualized mean returns: XLF:0.0726, XRP-USD:0.8979, VNQI:0.3214, PALL:1.6314\nCovariance matrix (annualized):\n[[0.019838, 0.017356, 0.009512, 0.000716], [0.017356, 0.258311, 0.000703, 0.056098], [0.009512, 0.000703, 0.009019, 0.004841], [0.000716, 0.056098, 0.004841, 0.13679]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_XRP-USD=0.0274, w_VNQI=0.6931, w_PALL=0.2794", "answer_numeric": 4.947632678299743, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_XRP-USD=0.0274, w_VNQI=0.6931, w_PALL=0.2794\nPortfolio annualized return: 70.32%, volatility: 13.41%\nSharpe ratio: (0.7032 - 0.0400) / 0.1341 = 4.9476", "metadata": {"weights": {"XLF": 0.0, "XRP-USD": 0.0274, "VNQI": 0.6931, "PALL": 0.2794}, "sharpe_ratio": 4.9476, "portfolio_return": 0.703245, "portfolio_vol": 0.134053, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250626_0283", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "LINK-USD", "SCHP", "HAUZ"], "decision_date": "2025-06-26", "context_summary": "4-asset optimization. Max-Sharpe: 4.286. Portfolio: return=44.96%, vol=9.56%. Weights: w_FXI=0.2304, w_LINK-USD=0.0000, w_SCHP=0.0840, w_HAUZ=0.6856.", "question": "Assets: FXI, LINK-USD, SCHP, HAUZ\nAnnualized mean returns: FXI:0.6194, LINK-USD:-0.1147, SCHP:0.0351, HAUZ:0.4434\nCovariance matrix (annualized):\n[[0.04518, 0.043237, -0.004193, 0.004176], [0.043237, 0.543679, -0.009074, -0.00631], [-0.004193, -0.009074, 0.002409, 0.000954], [0.004176, -0.00631, 0.000954, 0.011598]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2304, w_LINK-USD=0.0000, w_SCHP=0.0840, w_HAUZ=0.6856", "answer_numeric": 4.286139859145181, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.2304, w_LINK-USD=0.0000, w_SCHP=0.0840, w_HAUZ=0.6856\nPortfolio annualized return: 44.96%, volatility: 9.56%\nSharpe ratio: (0.4496 - 0.0400) / 0.0956 = 4.2861", "metadata": {"weights": {"FXI": 0.2304, "LINK-USD": 0.0, "SCHP": 0.084, "HAUZ": 0.6856}, "sharpe_ratio": 4.2861, "portfolio_return": 0.449617, "portfolio_vol": 0.095568, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250627_0286", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "DOT-USD", "MORT", "BIL"], "decision_date": "2025-06-27", "context_summary": "4-asset optimization. Max-Sharpe: 4.776. Portfolio: return=7.39%, vol=0.71%. Weights: w_EEM=0.0523, w_DOT-USD=0.0000, w_MORT=0.0000, w_BIL=0.9477.", "question": "Assets: EEM, DOT-USD, MORT, BIL\nAnnualized mean returns: EEM:0.6903, DOT-USD:-0.6045, MORT:0.2982, BIL:0.0398\nCovariance matrix (annualized):\n[[0.019948, 0.010705, 0.008319, -8.2e-05], [0.010705, 0.413289, 0.011515, 0.000138], [0.008319, 0.011515, 0.033288, -4.5e-05], [-8.2e-05, 0.000138, -4.5e-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_EEM=0.0523, w_DOT-USD=0.0000, w_MORT=0.0000, w_BIL=0.9477", "answer_numeric": 4.775585843997575, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0523, w_DOT-USD=0.0000, w_MORT=0.0000, w_BIL=0.9477\nPortfolio annualized return: 7.39%, volatility: 0.71%\nSharpe ratio: (0.0739 - 0.0400) / 0.0071 = 4.7756", "metadata": {"weights": {"EEM": 0.0523, "DOT-USD": 0.0, "MORT": 0.0, "BIL": 0.9477}, "sharpe_ratio": 4.7756, "portfolio_return": 0.073855, "portfolio_vol": 0.007089, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250313_0288", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VLUE", "ETH-USD", "PPLT", "VNQI"], "decision_date": "2025-03-13", "context_summary": "4-asset optimization. Max-Sharpe: 2.409. Portfolio: return=31.40%, vol=11.37%. Weights: w_VLUE=0.0000, w_ETH-USD=0.0000, w_PPLT=0.0236, w_VNQI=0.9764.", "question": "Assets: VLUE, ETH-USD, PPLT, VNQI\nAnnualized mean returns: VLUE:-0.0012, ETH-USD:-2.4811, PPLT:0.2107, VNQI:0.3165\nCovariance matrix (annualized):\n[[0.021579, 0.032364, 0.001161, 0.009255], [0.032364, 0.456923, 0.024924, 0.027519], [0.001161, 0.024924, 0.027804, 0.007581], [0.009255, 0.027519, 0.007581, 0.013187]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_ETH-USD=0.0000, w_PPLT=0.0236, w_VNQI=0.9764", "answer_numeric": 2.4090916152844826, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_ETH-USD=0.0000, w_PPLT=0.0236, w_VNQI=0.9764\nPortfolio annualized return: 31.40%, volatility: 11.37%\nSharpe ratio: (0.3140 - 0.0400) / 0.1137 = 2.4091", "metadata": {"weights": {"VLUE": 0.0, "ETH-USD": 0.0, "PPLT": 0.0236, "VNQI": 0.9764}, "sharpe_ratio": 2.4091, "portfolio_return": 0.314013, "portfolio_vol": 0.113741, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250916_0290", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLP", "XRP-USD", "TLH", "DBA"], "decision_date": "2025-09-16", "context_summary": "4-asset optimization. Max-Sharpe: 5.944. Portfolio: return=42.04%, vol=6.40%. Weights: w_XLP=0.0000, w_XRP-USD=0.0000, w_TLH=0.5601, w_DBA=0.4399.", "question": "Assets: XLP, XRP-USD, TLH, DBA\nAnnualized mean returns: XLP:-0.1310, XRP-USD:-0.5560, TLH:0.3619, DBA:0.4949\nCovariance matrix (annualized):\n[[0.011283, 0.015324, 0.002016, 0.001139], [0.015324, 0.38458, 0.010419, 0.001156], [0.002016, 0.010419, 0.00751, -0.001685], [0.001139, 0.001156, -0.001685, 0.013278]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_XRP-USD=0.0000, w_TLH=0.5601, w_DBA=0.4399", "answer_numeric": 5.944467204044356, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_XRP-USD=0.0000, w_TLH=0.5601, w_DBA=0.4399\nPortfolio annualized return: 42.04%, volatility: 6.40%\nSharpe ratio: (0.4204 - 0.0400) / 0.0640 = 5.9445", "metadata": {"weights": {"XLP": 0.0, "XRP-USD": 0.0, "TLH": 0.5601, "DBA": 0.4399}, "sharpe_ratio": 5.9445, "portfolio_return": 0.420398, "portfolio_vol": 0.063992, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250625_0293", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "XRP-USD", "INDS", "UNG"], "decision_date": "2025-06-25", "context_summary": "4-asset optimization. Max-Sharpe: 4.315. Portfolio: return=65.67%, vol=14.29%. Weights: w_VLUE=0.9722, w_XRP-USD=0.0000, w_INDS=0.0000, w_UNG=0.0278.", "question": "Assets: VLUE, XRP-USD, INDS, UNG\nAnnualized mean returns: VLUE:0.6648, XRP-USD:-0.2720, INDS:0.3819, UNG:0.3743\nCovariance matrix (annualized):\n[[0.021223, 0.031811, 0.012776, 0.00207], [0.031811, 0.280689, 0.004805, 0.000277], [0.012776, 0.004805, 0.019745, -0.003089], [0.00207, 0.000277, -0.003089, 0.325947]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.9722, w_XRP-USD=0.0000, w_INDS=0.0000, w_UNG=0.0278", "answer_numeric": 4.3154446074159925, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.9722, w_XRP-USD=0.0000, w_INDS=0.0000, w_UNG=0.0278\nPortfolio annualized return: 65.67%, volatility: 14.29%\nSharpe ratio: (0.6567 - 0.0400) / 0.1429 = 4.3154", "metadata": {"weights": {"VLUE": 0.9722, "XRP-USD": 0.0, "INDS": 0.0, "UNG": 0.0278}, "sharpe_ratio": 4.3154, "portfolio_return": 0.656728, "portfolio_vol": 0.142912, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250707_0297", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "DOT-USD", "TIP", "WEAT"], "decision_date": "2025-07-07", "context_summary": "4-asset optimization. Max-Sharpe: 0.415. Portfolio: return=14.19%, vol=24.53%. Weights: w_^VIX=0.0000, w_DOT-USD=0.0000, w_TIP=0.0000, w_WEAT=1.0000.", "question": "Assets: ^VIX, DOT-USD, TIP, WEAT\nAnnualized mean returns: ^VIX:-2.3460, DOT-USD:-0.7037, TIP:0.0341, WEAT:0.1419\nCovariance matrix (annualized):\n[[1.189431, -0.228039, 0.006811, 0.102528], [-0.228039, 0.488856, -0.003366, -0.033328], [0.006811, -0.003366, 0.000337, 0.000319], [0.102528, -0.033328, 0.000319, 0.060184]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_DOT-USD=0.0000, w_TIP=0.0000, w_WEAT=1.0000", "answer_numeric": 0.41516815971665716, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0000, w_DOT-USD=0.0000, w_TIP=0.0000, w_WEAT=1.0000\nPortfolio annualized return: 14.19%, volatility: 24.53%\nSharpe ratio: (0.1419 - 0.0400) / 0.2453 = 0.4152", "metadata": {"weights": {"^VIX": 0.0, "DOT-USD": 0.0, "TIP": 0.0, "WEAT": 1.0}, "sharpe_ratio": 0.4152, "portfolio_return": 0.141851, "portfolio_vol": 0.245324, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250624_0299", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ETH-USD", "BNDX", "VNQ"], "decision_date": "2025-06-24", "context_summary": "4-asset optimization. Max-Sharpe: 4.488. Portfolio: return=70.16%, vol=14.74%. Weights: w_IVV=0.9058, w_ETH-USD=0.0942, w_BNDX=0.0000, w_VNQ=0.0000.", "question": "Assets: IVV, ETH-USD, BNDX, VNQ\nAnnualized mean returns: IVV:0.5662, ETH-USD:2.0042, BNDX:0.0288, VNQ:0.2929\nCovariance matrix (annualized):\n[[0.016442, 0.025407, 0.000195, 0.010777], [0.025407, 0.440779, -0.003834, 0.003749], [0.000195, -0.003834, 0.001234, 0.002391], [0.010777, 0.003749, 0.002391, 0.017776]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.9058, w_ETH-USD=0.0942, w_BNDX=0.0000, w_VNQ=0.0000", "answer_numeric": 4.487928133854096, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.9058, w_ETH-USD=0.0942, w_BNDX=0.0000, w_VNQ=0.0000\nPortfolio annualized return: 70.16%, volatility: 14.74%\nSharpe ratio: (0.7016 - 0.0400) / 0.1474 = 4.4879", "metadata": {"weights": {"IVV": 0.9058, "ETH-USD": 0.0942, "BNDX": 0.0, "VNQ": 0.0}, "sharpe_ratio": 4.4879, "portfolio_return": 0.701637, "portfolio_vol": 0.147426, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251016_0301", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "AVAX-USD", "TLT", "SLV"], "decision_date": "2025-10-16", "context_summary": "4-asset optimization. Max-Sharpe: 10.055. Portfolio: return=98.14%, vol=9.36%. Weights: w_VLUE=0.2310, w_AVAX-USD=0.0000, w_TLT=0.4161, w_SLV=0.3529.", "question": "Assets: VLUE, AVAX-USD, TLT, SLV\nAnnualized mean returns: VLUE:0.4974, AVAX-USD:-0.2367, TLT:0.3374, SLV:2.0574\nCovariance matrix (annualized):\n[[0.019289, 0.073299, -0.00183, 0.001601], [0.073299, 0.890962, -0.014402, 0.027775], [-0.00183, -0.014402, 0.009826, -0.00254], [0.001601, 0.027775, -0.00254, 0.055171]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.2310, w_AVAX-USD=0.0000, w_TLT=0.4161, w_SLV=0.3529", "answer_numeric": 10.054988719917674, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.2310, w_AVAX-USD=0.0000, w_TLT=0.4161, w_SLV=0.3529\nPortfolio annualized return: 98.14%, volatility: 9.36%\nSharpe ratio: (0.9814 - 0.0400) / 0.0936 = 10.0550", "metadata": {"weights": {"VLUE": 0.231, "AVAX-USD": 0.0, "TLT": 0.4161, "SLV": 0.3529}, "sharpe_ratio": 10.055, "portfolio_return": 0.981437, "portfolio_vol": 0.093629, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251211_0304", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "SOL-USD", "REZ", "ICSH"], "decision_date": "2025-12-11", "context_summary": "4-asset optimization. Max-Sharpe: 4.273. Portfolio: return=73.69%, vol=16.31%. Weights: w_VLUE=1.0000, w_SOL-USD=0.0000, w_REZ=0.0000, w_ICSH=0.0000.", "question": "Assets: VLUE, SOL-USD, REZ, ICSH\nAnnualized mean returns: VLUE:0.7369, SOL-USD:-2.1882, REZ:0.1299, ICSH:0.0398\nCovariance matrix (annualized):\n[[0.026594, 0.048689, 0.00567, 3.7e-05], [0.048689, 0.504831, -0.001165, -9.2e-05], [0.00567, -0.001165, 0.020904, 8.7e-05], [3.7e-05, -9.2e-05, 8.7e-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_VLUE=1.0000, w_SOL-USD=0.0000, w_REZ=0.0000, w_ICSH=0.0000", "answer_numeric": 4.27330484484464, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=1.0000, w_SOL-USD=0.0000, w_REZ=0.0000, w_ICSH=0.0000\nPortfolio annualized return: 73.69%, volatility: 16.31%\nSharpe ratio: (0.7369 - 0.0400) / 0.1631 = 4.2733", "metadata": {"weights": {"VLUE": 1.0, "SOL-USD": 0.0, "REZ": 0.0, "ICSH": 0.0}, "sharpe_ratio": 4.2733, "portfolio_return": 0.736879, "portfolio_vol": 0.163077, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250724_0306", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "DOT-USD", "STIP", "IYR"], "decision_date": "2025-07-24", "context_summary": "4-asset optimization. Max-Sharpe: 4.865. Portfolio: return=15.37%, vol=2.34%. Weights: w_IWM=0.1227, w_DOT-USD=0.0000, w_STIP=0.8513, w_IYR=0.0260.", "question": "Assets: IWM, DOT-USD, STIP, IYR\nAnnualized mean returns: IWM:0.7262, DOT-USD:-0.4323, STIP:0.0630, IYR:0.4242\nCovariance matrix (annualized):\n[[0.028915, 0.025348, -0.000663, 0.012055], [0.025348, 0.377563, -0.000122, 0.011429], [-0.000663, -0.000122, 0.000225, 1.4e-05], [0.012055, 0.011429, 1.4e-05, 0.013651]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.1227, w_DOT-USD=0.0000, w_STIP=0.8513, w_IYR=0.0260", "answer_numeric": 4.865337551481547, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.1227, w_DOT-USD=0.0000, w_STIP=0.8513, w_IYR=0.0260\nPortfolio annualized return: 15.37%, volatility: 2.34%\nSharpe ratio: (0.1537 - 0.0400) / 0.0234 = 4.8653", "metadata": {"weights": {"IWM": 0.1227, "DOT-USD": 0.0, "STIP": 0.8513, "IYR": 0.026}, "sharpe_ratio": 4.8653, "portfolio_return": 0.153734, "portfolio_vol": 0.023376, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250404_0309", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLU", "BTC-USD", "SGOV", "TLT"], "decision_date": "2025-04-04", "context_summary": "4-asset optimization. Max-Sharpe: 2.505. Portfolio: return=5.02%, vol=0.41%. Weights: w_XLU=0.0000, w_BTC-USD=0.0000, w_SGOV=0.9725, w_TLT=0.0275.", "question": "Assets: XLU, BTC-USD, SGOV, TLT\nAnnualized mean returns: XLU:0.1192, BTC-USD:-0.8630, SGOV:0.0421, TLT:0.3359\nCovariance matrix (annualized):\n[[0.022015, -0.006076, -2.4e-05, 0.005647], [-0.006076, 0.206787, 4.7e-05, -0.019346], [-2.4e-05, 4.7e-05, 3e-06, 5e-06], [0.005647, -0.019346, 5e-06, 0.017302]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0000, w_BTC-USD=0.0000, w_SGOV=0.9725, w_TLT=0.0275", "answer_numeric": 2.504616659388926, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0000, w_BTC-USD=0.0000, w_SGOV=0.9725, w_TLT=0.0275\nPortfolio annualized return: 5.02%, volatility: 0.41%\nSharpe ratio: (0.0502 - 0.0400) / 0.0041 = 2.5046", "metadata": {"weights": {"XLU": 0.0, "BTC-USD": 0.0, "SGOV": 0.9725, "TLT": 0.0275}, "sharpe_ratio": 2.5046, "portfolio_return": 0.050205, "portfolio_vol": 0.004075, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251001_0312", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLE", "LINK-USD", "BIL", "DBB"], "decision_date": "2025-10-01", "context_summary": "4-asset optimization. Max-Sharpe: 3.926. Portfolio: return=15.38%, vol=2.90%. Weights: w_XLE=0.1106, w_LINK-USD=0.0000, w_BIL=0.6741, w_DBB=0.2154.", "question": "Assets: XLE, LINK-USD, BIL, DBB\nAnnualized mean returns: XLE:0.3158, LINK-USD:0.9767, BIL:0.0404, DBB:0.4254\nCovariance matrix (annualized):\n[[0.024907, 0.016678, -2e-05, -0.003269], [0.016678, 0.738044, 6.8e-05, 0.030268], [-2e-05, 6.8e-05, 4e-06, 1.1e-05], [-0.003269, 0.030268, 1.1e-05, 0.014856]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.1106, w_LINK-USD=0.0000, w_BIL=0.6741, w_DBB=0.2154", "answer_numeric": 3.925578859897492, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.1106, w_LINK-USD=0.0000, w_BIL=0.6741, w_DBB=0.2154\nPortfolio annualized return: 15.38%, volatility: 2.90%\nSharpe ratio: (0.1538 - 0.0400) / 0.0290 = 3.9256", "metadata": {"weights": {"XLE": 0.1106, "LINK-USD": 0.0, "BIL": 0.6741, "DBB": 0.2154}, "sharpe_ratio": 3.9256, "portfolio_return": 0.153775, "portfolio_vol": 0.028983, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251128_0314", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "SOL-USD", "PPLT", "REZ"], "decision_date": "2025-11-28", "context_summary": "4-asset optimization. Max-Sharpe: 1.672. Portfolio: return=21.62%, vol=10.54%. Weights: w_XLU=0.5560, w_SOL-USD=0.0000, w_PPLT=0.0423, w_REZ=0.4017.", "question": "Assets: XLU, SOL-USD, PPLT, REZ\nAnnualized mean returns: XLU:0.2108, SOL-USD:-2.6537, PPLT:0.2439, REZ:0.2208\nCovariance matrix (annualized):\n[[0.014159, 0.029526, 0.01336, 0.005796], [0.029526, 0.580596, 0.076046, -7.8e-05], [0.01336, 0.076046, 0.100595, 0.002897], [0.005796, -7.8e-05, 0.002897, 0.020036]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.5560, w_SOL-USD=0.0000, w_PPLT=0.0423, w_REZ=0.4017", "answer_numeric": 1.67224152472342, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.5560, w_SOL-USD=0.0000, w_PPLT=0.0423, w_REZ=0.4017\nPortfolio annualized return: 21.62%, volatility: 10.54%\nSharpe ratio: (0.2162 - 0.0400) / 0.1054 = 1.6722", "metadata": {"weights": {"XLU": 0.556, "SOL-USD": 0.0, "PPLT": 0.0423, "REZ": 0.4017}, "sharpe_ratio": 1.6722, "portfolio_return": 0.216232, "portfolio_vol": 0.105386, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250807_0316", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "SOL-USD", "LQD", "SCHH"], "decision_date": "2025-08-07", "context_summary": "4-asset optimization. Max-Sharpe: 3.508. Portfolio: return=22.48%, vol=5.27%. Weights: w_FXI=0.1225, w_SOL-USD=0.0000, w_LQD=0.8775, w_SCHH=0.0000.", "question": "Assets: FXI, SOL-USD, LQD, SCHH\nAnnualized mean returns: FXI:0.2845, SOL-USD:0.4235, LQD:0.2165, SCHH:-0.0441\nCovariance matrix (annualized):\n[[0.02992, 0.037712, 7e-06, 0.006923], [0.037712, 0.38002, 0.004775, 0.037425], [7e-06, 0.004775, 0.00302, 0.003477], [0.006923, 0.037425, 0.003477, 0.019264]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.1225, w_SOL-USD=0.0000, w_LQD=0.8775, w_SCHH=0.0000", "answer_numeric": 3.5077294651115074, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.1225, w_SOL-USD=0.0000, w_LQD=0.8775, w_SCHH=0.0000\nPortfolio annualized return: 22.48%, volatility: 5.27%\nSharpe ratio: (0.2248 - 0.0400) / 0.0527 = 3.5077", "metadata": {"weights": {"FXI": 0.1225, "SOL-USD": 0.0, "LQD": 0.8775, "SCHH": 0.0}, "sharpe_ratio": 3.5077, "portfolio_return": 0.224824, "portfolio_vol": 0.05269, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250311_0318", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "ADA-USD", "ICSH", "IAU"], "decision_date": "2025-03-11", "context_summary": "4-asset optimization. Max-Sharpe: 5.710. Portfolio: return=6.80%, vol=0.49%. Weights: w_EFA=0.0078, w_ADA-USD=0.0000, w_ICSH=0.9728, w_IAU=0.0194.", "question": "Assets: EFA, ADA-USD, ICSH, IAU\nAnnualized mean returns: EFA:0.4942, ADA-USD:-2.0732, ICSH:0.0558, IAU:0.5076\nCovariance matrix (annualized):\n[[0.023419, 0.009831, 5.9e-05, 0.007762], [0.009831, 0.790047, -0.000299, -0.000917], [5.9e-05, -0.000299, 1.4e-05, -8e-06], [0.007762, -0.000917, -8e-06, 0.017969]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0078, w_ADA-USD=0.0000, w_ICSH=0.9728, w_IAU=0.0194", "answer_numeric": 5.709588905758133, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0078, w_ADA-USD=0.0000, w_ICSH=0.9728, w_IAU=0.0194\nPortfolio annualized return: 6.80%, volatility: 0.49%\nSharpe ratio: (0.0680 - 0.0400) / 0.0049 = 5.7096", "metadata": {"weights": {"EFA": 0.0078, "ADA-USD": 0.0, "ICSH": 0.9728, "IAU": 0.0194}, "sharpe_ratio": 5.7096, "portfolio_return": 0.068017, "portfolio_vol": 0.004907, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250708_0321", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "LINK-USD", "TLT", "CPER"], "decision_date": "2025-07-08", "context_summary": "4-asset optimization. Max-Sharpe: 2.178. Portfolio: return=55.96%, vol=23.85%. Weights: w_EWJ=0.0000, w_LINK-USD=0.0000, w_TLT=0.0000, w_CPER=1.0000.", "question": "Assets: EWJ, LINK-USD, TLT, CPER\nAnnualized mean returns: EWJ:0.1405, LINK-USD:-1.1746, TLT:-0.0025, CPER:0.5596\nCovariance matrix (annualized):\n[[0.028807, 0.016041, 0.005516, 0.01361], [0.016041, 0.433304, -0.017175, 0.005751], [0.005516, -0.017175, 0.015754, 0.000576], [0.01361, 0.005751, 0.000576, 0.056901]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0000, w_TLT=0.0000, w_CPER=1.0000", "answer_numeric": 2.1784691877917344, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_LINK-USD=0.0000, w_TLT=0.0000, w_CPER=1.0000\nPortfolio annualized return: 55.96%, volatility: 23.85%\nSharpe ratio: (0.5596 - 0.0400) / 0.2385 = 2.1785", "metadata": {"weights": {"EWJ": 0.0, "LINK-USD": 0.0, "TLT": 0.0, "CPER": 1.0}, "sharpe_ratio": 2.1785, "portfolio_return": 0.559649, "portfolio_vol": 0.238539, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250729_0324", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EFA", "BNB-USD", "DBB", "CSHI"], "decision_date": "2025-07-29", "context_summary": "4-asset optimization. Max-Sharpe: 4.119. Portfolio: return=8.90%, vol=1.19%. Weights: w_EFA=0.0000, w_BNB-USD=0.0178, w_DBB=0.0562, w_CSHI=0.9259.", "question": "Assets: EFA, BNB-USD, DBB, CSHI\nAnnualized mean returns: EFA:0.1514, BNB-USD:0.6786, DBB:0.3520, CSHI:0.0617\nCovariance matrix (annualized):\n[[0.016581, 0.006909, 0.006428, 7.3e-05], [0.006909, 0.067522, 0.013788, -0.000147], [0.006428, 0.013788, 0.015077, -0.000209], [7.3e-05, -0.000147, -0.000209, 8.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0000, w_BNB-USD=0.0178, w_DBB=0.0562, w_CSHI=0.9259", "answer_numeric": 4.119483146401539, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0000, w_BNB-USD=0.0178, w_DBB=0.0562, w_CSHI=0.9259\nPortfolio annualized return: 8.90%, volatility: 1.19%\nSharpe ratio: (0.0890 - 0.0400) / 0.0119 = 4.1195", "metadata": {"weights": {"EFA": 0.0, "BNB-USD": 0.0178, "DBB": 0.0562, "CSHI": 0.9259}, "sharpe_ratio": 4.1195, "portfolio_return": 0.088979, "portfolio_vol": 0.01189, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250409_0326", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["^VIX", "AVAX-USD", "IYR", "BIL"], "decision_date": "2025-04-09", "context_summary": "4-asset optimization. Max-Sharpe: 4.033. Portfolio: return=7.27%, vol=0.81%. Weights: w_^VIX=0.0060, w_AVAX-USD=0.0024, w_IYR=0.0000, w_BIL=0.9916.", "question": "Assets: ^VIX, AVAX-USD, IYR, BIL\nAnnualized mean returns: ^VIX:5.5834, AVAX-USD:-0.8652, IYR:-0.6715, BIL:0.0416\nCovariance matrix (annualized):\n[[2.057724, -0.581109, -0.177145, 0.000201], [-0.581109, 0.799489, -0.001234, -0.000269], [-0.177145, -0.001234, 0.042329, -3e-05], [0.000201, -0.000269, -3e-05, 3e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0060, w_AVAX-USD=0.0024, w_IYR=0.0000, w_BIL=0.9916", "answer_numeric": 4.032576383210054, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0060, w_AVAX-USD=0.0024, w_IYR=0.0000, w_BIL=0.9916\nPortfolio annualized return: 7.27%, volatility: 0.81%\nSharpe ratio: (0.0727 - 0.0400) / 0.0081 = 4.0326", "metadata": {"weights": {"^VIX": 0.006, "AVAX-USD": 0.0024, "IYR": 0.0, "BIL": 0.9916}, "sharpe_ratio": 4.0326, "portfolio_return": 0.072677, "portfolio_vol": 0.008103, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251007_0329", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM", "DOT-USD", "WEAT", "ICSH"], "decision_date": "2025-10-07", "context_summary": "4-asset optimization. Max-Sharpe: 4.098. Portfolio: return=5.68%, vol=0.41%. Weights: w_MTUM=0.0252, w_DOT-USD=0.0001, w_WEAT=0.0000, w_ICSH=0.9747.", "question": "Assets: MTUM, DOT-USD, WEAT, ICSH\nAnnualized mean returns: MTUM:0.2698, DOT-USD:0.8790, WEAT:-0.2654, ICSH:0.0512\nCovariance matrix (annualized):\n[[0.011271, 0.023741, -0.003895, -5.8e-05], [0.023741, 0.44468, -0.004158, 0.000204], [-0.003895, -0.004158, 0.020937, -2e-06], [-5.8e-05, 0.000204, -2e-06, 1.3e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_MTUM=0.0252, w_DOT-USD=0.0001, w_WEAT=0.0000, w_ICSH=0.9747", "answer_numeric": 4.09777013351761, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.0252, w_DOT-USD=0.0001, w_WEAT=0.0000, w_ICSH=0.9747\nPortfolio annualized return: 5.68%, volatility: 0.41%\nSharpe ratio: (0.0568 - 0.0400) / 0.0041 = 4.0978", "metadata": {"weights": {"MTUM": 0.0252, "DOT-USD": 0.0001, "WEAT": 0.0, "ICSH": 0.9747}, "sharpe_ratio": 4.0978, "portfolio_return": 0.056815, "portfolio_vol": 0.004103, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251127_0332", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "XRP-USD", "INDS", "DBC"], "decision_date": "2025-11-27", "context_summary": "4-asset optimization. Max-Sharpe: 1.061. Portfolio: return=18.10%, vol=13.29%. Weights: w_EEM=0.3997, w_XRP-USD=0.0000, w_INDS=0.6003, w_DBC=0.0000.", "question": "Assets: EEM, XRP-USD, INDS, DBC\nAnnualized mean returns: EEM:0.1881, XRP-USD:-2.4519, INDS:0.1763, DBC:-0.0043\nCovariance matrix (annualized):\n[[0.030018, 0.079529, 0.010906, 0.013514], [0.079529, 0.499386, 0.027544, 0.040061], [0.010906, 0.027544, 0.021171, 0.005018], [0.013514, 0.040061, 0.005018, 0.017545]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.3997, w_XRP-USD=0.0000, w_INDS=0.6003, w_DBC=0.0000", "answer_numeric": 1.0612846034779493, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.3997, w_XRP-USD=0.0000, w_INDS=0.6003, w_DBC=0.0000\nPortfolio annualized return: 18.10%, volatility: 13.29%\nSharpe ratio: (0.1810 - 0.0400) / 0.1329 = 1.0613", "metadata": {"weights": {"EEM": 0.3997, "XRP-USD": 0.0, "INDS": 0.6003, "DBC": 0.0}, "sharpe_ratio": 1.0613, "portfolio_return": 0.181029, "portfolio_vol": 0.132885, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250128_0334", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "SOL-USD", "SGOV", "STIP"], "decision_date": "2025-01-28", "context_summary": "4-asset optimization. Max-Sharpe: 3.643. Portfolio: return=4.81%, vol=0.22%. Weights: w_VEA=0.0034, w_SOL-USD=0.0005, w_SGOV=0.9781, w_STIP=0.0180.", "question": "Assets: VEA, SOL-USD, SGOV, STIP\nAnnualized mean returns: VEA:0.1292, SOL-USD:0.6946, SGOV:0.0476, STIP:0.0468\nCovariance matrix (annualized):\n[[0.014933, 0.042416, -3.5e-05, 0.001006], [0.042416, 0.441212, -1.9e-05, 0.004088], [-3.5e-05, -1.9e-05, 5e-06, -6e-06], [0.001006, 0.004088, -6e-06, 0.000251]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0034, w_SOL-USD=0.0005, w_SGOV=0.9781, w_STIP=0.0180", "answer_numeric": 3.6425645882988076, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0034, w_SOL-USD=0.0005, w_SGOV=0.9781, w_STIP=0.0180\nPortfolio annualized return: 4.81%, volatility: 0.22%\nSharpe ratio: (0.0481 - 0.0400) / 0.0022 = 3.6426", "metadata": {"weights": {"VEA": 0.0034, "SOL-USD": 0.0005, "SGOV": 0.9781, "STIP": 0.018}, "sharpe_ratio": 3.6426, "portfolio_return": 0.048125, "portfolio_vol": 0.002231, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20251107_0337", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "DOT-USD", "IYR", "BNO"], "decision_date": "2025-11-07", "context_summary": "4-asset optimization. Max-Sharpe: -0.483. Portfolio: return=-7.43%, vol=23.65%. Weights: w_XLP=0.0000, w_DOT-USD=0.0000, w_IYR=0.0000, w_BNO=1.0000.", "question": "Assets: XLP, DOT-USD, IYR, BNO\nAnnualized mean returns: XLP:-0.3468, DOT-USD:-2.3441, IYR:-0.1648, BNO:-0.0743\nCovariance matrix (annualized):\n[[0.012919, -0.005734, 0.008477, -0.005286], [-0.005734, 0.601593, 0.00779, 0.055127], [0.008477, 0.00779, 0.015905, 3.3e-05], [-0.005286, 0.055127, 3.3e-05, 0.055947]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_DOT-USD=0.0000, w_IYR=0.0000, w_BNO=1.0000", "answer_numeric": -0.4832348625702369, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_DOT-USD=0.0000, w_IYR=0.0000, w_BNO=1.0000\nPortfolio annualized return: -7.43%, volatility: 23.65%\nSharpe ratio: (-0.0743 - 0.0400) / 0.2365 = -0.4832", "metadata": {"weights": {"XLP": 0.0, "DOT-USD": 0.0, "IYR": 0.0, "BNO": 1.0}, "sharpe_ratio": -0.4832, "portfolio_return": -0.0743, "portfolio_vol": 0.236531, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250123_0340", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "MATIC-USD", "VCIT", "CSHI"], "decision_date": "2025-01-23", "context_summary": "4-asset optimization. Max-Sharpe: 2.405. Portfolio: return=5.40%, vol=0.58%. Weights: w_EEM=0.0000, w_MATIC-USD=0.0000, w_VCIT=0.0000, w_CSHI=1.0000.", "question": "Assets: EEM, MATIC-USD, VCIT, CSHI\nAnnualized mean returns: EEM:0.0013, MATIC-USD:0.4558, VCIT:-0.0036, CSHI:0.0540\nCovariance matrix (annualized):\n[[0.017485, 0.028276, 0.003518, 0.000269], [0.028276, 0.872039, 0.01614, 0.00197], [0.003518, 0.01614, 0.003314, 0.000124], [0.000269, 0.00197, 0.000124, 3.4e-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_EEM=0.0000, w_MATIC-USD=0.0000, w_VCIT=0.0000, w_CSHI=1.0000", "answer_numeric": 2.405234876395822, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_MATIC-USD=0.0000, w_VCIT=0.0000, w_CSHI=1.0000\nPortfolio annualized return: 5.40%, volatility: 0.58%\nSharpe ratio: (0.0540 - 0.0400) / 0.0058 = 2.4052", "metadata": {"weights": {"EEM": 0.0, "MATIC-USD": 0.0, "VCIT": 0.0, "CSHI": 1.0}, "sharpe_ratio": 2.4052, "portfolio_return": 0.054016, "portfolio_vol": 0.005827, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20250416_0343", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VEA", "SOL-USD", "JNK", "CSHI"], "decision_date": "2025-04-16", "context_summary": "4-asset optimization. Max-Sharpe: -1.234. Portfolio: return=-117.32%, vol=98.30%. Weights: w_VEA=0.0000, w_SOL-USD=1.0000, w_JNK=0.0000, w_CSHI=0.0000.", "question": "Assets: VEA, SOL-USD, JNK, CSHI\nAnnualized mean returns: VEA:-0.1694, SOL-USD:-1.1732, JNK:-0.2098, CSHI:0.0086\nCovariance matrix (annualized):\n[[0.041064, 0.056666, 0.013786, 0.005916], [0.056666, 0.966239, 0.026013, 0.010063], [0.013786, 0.026013, 0.007304, 0.002916], [0.005916, 0.010063, 0.002916, 0.002046]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.0000, w_SOL-USD=1.0000, w_JNK=0.0000, w_CSHI=0.0000", "answer_numeric": -1.2341767430382387, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_SOL-USD=1.0000, w_JNK=0.0000, w_CSHI=0.0000\nPortfolio annualized return: -117.32%, volatility: 98.30%\nSharpe ratio: (-1.1732 - 0.0400) / 0.9830 = -1.2342", "metadata": {"weights": {"VEA": 0.0, "SOL-USD": 1.0, "JNK": 0.0, "CSHI": 0.0}, "sharpe_ratio": -1.2342, "portfolio_return": -1.173164, "portfolio_vol": 0.982975, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250102_0346", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "SOL-USD", "PPLT", "CSHI"], "decision_date": "2025-01-02", "context_summary": "4-asset optimization. Max-Sharpe: 3.173. Portfolio: return=5.71%, vol=0.54%. Weights: w_XLF=0.0000, w_SOL-USD=0.0021, w_PPLT=0.0000, w_CSHI=0.9979.", "question": "Assets: XLF, SOL-USD, PPLT, CSHI\nAnnualized mean returns: XLF:0.1073, SOL-USD:1.0227, PPLT:-0.5290, CSHI:0.0551\nCovariance matrix (annualized):\n[[0.027967, 0.068315, 0.003029, 0.000345], [0.068315, 0.519338, 0.035483, 0.000571], [0.003029, 0.035483, 0.039478, 1.9e-05], [0.000345, 0.000571, 1.9e-05, 2.4e-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_XLF=0.0000, w_SOL-USD=0.0021, w_PPLT=0.0000, w_CSHI=0.9979", "answer_numeric": 3.172981914641843, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_SOL-USD=0.0021, w_PPLT=0.0000, w_CSHI=0.9979\nPortfolio annualized return: 5.71%, volatility: 0.54%\nSharpe ratio: (0.0571 - 0.0400) / 0.0054 = 3.1730", "metadata": {"weights": {"XLF": 0.0, "SOL-USD": 0.0021, "PPLT": 0.0, "CSHI": 0.9979}, "sharpe_ratio": 3.173, "portfolio_return": 0.057126, "portfolio_vol": 0.005397, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250305_0349", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "SOL-USD", "VNQI", "CSHI"], "decision_date": "2025-03-05", "context_summary": "4-asset optimization. Max-Sharpe: 1.012. Portfolio: return=15.63%, vol=11.49%. Weights: w_XLY=0.0000, w_SOL-USD=0.0000, w_VNQI=1.0000, w_CSHI=0.0000.", "question": "Assets: XLY, SOL-USD, VNQI, CSHI\nAnnualized mean returns: XLY:-0.5254, SOL-USD:-1.8356, VNQI:0.1563, CSHI:0.0331\nCovariance matrix (annualized):\n[[0.031397, 0.058128, 0.008866, 0.000365], [0.058128, 0.789324, 0.010544, 0.001495], [0.008866, 0.010544, 0.013209, -5.2e-05], [0.000365, 0.001495, -5.2e-05, 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_XLY=0.0000, w_SOL-USD=0.0000, w_VNQI=1.0000, w_CSHI=0.0000", "answer_numeric": 1.012118144760484, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_SOL-USD=0.0000, w_VNQI=1.0000, w_CSHI=0.0000\nPortfolio annualized return: 15.63%, volatility: 11.49%\nSharpe ratio: (0.1563 - 0.0400) / 0.1149 = 1.0121", "metadata": {"weights": {"XLY": 0.0, "SOL-USD": 0.0, "VNQI": 1.0, "CSHI": 0.0}, "sharpe_ratio": 1.0121, "portfolio_return": 0.156325, "portfolio_vol": 0.114932, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250220_0352", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "LINK-USD", "ITB", "BNDX"], "decision_date": "2025-02-20", "context_summary": "4-asset optimization. Max-Sharpe: 1.278. Portfolio: return=24.66%, vol=16.17%. Weights: w_XLP=0.8526, w_LINK-USD=0.1474, w_ITB=0.0000, w_BNDX=0.0000.", "question": "Assets: XLP, LINK-USD, ITB, BNDX\nAnnualized mean returns: XLP:0.1451, LINK-USD:0.8333, ITB:-0.2296, BNDX:-0.0048\nCovariance matrix (annualized):\n[[0.015017, 0.003349, 0.011926, 0.001202], [0.003349, 0.661315, 0.022394, 0.005788], [0.011926, 0.022394, 0.058317, 0.003016], [0.001202, 0.005788, 0.003016, 0.001415]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.8526, w_LINK-USD=0.1474, w_ITB=0.0000, w_BNDX=0.0000", "answer_numeric": 1.2778901390401336, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.8526, w_LINK-USD=0.1474, w_ITB=0.0000, w_BNDX=0.0000\nPortfolio annualized return: 24.66%, volatility: 16.17%\nSharpe ratio: (0.2466 - 0.0400) / 0.1617 = 1.2779", "metadata": {"weights": {"XLP": 0.8526, "LINK-USD": 0.1474, "ITB": 0.0, "BNDX": 0.0}, "sharpe_ratio": 1.2779, "portfolio_return": 0.246577, "portfolio_vol": 0.161655, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250213_0354", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "ETH-USD", "HAUZ", "TIP"], "decision_date": "2025-02-13", "context_summary": "4-asset optimization. Max-Sharpe: 0.964. Portfolio: return=5.61%, vol=1.67%. Weights: w_IWM=0.0000, w_ETH-USD=0.0000, w_HAUZ=0.0000, w_TIP=1.0000.", "question": "Assets: IWM, ETH-USD, HAUZ, TIP\nAnnualized mean returns: IWM:-0.1952, ETH-USD:-0.3550, HAUZ:0.0413, TIP:0.0561\nCovariance matrix (annualized):\n[[0.032296, 0.041568, 0.019536, 0.001506], [0.041568, 0.324314, 0.036971, 0.002593], [0.019536, 0.036971, 0.018607, 0.001202], [0.001506, 0.002593, 0.001202, 0.000277]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ETH-USD=0.0000, w_HAUZ=0.0000, w_TIP=1.0000", "answer_numeric": 0.9644408448226989, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_ETH-USD=0.0000, w_HAUZ=0.0000, w_TIP=1.0000\nPortfolio annualized return: 5.61%, volatility: 1.67%\nSharpe ratio: (0.0561 - 0.0400) / 0.0167 = 0.9644", "metadata": {"weights": {"IWM": 0.0, "ETH-USD": 0.0, "HAUZ": 0.0, "TIP": 1.0}, "sharpe_ratio": 0.9644, "portfolio_return": 0.056062, "portfolio_vol": 0.016655, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20251023_0356", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLI", "BTC-USD", "USO", "ITB"], "decision_date": "2025-10-23", "context_summary": "4-asset optimization. Max-Sharpe: -0.198. Portfolio: return=1.41%, vol=13.05%. Weights: w_XLI=1.0000, w_BTC-USD=0.0000, w_USO=0.0000, w_ITB=0.0000.", "question": "Assets: XLI, BTC-USD, USO, ITB\nAnnualized mean returns: XLI:0.0141, BTC-USD:-0.6957, USO:-0.2969, ITB:-0.4689\nCovariance matrix (annualized):\n[[0.017023, 0.019933, -0.000665, 0.016535], [0.019933, 0.103729, 0.014957, 0.01885], [-0.000665, 0.014957, 0.069694, -0.01663], [0.016535, 0.01885, -0.01663, 0.056425]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLI=1.0000, w_BTC-USD=0.0000, w_USO=0.0000, w_ITB=0.0000", "answer_numeric": -0.19812762389729957, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLI=1.0000, w_BTC-USD=0.0000, w_USO=0.0000, w_ITB=0.0000\nPortfolio annualized return: 1.41%, volatility: 13.05%\nSharpe ratio: (0.0141 - 0.0400) / 0.1305 = -0.1981", "metadata": {"weights": {"XLI": 1.0, "BTC-USD": 0.0, "USO": 0.0, "ITB": 0.0}, "sharpe_ratio": -0.1981, "portfolio_return": 0.01415, "portfolio_vol": 0.130473, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251013_0358", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ADA-USD", "TLT", "SGOV"], "decision_date": "2025-10-13", "context_summary": "4-asset optimization. Max-Sharpe: 2.553. Portfolio: return=4.99%, vol=0.39%. Weights: w_QQQ=0.0125, w_ADA-USD=0.0000, w_TLT=0.0284, w_SGOV=0.9592.", "question": "Assets: QQQ, ADA-USD, TLT, SGOV\nAnnualized mean returns: QQQ:0.1034, ADA-USD:-1.0290, TLT:0.2535, SGOV:0.0432\nCovariance matrix (annualized):\n[[0.018102, 0.064319, -0.001419, -9.2e-05], [0.064319, 0.573957, -0.012693, -0.000221], [-0.001419, -0.012693, 0.010854, 3.7e-05], [-9.2e-05, -0.000221, 3.7e-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_QQQ=0.0125, w_ADA-USD=0.0000, w_TLT=0.0284, w_SGOV=0.9592", "answer_numeric": 2.5526110415053647, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0125, w_ADA-USD=0.0000, w_TLT=0.0284, w_SGOV=0.9592\nPortfolio annualized return: 4.99%, volatility: 0.39%\nSharpe ratio: (0.0499 - 0.0400) / 0.0039 = 2.5526", "metadata": {"weights": {"QQQ": 0.0125, "ADA-USD": 0.0, "TLT": 0.0284, "SGOV": 0.9592}, "sharpe_ratio": 2.5526, "portfolio_return": 0.049937, "portfolio_vol": 0.003893, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250604_0360", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "ADA-USD", "TLH", "SGOV"], "decision_date": "2025-06-04", "context_summary": "4-asset optimization. Max-Sharpe: 2.735. Portfolio: return=7.58%, vol=1.31%. Weights: w_SPY=0.0560, w_ADA-USD=0.0047, w_TLH=0.0000, w_SGOV=0.9393.", "question": "Assets: SPY, ADA-USD, TLH, SGOV\nAnnualized mean returns: SPY:0.5488, ADA-USD:1.1632, TLH:-0.3298, SGOV:0.0422\nCovariance matrix (annualized):\n[[0.03755, 0.052668, 0.011637, 9.1e-05], [0.052668, 0.479531, -0.003843, 0.000194], [0.011637, -0.003843, 0.015822, 2e-05], [9.1e-05, 0.000194, 2e-05, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.0560, w_ADA-USD=0.0047, w_TLH=0.0000, w_SGOV=0.9393", "answer_numeric": 2.7352376229147253, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.0560, w_ADA-USD=0.0047, w_TLH=0.0000, w_SGOV=0.9393\nPortfolio annualized return: 7.58%, volatility: 1.31%\nSharpe ratio: (0.0758 - 0.0400) / 0.0131 = 2.7352", "metadata": {"weights": {"SPY": 0.056, "ADA-USD": 0.0047, "TLH": 0.0, "SGOV": 0.9393}, "sharpe_ratio": 2.7352, "portfolio_return": 0.075811, "portfolio_vol": 0.013092, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250122_0363", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "SOL-USD", "CSHI", "XHB"], "decision_date": "2025-01-22", "context_summary": "4-asset optimization. Max-Sharpe: 1.872. Portfolio: return=5.13%, vol=0.60%. Weights: w_QQQ=0.0000, w_SOL-USD=0.0012, w_CSHI=0.9988, w_XHB=0.0000.", "question": "Assets: QQQ, SOL-USD, CSHI, XHB\nAnnualized mean returns: QQQ:0.2623, SOL-USD:0.5304, CSHI:0.0507, XHB:-0.4314\nCovariance matrix (annualized):\n[[0.036564, 0.066348, 0.000637, 0.021252], [0.066348, 0.499258, 0.000976, 0.037483], [0.000637, 0.000976, 3.3e-05, 0.000566], [0.021252, 0.037483, 0.000566, 0.0619]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0012, w_CSHI=0.9988, w_XHB=0.0000", "answer_numeric": 1.8720679456122058, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0000, w_SOL-USD=0.0012, w_CSHI=0.9988, w_XHB=0.0000\nPortfolio annualized return: 5.13%, volatility: 0.60%\nSharpe ratio: (0.0513 - 0.0400) / 0.0060 = 1.8721", "metadata": {"weights": {"QQQ": 0.0, "SOL-USD": 0.0012, "CSHI": 0.9988, "XHB": 0.0}, "sharpe_ratio": 1.8721, "portfolio_return": 0.051258, "portfolio_vol": 0.006014, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250806_0366", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IVV", "XRP-USD", "SCHH", "JNK"], "decision_date": "2025-08-06", "context_summary": "4-asset optimization. Max-Sharpe: 3.676. Portfolio: return=17.96%, vol=3.80%. Weights: w_IVV=0.0583, w_XRP-USD=0.0234, w_SCHH=0.0000, w_JNK=0.9183.", "question": "Assets: IVV, XRP-USD, SCHH, JNK\nAnnualized mean returns: IVV:0.3172, XRP-USD:1.4899, SCHH:-0.0005, JNK:0.1375\nCovariance matrix (annualized):\n[[0.009831, 0.020636, 0.005118, 0.00197], [0.020636, 0.438646, 0.024876, 0.00384], [0.005118, 0.024876, 0.019441, 0.00206], [0.00197, 0.00384, 0.00206, 0.000875]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0583, w_XRP-USD=0.0234, w_SCHH=0.0000, w_JNK=0.9183", "answer_numeric": 3.675733754214327, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0583, w_XRP-USD=0.0234, w_SCHH=0.0000, w_JNK=0.9183\nPortfolio annualized return: 17.96%, volatility: 3.80%\nSharpe ratio: (0.1796 - 0.0400) / 0.0380 = 3.6757", "metadata": {"weights": {"IVV": 0.0583, "XRP-USD": 0.0234, "SCHH": 0.0, "JNK": 0.9183}, "sharpe_ratio": 3.6757, "portfolio_return": 0.179615, "portfolio_vol": 0.037983, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250901_0369", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLY", "ADA-USD", "STIP", "CSHI"], "decision_date": "2025-09-01", "context_summary": "4-asset optimization. Max-Sharpe: 3.773. Portfolio: return=9.43%, vol=1.44%. Weights: w_XLY=0.0221, w_ADA-USD=0.0043, w_STIP=0.6311, w_CSHI=0.3425.", "question": "Assets: XLY, ADA-USD, STIP, CSHI\nAnnualized mean returns: XLY:0.3193, ADA-USD:1.7239, STIP:0.1021, CSHI:0.0450\nCovariance matrix (annualized):\n[[0.024919, 0.050951, 0.000289, 0.000329], [0.050951, 0.552672, 0.004617, 4e-06], [0.000289, 0.004617, 0.000346, -2.3e-05], [0.000329, 4e-06, -2.3e-05, 7.7e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0221, w_ADA-USD=0.0043, w_STIP=0.6311, w_CSHI=0.3425", "answer_numeric": 3.7726664154569516, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0221, w_ADA-USD=0.0043, w_STIP=0.6311, w_CSHI=0.3425\nPortfolio annualized return: 9.43%, volatility: 1.44%\nSharpe ratio: (0.0943 - 0.0400) / 0.0144 = 3.7727", "metadata": {"weights": {"XLY": 0.0221, "ADA-USD": 0.0043, "STIP": 0.6311, "CSHI": 0.3425}, "sharpe_ratio": 3.7727, "portfolio_return": 0.094323, "portfolio_vol": 0.014399, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250929_0372", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLY", "SOL-USD", "DBA", "EMB"], "decision_date": "2025-09-29", "context_summary": "4-asset optimization. Max-Sharpe: 3.847. Portfolio: return=23.58%, vol=5.09%. Weights: w_XLY=0.0942, w_SOL-USD=0.0000, w_DBA=0.0847, w_EMB=0.8211.", "question": "Assets: XLY, SOL-USD, DBA, EMB\nAnnualized mean returns: XLY:0.4494, SOL-USD:0.9362, DBA:0.2445, EMB:0.2103\nCovariance matrix (annualized):\n[[0.026864, 0.059464, 0.006317, 0.002865], [0.059464, 0.619816, 0.007323, 0.009786], [0.006317, 0.007323, 0.015468, 0.000975], [0.002865, 0.009786, 0.000975, 0.002315]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0942, w_SOL-USD=0.0000, w_DBA=0.0847, w_EMB=0.8211", "answer_numeric": 3.84664124200045, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0942, w_SOL-USD=0.0000, w_DBA=0.0847, w_EMB=0.8211\nPortfolio annualized return: 23.58%, volatility: 5.09%\nSharpe ratio: (0.2358 - 0.0400) / 0.0509 = 3.8466", "metadata": {"weights": {"XLY": 0.0942, "SOL-USD": 0.0, "DBA": 0.0847, "EMB": 0.8211}, "sharpe_ratio": 3.8466, "portfolio_return": 0.235754, "portfolio_vol": 0.05089, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250502_0374", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLE", "SOL-USD", "IEF", "BIL"], "decision_date": "2025-05-02", "context_summary": "4-asset optimization. Max-Sharpe: 1.207. Portfolio: return=4.73%, vol=0.60%. Weights: w_XLE=0.0000, w_SOL-USD=0.0067, w_IEF=0.0510, w_BIL=0.9423.", "question": "Assets: XLE, SOL-USD, IEF, BIL\nAnnualized mean returns: XLE:-0.2352, SOL-USD:0.8418, IEF:0.0678, BIL:0.0405\nCovariance matrix (annualized):\n[[0.101812, 0.130743, -0.001767, -2e-05], [0.130743, 0.747908, -0.016839, -0.000205], [-0.001767, -0.016839, 0.005071, -7e-06], [-2e-05, -0.000205, -7e-06, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0000, w_SOL-USD=0.0067, w_IEF=0.0510, w_BIL=0.9423", "answer_numeric": 1.2067891353514624, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_SOL-USD=0.0067, w_IEF=0.0510, w_BIL=0.9423\nPortfolio annualized return: 4.73%, volatility: 0.60%\nSharpe ratio: (0.0473 - 0.0400) / 0.0060 = 1.2068", "metadata": {"weights": {"XLE": 0.0, "SOL-USD": 0.0067, "IEF": 0.051, "BIL": 0.9423}, "sharpe_ratio": 1.2068, "portfolio_return": 0.047257, "portfolio_vol": 0.006013, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250509_0376", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "DOT-USD", "CPER", "SHV"], "decision_date": "2025-05-09", "context_summary": "4-asset optimization. Max-Sharpe: 2.455. Portfolio: return=147.93%, vol=58.62%. Weights: w_XLRE=0.0000, w_DOT-USD=1.0000, w_CPER=0.0000, w_SHV=0.0000.", "question": "Assets: XLRE, DOT-USD, CPER, SHV\nAnnualized mean returns: XLRE:-0.2079, DOT-USD:1.4793, CPER:0.0439, SHV:0.0386\nCovariance matrix (annualized):\n[[0.054184, 0.050318, 0.036752, -8e-06], [0.050318, 0.343648, 0.069159, 3.5e-05], [0.036752, 0.069159, 0.100683, -0.000133], [-8e-06, 3.5e-05, -0.000133, 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_XLRE=0.0000, w_DOT-USD=1.0000, w_CPER=0.0000, w_SHV=0.0000", "answer_numeric": 2.455165283514085, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_DOT-USD=1.0000, w_CPER=0.0000, w_SHV=0.0000\nPortfolio annualized return: 147.93%, volatility: 58.62%\nSharpe ratio: (1.4793 - 0.0400) / 0.5862 = 2.4552", "metadata": {"weights": {"XLRE": 0.0, "DOT-USD": 1.0, "CPER": 0.0, "SHV": 0.0}, "sharpe_ratio": 2.4552, "portfolio_return": 1.479254, "portfolio_vol": 0.586215, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251114_0379", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ETH-USD", "HAUZ", "LQD"], "decision_date": "2025-11-14", "context_summary": "4-asset optimization. Max-Sharpe: 0.831. Portfolio: return=14.35%, vol=12.45%. Weights: w_IVV=1.0000, w_ETH-USD=0.0000, w_HAUZ=0.0000, w_LQD=0.0000.", "question": "Assets: IVV, ETH-USD, HAUZ, LQD\nAnnualized mean returns: IVV:0.1435, ETH-USD:-3.2970, HAUZ:-0.1376, LQD:-0.0326\nCovariance matrix (annualized):\n[[0.015499, 0.042392, 0.005936, 0.000374], [0.042392, 0.335135, 0.024789, -0.000538], [0.005936, 0.024789, 0.010728, 0.002519], [0.000374, -0.000538, 0.002519, 0.00192]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ETH-USD=0.0000, w_HAUZ=0.0000, w_LQD=0.0000", "answer_numeric": 0.8314352121570127, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=1.0000, w_ETH-USD=0.0000, w_HAUZ=0.0000, w_LQD=0.0000\nPortfolio annualized return: 14.35%, volatility: 12.45%\nSharpe ratio: (0.1435 - 0.0400) / 0.1245 = 0.8314", "metadata": {"weights": {"IVV": 1.0, "ETH-USD": 0.0, "HAUZ": 0.0, "LQD": 0.0}, "sharpe_ratio": 0.8314, "portfolio_return": 0.143511, "portfolio_vol": 0.124497, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251202_0381", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "SOL-USD", "PALL", "SCHP"], "decision_date": "2025-12-02", "context_summary": "4-asset optimization. Max-Sharpe: 2.218. Portfolio: return=102.46%, vol=44.39%. Weights: w_EEM=0.0000, w_SOL-USD=0.0000, w_PALL=1.0000, w_SCHP=0.0000.", "question": "Assets: EEM, SOL-USD, PALL, SCHP\nAnnualized mean returns: EEM:0.0452, SOL-USD:-3.9389, PALL:1.0246, SCHP:0.0038\nCovariance matrix (annualized):\n[[0.030542, 0.075074, 0.034166, -0.000953], [0.075074, 0.547157, 0.097027, -0.003316], [0.034166, 0.097027, 0.197041, 0.001702], [-0.000953, -0.003316, 0.001702, 0.001047]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EEM=0.0000, w_SOL-USD=0.0000, w_PALL=1.0000, w_SCHP=0.0000", "answer_numeric": 2.218041346210511, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EEM=0.0000, w_SOL-USD=0.0000, w_PALL=1.0000, w_SCHP=0.0000\nPortfolio annualized return: 102.46%, volatility: 44.39%\nSharpe ratio: (1.0246 - 0.0400) / 0.4439 = 2.2180", "metadata": {"weights": {"EEM": 0.0, "SOL-USD": 0.0, "PALL": 1.0, "SCHP": 0.0}, "sharpe_ratio": 2.218, "portfolio_return": 1.024572, "portfolio_vol": 0.443893, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250312_0384", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "SOL-USD", "SGOV", "USO"], "decision_date": "2025-03-12", "context_summary": "4-asset optimization. Max-Sharpe: 1.184. Portfolio: return=4.24%, vol=0.20%. Weights: w_QUAL=0.0000, w_SOL-USD=0.0000, w_SGOV=1.0000, w_USO=0.0000.", "question": "Assets: QUAL, SOL-USD, SGOV, USO\nAnnualized mean returns: QUAL:-0.2033, SOL-USD:-1.6968, SGOV:0.0424, USO:-0.7338\nCovariance matrix (annualized):\n[[0.020234, 0.045414, -3e-05, 0.008209], [0.045414, 0.78307, 0.000169, 0.04698], [-3e-05, 0.000169, 4e-06, 0.000102], [0.008209, 0.04698, 0.000102, 0.056003]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0000, w_SOL-USD=0.0000, w_SGOV=1.0000, w_USO=0.0000", "answer_numeric": 1.1841397393920474, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_SOL-USD=0.0000, w_SGOV=1.0000, w_USO=0.0000\nPortfolio annualized return: 4.24%, volatility: 0.20%\nSharpe ratio: (0.0424 - 0.0400) / 0.0020 = 1.1841", "metadata": {"weights": {"QUAL": 0.0, "SOL-USD": 0.0, "SGOV": 1.0, "USO": 0.0}, "sharpe_ratio": 1.1841, "portfolio_return": 0.042384, "portfolio_vol": 0.002013, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250722_0387", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE", "LINK-USD", "VNQ", "DBC"], "decision_date": "2025-07-22", "context_summary": "4-asset optimization. Max-Sharpe: 4.123. Portfolio: return=35.84%, vol=7.72%. Weights: w_XLRE=0.0000, w_LINK-USD=0.0321, w_VNQ=0.5508, w_DBC=0.4171.", "question": "Assets: XLRE, LINK-USD, VNQ, DBC\nAnnualized mean returns: XLRE:0.2725, LINK-USD:0.7385, VNQ:0.3112, DBC:0.3915\nCovariance matrix (annualized):\n[[0.013283, 0.022902, 0.013119, -0.007879], [0.022902, 0.478054, 0.024751, -0.038094], [0.013119, 0.024751, 0.013396, -0.007417], [-0.007879, -0.038094, -0.007417, 0.028514]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_LINK-USD=0.0321, w_VNQ=0.5508, w_DBC=0.4171", "answer_numeric": 4.122827965098048, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_LINK-USD=0.0321, w_VNQ=0.5508, w_DBC=0.4171\nPortfolio annualized return: 35.84%, volatility: 7.72%\nSharpe ratio: (0.3584 - 0.0400) / 0.0772 = 4.1228", "metadata": {"weights": {"XLRE": 0.0, "LINK-USD": 0.0321, "VNQ": 0.5508, "DBC": 0.4171}, "sharpe_ratio": 4.1228, "portfolio_return": 0.358406, "portfolio_vol": 0.07723, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251125_0389", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "XRP-USD", "UNG", "VNQ"], "decision_date": "2025-11-25", "context_summary": "4-asset optimization. Max-Sharpe: 1.897. Portfolio: return=70.16%, vol=34.87%. Weights: w_SPY=0.2411, w_XRP-USD=0.0000, w_UNG=0.7589, w_VNQ=0.0000.", "question": "Assets: SPY, XRP-USD, UNG, VNQ\nAnnualized mean returns: SPY:0.0966, XRP-USD:-2.4117, UNG:0.8938, VNQ:-0.0118\nCovariance matrix (annualized):\n[[0.01997, 0.069092, 0.00736, 0.007165], [0.069092, 0.512719, -0.001449, 0.024977], [0.00736, -0.001449, 0.204394, 0.016059], [0.007165, 0.024977, 0.016059, 0.019384]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_SPY=0.2411, w_XRP-USD=0.0000, w_UNG=0.7589, w_VNQ=0.0000", "answer_numeric": 1.89737417300923, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.2411, w_XRP-USD=0.0000, w_UNG=0.7589, w_VNQ=0.0000\nPortfolio annualized return: 70.16%, volatility: 34.87%\nSharpe ratio: (0.7016 - 0.0400) / 0.3487 = 1.8974", "metadata": {"weights": {"SPY": 0.2411, "XRP-USD": 0.0, "UNG": 0.7589, "VNQ": 0.0}, "sharpe_ratio": 1.8974, "portfolio_return": 0.70156, "portfolio_vol": 0.348672, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20251119_0392", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "AVAX-USD", "EMB", "REZ"], "decision_date": "2025-11-19", "context_summary": "4-asset optimization. Max-Sharpe: 1.767. Portfolio: return=12.51%, vol=4.82%. Weights: w_VLUE=0.0917, w_AVAX-USD=0.0000, w_EMB=0.8847, w_REZ=0.0235.", "question": "Assets: VLUE, AVAX-USD, EMB, REZ\nAnnualized mean returns: VLUE:0.2356, AVAX-USD:-5.1973, EMB:0.1133, REZ:0.1375\nCovariance matrix (annualized):\n[[0.022696, 0.073074, 0.003528, 0.005386], [0.073074, 0.655008, 0.013468, 0.011786], [0.003528, 0.013468, 0.001842, 0.001901], [0.005386, 0.011786, 0.001901, 0.020489]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0917, w_AVAX-USD=0.0000, w_EMB=0.8847, w_REZ=0.0235", "answer_numeric": 1.7674805890305545, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0917, w_AVAX-USD=0.0000, w_EMB=0.8847, w_REZ=0.0235\nPortfolio annualized return: 12.51%, volatility: 4.82%\nSharpe ratio: (0.1251 - 0.0400) / 0.0482 = 1.7675", "metadata": {"weights": {"VLUE": 0.0917, "AVAX-USD": 0.0, "EMB": 0.8847, "REZ": 0.0235}, "sharpe_ratio": 1.7675, "portfolio_return": 0.125125, "portfolio_vol": 0.048162, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250715_0394", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLU", "DOT-USD", "PDBC", "REZ"], "decision_date": "2025-07-15", "context_summary": "4-asset optimization. Max-Sharpe: 2.016. Portfolio: return=23.95%, vol=9.90%. Weights: w_XLU=0.5101, w_DOT-USD=0.0000, w_PDBC=0.4899, w_REZ=0.0000.", "question": "Assets: XLU, DOT-USD, PDBC, REZ\nAnnualized mean returns: XLU:0.1860, DOT-USD:-0.6866, PDBC:0.2953, REZ:0.0885\nCovariance matrix (annualized):\n[[0.01906, -0.012397, -0.00522, 0.012621], [-0.012397, 0.380887, -0.02032, -0.000983], [-0.00522, -0.02032, 0.031024, -0.005816], [0.012621, -0.000983, -0.005816, 0.018366]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.5101, w_DOT-USD=0.0000, w_PDBC=0.4899, w_REZ=0.0000", "answer_numeric": 2.0158873414064367, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.5101, w_DOT-USD=0.0000, w_PDBC=0.4899, w_REZ=0.0000\nPortfolio annualized return: 23.95%, volatility: 9.90%\nSharpe ratio: (0.2395 - 0.0400) / 0.0990 = 2.0159", "metadata": {"weights": {"XLU": 0.5101, "DOT-USD": 0.0, "PDBC": 0.4899, "REZ": 0.0}, "sharpe_ratio": 2.0159, "portfolio_return": 0.23952, "portfolio_vol": 0.098974, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250718_0396", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE", "BNB-USD", "ICSH", "HAUZ"], "decision_date": "2025-07-18", "context_summary": "4-asset optimization. Max-Sharpe: 4.841. Portfolio: return=5.75%, vol=0.36%. Weights: w_XLRE=0.0000, w_BNB-USD=0.0020, w_ICSH=0.9898, w_HAUZ=0.0083.", "question": "Assets: XLRE, BNB-USD, ICSH, HAUZ\nAnnualized mean returns: XLRE:0.0128, BNB-USD:0.5725, ICSH:0.0543, HAUZ:0.3192\nCovariance matrix (annualized):\n[[0.017584, 0.001012, 0.000121, 0.008116], [0.001012, 0.079542, 0.000252, -0.000964], [0.000121, 0.000252, 9e-06, 0.000124], [0.008116, -0.000964, 0.000124, 0.010679]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_BNB-USD=0.0020, w_ICSH=0.9898, w_HAUZ=0.0083", "answer_numeric": 4.841286925636119, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_BNB-USD=0.0020, w_ICSH=0.9898, w_HAUZ=0.0083\nPortfolio annualized return: 5.75%, volatility: 0.36%\nSharpe ratio: (0.0575 - 0.0400) / 0.0036 = 4.8413", "metadata": {"weights": {"XLRE": 0.0, "BNB-USD": 0.002, "ICSH": 0.9898, "HAUZ": 0.0083}, "sharpe_ratio": 4.8413, "portfolio_return": 0.057526, "portfolio_vol": 0.00362, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250820_0399", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLK", "ETH-USD", "REZ", "IEF"], "decision_date": "2025-08-20", "context_summary": "4-asset optimization. Max-Sharpe: 4.653. Portfolio: return=58.55%, vol=11.72%. Weights: w_XLK=0.2689, w_ETH-USD=0.1447, w_REZ=0.0000, w_IEF=0.5864.", "question": "Assets: XLK, ETH-USD, REZ, IEF\nAnnualized mean returns: XLK:0.5265, ETH-USD:2.6999, REZ:0.0687, IEF:0.0907\nCovariance matrix (annualized):\n[[0.020623, 0.052016, -0.004195, -0.001386], [0.052016, 0.365945, 0.011605, 0.000139], [-0.004195, 0.011605, 0.022994, 0.003768], [-0.001386, 0.000139, 0.003768, 0.00278]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.2689, w_ETH-USD=0.1447, w_REZ=0.0000, w_IEF=0.5864", "answer_numeric": 4.652531686866235, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.2689, w_ETH-USD=0.1447, w_REZ=0.0000, w_IEF=0.5864\nPortfolio annualized return: 58.55%, volatility: 11.72%\nSharpe ratio: (0.5855 - 0.0400) / 0.1172 = 4.6525", "metadata": {"weights": {"XLK": 0.2689, "ETH-USD": 0.1447, "REZ": 0.0, "IEF": 0.5864}, "sharpe_ratio": 4.6525, "portfolio_return": 0.585505, "portfolio_vol": 0.117249, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250805_0401", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF", "BTC-USD", "HYG", "SCHH"], "decision_date": "2025-08-05", "context_summary": "4-asset optimization. Max-Sharpe: 3.780. Portfolio: return=16.78%, vol=3.38%. Weights: w_XLF=0.0000, w_BTC-USD=0.0581, w_HYG=0.9419, w_SCHH=0.0000.", "question": "Assets: XLF, BTC-USD, HYG, SCHH\nAnnualized mean returns: XLF:0.1764, BTC-USD:0.6820, HYG:0.1361, SCHH:0.0053\nCovariance matrix (annualized):\n[[0.019162, 0.012966, 0.002543, 0.009551], [0.012966, 0.077836, 0.001296, 0.014061], [0.002543, 0.001296, 0.000833, 0.002128], [0.009551, 0.014061, 0.002128, 0.019491]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_BTC-USD=0.0581, w_HYG=0.9419, w_SCHH=0.0000", "answer_numeric": 3.779603870150997, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_BTC-USD=0.0581, w_HYG=0.9419, w_SCHH=0.0000\nPortfolio annualized return: 16.78%, volatility: 3.38%\nSharpe ratio: (0.1678 - 0.0400) / 0.0338 = 3.7796", "metadata": {"weights": {"XLF": 0.0, "BTC-USD": 0.0581, "HYG": 0.9419, "SCHH": 0.0}, "sharpe_ratio": 3.7796, "portfolio_return": 0.16781, "portfolio_vol": 0.033816, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20250106_0405", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ETH-USD", "MORT", "TLH"], "decision_date": "2025-01-06", "context_summary": "4-asset optimization. Max-Sharpe: 2.526. Portfolio: return=168.80%, vol=65.24%. Weights: w_ACWI=0.0000, w_ETH-USD=1.0000, w_MORT=0.0000, w_TLH=0.0000.", "question": "Assets: ACWI, ETH-USD, MORT, TLH\nAnnualized mean returns: ACWI:-0.0398, ETH-USD:1.6880, MORT:0.0816, TLH:-0.0992\nCovariance matrix (annualized):\n[[0.013074, 0.037277, 0.013097, 0.004594], [0.037277, 0.425582, 0.054132, 0.025241], [0.013097, 0.054132, 0.027895, 0.008701], [0.004594, 0.025241, 0.008701, 0.010589]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ETH-USD=1.0000, w_MORT=0.0000, w_TLH=0.0000", "answer_numeric": 2.526200643994451, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.0000, w_ETH-USD=1.0000, w_MORT=0.0000, w_TLH=0.0000\nPortfolio annualized return: 168.80%, volatility: 65.24%\nSharpe ratio: (1.6880 - 0.0400) / 0.6524 = 2.5262", "metadata": {"weights": {"ACWI": 0.0, "ETH-USD": 1.0, "MORT": 0.0, "TLH": 0.0}, "sharpe_ratio": 2.5262, "portfolio_return": 1.688009, "portfolio_vol": 0.652367, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251222_0408", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "AVAX-USD", "BIL", "UNG"], "decision_date": "2025-12-22", "context_summary": "4-asset optimization. Max-Sharpe: -0.589. Portfolio: return=-27.84%, vol=54.11%. Weights: w_FXI=0.0000, w_AVAX-USD=0.0000, w_BIL=0.0000, w_UNG=1.0000.", "question": "Assets: FXI, AVAX-USD, BIL, UNG\nAnnualized mean returns: FXI:-0.1125, AVAX-USD:-2.6256, BIL:0.0395, UNG:-0.2784\nCovariance matrix (annualized):\n[[0.024724, 0.006806, 2e-06, 0.008516], [0.006806, 0.605837, 0.000456, -0.101239], [2e-06, 0.000456, 4e-06, -0.00014], [0.008516, -0.101239, -0.00014, 0.292762]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0000, w_AVAX-USD=0.0000, w_BIL=0.0000, w_UNG=1.0000", "answer_numeric": -0.588535473032131, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_AVAX-USD=0.0000, w_BIL=0.0000, w_UNG=1.0000\nPortfolio annualized return: -27.84%, volatility: 54.11%\nSharpe ratio: (-0.2784 - 0.0400) / 0.5411 = -0.5885", "metadata": {"weights": {"FXI": 0.0, "AVAX-USD": 0.0, "BIL": 0.0, "UNG": 1.0}, "sharpe_ratio": -0.5885, "portfolio_return": -0.278442, "portfolio_vol": 0.541074, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251217_0410", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "ETH-USD", "CPER", "SGOV"], "decision_date": "2025-12-17", "context_summary": "4-asset optimization. Max-Sharpe: 1.804. Portfolio: return=42.17%, vol=21.15%. Weights: w_VEA=0.0000, w_ETH-USD=0.0000, w_CPER=1.0000, w_SGOV=0.0000.", "question": "Assets: VEA, ETH-USD, CPER, SGOV\nAnnualized mean returns: VEA:0.1747, ETH-USD:-2.3013, CPER:0.4217, SGOV:0.0386\nCovariance matrix (annualized):\n[[0.013604, 0.027685, 0.016896, 7e-06], [0.027685, 0.366734, 0.038822, -0.000113], [0.016896, 0.038822, 0.04475, -2.8e-05], [7e-06, -0.000113, -2.8e-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_VEA=0.0000, w_ETH-USD=0.0000, w_CPER=1.0000, w_SGOV=0.0000", "answer_numeric": 1.8042206405848105, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_ETH-USD=0.0000, w_CPER=1.0000, w_SGOV=0.0000\nPortfolio annualized return: 42.17%, volatility: 21.15%\nSharpe ratio: (0.4217 - 0.0400) / 0.2115 = 1.8042", "metadata": {"weights": {"VEA": 0.0, "ETH-USD": 0.0, "CPER": 1.0, "SGOV": 0.0}, "sharpe_ratio": 1.8042, "portfolio_return": 0.421667, "portfolio_vol": 0.211541, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251117_0412", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "LINK-USD", "DBB", "ITB"], "decision_date": "2025-11-17", "context_summary": "4-asset optimization. Max-Sharpe: 2.584. Portfolio: return=37.65%, vol=13.02%. Weights: w_EFA=0.0706, w_LINK-USD=0.0000, w_DBB=0.9294, w_ITB=0.0000.", "question": "Assets: EFA, LINK-USD, DBB, ITB\nAnnualized mean returns: EFA:0.1441, LINK-USD:-3.8668, DBB:0.3941, ITB:-0.7489\nCovariance matrix (annualized):\n[[0.010617, 0.050996, 0.004835, 0.010172], [0.050996, 0.722378, 0.052415, 0.048994], [0.004835, 0.052415, 0.018829, -0.003208], [0.010172, 0.048994, -0.003208, 0.040914]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0706, w_LINK-USD=0.0000, w_DBB=0.9294, w_ITB=0.0000", "answer_numeric": 2.5842344225930876, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0706, w_LINK-USD=0.0000, w_DBB=0.9294, w_ITB=0.0000\nPortfolio annualized return: 37.65%, volatility: 13.02%\nSharpe ratio: (0.3765 - 0.0400) / 0.1302 = 2.5842", "metadata": {"weights": {"EFA": 0.0706, "LINK-USD": 0.0, "DBB": 0.9294, "ITB": 0.0}, "sharpe_ratio": 2.5842, "portfolio_return": 0.376473, "portfolio_vol": 0.130202, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250410_0415", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["FXI", "LINK-USD", "HYG", "SGOV"], "decision_date": "2025-04-10", "context_summary": "4-asset optimization. Max-Sharpe: 0.638. Portfolio: return=4.13%, vol=0.20%. Weights: w_FXI=0.0016, w_LINK-USD=0.0000, w_HYG=0.0000, w_SGOV=0.9984.", "question": "Assets: FXI, LINK-USD, HYG, SGOV\nAnnualized mean returns: FXI:0.1105, LINK-USD:-0.6974, HYG:-0.1313, SGOV:0.0411\nCovariance matrix (annualized):\n[[0.117531, 0.197528, 0.013139, 3.2e-05], [0.197528, 0.901705, 0.023827, -3.7e-05], [0.013139, 0.023827, 0.005412, -8e-06], [3.2e-05, -3.7e-05, -8e-06, 3e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.0016, w_LINK-USD=0.0000, w_HYG=0.0000, w_SGOV=0.9984", "answer_numeric": 0.6381429722131119, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0016, w_LINK-USD=0.0000, w_HYG=0.0000, w_SGOV=0.9984\nPortfolio annualized return: 4.13%, volatility: 0.20%\nSharpe ratio: (0.0413 - 0.0400) / 0.0020 = 0.6381", "metadata": {"weights": {"FXI": 0.0016, "LINK-USD": 0.0, "HYG": 0.0, "SGOV": 0.9984}, "sharpe_ratio": 0.6381, "portfolio_return": 0.041252, "portfolio_vol": 0.001963, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251010_0418", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "ADA-USD", "INDS", "PPLT"], "decision_date": "2025-10-10", "context_summary": "4-asset optimization. Max-Sharpe: 5.503. Portfolio: return=85.84%, vol=14.87%. Weights: w_IWM=0.4998, w_ADA-USD=0.0000, w_INDS=0.0558, w_PPLT=0.4445.", "question": "Assets: IWM, ADA-USD, INDS, PPLT\nAnnualized mean returns: IWM:0.6213, ADA-USD:0.8041, INDS:0.2819, PPLT:1.1975\nCovariance matrix (annualized):\n[[0.028658, 0.059755, 0.013973, 0.001366], [0.059755, 0.450247, 0.019735, 0.023182], [0.013973, 0.019735, 0.023908, -0.004005], [0.001366, 0.023182, -0.004005, 0.069351]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.4998, w_ADA-USD=0.0000, w_INDS=0.0558, w_PPLT=0.4445", "answer_numeric": 5.503045458402136, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.4998, w_ADA-USD=0.0000, w_INDS=0.0558, w_PPLT=0.4445\nPortfolio annualized return: 85.84%, volatility: 14.87%\nSharpe ratio: (0.8584 - 0.0400) / 0.1487 = 5.5030", "metadata": {"weights": {"IWM": 0.4998, "ADA-USD": 0.0, "INDS": 0.0558, "PPLT": 0.4445}, "sharpe_ratio": 5.503, "portfolio_return": 0.858447, "portfolio_vol": 0.148726, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250808_0421", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLV", "SOL-USD", "PALL", "SGOV"], "decision_date": "2025-08-08", "context_summary": "4-asset optimization. Max-Sharpe: 1.949. Portfolio: return=4.81%, vol=0.41%. Weights: w_XLV=0.0000, w_SOL-USD=0.0030, w_PALL=0.0074, w_SGOV=0.9896.", "question": "Assets: XLV, SOL-USD, PALL, SGOV\nAnnualized mean returns: XLV:-0.2161, SOL-USD:0.6742, PALL:0.6430, SGOV:0.0417\nCovariance matrix (annualized):\n[[0.026051, 0.004345, -0.002155, 3.3e-05], [0.004345, 0.381227, 0.055145, -0.000197], [-0.002155, 0.055145, 0.153451, -2.3e-05], [3.3e-05, -0.000197, -2.3e-05, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_SOL-USD=0.0030, w_PALL=0.0074, w_SGOV=0.9896", "answer_numeric": 1.9493921172351028, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_SOL-USD=0.0030, w_PALL=0.0074, w_SGOV=0.9896\nPortfolio annualized return: 4.81%, volatility: 0.41%\nSharpe ratio: (0.0481 - 0.0400) / 0.0041 = 1.9494", "metadata": {"weights": {"XLV": 0.0, "SOL-USD": 0.003, "PALL": 0.0074, "SGOV": 0.9896}, "sharpe_ratio": 1.9494, "portfolio_return": 0.048056, "portfolio_vol": 0.004133, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251120_0423", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "XRP-USD", "SGOV", "PALL"], "decision_date": "2025-11-20", "context_summary": "4-asset optimization. Max-Sharpe: 5.128. Portfolio: return=72.09%, vol=13.28%. Weights: w_XLV=0.8299, w_XRP-USD=0.0000, w_SGOV=0.0000, w_PALL=0.1701.", "question": "Assets: XLV, XRP-USD, SGOV, PALL\nAnnualized mean returns: XLV:0.6007, XRP-USD:-2.8786, SGOV:0.0370, PALL:1.3073\nCovariance matrix (annualized):\n[[0.017781, 0.029424, -2.8e-05, -0.001377], [0.029424, 0.466098, -0.000276, 0.041542], [-2.8e-05, -0.000276, 3e-06, -0.000214], [-0.001377, 0.041542, -0.000214, 0.199692]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.8299, w_XRP-USD=0.0000, w_SGOV=0.0000, w_PALL=0.1701", "answer_numeric": 5.127557178393195, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.8299, w_XRP-USD=0.0000, w_SGOV=0.0000, w_PALL=0.1701\nPortfolio annualized return: 72.09%, volatility: 13.28%\nSharpe ratio: (0.7209 - 0.0400) / 0.1328 = 5.1276", "metadata": {"weights": {"XLV": 0.8299, "XRP-USD": 0.0, "SGOV": 0.0, "PALL": 0.1701}, "sharpe_ratio": 5.1276, "portfolio_return": 0.720928, "portfolio_vol": 0.132798, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250919_0426", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ", "AVAX-USD", "IYR", "SLV"], "decision_date": "2025-09-19", "context_summary": "4-asset optimization. Max-Sharpe: 3.893. Portfolio: return=60.48%, vol=14.51%. Weights: w_EWJ=0.6942, w_AVAX-USD=0.0008, w_IYR=0.0000, w_SLV=0.3051.", "question": "Assets: EWJ, AVAX-USD, IYR, SLV\nAnnualized mean returns: EWJ:0.6200, AVAX-USD:1.4042, IYR:0.1009, SLV:0.5681\nCovariance matrix (annualized):\n[[0.027117, 0.042423, 0.006473, 0.009051], [0.042423, 0.676975, 0.022185, 0.068466], [0.006473, 0.022185, 0.021201, 0.007152], [0.009051, 0.068466, 0.007152, 0.043754]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.6942, w_AVAX-USD=0.0008, w_IYR=0.0000, w_SLV=0.3051", "answer_numeric": 3.8927923767092234, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.6942, w_AVAX-USD=0.0008, w_IYR=0.0000, w_SLV=0.3051\nPortfolio annualized return: 60.48%, volatility: 14.51%\nSharpe ratio: (0.6048 - 0.0400) / 0.1451 = 3.8928", "metadata": {"weights": {"EWJ": 0.6942, "AVAX-USD": 0.0008, "IYR": 0.0, "SLV": 0.3051}, "sharpe_ratio": 3.8928, "portfolio_return": 0.604777, "portfolio_vol": 0.145083, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250623_0429", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BNB-USD", "GLD", "BIL"], "decision_date": "2025-06-23", "context_summary": "4-asset optimization. Max-Sharpe: -1.364. Portfolio: return=-36.98%, vol=30.04%. Weights: w_^VIX=0.2500, w_BNB-USD=0.2500, w_GLD=0.2500, w_BIL=0.2500.", "question": "Assets: ^VIX, BNB-USD, GLD, BIL\nAnnualized mean returns: ^VIX:-2.0279, BNB-USD:0.3941, GLD:0.1126, BIL:0.0418\nCovariance matrix (annualized):\n[[1.188792, -0.067481, 0.125126, 0.000412], [-0.067481, 0.098024, -0.003555, -2.3e-05], [0.125126, -0.003555, 0.047914, 2.9e-05], [0.000412, -2.3e-05, 2.9e-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_^VIX=0.2500, w_BNB-USD=0.2500, w_GLD=0.2500, w_BIL=0.2500", "answer_numeric": -1.3643123713689194, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.2500, w_BNB-USD=0.2500, w_GLD=0.2500, w_BIL=0.2500\nPortfolio annualized return: -36.98%, volatility: 30.04%\nSharpe ratio: (-0.3698 - 0.0400) / 0.3004 = -1.3643", "metadata": {"weights": {"^VIX": 0.25, "BNB-USD": 0.25, "GLD": 0.25, "BIL": 0.25}, "sharpe_ratio": -1.3643, "portfolio_return": -0.369826, "portfolio_vol": 0.30039, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251230_0431", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "XRP-USD", "SGOV", "IAU"], "decision_date": "2025-12-30", "context_summary": "4-asset optimization. Max-Sharpe: 3.584. Portfolio: return=6.21%, vol=0.62%. Weights: w_^VIX=0.0010, w_XRP-USD=0.0000, w_SGOV=0.9585, w_IAU=0.0405.", "question": "Assets: ^VIX, XRP-USD, SGOV, IAU\nAnnualized mean returns: ^VIX:-1.1004, XRP-USD:-1.7897, SGOV:0.0410, IAU:0.5894\nCovariance matrix (annualized):\n[[1.221515, -0.273426, -0.000395, -0.068345], [-0.273426, 0.398763, 6.3e-05, 0.031864], [-0.000395, 6.3e-05, 3e-06, -2.4e-05], [-0.068345, 0.031864, -2.4e-05, 0.025557]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0010, w_XRP-USD=0.0000, w_SGOV=0.9585, w_IAU=0.0405", "answer_numeric": 3.5844184971906006, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0010, w_XRP-USD=0.0000, w_SGOV=0.9585, w_IAU=0.0405\nPortfolio annualized return: 6.21%, volatility: 0.62%\nSharpe ratio: (0.0621 - 0.0400) / 0.0062 = 3.5844", "metadata": {"weights": {"^VIX": 0.001, "XRP-USD": 0.0, "SGOV": 0.9585, "IAU": 0.0405}, "sharpe_ratio": 3.5844, "portfolio_return": 0.062135, "portfolio_vol": 0.006175, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250224_0433", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BNB-USD", "SHY", "CSHI"], "decision_date": "2025-02-24", "context_summary": "4-asset optimization. Max-Sharpe: 3.946. Portfolio: return=8.43%, vol=1.12%. Weights: w_EFA=0.0795, w_BNB-USD=0.0069, w_SHY=0.1672, w_CSHI=0.7464.", "question": "Assets: EFA, BNB-USD, SHY, CSHI\nAnnualized mean returns: EFA:0.4788, BNB-USD:0.2027, SHY:0.0601, CSHI:0.0466\nCovariance matrix (annualized):\n[[0.014671, -0.00338, 0.000525, 2.3e-05], [-0.00338, 0.165061, -0.001374, -0.00023], [0.000525, -0.001374, 0.000181, -7e-06], [2.3e-05, -0.00023, -7e-06, 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_EFA=0.0795, w_BNB-USD=0.0069, w_SHY=0.1672, w_CSHI=0.7464", "answer_numeric": 3.9463621236855504, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0795, w_BNB-USD=0.0069, w_SHY=0.1672, w_CSHI=0.7464\nPortfolio annualized return: 8.43%, volatility: 1.12%\nSharpe ratio: (0.0843 - 0.0400) / 0.0112 = 3.9464", "metadata": {"weights": {"EFA": 0.0795, "BNB-USD": 0.0069, "SHY": 0.1672, "CSHI": 0.7464}, "sharpe_ratio": 3.9464, "portfolio_return": 0.084298, "portfolio_vol": 0.011225, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250714_0435", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLK", "DOT-USD", "SCHP", "ITB"], "decision_date": "2025-07-14", "context_summary": "4-asset optimization. Max-Sharpe: 3.868. Portfolio: return=36.57%, vol=8.42%. Weights: w_XLK=0.5461, w_DOT-USD=0.0000, w_SCHP=0.4539, w_ITB=0.0000.", "question": "Assets: XLK, DOT-USD, SCHP, ITB\nAnnualized mean returns: XLK:0.5839, DOT-USD:-0.9085, SCHP:0.1031, ITB:0.4565\nCovariance matrix (annualized):\n[[0.020757, 0.026063, 0.001112, 0.015928], [0.026063, 0.391441, -0.00869, 0.039955], [0.001112, -0.00869, 0.00169, 0.004356], [0.015928, 0.039955, 0.004356, 0.081841]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLK=0.5461, w_DOT-USD=0.0000, w_SCHP=0.4539, w_ITB=0.0000", "answer_numeric": 3.868143751282459, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLK=0.5461, w_DOT-USD=0.0000, w_SCHP=0.4539, w_ITB=0.0000\nPortfolio annualized return: 36.57%, volatility: 8.42%\nSharpe ratio: (0.3657 - 0.0400) / 0.0842 = 3.8681", "metadata": {"weights": {"XLK": 0.5461, "DOT-USD": 0.0, "SCHP": 0.4539, "ITB": 0.0}, "sharpe_ratio": 3.8681, "portfolio_return": 0.365711, "portfolio_vol": 0.084203, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251203_0437", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "ETH-USD", "BNDX", "MORT"], "decision_date": "2025-12-03", "context_summary": "4-asset optimization. Max-Sharpe: 0.563. Portfolio: return=12.67%, vol=15.41%. Weights: w_XLP=0.0000, w_ETH-USD=0.0000, w_BNDX=0.0000, w_MORT=1.0000.", "question": "Assets: XLP, ETH-USD, BNDX, MORT\nAnnualized mean returns: XLP:0.0580, ETH-USD:-3.6730, BNDX:0.0267, MORT:0.1267\nCovariance matrix (annualized):\n[[0.01725, -0.008268, 0.000911, 0.012027], [-0.008268, 0.390734, -0.001366, 0.015601], [0.000911, -0.001366, 0.000645, 0.001086], [0.012027, 0.015601, 0.001086, 0.023739]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_ETH-USD=0.0000, w_BNDX=0.0000, w_MORT=1.0000", "answer_numeric": 0.5626162994770892, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_ETH-USD=0.0000, w_BNDX=0.0000, w_MORT=1.0000\nPortfolio annualized return: 12.67%, volatility: 15.41%\nSharpe ratio: (0.1267 - 0.0400) / 0.1541 = 0.5626", "metadata": {"weights": {"XLP": 0.0, "ETH-USD": 0.0, "BNDX": 0.0, "MORT": 1.0}, "sharpe_ratio": 0.5626, "portfolio_return": 0.126685, "portfolio_vol": 0.154075, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250612_0440", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BNB-USD", "CORN", "SCHP"], "decision_date": "2025-06-12", "context_summary": "4-asset optimization. Max-Sharpe: 3.739. Portfolio: return=41.93%, vol=10.14%. Weights: w_XLF=0.4642, w_BNB-USD=0.1811, w_CORN=0.0000, w_SCHP=0.3547.", "question": "Assets: XLF, BNB-USD, CORN, SCHP\nAnnualized mean returns: XLF:0.5453, BNB-USD:0.7613, CORN:-0.4195, SCHP:0.0795\nCovariance matrix (annualized):\n[[0.027041, 0.003733, -0.005284, 0.001353], [0.003733, 0.104262, -0.004236, -0.002948], [-0.005284, -0.004236, 0.018737, -0.002169], [0.001353, -0.002948, -0.002169, 0.002758]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.4642, w_BNB-USD=0.1811, w_CORN=0.0000, w_SCHP=0.3547", "answer_numeric": 3.7388856233139833, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.4642, w_BNB-USD=0.1811, w_CORN=0.0000, w_SCHP=0.3547\nPortfolio annualized return: 41.93%, volatility: 10.14%\nSharpe ratio: (0.4193 - 0.0400) / 0.1014 = 3.7389", "metadata": {"weights": {"XLF": 0.4642, "BNB-USD": 0.1811, "CORN": 0.0, "SCHP": 0.3547}, "sharpe_ratio": 3.7389, "portfolio_return": 0.419252, "portfolio_vol": 0.101435, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250814_0442", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["USMV", "BTC-USD", "JNK", "INDS"], "decision_date": "2025-08-14", "context_summary": "4-asset optimization. Max-Sharpe: 4.649. Portfolio: return=19.25%, vol=3.28%. Weights: w_USMV=0.0000, w_BTC-USD=0.0496, w_JNK=0.9504, w_INDS=0.0000.", "question": "Assets: USMV, BTC-USD, JNK, INDS\nAnnualized mean returns: USMV:0.0584, BTC-USD:0.7646, JNK:0.1626, INDS:-0.0831\nCovariance matrix (annualized):\n[[0.009115, 0.006067, 0.001676, 0.008524], [0.006067, 0.063226, 0.002077, 0.013764], [0.001676, 0.002077, 0.000802, 0.00176], [0.008524, 0.013764, 0.00176, 0.025834]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0000, w_BTC-USD=0.0496, w_JNK=0.9504, w_INDS=0.0000", "answer_numeric": 4.6492912259587005, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0000, w_BTC-USD=0.0496, w_JNK=0.9504, w_INDS=0.0000\nPortfolio annualized return: 19.25%, volatility: 3.28%\nSharpe ratio: (0.1925 - 0.0400) / 0.0328 = 4.6493", "metadata": {"weights": {"USMV": 0.0, "BTC-USD": 0.0496, "JNK": 0.9504, "INDS": 0.0}, "sharpe_ratio": 4.6493, "portfolio_return": 0.192523, "portfolio_vol": 0.032806, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250618_0445", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "AVAX-USD", "ICSH", "GLD"], "decision_date": "2025-06-18", "context_summary": "4-asset optimization. Max-Sharpe: 1.198. Portfolio: return=5.32%, vol=1.10%. Weights: w_XLRE=0.0586, w_AVAX-USD=0.0000, w_ICSH=0.9318, w_GLD=0.0096.", "question": "Assets: XLRE, AVAX-USD, ICSH, GLD\nAnnualized mean returns: XLRE:0.1959, AVAX-USD:-0.3034, ICSH:0.0441, GLD:0.0603\nCovariance matrix (annualized):\n[[0.021079, -0.009172, 0.000284, -0.007202], [-0.009172, 0.559047, -0.001001, -0.048071], [0.000284, -0.001001, 2.2e-05, 8.2e-05], [-0.007202, -0.048071, 8.2e-05, 0.05518]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0586, w_AVAX-USD=0.0000, w_ICSH=0.9318, w_GLD=0.0096", "answer_numeric": 1.198060429106851, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0586, w_AVAX-USD=0.0000, w_ICSH=0.9318, w_GLD=0.0096\nPortfolio annualized return: 5.32%, volatility: 1.10%\nSharpe ratio: (0.0532 - 0.0400) / 0.0110 = 1.1981", "metadata": {"weights": {"XLRE": 0.0586, "AVAX-USD": 0.0, "ICSH": 0.9318, "GLD": 0.0096}, "sharpe_ratio": 1.1981, "portfolio_return": 0.053167, "portfolio_vol": 0.01099, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250513_0447", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "AVAX-USD", "BIL", "REZ"], "decision_date": "2025-05-13", "context_summary": "4-asset optimization. Max-Sharpe: 4.027. Portfolio: return=8.94%, vol=1.23%. Weights: w_EWJ=0.0000, w_AVAX-USD=0.0159, w_BIL=0.9841, w_REZ=0.0000.", "question": "Assets: EWJ, AVAX-USD, BIL, REZ\nAnnualized mean returns: EWJ:0.2542, AVAX-USD:3.1118, BIL:0.0405, REZ:0.0558\nCovariance matrix (annualized):\n[[0.048641, 0.059861, 1e-06, 0.028012], [0.059861, 0.599099, -0.000189, 0.032472], [1e-06, -0.000189, 5e-06, -5.4e-05], [0.028012, 0.032472, -5.4e-05, 0.049746]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_AVAX-USD=0.0159, w_BIL=0.9841, w_REZ=0.0000", "answer_numeric": 4.027280944262467, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_AVAX-USD=0.0159, w_BIL=0.9841, w_REZ=0.0000\nPortfolio annualized return: 8.94%, volatility: 1.23%\nSharpe ratio: (0.0894 - 0.0400) / 0.0123 = 4.0273", "metadata": {"weights": {"EWJ": 0.0, "AVAX-USD": 0.0159, "BIL": 0.9841, "REZ": 0.0}, "sharpe_ratio": 4.0273, "portfolio_return": 0.089416, "portfolio_vol": 0.01227, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250429_0450", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VLUE", "XRP-USD", "TIP", "DBB"], "decision_date": "2025-04-29", "context_summary": "4-asset optimization. Max-Sharpe: 2.421. Portfolio: return=10.63%, vol=2.74%. Weights: w_VLUE=0.0000, w_XRP-USD=0.0000, w_TIP=1.0000, w_DBB=0.0000.", "question": "Assets: VLUE, XRP-USD, TIP, DBB\nAnnualized mean returns: VLUE:-0.4430, XRP-USD:-0.3046, TIP:0.1063, DBB:-0.2176\nCovariance matrix (annualized):\n[[0.060948, 0.059692, 0.000453, 0.029235], [0.059692, 0.723742, -0.002714, 0.063], [0.000453, -0.002714, 0.00075, -0.000829], [0.029235, 0.063, -0.000829, 0.037902]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.0000, w_XRP-USD=0.0000, w_TIP=1.0000, w_DBB=0.0000", "answer_numeric": 2.4214925693059737, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.0000, w_XRP-USD=0.0000, w_TIP=1.0000, w_DBB=0.0000\nPortfolio annualized return: 10.63%, volatility: 2.74%\nSharpe ratio: (0.1063 - 0.0400) / 0.0274 = 2.4215", "metadata": {"weights": {"VLUE": 0.0, "XRP-USD": 0.0, "TIP": 1.0, "DBB": 0.0}, "sharpe_ratio": 2.4215, "portfolio_return": 0.106304, "portfolio_vol": 0.027382, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250922_0454", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "BNB-USD", "HAUZ", "JNK"], "decision_date": "2025-09-22", "context_summary": "4-asset optimization. Max-Sharpe: 3.020. Portfolio: return=16.23%, vol=4.05%. Weights: w_QUAL=0.0000, w_BNB-USD=0.0406, w_HAUZ=0.0000, w_JNK=0.9594.", "question": "Assets: QUAL, BNB-USD, HAUZ, JNK\nAnnualized mean returns: QUAL:0.2246, BNB-USD:0.8816, HAUZ:0.1637, JNK:0.1319\nCovariance matrix (annualized):\n[[0.009815, 0.018676, 0.005419, 0.002339], [0.018676, 0.149661, 0.016561, 0.005429], [0.005419, 0.016561, 0.012193, 0.002171], [0.002339, 0.005429, 0.002171, 0.001055]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QUAL=0.0000, w_BNB-USD=0.0406, w_HAUZ=0.0000, w_JNK=0.9594", "answer_numeric": 3.0200766030999624, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_BNB-USD=0.0406, w_HAUZ=0.0000, w_JNK=0.9594\nPortfolio annualized return: 16.23%, volatility: 4.05%\nSharpe ratio: (0.1623 - 0.0400) / 0.0405 = 3.0201", "metadata": {"weights": {"QUAL": 0.0, "BNB-USD": 0.0406, "HAUZ": 0.0, "JNK": 0.9594}, "sharpe_ratio": 3.0201, "portfolio_return": 0.162342, "portfolio_vol": 0.040509, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251208_0456", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "LINK-USD", "TIP", "DBB"], "decision_date": "2025-12-08", "context_summary": "4-asset optimization. Max-Sharpe: 2.590. Portfolio: return=41.24%, vol=14.38%. Weights: w_XLY=0.0000, w_LINK-USD=0.0000, w_TIP=0.0000, w_DBB=1.0000.", "question": "Assets: XLY, LINK-USD, TIP, DBB\nAnnualized mean returns: XLY:0.0790, LINK-USD:-3.7997, TIP:0.0127, DBB:0.4124\nCovariance matrix (annualized):\n[[0.044684, 0.068814, 0.000185, 0.016274], [0.068814, 0.828191, -0.00123, 0.061282], [0.000185, -0.00123, 0.000173, 5.9e-05], [0.016274, 0.061282, 5.9e-05, 0.020668]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0000, w_LINK-USD=0.0000, w_TIP=0.0000, w_DBB=1.0000", "answer_numeric": 2.590232762581389, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_LINK-USD=0.0000, w_TIP=0.0000, w_DBB=1.0000\nPortfolio annualized return: 41.24%, volatility: 14.38%\nSharpe ratio: (0.4124 - 0.0400) / 0.1438 = 2.5902", "metadata": {"weights": {"XLY": 0.0, "LINK-USD": 0.0, "TIP": 0.0, "DBB": 1.0}, "sharpe_ratio": 2.5902, "portfolio_return": 0.412382, "portfolio_vol": 0.143764, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250912_0459", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ", "ADA-USD", "ICSH", "EMB"], "decision_date": "2025-09-12", "context_summary": "4-asset optimization. Max-Sharpe: 6.090. Portfolio: return=9.98%, vol=0.98%. Weights: w_EWJ=0.0089, w_ADA-USD=0.0000, w_ICSH=0.8157, w_EMB=0.1754.", "question": "Assets: EWJ, ADA-USD, ICSH, EMB\nAnnualized mean returns: EWJ:0.5631, ADA-USD:0.9649, ICSH:0.0542, EMB:0.2882\nCovariance matrix (annualized):\n[[0.027938, 0.038926, 7.2e-05, 0.00305], [0.038926, 0.481285, 5.3e-05, 0.010831], [7.2e-05, 5.3e-05, 2.1e-05, 2.8e-05], [0.00305, 0.010831, 2.8e-05, 0.001994]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0089, w_ADA-USD=0.0000, w_ICSH=0.8157, w_EMB=0.1754", "answer_numeric": 6.090002597794854, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0089, w_ADA-USD=0.0000, w_ICSH=0.8157, w_EMB=0.1754\nPortfolio annualized return: 9.98%, volatility: 0.98%\nSharpe ratio: (0.0998 - 0.0400) / 0.0098 = 6.0900", "metadata": {"weights": {"EWJ": 0.0089, "ADA-USD": 0.0, "ICSH": 0.8157, "EMB": 0.1754}, "sharpe_ratio": 6.09, "portfolio_return": 0.099782, "portfolio_vol": 0.009816, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250923_0462", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX", "ADA-USD", "IYR", "TIP"], "decision_date": "2025-09-23", "context_summary": "4-asset optimization. Max-Sharpe: 2.142. Portfolio: return=8.02%, vol=1.88%. Weights: w_^VIX=0.0034, w_ADA-USD=0.0048, w_IYR=0.0000, w_TIP=0.9918.", "question": "Assets: ^VIX, ADA-USD, IYR, TIP\nAnnualized mean returns: ^VIX:0.2772, ADA-USD:0.4963, IYR:-0.0527, TIP:0.0775\nCovariance matrix (annualized):\n[[1.056234, -0.336201, -0.041999, 0.000109], [-0.336201, 0.454111, 0.020114, 0.002993], [-0.041999, 0.020114, 0.020355, 0.001241], [0.000109, 0.002993, 0.001241, 0.000317]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_^VIX=0.0034, w_ADA-USD=0.0048, w_IYR=0.0000, w_TIP=0.9918", "answer_numeric": 2.142138075398915, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.0034, w_ADA-USD=0.0048, w_IYR=0.0000, w_TIP=0.9918\nPortfolio annualized return: 8.02%, volatility: 1.88%\nSharpe ratio: (0.0802 - 0.0400) / 0.0188 = 2.1421", "metadata": {"weights": {"^VIX": 0.0034, "ADA-USD": 0.0048, "IYR": 0.0, "TIP": 0.9918}, "sharpe_ratio": 2.1421, "portfolio_return": 0.080212, "portfolio_vol": 0.018772, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250114_0464", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "LINK-USD", "SGOV", "USO"], "decision_date": "2025-01-14", "context_summary": "4-asset optimization. Max-Sharpe: 6.147. Portfolio: return=5.80%, vol=0.29%. Weights: w_EWJ=0.0000, w_LINK-USD=0.0004, w_SGOV=0.9916, w_USO=0.0080.", "question": "Assets: EWJ, LINK-USD, SGOV, USO\nAnnualized mean returns: EWJ:-0.1361, LINK-USD:2.3912, SGOV:0.0495, USO:0.9770\nCovariance matrix (annualized):\n[[0.025023, 0.040564, -4.6e-05, -0.0021], [0.040564, 1.371363, 0.000388, 0.015531], [-4.6e-05, 0.000388, 5e-06, -3.2e-05], [-0.0021, 0.015531, -3.2e-05, 0.058919]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0004, w_SGOV=0.9916, w_USO=0.0080", "answer_numeric": 6.147134223742755, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_LINK-USD=0.0004, w_SGOV=0.9916, w_USO=0.0080\nPortfolio annualized return: 5.80%, volatility: 0.29%\nSharpe ratio: (0.0580 - 0.0400) / 0.0029 = 6.1471", "metadata": {"weights": {"EWJ": 0.0, "LINK-USD": 0.0004, "SGOV": 0.9916, "USO": 0.008}, "sharpe_ratio": 6.1471, "portfolio_return": 0.057994, "portfolio_vol": 0.002927, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250911_0466", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF", "ETH-USD", "MORT", "PDBC"], "decision_date": "2025-09-11", "context_summary": "4-asset optimization. Max-Sharpe: 2.462. Portfolio: return=78.87%, vol=30.41%. Weights: w_XLF=0.0000, w_ETH-USD=0.3464, w_MORT=0.6536, w_PDBC=0.0000.", "question": "Assets: XLF, ETH-USD, MORT, PDBC\nAnnualized mean returns: XLF:0.1139, ETH-USD:1.6483, MORT:0.3332, PDBC:-0.0300\nCovariance matrix (annualized):\n[[0.016687, 0.035444, 0.008875, 0.000722], [0.035444, 0.476199, 0.051545, 0.006912], [0.008875, 0.051545, 0.028082, -0.005058], [0.000722, 0.006912, -0.005058, 0.011913]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_ETH-USD=0.3464, w_MORT=0.6536, w_PDBC=0.0000", "answer_numeric": 2.462175466251255, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_ETH-USD=0.3464, w_MORT=0.6536, w_PDBC=0.0000\nPortfolio annualized return: 78.87%, volatility: 30.41%\nSharpe ratio: (0.7887 - 0.0400) / 0.3041 = 2.4622", "metadata": {"weights": {"XLF": 0.0, "ETH-USD": 0.3464, "MORT": 0.6536, "PDBC": 0.0}, "sharpe_ratio": 2.4622, "portfolio_return": 0.788714, "portfolio_vol": 0.304086, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250605_0469", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ADA-USD", "BIL", "VNQI"], "decision_date": "2025-06-05", "context_summary": "4-asset optimization. Max-Sharpe: 4.342. Portfolio: return=31.26%, vol=6.28%. Weights: w_IVV=0.0769, w_ADA-USD=0.0133, w_BIL=0.5628, w_VNQI=0.3470.", "question": "Assets: IVV, ADA-USD, BIL, VNQI\nAnnualized mean returns: IVV:0.5952, ADA-USD:0.9667, BIL:0.0408, VNQI:0.6657\nCovariance matrix (annualized):\n[[0.042324, 0.058883, -4e-05, 0.011563], [0.058883, 0.473823, -0.000172, 0.007731], [-4e-05, -0.000172, 5e-06, 4.1e-05], [0.011563, 0.007731, 4.1e-05, 0.023142]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0769, w_ADA-USD=0.0133, w_BIL=0.5628, w_VNQI=0.3470", "answer_numeric": 4.3422488007280595, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0769, w_ADA-USD=0.0133, w_BIL=0.5628, w_VNQI=0.3470\nPortfolio annualized return: 31.26%, volatility: 6.28%\nSharpe ratio: (0.3126 - 0.0400) / 0.0628 = 4.3422", "metadata": {"weights": {"IVV": 0.0769, "ADA-USD": 0.0133, "BIL": 0.5628, "VNQI": 0.347}, "sharpe_ratio": 4.3422, "portfolio_return": 0.312586, "portfolio_vol": 0.062775, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250902_0471", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EFA", "BTC-USD", "SGOV", "UNG"], "decision_date": "2025-09-02", "context_summary": "4-asset optimization. Max-Sharpe: 1.462. Portfolio: return=4.39%, vol=0.26%. Weights: w_EFA=0.0120, w_BTC-USD=0.0000, w_SGOV=0.9880, w_UNG=0.0000.", "question": "Assets: EFA, BTC-USD, SGOV, UNG\nAnnualized mean returns: EFA:0.1364, BTC-USD:-0.1546, SGOV:0.0427, UNG:-0.9904\nCovariance matrix (annualized):\n[[0.017383, 0.017745, -3.5e-05, -0.026398], [0.017745, 0.086729, -8.4e-05, -0.011287], [-3.5e-05, -8.4e-05, 5e-06, 9.1e-05], [-0.026398, -0.011287, 9.1e-05, 0.19279]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EFA=0.0120, w_BTC-USD=0.0000, w_SGOV=0.9880, w_UNG=0.0000", "answer_numeric": 1.4615099422361302, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EFA=0.0120, w_BTC-USD=0.0000, w_SGOV=0.9880, w_UNG=0.0000\nPortfolio annualized return: 4.39%, volatility: 0.26%\nSharpe ratio: (0.0439 - 0.0400) / 0.0026 = 1.4615", "metadata": {"weights": {"EFA": 0.012, "BTC-USD": 0.0, "SGOV": 0.988, "UNG": 0.0}, "sharpe_ratio": 1.4615, "portfolio_return": 0.043861, "portfolio_vol": 0.002642, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250829_0473", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["USMV", "AVAX-USD", "CSHI", "IAU"], "decision_date": "2025-08-29", "context_summary": "4-asset optimization. Max-Sharpe: 1.947. Portfolio: return=8.34%, vol=2.23%. Weights: w_USMV=0.0000, w_AVAX-USD=0.0015, w_CSHI=0.8300, w_IAU=0.1685.", "question": "Assets: USMV, AVAX-USD, CSHI, IAU\nAnnualized mean returns: USMV:0.0639, AVAX-USD:0.6435, CSHI:0.0441, IAU:0.2720\nCovariance matrix (annualized):\n[[0.008256, 0.012028, 7.2e-05, 0.00148], [0.012028, 0.578016, 0.001296, 0.029402], [7.2e-05, 0.001296, 8.1e-05, -0.000135], [0.00148, 0.029402, -0.000135, 0.016141]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_USMV=0.0000, w_AVAX-USD=0.0015, w_CSHI=0.8300, w_IAU=0.1685", "answer_numeric": 1.9473907036290812, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_USMV=0.0000, w_AVAX-USD=0.0015, w_CSHI=0.8300, w_IAU=0.1685\nPortfolio annualized return: 8.34%, volatility: 2.23%\nSharpe ratio: (0.0834 - 0.0400) / 0.0223 = 1.9474", "metadata": {"weights": {"USMV": 0.0, "AVAX-USD": 0.0015, "CSHI": 0.83, "IAU": 0.1685}, "sharpe_ratio": 1.9474, "portfolio_return": 0.083371, "portfolio_vol": 0.022271, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250116_0475", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "BTC-USD", "CSHI", "HAUZ"], "decision_date": "2025-01-16", "context_summary": "4-asset optimization. Max-Sharpe: 2.854. Portfolio: return=5.99%, vol=0.70%. Weights: w_QUAL=0.0000, w_BTC-USD=0.0073, w_CSHI=0.9927, w_HAUZ=0.0000.", "question": "Assets: QUAL, BTC-USD, CSHI, HAUZ\nAnnualized mean returns: QUAL:0.0153, BTC-USD:0.9463, CSHI:0.0534, HAUZ:-0.2852\nCovariance matrix (annualized):\n[[0.014088, 0.024822, 0.000338, 0.011797], [0.024822, 0.196221, 0.000791, 0.021821], [0.000338, 0.000791, 2.7e-05, 0.000386], [0.011797, 0.021821, 0.000386, 0.018407]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_BTC-USD=0.0073, w_CSHI=0.9927, w_HAUZ=0.0000", "answer_numeric": 2.8543209523416455, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_BTC-USD=0.0073, w_CSHI=0.9927, w_HAUZ=0.0000\nPortfolio annualized return: 5.99%, volatility: 0.70%\nSharpe ratio: (0.0599 - 0.0400) / 0.0070 = 2.8543", "metadata": {"weights": {"QUAL": 0.0, "BTC-USD": 0.0073, "CSHI": 0.9927, "HAUZ": 0.0}, "sharpe_ratio": 2.8543, "portfolio_return": 0.059868, "portfolio_vol": 0.006961, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250117_0478", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "AVAX-USD", "PALL", "MORT"], "decision_date": "2025-01-17", "context_summary": "4-asset optimization. Max-Sharpe: 2.115. Portfolio: return=237.67%, vol=110.49%. Weights: w_XLV=0.0000, w_AVAX-USD=1.0000, w_PALL=0.0000, w_MORT=0.0000.", "question": "Assets: XLV, AVAX-USD, PALL, MORT\nAnnualized mean returns: XLV:-0.0032, AVAX-USD:2.3767, PALL:-0.0562, MORT:0.0694\nCovariance matrix (annualized):\n[[0.013865, 0.011232, 0.004871, 0.008003], [0.011232, 1.220728, 0.040897, 0.065833], [0.004871, 0.040897, 0.080083, 0.013387], [0.008003, 0.065833, 0.013387, 0.030765]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_AVAX-USD=1.0000, w_PALL=0.0000, w_MORT=0.0000", "answer_numeric": 2.114921475572854, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_AVAX-USD=1.0000, w_PALL=0.0000, w_MORT=0.0000\nPortfolio annualized return: 237.67%, volatility: 110.49%\nSharpe ratio: (2.3767 - 0.0400) / 1.1049 = 2.1149", "metadata": {"weights": {"XLV": 0.0, "AVAX-USD": 1.0, "PALL": 0.0, "MORT": 0.0}, "sharpe_ratio": 2.1149, "portfolio_return": 2.376704, "portfolio_vol": 1.104866, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251212_0481", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "AVAX-USD", "PPLT", "ITB"], "decision_date": "2025-12-12", "context_summary": "4-asset optimization. Max-Sharpe: 2.655. Portfolio: return=43.19%, vol=14.76%. Weights: w_EWJ=0.8653, w_AVAX-USD=0.0000, w_PPLT=0.1347, w_ITB=0.0000.", "question": "Assets: EWJ, AVAX-USD, PPLT, ITB\nAnnualized mean returns: EWJ:0.4226, AVAX-USD:-3.2457, PPLT:0.4911, ITB:0.1900\nCovariance matrix (annualized):\n[[0.022676, 0.01029, 0.012258, 0.016177], [0.01029, 0.577993, 0.080996, 0.022109], [0.012258, 0.080996, 0.107418, -0.005011], [0.016177, 0.022109, -0.005011, 0.070736]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.8653, w_AVAX-USD=0.0000, w_PPLT=0.1347, w_ITB=0.0000", "answer_numeric": 2.6549766104834815, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.8653, w_AVAX-USD=0.0000, w_PPLT=0.1347, w_ITB=0.0000\nPortfolio annualized return: 43.19%, volatility: 14.76%\nSharpe ratio: (0.4319 - 0.0400) / 0.1476 = 2.6550", "metadata": {"weights": {"EWJ": 0.8653, "AVAX-USD": 0.0, "PPLT": 0.1347, "ITB": 0.0}, "sharpe_ratio": 2.655, "portfolio_return": 0.431872, "portfolio_vol": 0.147599, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250331_0484", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["FXI", "DOT-USD", "CSHI", "IGOV"], "decision_date": "2025-03-31", "context_summary": "4-asset optimization. Max-Sharpe: 2.510. Portfolio: return=34.53%, vol=12.16%. Weights: w_FXI=0.3025, w_DOT-USD=0.0000, w_CSHI=0.0000, w_IGOV=0.6975.", "question": "Assets: FXI, DOT-USD, CSHI, IGOV\nAnnualized mean returns: FXI:0.7225, DOT-USD:-0.2844, CSHI:0.0373, IGOV:0.1817\nCovariance matrix (annualized):\n[[0.091732, 0.109663, 0.000672, 0.007625], [0.109663, 0.514999, 0.001292, -0.004159], [0.000672, 0.001292, 0.000118, -4.4e-05], [0.007625, -0.004159, -4.4e-05, 0.006535]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.3025, w_DOT-USD=0.0000, w_CSHI=0.0000, w_IGOV=0.6975", "answer_numeric": 2.5102907804692176, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.3025, w_DOT-USD=0.0000, w_CSHI=0.0000, w_IGOV=0.6975\nPortfolio annualized return: 34.53%, volatility: 12.16%\nSharpe ratio: (0.3453 - 0.0400) / 0.1216 = 2.5103", "metadata": {"weights": {"FXI": 0.3025, "DOT-USD": 0.0, "CSHI": 0.0, "IGOV": 0.6975}, "sharpe_ratio": 2.5103, "portfolio_return": 0.345308, "portfolio_vol": 0.121623, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250925_0486", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLV", "SOL-USD", "ITB", "BIL"], "decision_date": "2025-09-25", "context_summary": "4-asset optimization. Max-Sharpe: 1.643. Portfolio: return=4.61%, vol=0.37%. Weights: w_XLV=0.0000, w_SOL-USD=0.0019, w_ITB=0.0077, w_BIL=0.9904.", "question": "Assets: XLV, SOL-USD, ITB, BIL\nAnnualized mean returns: XLV:0.0234, SOL-USD:0.7013, ITB:0.4039, BIL:0.0420\nCovariance matrix (annualized):\n[[0.020804, 0.021319, 0.018295, 6.7e-05], [0.021319, 0.536137, 0.057655, 4e-06], [0.018295, 0.057655, 0.08264, 6.8e-05], [6.7e-05, 4e-06, 6.8e-05, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLV=0.0000, w_SOL-USD=0.0019, w_ITB=0.0077, w_BIL=0.9904", "answer_numeric": 1.643281305735209, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLV=0.0000, w_SOL-USD=0.0019, w_ITB=0.0077, w_BIL=0.9904\nPortfolio annualized return: 4.61%, volatility: 0.37%\nSharpe ratio: (0.0461 - 0.0400) / 0.0037 = 1.6433", "metadata": {"weights": {"XLV": 0.0, "SOL-USD": 0.0019, "ITB": 0.0077, "BIL": 0.9904}, "sharpe_ratio": 1.6433, "portfolio_return": 0.046055, "portfolio_vol": 0.003685, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250403_0488", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VEA", "ADA-USD", "DBB", "TLH"], "decision_date": "2025-04-03", "context_summary": "4-asset optimization. Max-Sharpe: 2.796. Portfolio: return=22.23%, vol=6.52%. Weights: w_VEA=0.1567, w_ADA-USD=0.0000, w_DBB=0.2205, w_TLH=0.6228.", "question": "Assets: VEA, ADA-USD, DBB, TLH\nAnnualized mean returns: VEA:0.1713, ADA-USD:-2.4204, DBB:0.1035, TLH:0.2772\nCovariance matrix (annualized):\n[[0.021746, 0.017894, 0.004184, -0.002037], [0.017894, 0.789529, 0.024895, -0.028574], [0.004184, 0.024895, 0.016233, -0.004422], [-0.002037, -0.028574, -0.004422, 0.010958]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.1567, w_ADA-USD=0.0000, w_DBB=0.2205, w_TLH=0.6228", "answer_numeric": 2.7959955083022336, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.1567, w_ADA-USD=0.0000, w_DBB=0.2205, w_TLH=0.6228\nPortfolio annualized return: 22.23%, volatility: 6.52%\nSharpe ratio: (0.2223 - 0.0400) / 0.0652 = 2.7960", "metadata": {"weights": {"VEA": 0.1567, "ADA-USD": 0.0, "DBB": 0.2205, "TLH": 0.6228}, "sharpe_ratio": 2.796, "portfolio_return": 0.222291, "portfolio_vol": 0.065197, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250217_0491", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "XRP-USD", "SGOV", "UNG"], "decision_date": "2025-02-17", "context_summary": "4-asset optimization. Max-Sharpe: 0.556. Portfolio: return=26.61%, vol=40.64%. Weights: w_^VIX=0.2500, w_XRP-USD=0.2500, w_SGOV=0.2500, w_UNG=0.2500.", "question": "Assets: ^VIX, XRP-USD, SGOV, UNG\nAnnualized mean returns: ^VIX:-3.5598, XRP-USD:2.7476, SGOV:0.0464, UNG:1.8302\nCovariance matrix (annualized):\n[[1.643037, -0.171785, -0.000326, 0.037817], [-0.171785, 0.463459, 0.000178, 0.116968], [-0.000326, 0.000178, 4e-06, -0.000415], [0.037817, 0.116968, -0.000415, 0.570607]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.2500, w_XRP-USD=0.2500, w_SGOV=0.2500, w_UNG=0.2500", "answer_numeric": 0.5564575678411456, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_^VIX=0.2500, w_XRP-USD=0.2500, w_SGOV=0.2500, w_UNG=0.2500\nPortfolio annualized return: 26.61%, volatility: 40.64%\nSharpe ratio: (0.2661 - 0.0400) / 0.4064 = 0.5565", "metadata": {"weights": {"^VIX": 0.25, "XRP-USD": 0.25, "SGOV": 0.25, "UNG": 0.25}, "sharpe_ratio": 0.5565, "portfolio_return": 0.266119, "portfolio_vol": 0.406354, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251103_0493", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "BNB-USD", "EMB", "BIL"], "decision_date": "2025-11-03", "context_summary": "4-asset optimization. Max-Sharpe: 4.444. Portfolio: return=15.29%, vol=2.54%. Weights: w_VLUE=0.1265, w_BNB-USD=0.0000, w_EMB=0.2559, w_BIL=0.6175.", "question": "Assets: VLUE, BNB-USD, EMB, BIL\nAnnualized mean returns: VLUE:0.5961, BNB-USD:-0.3674, EMB:0.2094, BIL:0.0387\nCovariance matrix (annualized):\n[[0.01889, 0.017471, 0.003202, -4.7e-05], [0.017471, 0.412013, 0.003347, 5e-06], [0.003202, 0.003347, 0.002236, -1.4e-05], [-4.7e-05, 5e-06, -1.4e-05, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.1265, w_BNB-USD=0.0000, w_EMB=0.2559, w_BIL=0.6175", "answer_numeric": 4.443553467000297, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.1265, w_BNB-USD=0.0000, w_EMB=0.2559, w_BIL=0.6175\nPortfolio annualized return: 15.29%, volatility: 2.54%\nSharpe ratio: (0.1529 - 0.0400) / 0.0254 = 4.4436", "metadata": {"weights": {"VLUE": 0.1265, "BNB-USD": 0.0, "EMB": 0.2559, "BIL": 0.6175}, "sharpe_ratio": 4.4436, "portfolio_return": 0.152915, "portfolio_vol": 0.025411, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250310_0495", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "DOT-USD", "ITB", "USO"], "decision_date": "2025-03-10", "context_summary": "4-asset optimization. Max-Sharpe: 0.694. Portfolio: return=13.87%, vol=14.22%. Weights: w_VLUE=1.0000, w_DOT-USD=0.0000, w_ITB=0.0000, w_USO=0.0000.", "question": "Assets: VLUE, DOT-USD, ITB, USO\nAnnualized mean returns: VLUE:0.1387, DOT-USD:-0.0387, ITB:-0.1458, USO:-0.4169\nCovariance matrix (annualized):\n[[0.020224, 0.028253, 0.021374, 0.002092], [0.028253, 0.568492, 0.024811, 0.012778], [0.021374, 0.024811, 0.07235, -0.009117], [0.002092, 0.012778, -0.009117, 0.069147]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_DOT-USD=0.0000, w_ITB=0.0000, w_USO=0.0000", "answer_numeric": 0.6941657075615449, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=1.0000, w_DOT-USD=0.0000, w_ITB=0.0000, w_USO=0.0000\nPortfolio annualized return: 13.87%, volatility: 14.22%\nSharpe ratio: (0.1387 - 0.0400) / 0.1422 = 0.6942", "metadata": {"weights": {"VLUE": 1.0, "DOT-USD": 0.0, "ITB": 0.0, "USO": 0.0}, "sharpe_ratio": 0.6942, "portfolio_return": 0.138718, "portfolio_vol": 0.142211, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250619_0497", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "DOT-USD", "IEF", "CSHI"], "decision_date": "2025-06-19", "context_summary": "4-asset optimization. Max-Sharpe: 4.136. Portfolio: return=10.98%, vol=1.69%. Weights: w_EWJ=0.0586, w_DOT-USD=0.0000, w_IEF=0.0000, w_CSHI=0.9414.", "question": "Assets: EWJ, DOT-USD, IEF, CSHI\nAnnualized mean returns: EWJ:0.4720, DOT-USD:-0.1363, IEF:0.0325, CSHI:0.0873\nCovariance matrix (annualized):\n[[0.020983, 0.010802, 0.002272, 0.000567], [0.010802, 0.398786, -0.011061, 0.002048], [0.002272, -0.011061, 0.004267, 6e-06], [0.000567, 0.002048, 6e-06, 0.00017]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0586, w_DOT-USD=0.0000, w_IEF=0.0000, w_CSHI=0.9414", "answer_numeric": 4.135606273137131, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0586, w_DOT-USD=0.0000, w_IEF=0.0000, w_CSHI=0.9414\nPortfolio annualized return: 10.98%, volatility: 1.69%\nSharpe ratio: (0.1098 - 0.0400) / 0.0169 = 4.1356", "metadata": {"weights": {"EWJ": 0.0586, "DOT-USD": 0.0, "IEF": 0.0, "CSHI": 0.9414}, "sharpe_ratio": 4.1356, "portfolio_return": 0.109835, "portfolio_vol": 0.016886, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251110_0500", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "AVAX-USD", "INDS", "IGOV"], "decision_date": "2025-11-10", "context_summary": "4-asset optimization. Max-Sharpe: 0.924. Portfolio: return=17.31%, vol=14.41%. Weights: w_XLE=0.0000, w_AVAX-USD=0.0000, w_INDS=1.0000, w_IGOV=0.0000.", "question": "Assets: XLE, AVAX-USD, INDS, IGOV\nAnnualized mean returns: XLE:0.0799, AVAX-USD:-3.2558, INDS:0.1731, IGOV:-0.0717\nCovariance matrix (annualized):\n[[0.027476, 0.046644, 0.007198, -0.001656], [0.046644, 0.75111, 0.044135, -0.004828], [0.007198, 0.044135, 0.020754, 0.003276], [-0.001656, -0.004828, 0.003276, 0.003778]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLE=0.0000, w_AVAX-USD=0.0000, w_INDS=1.0000, w_IGOV=0.0000", "answer_numeric": 0.9237386577345726, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_AVAX-USD=0.0000, w_INDS=1.0000, w_IGOV=0.0000\nPortfolio annualized return: 17.31%, volatility: 14.41%\nSharpe ratio: (0.1731 - 0.0400) / 0.1441 = 0.9237", "metadata": {"weights": {"XLE": 0.0, "AVAX-USD": 0.0, "INDS": 1.0, "IGOV": 0.0}, "sharpe_ratio": 0.9237, "portfolio_return": 0.173078, "portfolio_vol": 0.144064, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250519_0502", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ETH-USD", "CSHI", "LQD"], "decision_date": "2025-05-19", "context_summary": "4-asset optimization. Max-Sharpe: 2.366. Portfolio: return=181.10%, vol=74.86%. Weights: w_FXI=0.0000, w_ETH-USD=1.0000, w_CSHI=0.0000, w_LQD=0.0000.", "question": "Assets: FXI, ETH-USD, CSHI, LQD\nAnnualized mean returns: FXI:-0.1268, ETH-USD:1.8110, CSHI:0.0456, LQD:-0.0230\nCovariance matrix (annualized):\n[[0.100131, 0.110207, 0.008562, 0.006638], [0.110207, 0.560451, 0.016224, 0.018043], [0.008562, 0.016224, 0.00207, 0.001649], [0.006638, 0.018043, 0.001649, 0.008225]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_CSHI=0.0000, w_LQD=0.0000", "answer_numeric": 2.365638616161308, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.0000, w_ETH-USD=1.0000, w_CSHI=0.0000, w_LQD=0.0000\nPortfolio annualized return: 181.10%, volatility: 74.86%\nSharpe ratio: (1.8110 - 0.0400) / 0.7486 = 2.3656", "metadata": {"weights": {"FXI": 0.0, "ETH-USD": 1.0, "CSHI": 0.0, "LQD": 0.0}, "sharpe_ratio": 2.3656, "portfolio_return": 1.810995, "portfolio_vol": 0.748633, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250505_0505", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ETH-USD", "DBC", "SGOV"], "decision_date": "2025-05-05", "context_summary": "4-asset optimization. Max-Sharpe: 1.661. Portfolio: return=4.35%, vol=0.21%. Weights: w_XLY=0.0000, w_ETH-USD=0.0001, w_DBC=0.0000, w_SGOV=0.9999.", "question": "Assets: XLY, ETH-USD, DBC, SGOV\nAnnualized mean returns: XLY:-0.5434, ETH-USD:0.3238, DBC:-0.2451, SGOV:0.0435\nCovariance matrix (annualized):\n[[0.107393, 0.137591, 0.036824, 9.7e-05], [0.137591, 0.4397, 0.050622, 0.000335], [0.036824, 0.050622, 0.032795, 4.5e-05], [9.7e-05, 0.000335, 4.5e-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_XLY=0.0000, w_ETH-USD=0.0001, w_DBC=0.0000, w_SGOV=0.9999", "answer_numeric": 1.6605681975596702, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_ETH-USD=0.0001, w_DBC=0.0000, w_SGOV=0.9999\nPortfolio annualized return: 4.35%, volatility: 0.21%\nSharpe ratio: (0.0435 - 0.0400) / 0.0021 = 1.6606", "metadata": {"weights": {"XLY": 0.0, "ETH-USD": 0.0001, "DBC": 0.0, "SGOV": 0.9999}, "sharpe_ratio": 1.6606, "portfolio_return": 0.043503, "portfolio_vol": 0.002109, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250113_0508", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "LINK-USD", "PDBC", "VCIT"], "decision_date": "2025-01-13", "context_summary": "4-asset optimization. Max-Sharpe: 3.345. Portfolio: return=53.20%, vol=14.71%. Weights: w_IWM=0.0000, w_LINK-USD=0.0711, w_PDBC=0.9289, w_VCIT=0.0000.", "question": "Assets: IWM, LINK-USD, PDBC, VCIT\nAnnualized mean returns: IWM:-0.4626, LINK-USD:2.3020, PDBC:0.3965, VCIT:-0.0747\nCovariance matrix (annualized):\n[[0.031422, 0.056442, -0.001573, 0.005855], [0.056442, 1.3787, 0.001603, 0.011103], [-0.001573, 0.001603, 0.016756, -0.001206], [0.005855, 0.011103, -0.001206, 0.002499]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0711, w_PDBC=0.9289, w_VCIT=0.0000", "answer_numeric": 3.344595195110595, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_LINK-USD=0.0711, w_PDBC=0.9289, w_VCIT=0.0000\nPortfolio annualized return: 53.20%, volatility: 14.71%\nSharpe ratio: (0.5320 - 0.0400) / 0.1471 = 3.3446", "metadata": {"weights": {"IWM": 0.0, "LINK-USD": 0.0711, "PDBC": 0.9289, "VCIT": 0.0}, "sharpe_ratio": 3.3446, "portfolio_return": 0.53196, "portfolio_vol": 0.147091, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251022_0511", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "DOT-USD", "REZ", "SGOV"], "decision_date": "2025-10-22", "context_summary": "4-asset optimization. Max-Sharpe: -1.431. Portfolio: return=-26.53%, vol=21.34%. Weights: w_VLUE=0.2500, w_DOT-USD=0.2500, w_REZ=0.2500, w_SGOV=0.2500.", "question": "Assets: VLUE, DOT-USD, REZ, SGOV\nAnnualized mean returns: VLUE:0.4809, DOT-USD:-1.6591, REZ:0.0762, SGOV:0.0408\nCovariance matrix (annualized):\n[[0.017952, 0.059577, 0.007668, -8.8e-05], [0.059577, 0.568477, -0.002754, -0.000732], [0.007668, -0.002754, 0.014861, 3.6e-05], [-8.8e-05, -0.000732, 3.6e-05, 5e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VLUE=0.2500, w_DOT-USD=0.2500, w_REZ=0.2500, w_SGOV=0.2500", "answer_numeric": -1.4305165654694771, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VLUE=0.2500, w_DOT-USD=0.2500, w_REZ=0.2500, w_SGOV=0.2500\nPortfolio annualized return: -26.53%, volatility: 21.34%\nSharpe ratio: (-0.2653 - 0.0400) / 0.2134 = -1.4305", "metadata": {"weights": {"VLUE": 0.25, "DOT-USD": 0.25, "REZ": 0.25, "SGOV": 0.25}, "sharpe_ratio": -1.4305, "portfolio_return": -0.265288, "portfolio_vol": 0.213411, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250813_0514", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI", "ETH-USD", "CSHI", "VNQ"], "decision_date": "2025-08-13", "context_summary": "4-asset optimization. Max-Sharpe: 5.657. Portfolio: return=148.26%, vol=25.50%. Weights: w_ACWI=0.6172, w_ETH-USD=0.3828, w_CSHI=0.0000, w_VNQ=0.0000.", "question": "Assets: ACWI, ETH-USD, CSHI, VNQ\nAnnualized mean returns: ACWI:0.4173, ETH-USD:3.2004, CSHI:0.0541, VNQ:0.0105\nCovariance matrix (annualized):\n[[0.00971, 0.028784, 0.000268, 0.005429], [0.028784, 0.325847, 0.001317, 0.024796], [0.000268, 0.001317, 0.0001, 9e-06], [0.005429, 0.024796, 9e-06, 0.01938]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.6172, w_ETH-USD=0.3828, w_CSHI=0.0000, w_VNQ=0.0000", "answer_numeric": 5.656592346359897, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.6172, w_ETH-USD=0.3828, w_CSHI=0.0000, w_VNQ=0.0000\nPortfolio annualized return: 148.26%, volatility: 25.50%\nSharpe ratio: (1.4826 - 0.0400) / 0.2550 = 5.6566", "metadata": {"weights": {"ACWI": 0.6172, "ETH-USD": 0.3828, "CSHI": 0.0, "VNQ": 0.0}, "sharpe_ratio": 5.6566, "portfolio_return": 1.482581, "portfolio_vol": 0.255026, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250207_0516", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "XRP-USD", "BIL", "STIP"], "decision_date": "2025-02-07", "context_summary": "4-asset optimization. Max-Sharpe: 2.003. Portfolio: return=4.49%, vol=0.25%. Weights: w_VTI=0.0000, w_XRP-USD=0.0009, w_BIL=0.9695, w_STIP=0.0296.", "question": "Assets: VTI, XRP-USD, BIL, STIP\nAnnualized mean returns: VTI:-0.0165, XRP-USD:0.8526, BIL:0.0440, STIP:0.0515\nCovariance matrix (annualized):\n[[0.021587, 0.052892, -1.5e-05, 0.001059], [0.052892, 0.677405, 0.000224, 0.006288], [-1.5e-05, 0.000224, 5e-06, 1e-06], [0.001059, 0.006288, 1e-06, 0.000254]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_XRP-USD=0.0009, w_BIL=0.9695, w_STIP=0.0296", "answer_numeric": 2.0032037928869757, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_XRP-USD=0.0009, w_BIL=0.9695, w_STIP=0.0296\nPortfolio annualized return: 4.49%, volatility: 0.25%\nSharpe ratio: (0.0449 - 0.0400) / 0.0025 = 2.0032", "metadata": {"weights": {"VTI": 0.0, "XRP-USD": 0.0009, "BIL": 0.9695, "STIP": 0.0296}, "sharpe_ratio": 2.0032, "portfolio_return": 0.044922, "portfolio_vol": 0.002457, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9047}} +{"id": "T5_all_20250408_0520", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLF", "XRP-USD", "CPER", "ITB"], "decision_date": "2025-04-08", "context_summary": "4-asset optimization. Max-Sharpe: -1.358. Portfolio: return=-112.43%, vol=85.73%. Weights: w_XLF=0.0000, w_XRP-USD=1.0000, w_CPER=0.0000, w_ITB=0.0000.", "question": "Assets: XLF, XRP-USD, CPER, ITB\nAnnualized mean returns: XLF:-0.6849, XRP-USD:-1.1243, CPER:-0.0475, ITB:-0.9146\nCovariance matrix (annualized):\n[[0.047901, 0.010553, 0.018673, 0.023649], [0.010553, 0.735002, 0.039725, 0.045639], [0.018673, 0.039725, 0.087112, 0.006686], [0.023649, 0.045639, 0.006686, 0.079659]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_XRP-USD=1.0000, w_CPER=0.0000, w_ITB=0.0000", "answer_numeric": -1.3580803953368963, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_XRP-USD=1.0000, w_CPER=0.0000, w_ITB=0.0000\nPortfolio annualized return: -112.43%, volatility: 85.73%\nSharpe ratio: (-1.1243 - 0.0400) / 0.8573 = -1.3581", "metadata": {"weights": {"XLF": 0.0, "XRP-USD": 1.0, "CPER": 0.0, "ITB": 0.0}, "sharpe_ratio": -1.3581, "portfolio_return": -1.124313, "portfolio_vol": 0.857323, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250204_0522", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "AVAX-USD", "SGOV", "IYR"], "decision_date": "2025-02-04", "context_summary": "4-asset optimization. Max-Sharpe: 3.264. Portfolio: return=4.72%, vol=0.22%. Weights: w_EWJ=0.0000, w_AVAX-USD=0.0000, w_SGOV=1.0000, w_IYR=0.0000.", "question": "Assets: EWJ, AVAX-USD, SGOV, IYR\nAnnualized mean returns: EWJ:-0.2186, AVAX-USD:-0.4984, SGOV:0.0472, IYR:-0.2365\nCovariance matrix (annualized):\n[[0.025405, 0.038098, -3.6e-05, 0.013846], [0.038098, 0.84263, 9.3e-05, 0.050196], [-3.6e-05, 9.3e-05, 5e-06, -7e-05], [0.013846, 0.050196, -7e-05, 0.036969]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_AVAX-USD=0.0000, w_SGOV=1.0000, w_IYR=0.0000", "answer_numeric": 3.2639913268572247, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_AVAX-USD=0.0000, w_SGOV=1.0000, w_IYR=0.0000\nPortfolio annualized return: 4.72%, volatility: 0.22%\nSharpe ratio: (0.0472 - 0.0400) / 0.0022 = 3.2640", "metadata": {"weights": {"EWJ": 0.0, "AVAX-USD": 0.0, "SGOV": 1.0, "IYR": 0.0}, "sharpe_ratio": 3.264, "portfolio_return": 0.047229, "portfolio_vol": 0.002215, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20250730_0525", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI", "ETH-USD", "TLH", "SCHH"], "decision_date": "2025-07-30", "context_summary": "4-asset optimization. Max-Sharpe: 5.213. Portfolio: return=61.92%, vol=11.11%. Weights: w_ACWI=0.7785, w_ETH-USD=0.1184, w_TLH=0.1031, w_SCHH=0.0000.", "question": "Assets: ACWI, ETH-USD, TLH, SCHH\nAnnualized mean returns: ACWI:0.4147, ETH-USD:2.3970, TLH:0.1213, SCHH:0.1395\nCovariance matrix (annualized):\n[[0.007642, 0.016437, 0.000857, 0.004523], [0.016437, 0.315607, 0.000535, 0.020147], [0.000857, 0.000535, 0.009714, 0.004232], [0.004523, 0.020147, 0.004232, 0.015966]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.7785, w_ETH-USD=0.1184, w_TLH=0.1031, w_SCHH=0.0000", "answer_numeric": 5.213225870611135, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.7785, w_ETH-USD=0.1184, w_TLH=0.1031, w_SCHH=0.0000\nPortfolio annualized return: 61.92%, volatility: 11.11%\nSharpe ratio: (0.6192 - 0.0400) / 0.1111 = 5.2132", "metadata": {"weights": {"ACWI": 0.7785, "ETH-USD": 0.1184, "TLH": 0.1031, "SCHH": 0.0}, "sharpe_ratio": 5.2132, "portfolio_return": 0.619194, "portfolio_vol": 0.111101, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20250124_0528", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "AVAX-USD", "TIP", "USO"], "decision_date": "2025-01-24", "context_summary": "4-asset optimization. Max-Sharpe: 2.222. Portfolio: return=37.91%, vol=15.26%. Weights: w_MTUM=0.4906, w_AVAX-USD=0.0196, w_TIP=0.0000, w_USO=0.4898.", "question": "Assets: MTUM, AVAX-USD, TIP, USO\nAnnualized mean returns: MTUM:0.2837, AVAX-USD:1.0645, TIP:0.0450, USO:0.4471\nCovariance matrix (annualized):\n[[0.033873, 0.090414, 0.001432, -0.003357], [0.090414, 0.975863, 0.004565, 0.014065], [0.001432, 0.004565, 0.000246, 0.000363], [-0.003357, 0.014065, 0.000363, 0.059906]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.4906, w_AVAX-USD=0.0196, w_TIP=0.0000, w_USO=0.4898", "answer_numeric": 2.2215856705068115, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_MTUM=0.4906, w_AVAX-USD=0.0196, w_TIP=0.0000, w_USO=0.4898\nPortfolio annualized return: 37.91%, volatility: 15.26%\nSharpe ratio: (0.3791 - 0.0400) / 0.1526 = 2.2216", "metadata": {"weights": {"MTUM": 0.4906, "AVAX-USD": 0.0196, "TIP": 0.0, "USO": 0.4898}, "sharpe_ratio": 2.2216, "portfolio_return": 0.37909, "portfolio_vol": 0.152634, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20250702_0530", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "SOL-USD", "IEF", "BIL"], "decision_date": "2025-07-02", "context_summary": "4-asset optimization. Max-Sharpe: -0.080. Portfolio: return=2.66%, vol=16.67%. Weights: w_SPY=0.2500, w_SOL-USD=0.2500, w_IEF=0.2500, w_BIL=0.2500.", "question": "Assets: SPY, SOL-USD, IEF, BIL\nAnnualized mean returns: SPY:0.4867, SOL-USD:-0.5033, IEF:0.0816, BIL:0.0414\nCovariance matrix (annualized):\n[[0.014578, 0.018567, 0.0002, -6.5e-05], [0.018567, 0.406085, -0.008865, 0.000185], [0.0002, -0.008865, 0.003785, -1.9e-05], [-6.5e-05, 0.000185, -1.9e-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_SPY=0.2500, w_SOL-USD=0.2500, w_IEF=0.2500, w_BIL=0.2500", "answer_numeric": -0.08031875881889287, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_SPY=0.2500, w_SOL-USD=0.2500, w_IEF=0.2500, w_BIL=0.2500\nPortfolio annualized return: 2.66%, volatility: 16.67%\nSharpe ratio: (0.0266 - 0.0400) / 0.1667 = -0.0803", "metadata": {"weights": {"SPY": 0.25, "SOL-USD": 0.25, "IEF": 0.25, "BIL": 0.25}, "sharpe_ratio": -0.0803, "portfolio_return": 0.026613, "portfolio_vol": 0.166669, "n_assets": 4, "optimizer_success": false, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250210_0532", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "BNB-USD", "MORT", "CSHI"], "decision_date": "2025-02-10", "context_summary": "4-asset optimization. Max-Sharpe: 1.704. Portfolio: return=5.05%, vol=0.62%. Weights: w_QQQ=0.0000, w_BNB-USD=0.0000, w_MORT=0.0056, w_CSHI=0.9944.", "question": "Assets: QQQ, BNB-USD, MORT, CSHI\nAnnualized mean returns: QQQ:-0.0775, BNB-USD:0.1823, MORT:0.1866, CSHI:0.0498\nCovariance matrix (annualized):\n[[0.041338, 0.01994, 0.017218, 0.000707], [0.01994, 0.139241, 0.008647, 0.00051], [0.017218, 0.008647, 0.037803, 0.000323], [0.000707, 0.00051, 0.000323, 3.4e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_QQQ=0.0000, w_BNB-USD=0.0000, w_MORT=0.0056, w_CSHI=0.9944", "answer_numeric": 1.704124850786897, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QQQ=0.0000, w_BNB-USD=0.0000, w_MORT=0.0056, w_CSHI=0.9944\nPortfolio annualized return: 5.05%, volatility: 0.62%\nSharpe ratio: (0.0505 - 0.0400) / 0.0062 = 1.7041", "metadata": {"weights": {"QQQ": 0.0, "BNB-USD": 0.0, "MORT": 0.0056, "CSHI": 0.9944}, "sharpe_ratio": 1.7041, "portfolio_return": 0.050538, "portfolio_vol": 0.006184, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20251215_0535", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "AVAX-USD", "VCIT", "BIL"], "decision_date": "2025-12-15", "context_summary": "4-asset optimization. Max-Sharpe: 0.218. Portfolio: return=8.58%, vol=21.02%. Weights: w_IWM=1.0000, w_AVAX-USD=0.0000, w_VCIT=0.0000, w_BIL=0.0000.", "question": "Assets: IWM, AVAX-USD, VCIT, BIL\nAnnualized mean returns: IWM:0.0858, AVAX-USD:-3.3857, VCIT:-0.0020, BIL:0.0399\nCovariance matrix (annualized):\n[[0.044168, 0.06757, 0.002404, 1.4e-05], [0.06757, 0.567768, 0.003437, 0.000349], [0.002404, 0.003437, 0.001185, -2.1e-05], [1.4e-05, 0.000349, -2.1e-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_IWM=1.0000, w_AVAX-USD=0.0000, w_VCIT=0.0000, w_BIL=0.0000", "answer_numeric": 0.21804546064412456, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=1.0000, w_AVAX-USD=0.0000, w_VCIT=0.0000, w_BIL=0.0000\nPortfolio annualized return: 8.58%, volatility: 21.02%\nSharpe ratio: (0.0858 - 0.0400) / 0.2102 = 0.2180", "metadata": {"weights": {"IWM": 1.0, "AVAX-USD": 0.0, "VCIT": 0.0, "BIL": 0.0}, "sharpe_ratio": 0.218, "portfolio_return": 0.085825, "portfolio_vol": 0.210161, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250411_0539", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["IVV", "MATIC-USD", "XHB", "LQD"], "decision_date": "2025-04-11", "context_summary": "4-asset optimization. Max-Sharpe: 0.736. Portfolio: return=8.40%, vol=5.97%. Weights: w_IVV=0.0000, w_MATIC-USD=0.0000, w_XHB=0.0000, w_LQD=1.0000.", "question": "Assets: IVV, MATIC-USD, XHB, LQD\nAnnualized mean returns: IVV:-0.3917, MATIC-USD:-2.5661, XHB:-0.6429, LQD:0.0840\nCovariance matrix (annualized):\n[[0.027255, 0.030914, 0.023276, 0.000291], [0.030914, 0.470231, 0.041091, -0.008805], [0.023276, 0.041091, 0.061161, 0.004442], [0.000291, -0.008805, 0.004442, 0.003565]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.0000, w_MATIC-USD=0.0000, w_XHB=0.0000, w_LQD=1.0000", "answer_numeric": 0.7360789753060284, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_MATIC-USD=0.0000, w_XHB=0.0000, w_LQD=1.0000\nPortfolio annualized return: 8.40%, volatility: 5.97%\nSharpe ratio: (0.0840 - 0.0400) / 0.0597 = 0.7361", "metadata": {"weights": {"IVV": 0.0, "MATIC-USD": 0.0, "XHB": 0.0, "LQD": 1.0}, "sharpe_ratio": 0.7361, "portfolio_return": 0.083952, "portfolio_vol": 0.059711, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251029_0541", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF", "ETH-USD", "SGOV", "VCIT"], "decision_date": "2025-10-29", "context_summary": "4-asset optimization. Max-Sharpe: 3.455. Portfolio: return=15.02%, vol=3.19%. Weights: w_XLF=0.0000, w_ETH-USD=0.0000, w_SGOV=0.0000, w_VCIT=1.0000.", "question": "Assets: XLF, ETH-USD, SGOV, VCIT\nAnnualized mean returns: XLF:-0.0947, ETH-USD:-1.4060, SGOV:0.0390, VCIT:0.1502\nCovariance matrix (annualized):\n[[0.01972, 0.023344, -1.6e-05, -0.000105], [0.023344, 0.289267, -0.00018, 0.000559], [-1.6e-05, -0.00018, 4e-06, 5e-06], [-0.000105, 0.000559, 5e-06, 0.001017]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLF=0.0000, w_ETH-USD=0.0000, w_SGOV=0.0000, w_VCIT=1.0000", "answer_numeric": 3.4548291297248355, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLF=0.0000, w_ETH-USD=0.0000, w_SGOV=0.0000, w_VCIT=1.0000\nPortfolio annualized return: 15.02%, volatility: 3.19%\nSharpe ratio: (0.1502 - 0.0400) / 0.0319 = 3.4548", "metadata": {"weights": {"XLF": 0.0, "ETH-USD": 0.0, "SGOV": 0.0, "VCIT": 1.0}, "sharpe_ratio": 3.4548, "portfolio_return": 0.150195, "portfolio_vol": 0.031896, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250501_0544", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EWJ", "XRP-USD", "SLV", "JNK"], "decision_date": "2025-05-01", "context_summary": "4-asset optimization. Max-Sharpe: 1.707. Portfolio: return=51.47%, vol=27.81%. Weights: w_EWJ=0.0000, w_XRP-USD=0.0000, w_SLV=1.0000, w_JNK=0.0000.", "question": "Assets: EWJ, XRP-USD, SLV, JNK\nAnnualized mean returns: EWJ:0.2030, XRP-USD:-0.4265, SLV:0.5147, JNK:-0.1349\nCovariance matrix (annualized):\n[[0.055514, 0.048835, 0.033072, 0.017124], [0.048835, 0.708553, 0.032439, 0.023231], [0.033072, 0.032439, 0.077341, 0.009706], [0.017124, 0.023231, 0.009706, 0.008588]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_XRP-USD=0.0000, w_SLV=1.0000, w_JNK=0.0000", "answer_numeric": 1.7070897725822256, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_XRP-USD=0.0000, w_SLV=1.0000, w_JNK=0.0000\nPortfolio annualized return: 51.47%, volatility: 27.81%\nSharpe ratio: (0.5147 - 0.0400) / 0.2781 = 1.7071", "metadata": {"weights": {"EWJ": 0.0, "XRP-USD": 0.0, "SLV": 1.0, "JNK": 0.0}, "sharpe_ratio": 1.7071, "portfolio_return": 0.514746, "portfolio_vol": 0.278103, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250127_0546", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ETH-USD", "VCIT", "XHB"], "decision_date": "2025-01-27", "context_summary": "4-asset optimization. Max-Sharpe: 0.313. Portfolio: return=23.02%, vol=60.82%. Weights: w_QUAL=0.0000, w_ETH-USD=1.0000, w_VCIT=0.0000, w_XHB=0.0000.", "question": "Assets: QUAL, ETH-USD, VCIT, XHB\nAnnualized mean returns: QUAL:0.0148, ETH-USD:0.2302, VCIT:-0.0624, XHB:-0.6086\nCovariance matrix (annualized):\n[[0.015497, 0.040105, 0.004381, 0.018877], [0.040105, 0.369894, 0.014836, 0.046693], [0.004381, 0.014836, 0.002883, 0.006883], [0.018877, 0.046693, 0.006883, 0.045749]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=1.0000, w_VCIT=0.0000, w_XHB=0.0000", "answer_numeric": 0.3127081699835776, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_QUAL=0.0000, w_ETH-USD=1.0000, w_VCIT=0.0000, w_XHB=0.0000\nPortfolio annualized return: 23.02%, volatility: 60.82%\nSharpe ratio: (0.2302 - 0.0400) / 0.6082 = 0.3127", "metadata": {"weights": {"QUAL": 0.0, "ETH-USD": 1.0, "VCIT": 0.0, "XHB": 0.0}, "sharpe_ratio": 0.3127, "portfolio_return": 0.230186, "portfolio_vol": 0.608189, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20250508_0548", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "MATIC-USD", "USO", "VNQI"], "decision_date": "2025-05-08", "context_summary": "4-asset optimization. Max-Sharpe: 1.690. Portfolio: return=31.87%, vol=16.49%. Weights: w_EWJ=1.0000, w_MATIC-USD=0.0000, w_USO=0.0000, w_VNQI=0.0000.", "question": "Assets: EWJ, MATIC-USD, USO, VNQI\nAnnualized mean returns: EWJ:0.3187, MATIC-USD:-2.9907, USO:-0.0693, VNQI:0.1074\nCovariance matrix (annualized):\n[[0.027185, 0.015227, 0.0003, 0.015003], [0.015227, 0.475762, 0.03592, 0.017797], [0.0003, 0.03592, 0.048574, 0.0022], [0.015003, 0.017797, 0.0022, 0.01287]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_MATIC-USD=0.0000, w_USO=0.0000, w_VNQI=0.0000", "answer_numeric": 1.6901145083283287, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=1.0000, w_MATIC-USD=0.0000, w_USO=0.0000, w_VNQI=0.0000\nPortfolio annualized return: 31.87%, volatility: 16.49%\nSharpe ratio: (0.3187 - 0.0400) / 0.1649 = 1.6901", "metadata": {"weights": {"EWJ": 1.0, "MATIC-USD": 0.0, "USO": 0.0, "VNQI": 0.0}, "sharpe_ratio": 1.6901, "portfolio_return": 0.318666, "portfolio_vol": 0.16488, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250428_0550", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLP", "BTC-USD", "BNO", "SGOV"], "decision_date": "2025-04-28", "context_summary": "4-asset optimization. Max-Sharpe: 2.509. Portfolio: return=4.93%, vol=0.37%. Weights: w_XLP=0.0000, w_BTC-USD=0.0056, w_BNO=0.0000, w_SGOV=0.9944.", "question": "Assets: XLP, BTC-USD, BNO, SGOV\nAnnualized mean returns: XLP:-0.0402, BTC-USD:1.1046, BNO:-0.3024, SGOV:0.0434\nCovariance matrix (annualized):\n[[0.033738, 0.020002, 0.027173, 8.2e-05], [0.020002, 0.259349, 0.065212, 0.000121], [0.027173, 0.065212, 0.121058, 8.5e-05], [8.2e-05, 0.000121, 8.5e-05, 4e-06]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLP=0.0000, w_BTC-USD=0.0056, w_BNO=0.0000, w_SGOV=0.9944", "answer_numeric": 2.5094777791666316, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.0000, w_BTC-USD=0.0056, w_BNO=0.0000, w_SGOV=0.9944\nPortfolio annualized return: 4.93%, volatility: 0.37%\nSharpe ratio: (0.0493 - 0.0400) / 0.0037 = 2.5095", "metadata": {"weights": {"XLP": 0.0, "BTC-USD": 0.0056, "BNO": 0.0, "SGOV": 0.9944}, "sharpe_ratio": 2.5095, "portfolio_return": 0.049326, "portfolio_vol": 0.003716, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9047}} +{"id": "T5_all_20250828_0553", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE", "BTC-USD", "SGOV", "GLD"], "decision_date": "2025-08-28", "context_summary": "4-asset optimization. Max-Sharpe: 1.602. Portfolio: return=5.19%, vol=0.75%. Weights: w_XLRE=0.0129, w_BTC-USD=0.0000, w_SGOV=0.9382, w_GLD=0.0488.", "question": "Assets: XLRE, BTC-USD, SGOV, GLD\nAnnualized mean returns: XLRE:0.1541, BTC-USD:0.0750, SGOV:0.0411, GLD:0.2327\nCovariance matrix (annualized):\n[[0.018872, 0.01447, -2.9e-05, 0.006436], [0.01447, 0.08115, 9e-06, 0.010323], [-2.9e-05, 9e-06, 5e-06, 1.8e-05], [0.006436, 0.010323, 1.8e-05, 0.016332]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0129, w_BTC-USD=0.0000, w_SGOV=0.9382, w_GLD=0.0488", "answer_numeric": 1.6015690060322982, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0129, w_BTC-USD=0.0000, w_SGOV=0.9382, w_GLD=0.0488\nPortfolio annualized return: 5.19%, volatility: 0.75%\nSharpe ratio: (0.0519 - 0.0400) / 0.0075 = 1.6016", "metadata": {"weights": {"XLRE": 0.0129, "BTC-USD": 0.0, "SGOV": 0.9382, "GLD": 0.0488}, "sharpe_ratio": 1.6016, "portfolio_return": 0.051944, "portfolio_vol": 0.007458, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20251210_0555", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "XRP-USD", "UNG", "ICSH"], "decision_date": "2025-12-10", "context_summary": "4-asset optimization. Max-Sharpe: 1.745. Portfolio: return=93.86%, vol=51.49%. Weights: w_XLRE=0.0000, w_XRP-USD=0.0000, w_UNG=1.0000, w_ICSH=0.0000.", "question": "Assets: XLRE, XRP-USD, UNG, ICSH\nAnnualized mean returns: XLRE:-0.0273, XRP-USD:-1.8095, UNG:0.9386, ICSH:0.0371\nCovariance matrix (annualized):\n[[0.019565, 0.012909, 0.016682, 8.5e-05], [0.012909, 0.416582, -0.070207, -5.6e-05], [0.016682, -0.070207, 0.265077, 0.000265], [8.5e-05, -5.6e-05, 0.000265, 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_XLRE=0.0000, w_XRP-USD=0.0000, w_UNG=1.0000, w_ICSH=0.0000", "answer_numeric": 1.7453464546723254, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_XRP-USD=0.0000, w_UNG=1.0000, w_ICSH=0.0000\nPortfolio annualized return: 93.86%, volatility: 51.49%\nSharpe ratio: (0.9386 - 0.0400) / 0.5149 = 1.7453", "metadata": {"weights": {"XLRE": 0.0, "XRP-USD": 0.0, "UNG": 1.0, "ICSH": 0.0}, "sharpe_ratio": 1.7453, "portfolio_return": 0.938602, "portfolio_vol": 0.514856, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20251002_0557", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "ETH-USD", "CSHI", "SCHH"], "decision_date": "2025-10-02", "context_summary": "4-asset optimization. Max-Sharpe: 3.710. Portfolio: return=15.83%, vol=3.19%. Weights: w_FXI=0.1379, w_ETH-USD=0.0000, w_CSHI=0.7704, w_SCHH=0.0916.", "question": "Assets: FXI, ETH-USD, CSHI, SCHH\nAnnualized mean returns: FXI:0.6989, ETH-USD:1.2899, CSHI:0.0511, SCHH:0.2457\nCovariance matrix (annualized):\n[[0.037108, 0.057873, 0.000338, 0.003096], [0.057873, 0.500777, 0.001157, 0.0242], [0.000338, 0.001157, 6.1e-05, 2.1e-05], [0.003096, 0.0242, 2.1e-05, 0.014461]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.1379, w_ETH-USD=0.0000, w_CSHI=0.7704, w_SCHH=0.0916", "answer_numeric": 3.7103933271085374, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.1379, w_ETH-USD=0.0000, w_CSHI=0.7704, w_SCHH=0.0916\nPortfolio annualized return: 15.83%, volatility: 3.19%\nSharpe ratio: (0.1583 - 0.0400) / 0.0319 = 3.7104", "metadata": {"weights": {"FXI": 0.1379, "ETH-USD": 0.0, "CSHI": 0.7704, "SCHH": 0.0916}, "sharpe_ratio": 3.7104, "portfolio_return": 0.158322, "portfolio_vol": 0.031889, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250526_0560", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "AVAX-USD", "VNQI", "DBC"], "decision_date": "2025-05-26", "context_summary": "4-asset optimization. Max-Sharpe: 2.862. Portfolio: return=60.72%, vol=19.82%. Weights: w_EWJ=0.0000, w_AVAX-USD=0.1609, w_VNQI=0.8391, w_DBC=0.0000.", "question": "Assets: EWJ, AVAX-USD, VNQI, DBC\nAnnualized mean returns: EWJ:0.1428, AVAX-USD:1.7038, VNQI:0.3969, DBC:-0.1448\nCovariance matrix (annualized):\n[[0.047487, 0.03992, 0.02367, 0.022779], [0.03992, 0.660498, 0.010624, 0.05516], [0.02367, 0.010624, 0.027409, 0.015851], [0.022779, 0.05516, 0.015851, 0.038782]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_EWJ=0.0000, w_AVAX-USD=0.1609, w_VNQI=0.8391, w_DBC=0.0000", "answer_numeric": 2.8623059787729126, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.0000, w_AVAX-USD=0.1609, w_VNQI=0.8391, w_DBC=0.0000\nPortfolio annualized return: 60.72%, volatility: 19.82%\nSharpe ratio: (0.6072 - 0.0400) / 0.1982 = 2.8623", "metadata": {"weights": {"EWJ": 0.0, "AVAX-USD": 0.1609, "VNQI": 0.8391, "DBC": 0.0}, "sharpe_ratio": 2.8623, "portfolio_return": 0.607184, "portfolio_vol": 0.198156, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250731_0562", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IVV", "BNB-USD", "TLH", "SCHH"], "decision_date": "2025-07-31", "context_summary": "4-asset optimization. Max-Sharpe: 5.229. Portfolio: return=45.51%, vol=7.94%. Weights: w_IVV=0.9314, w_BNB-USD=0.0161, w_TLH=0.0525, w_SCHH=0.0000.", "question": "Assets: IVV, BNB-USD, TLH, SCHH\nAnnualized mean returns: IVV:0.4728, BNB-USD:0.6236, TLH:0.0891, SCHH:0.0392\nCovariance matrix (annualized):\n[[0.006895, 0.008365, 0.000248, 0.003784], [0.008365, 0.064798, 0.000487, 0.012486], [0.000248, 0.000487, 0.00964, 0.004651], [0.003784, 0.012486, 0.004651, 0.017201]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IVV=0.9314, w_BNB-USD=0.0161, w_TLH=0.0525, w_SCHH=0.0000", "answer_numeric": 5.229492635310898, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.9314, w_BNB-USD=0.0161, w_TLH=0.0525, w_SCHH=0.0000\nPortfolio annualized return: 45.51%, volatility: 7.94%\nSharpe ratio: (0.4551 - 0.0400) / 0.0794 = 5.2295", "metadata": {"weights": {"IVV": 0.9314, "BNB-USD": 0.0161, "TLH": 0.0525, "SCHH": 0.0}, "sharpe_ratio": 5.2295, "portfolio_return": 0.455088, "portfolio_vol": 0.079374, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250515_0565", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "XRP-USD", "PALL", "VCIT"], "decision_date": "2025-05-15", "context_summary": "4-asset optimization. Max-Sharpe: 1.579. Portfolio: return=109.70%, vol=66.94%. Weights: w_XLE=0.0000, w_XRP-USD=1.0000, w_PALL=0.0000, w_VCIT=0.0000.", "question": "Assets: XLE, XRP-USD, PALL, VCIT\nAnnualized mean returns: XLE:0.1632, XRP-USD:1.0970, PALL:-0.0600, VCIT:0.0422\nCovariance matrix (annualized):\n[[0.097032, 0.096, 0.021623, 0.008739], [0.096, 0.448052, -0.004329, 0.012078], [0.021623, -0.004329, 0.05778, 0.003556], [0.008739, 0.012078, 0.003556, 0.004611]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_PALL=0.0000, w_VCIT=0.0000", "answer_numeric": 1.5791455777231111, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLE=0.0000, w_XRP-USD=1.0000, w_PALL=0.0000, w_VCIT=0.0000\nPortfolio annualized return: 109.70%, volatility: 66.94%\nSharpe ratio: (1.0970 - 0.0400) / 0.6694 = 1.5791", "metadata": {"weights": {"XLE": 0.0, "XRP-USD": 1.0, "PALL": 0.0, "VCIT": 0.0}, "sharpe_ratio": 1.5791, "portfolio_return": 1.097028, "portfolio_vol": 0.669367, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250815_0568", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VEA", "BNB-USD", "VNQ", "GLD"], "decision_date": "2025-08-15", "context_summary": "4-asset optimization. Max-Sharpe: 3.874. Portfolio: return=86.71%, vol=21.35%. Weights: w_VEA=0.2428, w_BNB-USD=0.7572, w_VNQ=0.0000, w_GLD=0.0000.", "question": "Assets: VEA, BNB-USD, VNQ, GLD\nAnnualized mean returns: VEA:0.3027, BNB-USD:1.0481, VNQ:0.0232, GLD:-0.1644\nCovariance matrix (annualized):\n[[0.015433, 0.014171, 0.00933, -0.001163], [0.014171, 0.068842, 0.014548, 0.004512], [0.00933, 0.014548, 0.01928, 0.005331], [-0.001163, 0.004512, 0.005331, 0.019538]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VEA=0.2428, w_BNB-USD=0.7572, w_VNQ=0.0000, w_GLD=0.0000", "answer_numeric": 3.8738108148329577, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.2428, w_BNB-USD=0.7572, w_VNQ=0.0000, w_GLD=0.0000\nPortfolio annualized return: 86.71%, volatility: 21.35%\nSharpe ratio: (0.8671 - 0.0400) / 0.2135 = 3.8738", "metadata": {"weights": {"VEA": 0.2428, "BNB-USD": 0.7572, "VNQ": 0.0, "GLD": 0.0}, "sharpe_ratio": 3.8738, "portfolio_return": 0.867119, "portfolio_vol": 0.213516, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250905_0570", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLU", "DOT-USD", "ICSH", "SLV"], "decision_date": "2025-09-05", "context_summary": "4-asset optimization. Max-Sharpe: 3.741. Portfolio: return=6.15%, vol=0.57%. Weights: w_XLU=0.0041, w_DOT-USD=0.0000, w_ICSH=0.9830, w_SLV=0.0129.", "question": "Assets: XLU, DOT-USD, ICSH, SLV\nAnnualized mean returns: XLU:0.1338, DOT-USD:-0.0422, ICSH:0.0542, SLV:0.5950\nCovariance matrix (annualized):\n[[0.014164, 0.030457, 7.5e-05, 0.000948], [0.030457, 0.487441, -0.000116, 0.068095], [7.5e-05, -0.000116, 1.9e-05, 0.000196], [0.000948, 0.068095, 0.000196, 0.050882]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLU=0.0041, w_DOT-USD=0.0000, w_ICSH=0.9830, w_SLV=0.0129", "answer_numeric": 3.7414066288783236, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLU=0.0041, w_DOT-USD=0.0000, w_ICSH=0.9830, w_SLV=0.0129\nPortfolio annualized return: 6.15%, volatility: 0.57%\nSharpe ratio: (0.0615 - 0.0400) / 0.0057 = 3.7414", "metadata": {"weights": {"XLU": 0.0041, "DOT-USD": 0.0, "ICSH": 0.983, "SLV": 0.0129}, "sharpe_ratio": 3.7414, "portfolio_return": 0.061499, "portfolio_vol": 0.005746, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250418_0572", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLRE", "LINK-USD", "JNK", "INDS"], "decision_date": "2025-04-18", "context_summary": "4-asset optimization. Max-Sharpe: -1.181. Portfolio: return=-107.02%, vol=93.99%. Weights: w_XLRE=0.0000, w_LINK-USD=1.0000, w_JNK=0.0000, w_INDS=0.0000.", "question": "Assets: XLRE, LINK-USD, JNK, INDS\nAnnualized mean returns: XLRE:-0.2815, LINK-USD:-1.0702, JNK:-0.1673, INDS:-0.3406\nCovariance matrix (annualized):\n[[0.055437, 0.047834, 0.017118, 0.05768], [0.047834, 0.883463, 0.028265, 0.053198], [0.017118, 0.028265, 0.007267, 0.017843], [0.05768, 0.053198, 0.017843, 0.067638]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bear\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_LINK-USD=1.0000, w_JNK=0.0000, w_INDS=0.0000", "answer_numeric": -1.1811778159562842, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_LINK-USD=1.0000, w_JNK=0.0000, w_INDS=0.0000\nPortfolio annualized return: -107.02%, volatility: 93.99%\nSharpe ratio: (-1.0702 - 0.0400) / 0.9399 = -1.1812", "metadata": {"weights": {"XLRE": 0.0, "LINK-USD": 1.0, "JNK": 0.0, "INDS": 0.0}, "sharpe_ratio": -1.1812, "portfolio_return": -1.070221, "portfolio_vol": 0.939927, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250703_0576", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "LINK-USD", "SCHH", "IEF"], "decision_date": "2025-07-03", "context_summary": "4-asset optimization. Max-Sharpe: 0.550. Portfolio: return=7.51%, vol=6.38%. Weights: w_XLP=0.3378, w_LINK-USD=0.0000, w_SCHH=0.0000, w_IEF=0.6622.", "question": "Assets: XLP, LINK-USD, SCHH, IEF\nAnnualized mean returns: XLP:0.0916, LINK-USD:-0.2506, SCHH:0.0637, IEF:0.0667\nCovariance matrix (annualized):\n[[0.014017, -0.005432, 0.012982, 0.001876], [-0.005432, 0.554818, 0.001121, -0.01359], [0.012982, 0.001121, 0.019968, 0.003381], [0.001876, -0.01359, 0.003381, 0.003726]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.3378, w_LINK-USD=0.0000, w_SCHH=0.0000, w_IEF=0.6622", "answer_numeric": 0.5504297120514067, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLP=0.3378, w_LINK-USD=0.0000, w_SCHH=0.0000, w_IEF=0.6622\nPortfolio annualized return: 7.51%, volatility: 6.38%\nSharpe ratio: (0.0751 - 0.0400) / 0.0638 = 0.5504", "metadata": {"weights": {"XLP": 0.3378, "LINK-USD": 0.0, "SCHH": 0.0, "IEF": 0.6622}, "sharpe_ratio": 0.5504, "portfolio_return": 0.075128, "portfolio_vol": 0.063819, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250226_0579", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "XRP-USD", "EMB", "PDBC"], "decision_date": "2025-02-26", "context_summary": "4-asset optimization. Max-Sharpe: 4.404. Portfolio: return=28.09%, vol=5.47%. Weights: w_IWM=0.0000, w_XRP-USD=0.0096, w_EMB=0.7001, w_PDBC=0.2904.", "question": "Assets: IWM, XRP-USD, EMB, PDBC\nAnnualized mean returns: IWM:-0.2115, XRP-USD:2.0573, EMB:0.2131, PDBC:0.3861\nCovariance matrix (annualized):\n[[0.02722, 0.035085, 0.00559, 0.001291], [0.035085, 0.589231, 0.016945, 0.02604], [0.00559, 0.016945, 0.003457, -0.001489], [0.001291, 0.02604, -0.001489, 0.017537]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_IWM=0.0000, w_XRP-USD=0.0096, w_EMB=0.7001, w_PDBC=0.2904", "answer_numeric": 4.404318095543059, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IWM=0.0000, w_XRP-USD=0.0096, w_EMB=0.7001, w_PDBC=0.2904\nPortfolio annualized return: 28.09%, volatility: 5.47%\nSharpe ratio: (0.2809 - 0.0400) / 0.0547 = 4.4043", "metadata": {"weights": {"IWM": 0.0, "XRP-USD": 0.0096, "EMB": 0.7001, "PDBC": 0.2904}, "sharpe_ratio": 4.4043, "portfolio_return": 0.280942, "portfolio_vol": 0.054706, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250205_0582", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "BNDX", "CSHI"], "decision_date": "2025-02-05", "context_summary": "4-asset optimization. Max-Sharpe: 2.270. Portfolio: return=5.44%, vol=0.64%. Weights: w_VEA=0.0000, w_BTC-USD=0.0035, w_BNDX=0.0000, w_CSHI=0.9965.", "question": "Assets: VEA, BTC-USD, BNDX, CSHI\nAnnualized mean returns: VEA:-0.0081, BTC-USD:0.5896, BNDX:-0.0249, CSHI:0.0526\nCovariance matrix (annualized):\n[[0.01722, 0.023459, 0.002129, 0.000203], [0.023459, 0.18985, 0.006486, 0.000879], [0.002129, 0.006486, 0.001365, 3.8e-05], [0.000203, 0.000879, 3.8e-05, 3.2e-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_VEA=0.0000, w_BTC-USD=0.0035, w_BNDX=0.0000, w_CSHI=0.9965", "answer_numeric": 2.270023929957179, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VEA=0.0000, w_BTC-USD=0.0035, w_BNDX=0.0000, w_CSHI=0.9965\nPortfolio annualized return: 5.44%, volatility: 0.64%\nSharpe ratio: (0.0544 - 0.0400) / 0.0064 = 2.2700", "metadata": {"weights": {"VEA": 0.0, "BTC-USD": 0.0035, "BNDX": 0.0, "CSHI": 0.9965}, "sharpe_ratio": 2.27, "portfolio_return": 0.054443, "portfolio_vol": 0.006362, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9044}} +{"id": "T5_all_20250103_0584", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BNB-USD", "BNO", "IYR"], "decision_date": "2025-01-03", "context_summary": "4-asset optimization. Max-Sharpe: 2.048. Portfolio: return=59.93%, vol=27.31%. Weights: w_XLB=0.0000, w_BNB-USD=0.3495, w_BNO=0.6505, w_IYR=0.0000.", "question": "Assets: XLB, BNB-USD, BNO, IYR\nAnnualized mean returns: XLB:-0.6603, BNB-USD:1.0659, BNO:0.3486, IYR:-0.2100\nCovariance matrix (annualized):\n[[0.019512, 0.020827, 0.005831, 0.013387], [0.020827, 0.336019, 0.02987, 0.008061], [0.005831, 0.02987, 0.047232, 0.004059], [0.013387, 0.008061, 0.004059, 0.030055]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLB=0.0000, w_BNB-USD=0.3495, w_BNO=0.6505, w_IYR=0.0000", "answer_numeric": 2.047538757437186, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLB=0.0000, w_BNB-USD=0.3495, w_BNO=0.6505, w_IYR=0.0000\nPortfolio annualized return: 59.93%, volatility: 27.31%\nSharpe ratio: (0.5993 - 0.0400) / 0.2731 = 2.0475", "metadata": {"weights": {"XLB": 0.0, "BNB-USD": 0.3495, "BNO": 0.6505, "IYR": 0.0}, "sharpe_ratio": 2.0475, "portfolio_return": 0.59927, "portfolio_vol": 0.273143, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250723_0587", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI", "ADA-USD", "DBB", "CSHI"], "decision_date": "2025-07-23", "context_summary": "4-asset optimization. Max-Sharpe: 4.957. Portfolio: return=13.58%, vol=1.93%. Weights: w_ACWI=0.1381, w_ADA-USD=0.0019, w_DBB=0.0489, w_CSHI=0.8111.", "question": "Assets: ACWI, ADA-USD, DBB, CSHI\nAnnualized mean returns: ACWI:0.4616, ADA-USD:1.0857, DBB:0.4074, CSHI:0.0617\nCovariance matrix (annualized):\n[[0.008851, 0.020028, 0.005653, 0.000131], [0.020028, 0.388684, 0.022854, -0.000687], [0.005653, 0.022854, 0.01528, -0.000171], [0.000131, -0.000687, -0.000171, 9.4e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_ACWI=0.1381, w_ADA-USD=0.0019, w_DBB=0.0489, w_CSHI=0.8111", "answer_numeric": 4.956686741076444, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_ACWI=0.1381, w_ADA-USD=0.0019, w_DBB=0.0489, w_CSHI=0.8111\nPortfolio annualized return: 13.58%, volatility: 1.93%\nSharpe ratio: (0.1358 - 0.0400) / 0.0193 = 4.9567", "metadata": {"weights": {"ACWI": 0.1381, "ADA-USD": 0.0019, "DBB": 0.0489, "CSHI": 0.8111}, "sharpe_ratio": 4.9567, "portfolio_return": 0.135782, "portfolio_vol": 0.019324, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250211_0589", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ETH-USD", "MORT", "CSHI"], "decision_date": "2025-02-11", "context_summary": "4-asset optimization. Max-Sharpe: 1.943. Portfolio: return=5.19%, vol=0.61%. Weights: w_IVV=0.0000, w_ETH-USD=0.0000, w_MORT=0.0048, w_CSHI=0.9952.", "question": "Assets: IVV, ETH-USD, MORT, CSHI\nAnnualized mean returns: IVV:0.0276, ETH-USD:-0.5126, MORT:0.1982, CSHI:0.0512\nCovariance matrix (annualized):\n[[0.02174, 0.042104, 0.016611, 0.000465], [0.042104, 0.31153, 0.038575, 0.001709], [0.016611, 0.038575, 0.037764, 0.000321], [0.000465, 0.001709, 0.000321, 3.4e-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_IVV=0.0000, w_ETH-USD=0.0000, w_MORT=0.0048, w_CSHI=0.9952", "answer_numeric": 1.9428436176349007, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_IVV=0.0000, w_ETH-USD=0.0000, w_MORT=0.0048, w_CSHI=0.9952\nPortfolio annualized return: 5.19%, volatility: 0.61%\nSharpe ratio: (0.0519 - 0.0400) / 0.0061 = 1.9428", "metadata": {"weights": {"IVV": 0.0, "ETH-USD": 0.0, "MORT": 0.0048, "CSHI": 0.9952}, "sharpe_ratio": 1.9428, "portfolio_return": 0.051943, "portfolio_vol": 0.006147, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9046}} +{"id": "T5_all_20250321_0591", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "LINK-USD", "SLV", "JNK"], "decision_date": "2025-03-21", "context_summary": "4-asset optimization. Max-Sharpe: 2.959. Portfolio: return=61.64%, vol=19.48%. Weights: w_VTI=0.0000, w_LINK-USD=0.0000, w_SLV=1.0000, w_JNK=0.0000.", "question": "Assets: VTI, LINK-USD, SLV, JNK\nAnnualized mean returns: VTI:-0.3645, LINK-USD:-1.6033, SLV:0.6164, JNK:0.0300\nCovariance matrix (annualized):\n[[0.027705, 0.046945, 0.009339, 0.00508], [0.046945, 0.7784, 0.028183, 0.007859], [0.009339, 0.028183, 0.037951, -0.000318], [0.00508, 0.007859, -0.000318, 0.001662]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0000, w_LINK-USD=0.0000, w_SLV=1.0000, w_JNK=0.0000", "answer_numeric": 2.958991254601369, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0000, w_LINK-USD=0.0000, w_SLV=1.0000, w_JNK=0.0000\nPortfolio annualized return: 61.64%, volatility: 19.48%\nSharpe ratio: (0.6164 - 0.0400) / 0.1948 = 2.9590", "metadata": {"weights": {"VTI": 0.0, "LINK-USD": 0.0, "SLV": 1.0, "JNK": 0.0}, "sharpe_ratio": 2.959, "portfolio_return": 0.616443, "portfolio_vol": 0.194811, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250110_0593", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "XRP-USD", "CORN", "IYR"], "decision_date": "2025-01-10", "context_summary": "4-asset optimization. Max-Sharpe: 5.089. Portfolio: return=595.25%, vol=116.18%. Weights: w_XLY=0.0000, w_XRP-USD=0.9807, w_CORN=0.0193, w_IYR=0.0000.", "question": "Assets: XLY, XRP-USD, CORN, IYR\nAnnualized mean returns: XLY:0.2848, XRP-USD:6.0683, CORN:0.0664, IYR:-0.4293\nCovariance matrix (annualized):\n[[0.040901, 0.060364, 0.002066, 0.015953], [0.060364, 1.403263, 0.005799, 0.012216], [0.002066, 0.005799, 0.017905, 2.6e-05], [0.015953, 0.012216, 2.6e-05, 0.023978]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: sideways\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLY=0.0000, w_XRP-USD=0.9807, w_CORN=0.0193, w_IYR=0.0000", "answer_numeric": 5.088942706929354, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_XRP-USD=0.9807, w_CORN=0.0193, w_IYR=0.0000\nPortfolio annualized return: 595.25%, volatility: 116.18%\nSharpe ratio: (5.9525 - 0.0400) / 1.1618 = 5.0889", "metadata": {"weights": {"XLY": 0.0, "XRP-USD": 0.9807, "CORN": 0.0193, "IYR": 0.0}, "sharpe_ratio": 5.0889, "portfolio_return": 5.952465, "portfolio_vol": 1.161826, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 9045}} +{"id": "T5_all_20250728_0596", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLRE", "ETH-USD", "TIP", "VNQI"], "decision_date": "2025-07-28", "context_summary": "4-asset optimization. Max-Sharpe: 4.768. Portfolio: return=21.64%, vol=3.70%. Weights: w_XLRE=0.0000, w_ETH-USD=0.0421, w_TIP=0.7374, w_VNQI=0.2205.", "question": "Assets: XLRE, ETH-USD, TIP, VNQI\nAnnualized mean returns: XLRE:0.2785, ETH-USD:2.1675, TIP:0.0648, VNQI:0.3511\nCovariance matrix (annualized):\n[[0.013175, 0.013849, -4.3e-05, 0.006624], [0.013849, 0.328576, 0.000538, 0.010373], [-4.3e-05, 0.000538, 0.000219, 3.6e-05], [0.006624, 0.010373, 3.6e-05, 0.008844]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_XLRE=0.0000, w_ETH-USD=0.0421, w_TIP=0.7374, w_VNQI=0.2205", "answer_numeric": 4.768144685099367, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLRE=0.0000, w_ETH-USD=0.0421, w_TIP=0.7374, w_VNQI=0.2205\nPortfolio annualized return: 21.64%, volatility: 3.70%\nSharpe ratio: (0.2164 - 0.0400) / 0.0370 = 4.7681", "metadata": {"weights": {"XLRE": 0.0, "ETH-USD": 0.0421, "TIP": 0.7374, "VNQI": 0.2205}, "sharpe_ratio": 4.7681, "portfolio_return": 0.216398, "portfolio_vol": 0.036995, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250611_0598", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BTC-USD", "BIL", "DBA"], "decision_date": "2025-06-11", "context_summary": "4-asset optimization. Max-Sharpe: 5.723. Portfolio: return=11.29%, vol=1.27%. Weights: w_VTI=0.0502, w_BTC-USD=0.0253, w_BIL=0.9227, w_DBA=0.0018.", "question": "Assets: VTI, BTC-USD, BIL, DBA\nAnnualized mean returns: VTI:0.7537, BTC-USD:1.4545, BIL:0.0411, DBA:0.1865\nCovariance matrix (annualized):\n[[0.029241, 0.006051, -3.7e-05, 0.001549], [0.006051, 0.11213, -7e-06, 0.007988], [-3.7e-05, -7e-06, 5e-06, 2.2e-05], [0.001549, 0.007988, 2.2e-05, 0.01454]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.0502, w_BTC-USD=0.0253, w_BIL=0.9227, w_DBA=0.0018", "answer_numeric": 5.723288532808898, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0502, w_BTC-USD=0.0253, w_BIL=0.9227, w_DBA=0.0018\nPortfolio annualized return: 11.29%, volatility: 1.27%\nSharpe ratio: (0.1129 - 0.0400) / 0.0127 = 5.7233", "metadata": {"weights": {"VTI": 0.0502, "BTC-USD": 0.0253, "BIL": 0.9227, "DBA": 0.0018}, "sharpe_ratio": 5.7233, "portfolio_return": 0.112925, "portfolio_vol": 0.012742, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250930_0601", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "ETH-USD", "CORN", "CSHI"], "decision_date": "2025-09-30", "context_summary": "4-asset optimization. Max-Sharpe: 2.635. Portfolio: return=19.03%, vol=5.71%. Weights: w_FXI=0.2654, w_ETH-USD=0.0000, w_CORN=0.0813, w_CSHI=0.6533.", "question": "Assets: FXI, ETH-USD, CORN, CSHI\nAnnualized mean returns: FXI:0.5553, ETH-USD:0.7748, CORN:0.1402, CSHI:0.0483\nCovariance matrix (annualized):\n[[0.040208, 0.06576, 0.001995, 0.000502], [0.06576, 0.520567, -0.009391, 0.001738], [0.001995, -0.009391, 0.020064, 1.3e-05], [0.000502, 0.001738, 1.3e-05, 7e-05]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_FXI=0.2654, w_ETH-USD=0.0000, w_CORN=0.0813, w_CSHI=0.6533", "answer_numeric": 2.634500706743261, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_FXI=0.2654, w_ETH-USD=0.0000, w_CORN=0.0813, w_CSHI=0.6533\nPortfolio annualized return: 19.03%, volatility: 5.71%\nSharpe ratio: (0.1903 - 0.0400) / 0.0571 = 2.6345", "metadata": {"weights": {"FXI": 0.2654, "ETH-USD": 0.0, "CORN": 0.0813, "CSHI": 0.6533}, "sharpe_ratio": 2.6345, "portfolio_return": 0.190312, "portfolio_vol": 0.057055, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250507_0603", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "AVAX-USD", "BIL", "ITB"], "decision_date": "2025-05-07", "context_summary": "4-asset optimization. Max-Sharpe: 3.045. Portfolio: return=8.62%, vol=1.52%. Weights: w_XLY=0.0000, w_AVAX-USD=0.0197, w_BIL=0.9803, w_ITB=0.0000.", "question": "Assets: XLY, AVAX-USD, BIL, ITB\nAnnualized mean returns: XLY:-0.4938, AVAX-USD:2.3626, BIL:0.0405, ITB:-0.4895\nCovariance matrix (annualized):\n[[0.104629, 0.124542, -4.8e-05, 0.073981], [0.124542, 0.617813, -0.000341, 0.081087], [-4.8e-05, -0.000341, 4e-06, -8.1e-05], [0.073981, 0.081087, -8.1e-05, 0.104023]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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_AVAX-USD=0.0197, w_BIL=0.9803, w_ITB=0.0000", "answer_numeric": 3.044563454364132, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_XLY=0.0000, w_AVAX-USD=0.0197, w_BIL=0.9803, w_ITB=0.0000\nPortfolio annualized return: 8.62%, volatility: 1.52%\nSharpe ratio: (0.0862 - 0.0400) / 0.0152 = 3.0446", "metadata": {"weights": {"XLY": 0.0, "AVAX-USD": 0.0197, "BIL": 0.9803, "ITB": 0.0}, "sharpe_ratio": 3.0446, "portfolio_return": 0.086181, "portfolio_vol": 0.015168, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20250325_0606", "template": "T5", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "MATIC-USD", "VNQ", "TLT"], "decision_date": "2025-03-25", "context_summary": "4-asset optimization. Max-Sharpe: 2.192. Portfolio: return=27.25%, vol=10.61%. Weights: w_EWJ=0.4336, w_MATIC-USD=0.0000, w_VNQ=0.0000, w_TLT=0.5664.", "question": "Assets: EWJ, MATIC-USD, VNQ, TLT\nAnnualized mean returns: EWJ:0.2963, MATIC-USD:-3.1559, VNQ:0.0981, TLT:0.2543\nCovariance matrix (annualized):\n[[0.02642, 0.003579, 0.01328, 0.001665], [0.003579, 0.479153, 0.009592, -0.018519], [0.01328, 0.009592, 0.02653, 0.004471], [0.001665, -0.018519, 0.004471, 0.017026]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 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=0.4336, w_MATIC-USD=0.0000, w_VNQ=0.0000, w_TLT=0.5664", "answer_numeric": 2.1924560254077967, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_EWJ=0.4336, w_MATIC-USD=0.0000, w_VNQ=0.0000, w_TLT=0.5664\nPortfolio annualized return: 27.25%, volatility: 10.61%\nSharpe ratio: (0.2725 - 0.0400) / 0.1061 = 2.1925", "metadata": {"weights": {"EWJ": 0.4336, "MATIC-USD": 0.0, "VNQ": 0.0, "TLT": 0.5664}, "sharpe_ratio": 2.1925, "portfolio_return": 0.272518, "portfolio_vol": 0.106054, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T5_all_20251021_0609", "template": "T5", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VTI", "LINK-USD", "BIL", "IGOV"], "decision_date": "2025-10-21", "context_summary": "4-asset optimization. Max-Sharpe: 2.977. Portfolio: return=5.89%, vol=0.64%. Weights: w_VTI=0.0527, w_LINK-USD=0.0000, w_BIL=0.9369, w_IGOV=0.0104.", "question": "Assets: VTI, LINK-USD, BIL, IGOV\nAnnualized mean returns: VTI:0.3645, LINK-USD:-1.2610, BIL:0.0411, IGOV:0.1124\nCovariance matrix (annualized):\n[[0.01332, 0.06643, -2.3e-05, 0.001226], [0.06643, 0.729349, -7.6e-05, 0.003818], [-2.3e-05, -7.6e-05, 4e-06, 2.3e-05], [0.001226, 0.003818, 2.3e-05, 0.006589]]\nRisk-free rate: 4.00%\nConstraints: weights sum to 1, all weights \u2265 0\nMarket regime: bull\n\nCompute the portfolio weights that maximize the Sharpe Ratio for the above assets.", "answer": "w_VTI=0.0527, w_LINK-USD=0.0000, w_BIL=0.9369, w_IGOV=0.0104", "answer_numeric": 2.9770577025125107, "explanation": "Solved max-Sharpe via SLSQP numerical optimization.\nOptimal weights: w_VTI=0.0527, w_LINK-USD=0.0000, w_BIL=0.9369, w_IGOV=0.0104\nPortfolio annualized return: 5.89%, volatility: 0.64%\nSharpe ratio: (0.0589 - 0.0400) / 0.0064 = 2.9771", "metadata": {"weights": {"VTI": 0.0527, "LINK-USD": 0.0, "BIL": 0.9369, "IGOV": 0.0104}, "sharpe_ratio": 2.9771, "portfolio_return": 0.058907, "portfolio_vol": 0.006351, "n_assets": 4, "optimizer_success": true, "has_text": true, "text_chars": 3020}} +{"id": "T6_all_20251027_0001", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VTI", "ADA-USD", "SCHH", "CPER"], "decision_date": "2025-10-27", "context_summary": "Max weight deviation: 0.0171, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VTI: current=0.2541, target=0.2500\n ADA-USD: current=0.2423, target=0.2500\n SCHH: current=0.2671, target=0.2500\n CPER: current=0.2365, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0171.\nRebalancing threshold: 0.0500.\n0.0171 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0424, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2541, "ADA-USD": 0.2423, "SCHH": 0.2671, "CPER": 0.2365}, "target_weights": {"VTI": 0.25, "ADA-USD": 0.25, "SCHH": 0.25, "CPER": 0.25}, "max_deviation": 0.0171, "total_turnover": 0.042376, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9044, "primary_asset": "SCHH", "primary_trade": 0.0171}} +{"id": "T6_all_20251209_0002", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BTC-USD", "IAU", "IYR"], "decision_date": "2025-12-09", "context_summary": "Max weight deviation: 0.0454, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VTI: current=0.2534, target=0.2500\n BTC-USD: current=0.2874, target=0.2500\n IAU: current=0.1850, target=0.2500\n IYR: current=0.2742, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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 IAU", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0454.\nRebalancing threshold: 0.0500.\n0.0454 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0908, transaction cost = 0.000091 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2534, "BTC-USD": 0.2874, "IAU": 0.185, "IYR": 0.2742}, "target_weights": {"VTI": 0.25, "BTC-USD": 0.25, "IAU": 0.25, "IYR": 0.25}, "max_deviation": 0.065, "total_turnover": 0.090808, "transaction_cost": 9.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "IAU", "primary_trade": -0.065}} +{"id": "T6_all_20250716_0004", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IVV", "XRP-USD", "HAUZ", "WEAT"], "decision_date": "2025-07-16", "context_summary": "Max weight deviation: 0.0299, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2728, target=0.2500\n XRP-USD: current=0.2523, target=0.2500\n HAUZ: current=0.2899, target=0.2500\n WEAT: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of WEAT", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0299.\nRebalancing threshold: 0.0500.\n0.0299 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0598, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2728, "XRP-USD": 0.2523, "HAUZ": 0.2899, "WEAT": 0.185}, "target_weights": {"IVV": 0.25, "XRP-USD": 0.25, "HAUZ": 0.25, "WEAT": 0.25}, "max_deviation": 0.06504, "total_turnover": 0.059819, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "WEAT", "primary_trade": -0.065}} +{"id": "T6_all_20250424_0006", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY", "MATIC-USD", "VNQ", "SOYB"], "decision_date": "2025-04-24", "context_summary": "Max weight deviation: 0.0272, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n SPY: current=0.2261, target=0.2500\n MATIC-USD: current=0.2999, target=0.2500\n VNQ: current=0.1850, target=0.2500\n SOYB: current=0.2890, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0272.\nRebalancing threshold: 0.0500.\n0.0272 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0744, transaction cost = 0.000074 (negligible vs. drift).", "metadata": {"current_weights": {"SPY": 0.2261, "MATIC-USD": 0.2999, "VNQ": 0.185, "SOYB": 0.289}, "target_weights": {"SPY": 0.25, "MATIC-USD": 0.25, "VNQ": 0.25, "SOYB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.074419, "transaction_cost": 7.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9044, "primary_asset": "VNQ", "primary_trade": -0.065}} +{"id": "T6_all_20250521_0009", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "LINK-USD", "BIL", "VNQ"], "decision_date": "2025-05-21", "context_summary": "Max weight deviation: 0.0342, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.2708, target=0.2500\n LINK-USD: current=0.2158, target=0.2500\n BIL: current=0.2409, target=0.2500\n VNQ: current=0.2725, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0342.\nRebalancing threshold: 0.0500.\n0.0342 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0867, transaction cost = 0.000087 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2708, "LINK-USD": 0.2158, "BIL": 0.2409, "VNQ": 0.2725}, "target_weights": {"ACWI": 0.25, "LINK-USD": 0.25, "BIL": 0.25, "VNQ": 0.25}, "max_deviation": 0.0342, "total_turnover": 0.086697, "transaction_cost": 8.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": -0.0342}} +{"id": "T6_all_20250131_0010", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "LINK-USD", "DBB", "ICSH"], "decision_date": "2025-01-31", "context_summary": "Max weight deviation: 0.0041, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.1853, target=0.2500\n LINK-USD: current=0.2440, target=0.2500\n DBB: current=0.2710, target=0.2500\n ICSH: current=0.2996, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0647 of EEM", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0041.\nRebalancing threshold: 0.0500.\n0.0041 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0090, transaction cost = 0.000009 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.1853, "LINK-USD": 0.244, "DBB": 0.271, "ICSH": 0.2996}, "target_weights": {"EEM": 0.25, "LINK-USD": 0.25, "DBB": 0.25, "ICSH": 0.25}, "max_deviation": 0.064706, "total_turnover": 0.008968, "transaction_cost": 9e-06, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "EEM", "primary_trade": -0.0647}} +{"id": "T6_all_20250225_0013", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "XRP-USD", "HYG", "CPER"], "decision_date": "2025-02-25", "context_summary": "Max weight deviation: 0.0279, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.2221, target=0.2500\n XRP-USD: current=0.2410, target=0.2500\n HYG: current=0.2709, target=0.2500\n CPER: current=0.2660, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0279.\nRebalancing threshold: 0.0500.\n0.0279 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0738, transaction cost = 0.000074 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.2221, "XRP-USD": 0.241, "HYG": 0.2709, "CPER": 0.266}, "target_weights": {"XLP": 0.25, "XRP-USD": 0.25, "HYG": 0.25, "CPER": 0.25}, "max_deviation": 0.0279, "total_turnover": 0.0738, "transaction_cost": 7.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "XLP", "primary_trade": -0.0279}} +{"id": "T6_all_20250520_0016", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "MATIC-USD", "SHV", "VNQI"], "decision_date": "2025-05-20", "context_summary": "Max weight deviation: 0.0210, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VLUE: current=0.2704, target=0.2500\n MATIC-USD: current=0.2887, target=0.2500\n SHV: current=0.1850, target=0.2500\n VNQI: 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 SHV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0210.\nRebalancing threshold: 0.0500.\n0.0210 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0421, transaction cost = 0.000042 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2704, "MATIC-USD": 0.2887, "SHV": 0.185, "VNQI": 0.2559}, "target_weights": {"VLUE": 0.25, "MATIC-USD": 0.25, "SHV": 0.25, "VNQI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.042098, "transaction_cost": 4.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SHV", "primary_trade": -0.065}} +{"id": "T6_all_20250221_0019", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "MATIC-USD", "SCHP", "SGOV"], "decision_date": "2025-02-21", "context_summary": "Max weight deviation: 0.0138, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2550, target=0.2500\n MATIC-USD: current=0.2510, target=0.2500\n SCHP: current=0.2362, target=0.2500\n SGOV: current=0.2578, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0138.\nRebalancing threshold: 0.0500.\n0.0138 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0277, transaction cost = 0.000028 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.255, "MATIC-USD": 0.251, "SCHP": 0.2362, "SGOV": 0.2578}, "target_weights": {"QUAL": 0.25, "MATIC-USD": 0.25, "SCHP": 0.25, "SGOV": 0.25}, "max_deviation": 0.0138, "total_turnover": 0.027687, "transaction_cost": 2.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9044, "primary_asset": "SCHP", "primary_trade": -0.0138}} +{"id": "T6_all_20250317_0020", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EEM", "BTC-USD", "DBA", "ICSH"], "decision_date": "2025-03-17", "context_summary": "Max weight deviation: 0.0372, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.2331, target=0.2500\n BTC-USD: current=0.2411, target=0.2500\n DBA: current=0.2107, target=0.2500\n ICSH: current=0.3151, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0372.\nRebalancing threshold: 0.0500.\n0.0372 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0745, transaction cost = 0.000074 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2331, "BTC-USD": 0.2411, "DBA": 0.2107, "ICSH": 0.3151}, "target_weights": {"EEM": 0.25, "BTC-USD": 0.25, "DBA": 0.25, "ICSH": 0.25}, "max_deviation": 0.065055, "total_turnover": 0.074477, "transaction_cost": 7.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "ICSH", "primary_trade": 0.0651}} +{"id": "T6_all_20250203_0026", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "ETH-USD", "ICSH", "JNK"], "decision_date": "2025-02-03", "context_summary": "Max weight deviation: 0.0101, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n SPY: current=0.2193, target=0.2500\n ETH-USD: current=0.3152, target=0.2500\n ICSH: current=0.2656, target=0.2500\n JNK: current=0.1999, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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 ETH-USD", "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 = 0.0251, transaction cost = 0.000025 (negligible vs. drift).", "metadata": {"current_weights": {"SPY": 0.2193, "ETH-USD": 0.3152, "ICSH": 0.2656, "JNK": 0.1999}, "target_weights": {"SPY": 0.25, "ETH-USD": 0.25, "ICSH": 0.25, "JNK": 0.25}, "max_deviation": 0.065203, "total_turnover": 0.025083, "transaction_cost": 2.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "ETH-USD", "primary_trade": 0.0652}} +{"id": "T6_all_20251008_0027", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VTI", "BNB-USD", "SOYB", "LQD"], "decision_date": "2025-10-08", "context_summary": "Max weight deviation: 0.0247, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VTI: current=0.2339, target=0.2500\n BNB-USD: current=0.2545, target=0.2500\n SOYB: current=0.2747, target=0.2500\n LQD: current=0.2370, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0247.\nRebalancing threshold: 0.0500.\n0.0247 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0583, transaction cost = 0.000058 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2339, "BNB-USD": 0.2545, "SOYB": 0.2747, "LQD": 0.237}, "target_weights": {"VTI": 0.25, "BNB-USD": 0.25, "SOYB": 0.25, "LQD": 0.25}, "max_deviation": 0.0247, "total_turnover": 0.058298, "transaction_cost": 5.8e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SOYB", "primary_trade": 0.0247}} +{"id": "T6_all_20250108_0030", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "BNB-USD", "VNQ", "IGOV"], "decision_date": "2025-01-08", "context_summary": "Max weight deviation: 0.0283, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLF: current=0.2958, target=0.2500\n BNB-USD: current=0.1850, target=0.2500\n VNQ: current=0.2491, target=0.2500\n IGOV: current=0.2700, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of BNB-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0283.\nRebalancing threshold: 0.0500.\n0.0283 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0573, transaction cost = 0.000057 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2958, "BNB-USD": 0.185, "VNQ": 0.2491, "IGOV": 0.27}, "target_weights": {"XLF": 0.25, "BNB-USD": 0.25, "VNQ": 0.25, "IGOV": 0.25}, "max_deviation": 0.064957, "total_turnover": 0.057293, "transaction_cost": 5.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "BNB-USD", "primary_trade": -0.065}} +{"id": "T6_all_20250212_0032", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "BNB-USD", "BIL", "VNQ"], "decision_date": "2025-02-12", "context_summary": "Max weight deviation: 0.0248, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLI: current=0.3043, target=0.2500\n BNB-USD: current=0.2372, target=0.2500\n BIL: current=0.2736, target=0.2500\n VNQ: 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 VNQ", "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 = 0.0594, transaction cost = 0.000059 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.3043, "BNB-USD": 0.2372, "BIL": 0.2736, "VNQ": 0.185}, "target_weights": {"XLI": 0.25, "BNB-USD": 0.25, "BIL": 0.25, "VNQ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.059384, "transaction_cost": 5.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "VNQ", "primary_trade": -0.065}} +{"id": "T6_all_20251106_0034", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "BNB-USD", "CSHI", "BNO"], "decision_date": "2025-11-06", "context_summary": "Max weight deviation: 0.0072, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLB: current=0.2825, target=0.2500\n BNB-USD: current=0.2789, target=0.2500\n CSHI: current=0.1850, target=0.2500\n BNO: 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 CSHI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0072.\nRebalancing threshold: 0.0500.\n0.0072 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0144, transaction cost = 0.000014 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2825, "BNB-USD": 0.2789, "CSHI": 0.185, "BNO": 0.2536}, "target_weights": {"XLB": 0.25, "BNB-USD": 0.25, "CSHI": 0.25, "BNO": 0.25}, "max_deviation": 0.065, "total_turnover": 0.014429, "transaction_cost": 1.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "CSHI", "primary_trade": -0.065}} +{"id": "T6_all_20250318_0036", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ETH-USD", "ICSH", "ITB"], "decision_date": "2025-03-18", "context_summary": "Max weight deviation: 0.0196, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.1922, target=0.2500\n ETH-USD: current=0.3149, target=0.2500\n ICSH: current=0.2406, target=0.2500\n ITB: 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 0.0649 of ETH-USD", "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 = 0.0405, transaction cost = 0.000040 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.1922, "ETH-USD": 0.3149, "ICSH": 0.2406, "ITB": 0.2522}, "target_weights": {"QUAL": 0.25, "ETH-USD": 0.25, "ICSH": 0.25, "ITB": 0.25}, "max_deviation": 0.064896, "total_turnover": 0.040493, "transaction_cost": 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_20251121_0037", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "BNB-USD", "IEF", "PDBC"], "decision_date": "2025-11-21", "context_summary": "Max weight deviation: 0.0240, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.2713, target=0.2500\n BNB-USD: current=0.2427, target=0.2500\n IEF: current=0.2600, target=0.2500\n PDBC: current=0.2260, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (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 = 0.0626, transaction cost = 0.000063 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.2713, "BNB-USD": 0.2427, "IEF": 0.26, "PDBC": 0.226}, "target_weights": {"EFA": 0.25, "BNB-USD": 0.25, "IEF": 0.25, "PDBC": 0.25}, "max_deviation": 0.024, "total_turnover": 0.062616, "transaction_cost": 6.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "PDBC", "primary_trade": -0.024}} +{"id": "T6_all_20251020_0041", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF", "ADA-USD", "BNO", "HAUZ"], "decision_date": "2025-10-20", "context_summary": "Max weight deviation: 0.0416, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLF: current=0.2638, target=0.2500\n ADA-USD: current=0.2411, target=0.2500\n BNO: current=0.2084, target=0.2500\n HAUZ: current=0.2866, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0416.\nRebalancing threshold: 0.0500.\n0.0416 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1009, transaction cost = 0.000101 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.2638, "ADA-USD": 0.2411, "BNO": 0.2084, "HAUZ": 0.2866}, "target_weights": {"XLF": 0.25, "ADA-USD": 0.25, "BNO": 0.25, "HAUZ": 0.25}, "max_deviation": 0.0416, "total_turnover": 0.100945, "transaction_cost": 0.000101, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNO", "primary_trade": -0.0416}} +{"id": "T6_all_20250422_0044", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["^VIX", "AVAX-USD", "IYR", "SCHP"], "decision_date": "2025-04-22", "context_summary": "Max weight deviation: 0.0193, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.1911, target=0.2500\n AVAX-USD: current=0.2167, target=0.2500\n IYR: current=0.2770, target=0.2500\n SCHP: current=0.3151, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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 SCHP", "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 = 0.0547, transaction cost = 0.000055 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.1911, "AVAX-USD": 0.2167, "IYR": 0.277, "SCHP": 0.3151}, "target_weights": {"^VIX": 0.25, "AVAX-USD": 0.25, "IYR": 0.25, "SCHP": 0.25}, "max_deviation": 0.065106, "total_turnover": 0.054698, "transaction_cost": 5.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SCHP", "primary_trade": 0.0651}} +{"id": "T6_all_20250430_0045", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLU", "LINK-USD", "ITB", "IGOV"], "decision_date": "2025-04-30", "context_summary": "Max weight deviation: 0.0133, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLU: current=0.2436, target=0.2500\n LINK-USD: current=0.2487, target=0.2500\n ITB: current=0.2633, target=0.2500\n IGOV: current=0.2444, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (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 = 0.0266, transaction cost = 0.000027 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2436, "LINK-USD": 0.2487, "ITB": 0.2633, "IGOV": 0.2444}, "target_weights": {"XLU": 0.25, "LINK-USD": 0.25, "ITB": 0.25, "IGOV": 0.25}, "max_deviation": 0.0133, "total_turnover": 0.026555, "transaction_cost": 2.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ITB", "primary_trade": 0.0133}} +{"id": "T6_all_20251218_0046", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "ADA-USD", "WEAT", "VCIT"], "decision_date": "2025-12-18", "context_summary": "Max weight deviation: 0.0162, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2925, target=0.2500\n ADA-USD: current=0.2271, target=0.2500\n WEAT: current=0.2953, 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: 0.0162.\nRebalancing threshold: 0.0500.\n0.0162 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0438, transaction cost = 0.000044 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2925, "ADA-USD": 0.2271, "WEAT": 0.2953, "VCIT": 0.185}, "target_weights": {"XLY": 0.25, "ADA-USD": 0.25, "WEAT": 0.25, "VCIT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.043817, "transaction_cost": 4.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "VCIT", "primary_trade": -0.065}} +{"id": "T6_all_20250303_0048", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "AVAX-USD", "CSHI", "INDS"], "decision_date": "2025-03-03", "context_summary": "Max weight deviation: 0.0320, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2758, target=0.2500\n AVAX-USD: current=0.1850, target=0.2500\n CSHI: current=0.2776, target=0.2500\n INDS: current=0.2616, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0320.\nRebalancing threshold: 0.0500.\n0.0320 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0641, transaction cost = 0.000064 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2758, "AVAX-USD": 0.185, "CSHI": 0.2776, "INDS": 0.2616}, "target_weights": {"QUAL": 0.25, "AVAX-USD": 0.25, "CSHI": 0.25, "INDS": 0.25}, "max_deviation": 0.065, "total_turnover": 0.064068, "transaction_cost": 6.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "AVAX-USD", "primary_trade": -0.065}} +{"id": "T6_all_20251009_0049", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "ADA-USD", "BNDX", "ICSH"], "decision_date": "2025-10-09", "context_summary": "Max weight deviation: 0.0510, threshold: 0.05. Decision: yes (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.2432, target=0.2500\n ADA-USD: current=0.2515, target=0.2500\n BNDX: current=0.2253, target=0.2500\n ICSH: current=0.2800, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0510.\nRebalancing threshold: 0.0500.\n0.0510 > 0.0500 \u2192 decision: 'yes'.\nIf rebalanced: total turnover = 0.1069, transaction cost = 0.000107 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2432, "ADA-USD": 0.2515, "BNDX": 0.2253, "ICSH": 0.28}, "target_weights": {"IWM": 0.25, "ADA-USD": 0.25, "BNDX": 0.25, "ICSH": 0.25}, "max_deviation": 0.029984, "total_turnover": 0.106902, "transaction_cost": 0.000107, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": 0.03}} +{"id": "T6_all_20250602_0051", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "XRP-USD", "SGOV", "LQD"], "decision_date": "2025-06-02", "context_summary": "Max weight deviation: 0.0175, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.2497, target=0.2500\n XRP-USD: current=0.2675, target=0.2500\n SGOV: current=0.2334, target=0.2500\n LQD: current=0.2494, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (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 = 0.0351, transaction cost = 0.000035 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2497, "XRP-USD": 0.2675, "SGOV": 0.2334, "LQD": 0.2494}, "target_weights": {"USMV": 0.25, "XRP-USD": 0.25, "SGOV": 0.25, "LQD": 0.25}, "max_deviation": 0.0175, "total_turnover": 0.035087, "transaction_cost": 3.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": 0.0175}} +{"id": "T6_all_20250523_0053", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "SOL-USD", "SHV", "BIL"], "decision_date": "2025-05-23", "context_summary": "Max weight deviation: 0.0367, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n SPY: current=0.2264, target=0.2500\n SOL-USD: current=0.2283, target=0.2500\n SHV: current=0.2585, target=0.2500\n BIL: 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 = 0.0905, transaction cost = 0.000091 (negligible vs. drift).", "metadata": {"current_weights": {"SPY": 0.2264, "SOL-USD": 0.2283, "SHV": 0.2585, "BIL": 0.2867}, "target_weights": {"SPY": 0.25, "SOL-USD": 0.25, "SHV": 0.25, "BIL": 0.25}, "max_deviation": 0.0367, "total_turnover": 0.090545, "transaction_cost": 9.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BIL", "primary_trade": 0.0367}} +{"id": "T6_all_20251216_0054", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "DOT-USD", "VCIT", "VNQI"], "decision_date": "2025-12-16", "context_summary": "Max weight deviation: 0.0190, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n SPY: current=0.2079, target=0.2500\n DOT-USD: current=0.2349, target=0.2500\n VCIT: current=0.3150, target=0.2500\n VNQI: current=0.2421, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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 VCIT", "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 = 0.0380, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"SPY": 0.2079, "DOT-USD": 0.2349, "VCIT": 0.315, "VNQI": 0.2421}, "target_weights": {"SPY": 0.25, "DOT-USD": 0.25, "VCIT": 0.25, "VNQI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.037967, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "VCIT", "primary_trade": 0.065}} +{"id": "T6_all_20251223_0056", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "XRP-USD", "MORT", "SGOV"], "decision_date": "2025-12-23", "context_summary": "Max weight deviation: 0.0377, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2113, target=0.2500\n XRP-USD: current=0.2670, target=0.2500\n MORT: current=0.2067, 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: 0.0377.\nRebalancing threshold: 0.0500.\n0.0377 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0952, transaction cost = 0.000095 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2113, "XRP-USD": 0.267, "MORT": 0.2067, "SGOV": 0.3149}, "target_weights": {"XLY": 0.25, "XRP-USD": 0.25, "MORT": 0.25, "SGOV": 0.25}, "max_deviation": 0.064946, "total_turnover": 0.09516, "transaction_cost": 9.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "SGOV", "primary_trade": 0.0649}} +{"id": "T6_all_20250721_0057", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "DOT-USD", "DBA", "VNQ"], "decision_date": "2025-07-21", "context_summary": "Max weight deviation: 0.0299, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n FXI: current=0.2649, target=0.2500\n DOT-USD: current=0.2518, target=0.2500\n DBA: current=0.2201, target=0.2500\n VNQ: current=0.2632, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0299.\nRebalancing threshold: 0.0500.\n0.0299 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0598, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2649, "DOT-USD": 0.2518, "DBA": 0.2201, "VNQ": 0.2632}, "target_weights": {"FXI": 0.25, "DOT-USD": 0.25, "DBA": 0.25, "VNQ": 0.25}, "max_deviation": 0.0299, "total_turnover": 0.059796, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DBA", "primary_trade": -0.0299}} +{"id": "T6_all_20250826_0061", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY", "DOT-USD", "BNO", "ICSH"], "decision_date": "2025-08-26", "context_summary": "Max weight deviation: 0.0034, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n SPY: current=0.2533, target=0.2500\n DOT-USD: current=0.2510, target=0.2500\n BNO: current=0.2491, target=0.2500\n ICSH: current=0.2466, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0034.\nRebalancing threshold: 0.0500.\n0.0034 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0085, transaction cost = 0.000009 (negligible vs. drift).", "metadata": {"current_weights": {"SPY": 0.2533, "DOT-USD": 0.251, "BNO": 0.2491, "ICSH": 0.2466}, "target_weights": {"SPY": 0.25, "DOT-USD": 0.25, "BNO": 0.25, "ICSH": 0.25}, "max_deviation": 0.0034, "total_turnover": 0.008547, "transaction_cost": 9e-06, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.0034}} +{"id": "T6_all_20251030_0063", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLI", "AVAX-USD", "BNDX", "PDBC"], "decision_date": "2025-10-30", "context_summary": "Max weight deviation: 0.0204, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLI: current=0.2507, target=0.2500\n AVAX-USD: current=0.2296, target=0.2500\n BNDX: current=0.2640, target=0.2500\n PDBC: current=0.2558, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0204.\nRebalancing threshold: 0.0500.\n0.0204 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0408, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2507, "AVAX-USD": 0.2296, "BNDX": 0.264, "PDBC": 0.2558}, "target_weights": {"XLI": 0.25, "AVAX-USD": 0.25, "BNDX": 0.25, "PDBC": 0.25}, "max_deviation": 0.0204, "total_turnover": 0.0408, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9044, "primary_asset": "AVAX-USD", "primary_trade": -0.0204}} +{"id": "T6_all_20250915_0068", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IVV", "BNB-USD", "SGOV", "IYR"], "decision_date": "2025-09-15", "context_summary": "Max weight deviation: 0.0381, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2274, target=0.2500\n BNB-USD: current=0.3149, target=0.2500\n SGOV: current=0.2148, target=0.2500\n IYR: current=0.2428, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0649 of BNB-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0381.\nRebalancing threshold: 0.0500.\n0.0381 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0762, transaction cost = 0.000076 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2274, "BNB-USD": 0.3149, "SGOV": 0.2148, "IYR": 0.2428}, "target_weights": {"IVV": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "IYR": 0.25}, "max_deviation": 0.064946, "total_turnover": 0.076181, "transaction_cost": 7.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": 0.0649}} +{"id": "T6_all_20250130_0069", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VEA", "BTC-USD", "VNQI", "BIL"], "decision_date": "2025-01-30", "context_summary": "Max weight deviation: 0.0127, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VEA: current=0.2627, target=0.2500\n BTC-USD: current=0.2380, target=0.2500\n VNQI: current=0.2604, target=0.2500\n BIL: current=0.2389, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0127.\nRebalancing threshold: 0.0500.\n0.0127 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0462, transaction cost = 0.000046 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.2627, "BTC-USD": 0.238, "VNQI": 0.2604, "BIL": 0.2389}, "target_weights": {"VEA": 0.25, "BTC-USD": 0.25, "VNQI": 0.25, "BIL": 0.25}, "max_deviation": 0.0127, "total_turnover": 0.046214, "transaction_cost": 4.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "VEA", "primary_trade": 0.0127}} +{"id": "T6_all_20250307_0071", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "SOL-USD", "VNQ", "ICSH"], "decision_date": "2025-03-07", "context_summary": "Max weight deviation: 0.0172, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2374, target=0.2500\n SOL-USD: current=0.2408, target=0.2500\n VNQ: current=0.2672, target=0.2500\n ICSH: current=0.2546, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0172.\nRebalancing threshold: 0.0500.\n0.0172 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0436, transaction cost = 0.000044 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2374, "SOL-USD": 0.2408, "VNQ": 0.2672, "ICSH": 0.2546}, "target_weights": {"IVV": 0.25, "SOL-USD": 0.25, "VNQ": 0.25, "ICSH": 0.25}, "max_deviation": 0.0172, "total_turnover": 0.043553, "transaction_cost": 4.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "VNQ", "primary_trade": 0.0172}} +{"id": "T6_all_20250512_0073", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "ETH-USD", "BIL", "IAU"], "decision_date": "2025-05-12", "context_summary": "Max weight deviation: 0.0180, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VLUE: current=0.2320, target=0.2500\n ETH-USD: current=0.2498, target=0.2500\n BIL: current=0.2673, target=0.2500\n IAU: current=0.2510, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0180.\nRebalancing threshold: 0.0500.\n0.0180 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0366, transaction cost = 0.000037 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.232, "ETH-USD": 0.2498, "BIL": 0.2673, "IAU": 0.251}, "target_weights": {"VLUE": 0.25, "ETH-USD": 0.25, "BIL": 0.25, "IAU": 0.25}, "max_deviation": 0.018, "total_turnover": 0.036566, "transaction_cost": 3.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "VLUE", "primary_trade": -0.018}} +{"id": "T6_all_20250129_0075", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "ADA-USD", "ICSH", "DBA"], "decision_date": "2025-01-29", "context_summary": "Max weight deviation: 0.0120, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.2496, target=0.2500\n ADA-USD: current=0.2411, target=0.2500\n ICSH: current=0.2472, target=0.2500\n DBA: 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: 0.0120.\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": {"USMV": 0.2496, "ADA-USD": 0.2411, "ICSH": 0.2472, "DBA": 0.262}, "target_weights": {"USMV": 0.25, "ADA-USD": 0.25, "ICSH": 0.25, "DBA": 0.25}, "max_deviation": 0.012, "total_turnover": 0.024084, "transaction_cost": 2.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9044, "primary_asset": "DBA", "primary_trade": 0.012}} +{"id": "T6_all_20251118_0077", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "LINK-USD", "HYG", "XHB"], "decision_date": "2025-11-18", "context_summary": "Max weight deviation: 0.0069, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2434, target=0.2500\n LINK-USD: current=0.2561, target=0.2500\n HYG: current=0.2569, target=0.2500\n XHB: current=0.2436, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0069.\nRebalancing threshold: 0.0500.\n0.0069 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0261, transaction cost = 0.000026 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2434, "LINK-USD": 0.2561, "HYG": 0.2569, "XHB": 0.2436}, "target_weights": {"QUAL": 0.25, "LINK-USD": 0.25, "HYG": 0.25, "XHB": 0.25}, "max_deviation": 0.0069, "total_turnover": 0.026099, "transaction_cost": 2.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "HYG", "primary_trade": 0.0069}} +{"id": "T6_all_20250609_0079", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "SOL-USD", "HYG", "BNO"], "decision_date": "2025-06-09", "context_summary": "Max weight deviation: 0.0119, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.2562, target=0.2500\n SOL-USD: current=0.2381, target=0.2500\n HYG: current=0.2517, target=0.2500\n BNO: 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: 0.0119.\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": {"USMV": 0.2562, "SOL-USD": 0.2381, "HYG": 0.2517, "BNO": 0.254}, "target_weights": {"USMV": 0.25, "SOL-USD": 0.25, "HYG": 0.25, "BNO": 0.25}, "max_deviation": 0.0119, "total_turnover": 0.023818, "transaction_cost": 2.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "SOL-USD", "primary_trade": -0.0119}} +{"id": "T6_all_20251231_0082", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "ETH-USD", "EMB", "SGOV"], "decision_date": "2025-12-31", "context_summary": "Max weight deviation: 0.0420, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.3144, target=0.2500\n ETH-USD: current=0.2546, target=0.2500\n EMB: current=0.1850, target=0.2500\n SGOV: current=0.2460, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0420.\nRebalancing threshold: 0.0500.\n0.0420 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0892, transaction cost = 0.000089 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.3144, "ETH-USD": 0.2546, "EMB": 0.185, "SGOV": 0.246}, "target_weights": {"USMV": 0.25, "ETH-USD": 0.25, "EMB": 0.25, "SGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.089174, "transaction_cost": 8.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "EMB", "primary_trade": -0.065}} +{"id": "T6_all_20251113_0085", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "XRP-USD", "TLH", "GLD"], "decision_date": "2025-11-13", "context_summary": "Max weight deviation: 0.0337, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.2557, target=0.2500\n XRP-USD: current=0.2568, target=0.2500\n TLH: current=0.2163, target=0.2500\n GLD: current=0.2712, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "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": {"^VIX": 0.2557, "XRP-USD": 0.2568, "TLH": 0.2163, "GLD": 0.2712}, "target_weights": {"^VIX": 0.25, "XRP-USD": 0.25, "TLH": 0.25, "GLD": 0.25}, "max_deviation": 0.0337, "total_turnover": 0.067429, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "TLH", "primary_trade": -0.0337}} +{"id": "T6_all_20250121_0092", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ETH-USD", "WEAT", "CSHI"], "decision_date": "2025-01-21", "context_summary": "Max weight deviation: 0.0203, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.3090, target=0.2500\n ETH-USD: current=0.2488, target=0.2500\n WEAT: current=0.2571, target=0.2500\n CSHI: 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 CSHI", "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 = 0.0413, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.309, "ETH-USD": 0.2488, "WEAT": 0.2571, "CSHI": 0.1851}, "target_weights": {"ACWI": 0.25, "ETH-USD": 0.25, "WEAT": 0.25, "CSHI": 0.25}, "max_deviation": 0.064941, "total_turnover": 0.041338, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "CSHI", "primary_trade": -0.0649}} +{"id": "T6_all_20250926_0094", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM", "DOT-USD", "CORN", "SGOV"], "decision_date": "2025-09-26", "context_summary": "Max weight deviation: 0.0347, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n MTUM: current=0.3030, target=0.2500\n DOT-USD: current=0.2614, target=0.2500\n CORN: current=0.1850, target=0.2500\n SGOV: current=0.2506, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of CORN", "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 = 0.0695, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.303, "DOT-USD": 0.2614, "CORN": 0.185, "SGOV": 0.2506}, "target_weights": {"MTUM": 0.25, "DOT-USD": 0.25, "CORN": 0.25, "SGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.06945, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "CORN", "primary_trade": -0.065}} +{"id": "T6_all_20250417_0097", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["IVV", "SOL-USD", "IAU", "HAUZ"], "decision_date": "2025-04-17", "context_summary": "Max weight deviation: 0.0219, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2677, target=0.2500\n SOL-USD: current=0.2281, target=0.2500\n IAU: current=0.2537, target=0.2500\n HAUZ: current=0.2504, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0219.\nRebalancing threshold: 0.0500.\n0.0219 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0438, transaction cost = 0.000044 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2677, "SOL-USD": 0.2281, "IAU": 0.2537, "HAUZ": 0.2504}, "target_weights": {"IVV": 0.25, "SOL-USD": 0.25, "IAU": 0.25, "HAUZ": 0.25}, "max_deviation": 0.0219, "total_turnover": 0.043803, "transaction_cost": 4.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SOL-USD", "primary_trade": -0.0219}} +{"id": "T6_all_20250801_0098", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["MTUM", "SOL-USD", "BIL", "REZ"], "decision_date": "2025-08-01", "context_summary": "Max weight deviation: 0.0128, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n MTUM: current=0.2053, target=0.2500\n SOL-USD: current=0.2754, target=0.2500\n BIL: current=0.2043, target=0.2500\n REZ: current=0.3150, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of REZ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0128.\nRebalancing threshold: 0.0500.\n0.0128 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0356, transaction cost = 0.000036 (negligible vs. drift).", "metadata": {"current_weights": {"MTUM": 0.2053, "SOL-USD": 0.2754, "BIL": 0.2043, "REZ": 0.315}, "target_weights": {"MTUM": 0.25, "SOL-USD": 0.25, "BIL": 0.25, "REZ": 0.25}, "max_deviation": 0.065, "total_turnover": 0.03561, "transaction_cost": 3.6e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "REZ", "primary_trade": 0.065}} +{"id": "T6_all_20250617_0100", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "BTC-USD", "GLD", "XHB"], "decision_date": "2025-06-17", "context_summary": "Max weight deviation: 0.0238, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2552, target=0.2500\n BTC-USD: current=0.1935, target=0.2500\n GLD: current=0.3150, target=0.2500\n XHB: 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": "yes; sell 0.0650 of GLD", "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 = 0.0515, transaction cost = 0.000052 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2552, "BTC-USD": 0.1935, "GLD": 0.315, "XHB": 0.2363}, "target_weights": {"IVV": 0.25, "BTC-USD": 0.25, "GLD": 0.25, "XHB": 0.25}, "max_deviation": 0.065, "total_turnover": 0.051547, "transaction_cost": 5.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "GLD", "primary_trade": 0.065}} +{"id": "T6_all_20250522_0101", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "LINK-USD", "CSHI", "REZ"], "decision_date": "2025-05-22", "context_summary": "Max weight deviation: 0.0288, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.2212, target=0.2500\n LINK-USD: current=0.2742, target=0.2500\n CSHI: current=0.2637, target=0.2500\n REZ: current=0.2409, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0288.\nRebalancing threshold: 0.0500.\n0.0288 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0759, transaction cost = 0.000076 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2212, "LINK-USD": 0.2742, "CSHI": 0.2637, "REZ": 0.2409}, "target_weights": {"^VIX": 0.25, "LINK-USD": 0.25, "CSHI": 0.25, "REZ": 0.25}, "max_deviation": 0.0288, "total_turnover": 0.075861, "transaction_cost": 7.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "^VIX", "primary_trade": -0.0288}} +{"id": "T6_all_20250314_0102", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EEM", "LINK-USD", "BIL", "SCHP"], "decision_date": "2025-03-14", "context_summary": "Max weight deviation: 0.0133, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.2823, target=0.2500\n LINK-USD: current=0.1850, target=0.2500\n BIL: current=0.2402, target=0.2500\n SCHP: current=0.2925, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0133.\nRebalancing threshold: 0.0500.\n0.0133 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0305, transaction cost = 0.000030 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2823, "LINK-USD": 0.185, "BIL": 0.2402, "SCHP": 0.2925}, "target_weights": {"EEM": 0.25, "LINK-USD": 0.25, "BIL": 0.25, "SCHP": 0.25}, "max_deviation": 0.065, "total_turnover": 0.030478, "transaction_cost": 3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": -0.065}} +{"id": "T6_all_20250516_0106", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "DOT-USD", "ICSH", "SHY"], "decision_date": "2025-05-16", "context_summary": "Max weight deviation: 0.0090, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2632, target=0.2500\n DOT-USD: current=0.2632, target=0.2500\n ICSH: current=0.1851, target=0.2500\n SHY: current=0.2885, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0649 of ICSH", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0090.\nRebalancing threshold: 0.0500.\n0.0090 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0180, transaction cost = 0.000018 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2632, "DOT-USD": 0.2632, "ICSH": 0.1851, "SHY": 0.2885}, "target_weights": {"QUAL": 0.25, "DOT-USD": 0.25, "ICSH": 0.25, "SHY": 0.25}, "max_deviation": 0.064866, "total_turnover": 0.017954, "transaction_cost": 1.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.0649}} +{"id": "T6_all_20251219_0107", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "ETH-USD", "TIP", "GLD"], "decision_date": "2025-12-19", "context_summary": "Max weight deviation: 0.0241, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2371, target=0.2500\n ETH-USD: current=0.2717, target=0.2500\n TIP: current=0.2259, target=0.2500\n GLD: current=0.2653, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "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 = 0.0741, transaction cost = 0.000074 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2371, "ETH-USD": 0.2717, "TIP": 0.2259, "GLD": 0.2653}, "target_weights": {"IVV": 0.25, "ETH-USD": 0.25, "TIP": 0.25, "GLD": 0.25}, "max_deviation": 0.0241, "total_turnover": 0.074069, "transaction_cost": 7.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "TIP", "primary_trade": -0.0241}} +{"id": "T6_all_20250506_0108", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BTC-USD", "ICSH", "MORT"], "decision_date": "2025-05-06", "context_summary": "Max weight deviation: 0.0539, threshold: 0.05. Decision: yes (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.2961, target=0.2500\n BTC-USD: current=0.1961, target=0.2500\n ICSH: current=0.2508, target=0.2500\n MORT: current=0.2571, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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 0.0539 of BTC-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0539.\nRebalancing threshold: 0.0500.\n0.0539 > 0.0500 \u2192 decision: 'yes'.\nIf rebalanced: total turnover = 0.1078, transaction cost = 0.000108 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2961, "BTC-USD": 0.1961, "ICSH": 0.2508, "MORT": 0.2571}, "target_weights": {"IWM": 0.25, "BTC-USD": 0.25, "ICSH": 0.25, "MORT": 0.25}, "max_deviation": 0.0539, "total_turnover": 0.107763, "transaction_cost": 0.000108, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "BTC-USD", "primary_trade": -0.0539}} +{"id": "T6_all_20250107_0110", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLF", "ETH-USD", "SOYB", "SGOV"], "decision_date": "2025-01-07", "context_summary": "Max weight deviation: 0.0242, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLF: current=0.1912, target=0.2500\n ETH-USD: current=0.2411, target=0.2500\n SOYB: current=0.2527, target=0.2500\n SGOV: 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 SGOV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0242.\nRebalancing threshold: 0.0500.\n0.0242 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0504, transaction cost = 0.000050 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.1912, "ETH-USD": 0.2411, "SOYB": 0.2527, "SGOV": 0.315}, "target_weights": {"XLF": 0.25, "ETH-USD": 0.25, "SOYB": 0.25, "SGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.050402, "transaction_cost": 5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "SGOV", "primary_trade": 0.065}} +{"id": "T6_all_20251112_0114", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLY", "LINK-USD", "EMB", "BNO"], "decision_date": "2025-11-12", "context_summary": "Max weight deviation: 0.0383, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2383, target=0.2500\n LINK-USD: current=0.2370, target=0.2500\n EMB: current=0.2096, target=0.2500\n BNO: current=0.3151, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0651 of BNO", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0383.\nRebalancing threshold: 0.0500.\n0.0383 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0766, transaction cost = 0.000077 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2383, "LINK-USD": 0.237, "EMB": 0.2096, "BNO": 0.3151}, "target_weights": {"XLY": 0.25, "LINK-USD": 0.25, "EMB": 0.25, "BNO": 0.25}, "max_deviation": 0.065053, "total_turnover": 0.076644, "transaction_cost": 7.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "BNO", "primary_trade": 0.0651}} +{"id": "T6_all_20250219_0118", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "BNB-USD", "SGOV", "PPLT"], "decision_date": "2025-02-19", "context_summary": "Max weight deviation: 0.0242, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.3150, target=0.2500\n BNB-USD: current=0.1885, target=0.2500\n SGOV: current=0.2156, target=0.2500\n PPLT: current=0.2809, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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 IWM", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0242.\nRebalancing threshold: 0.0500.\n0.0242 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0714, transaction cost = 0.000071 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.315, "BNB-USD": 0.1885, "SGOV": 0.2156, "PPLT": 0.2809}, "target_weights": {"IWM": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "PPLT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.071423, "transaction_cost": 7.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "IWM", "primary_trade": 0.065}} +{"id": "T6_all_20250115_0121", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLI", "XRP-USD", "VCIT", "IYR"], "decision_date": "2025-01-15", "context_summary": "Max weight deviation: 0.0412, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLI: current=0.2716, target=0.2500\n XRP-USD: current=0.2532, target=0.2500\n VCIT: current=0.2088, target=0.2500\n IYR: current=0.2665, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0412.\nRebalancing threshold: 0.0500.\n0.0412 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0824, transaction cost = 0.000082 (negligible vs. drift).", "metadata": {"current_weights": {"XLI": 0.2716, "XRP-USD": 0.2532, "VCIT": 0.2088, "IYR": 0.2665}, "target_weights": {"XLI": 0.25, "XRP-USD": 0.25, "VCIT": 0.25, "IYR": 0.25}, "max_deviation": 0.0412, "total_turnover": 0.082401, "transaction_cost": 8.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "VCIT", "primary_trade": -0.0412}} +{"id": "T6_all_20250304_0122", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IVV", "SOL-USD", "SHV", "ICSH"], "decision_date": "2025-03-04", "context_summary": "Max weight deviation: 0.0227, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2386, target=0.2500\n SOL-USD: current=0.3151, target=0.2500\n SHV: current=0.2601, target=0.2500\n ICSH: current=0.1862, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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 SOL-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0227.\nRebalancing threshold: 0.0500.\n0.0227 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0525, transaction cost = 0.000052 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.2386, "SOL-USD": 0.3151, "SHV": 0.2601, "ICSH": 0.1862}, "target_weights": {"IVV": 0.25, "SOL-USD": 0.25, "SHV": 0.25, "ICSH": 0.25}, "max_deviation": 0.06509, "total_turnover": 0.052463, "transaction_cost": 5.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "SOL-USD", "primary_trade": 0.0651}} +{"id": "T6_all_20250818_0124", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLK", "BNB-USD", "IYR", "SGOV"], "decision_date": "2025-08-18", "context_summary": "Max weight deviation: 0.0282, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.1961, target=0.2500\n BNB-USD: current=0.2385, target=0.2500\n IYR: current=0.2505, target=0.2500\n SGOV: current=0.3150, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of SGOV", "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 = 0.0567, transaction cost = 0.000057 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.1961, "BNB-USD": 0.2385, "IYR": 0.2505, "SGOV": 0.315}, "target_weights": {"XLK": 0.25, "BNB-USD": 0.25, "IYR": 0.25, "SGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.05674, "transaction_cost": 5.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": 0.065}} +{"id": "T6_all_20250320_0125", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ADA-USD", "LQD", "BNO"], "decision_date": "2025-03-20", "context_summary": "Max weight deviation: 0.0345, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.2481, target=0.2500\n ADA-USD: current=0.2641, target=0.2500\n LQD: current=0.2155, target=0.2500\n BNO: current=0.2723, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0345.\nRebalancing threshold: 0.0500.\n0.0345 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0728, transaction cost = 0.000073 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2481, "ADA-USD": 0.2641, "LQD": 0.2155, "BNO": 0.2723}, "target_weights": {"XLRE": 0.25, "ADA-USD": 0.25, "LQD": 0.25, "BNO": 0.25}, "max_deviation": 0.0345, "total_turnover": 0.072765, "transaction_cost": 7.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "LQD", "primary_trade": -0.0345}} +{"id": "T6_all_20250616_0126", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "DOT-USD", "PALL", "SHY"], "decision_date": "2025-06-16", "context_summary": "Max weight deviation: 0.0124, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n SPY: current=0.3150, target=0.2500\n DOT-USD: current=0.1944, target=0.2500\n PALL: current=0.2715, target=0.2500\n SHY: current=0.2191, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of SPY", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0124.\nRebalancing threshold: 0.0500.\n0.0124 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0331, transaction cost = 0.000033 (negligible vs. drift).", "metadata": {"current_weights": {"SPY": 0.315, "DOT-USD": 0.1944, "PALL": 0.2715, "SHY": 0.2191}, "target_weights": {"SPY": 0.25, "DOT-USD": 0.25, "PALL": 0.25, "SHY": 0.25}, "max_deviation": 0.065, "total_turnover": 0.033146, "transaction_cost": 3.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SPY", "primary_trade": 0.065}} +{"id": "T6_all_20250610_0128", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["^VIX", "BTC-USD", "REZ", "IAU"], "decision_date": "2025-06-10", "context_summary": "Max weight deviation: 0.0145, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.2366, target=0.2500\n BTC-USD: current=0.2805, target=0.2500\n REZ: current=0.2980, target=0.2500\n IAU: 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 IAU", "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 = 0.0350, transaction cost = 0.000035 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2366, "BTC-USD": 0.2805, "REZ": 0.298, "IAU": 0.185}, "target_weights": {"^VIX": 0.25, "BTC-USD": 0.25, "REZ": 0.25, "IAU": 0.25}, "max_deviation": 0.065, "total_turnover": 0.034986, "transaction_cost": 3.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IAU", "primary_trade": -0.065}} +{"id": "T6_all_20250704_0129", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLE", "DOT-USD", "HYG", "BNO"], "decision_date": "2025-07-04", "context_summary": "Max weight deviation: 0.0256, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLE: current=0.2695, target=0.2500\n DOT-USD: current=0.2244, target=0.2500\n HYG: current=0.2673, target=0.2500\n BNO: 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: 0.0256.\nRebalancing threshold: 0.0500.\n0.0256 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0736, transaction cost = 0.000074 (negligible vs. drift).", "metadata": {"current_weights": {"XLE": 0.2695, "DOT-USD": 0.2244, "HYG": 0.2673, "BNO": 0.2388}, "target_weights": {"XLE": 0.25, "DOT-USD": 0.25, "HYG": 0.25, "BNO": 0.25}, "max_deviation": 0.0256, "total_turnover": 0.073628, "transaction_cost": 7.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "DOT-USD", "primary_trade": -0.0256}} +{"id": "T6_all_20250701_0132", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "ETH-USD", "UNG", "IEF"], "decision_date": "2025-07-01", "context_summary": "Max weight deviation: 0.0170, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.2894, target=0.2500\n ETH-USD: current=0.1850, target=0.2500\n UNG: current=0.2833, target=0.2500\n IEF: 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": "yes; buy 0.0650 of ETH-USD", "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 = 0.0380, transaction cost = 0.000038 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2894, "ETH-USD": 0.185, "UNG": 0.2833, "IEF": 0.2424}, "target_weights": {"EEM": 0.25, "ETH-USD": 0.25, "UNG": 0.25, "IEF": 0.25}, "max_deviation": 0.065, "total_turnover": 0.038032, "transaction_cost": 3.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": -0.065}} +{"id": "T6_all_20250910_0134", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "BTC-USD", "CSHI", "DBB"], "decision_date": "2025-09-10", "context_summary": "Max weight deviation: 0.0350, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n FXI: current=0.2349, target=0.2500\n BTC-USD: current=0.2141, target=0.2500\n CSHI: current=0.3149, target=0.2500\n DBB: current=0.2360, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0649 of CSHI", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0350.\nRebalancing threshold: 0.0500.\n0.0350 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0701, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2349, "BTC-USD": 0.2141, "CSHI": 0.3149, "DBB": 0.236}, "target_weights": {"FXI": 0.25, "BTC-USD": 0.25, "CSHI": 0.25, "DBB": 0.25}, "max_deviation": 0.064942, "total_turnover": 0.070052, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "CSHI", "primary_trade": 0.0649}} +{"id": "T6_all_20251201_0137", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EEM", "BNB-USD", "HYG", "PALL"], "decision_date": "2025-12-01", "context_summary": "Max weight deviation: 0.0116, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.2411, target=0.2500\n BNB-USD: current=0.2420, target=0.2500\n HYG: current=0.2552, target=0.2500\n PALL: current=0.2616, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (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 = 0.0337, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2411, "BNB-USD": 0.242, "HYG": 0.2552, "PALL": 0.2616}, "target_weights": {"EEM": 0.25, "BNB-USD": 0.25, "HYG": 0.25, "PALL": 0.25}, "max_deviation": 0.0116, "total_turnover": 0.033658, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "PALL", "primary_trade": 0.0116}} +{"id": "T6_all_20250313_0140", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EWJ", "AVAX-USD", "REZ", "ICSH"], "decision_date": "2025-03-13", "context_summary": "Max weight deviation: 0.0131, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.2277, target=0.2500\n AVAX-USD: current=0.3150, target=0.2500\n REZ: current=0.2029, target=0.2500\n ICSH: current=0.2545, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0131.\nRebalancing threshold: 0.0500.\n0.0131 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0280, transaction cost = 0.000028 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2277, "AVAX-USD": 0.315, "REZ": 0.2029, "ICSH": 0.2545}, "target_weights": {"EWJ": 0.25, "AVAX-USD": 0.25, "REZ": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.028005, "transaction_cost": 2.8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "AVAX-USD", "primary_trade": 0.065}} +{"id": "T6_all_20250916_0142", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VTI", "BTC-USD", "SGOV", "VNQI"], "decision_date": "2025-09-16", "context_summary": "Max weight deviation: 0.0277, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VTI: current=0.2024, target=0.2500\n BTC-USD: current=0.3150, target=0.2500\n SGOV: current=0.2519, target=0.2500\n VNQI: current=0.2308, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of BTC-USD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0277.\nRebalancing threshold: 0.0500.\n0.0277 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0571, transaction cost = 0.000057 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2024, "BTC-USD": 0.315, "SGOV": 0.2519, "VNQI": 0.2308}, "target_weights": {"VTI": 0.25, "BTC-USD": 0.25, "SGOV": 0.25, "VNQI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.057061, "transaction_cost": 5.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BTC-USD", "primary_trade": 0.065}} +{"id": "T6_all_20250707_0144", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "LINK-USD", "GLD", "HYG"], "decision_date": "2025-07-07", "context_summary": "Max weight deviation: 0.0359, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n SPY: current=0.2337, target=0.2500\n LINK-USD: current=0.2259, target=0.2500\n GLD: current=0.2254, target=0.2500\n HYG: 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 HYG", "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": {"SPY": 0.2337, "LINK-USD": 0.2259, "GLD": 0.2254, "HYG": 0.315}, "target_weights": {"SPY": 0.25, "LINK-USD": 0.25, "GLD": 0.25, "HYG": 0.25}, "max_deviation": 0.065, "total_turnover": 0.07181, "transaction_cost": 7.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "HYG", "primary_trade": 0.065}} +{"id": "T6_all_20251016_0145", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY", "BTC-USD", "STIP", "BIL"], "decision_date": "2025-10-16", "context_summary": "Max weight deviation: 0.0218, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n SPY: current=0.2718, target=0.2500\n BTC-USD: current=0.2587, target=0.2500\n STIP: current=0.2331, target=0.2500\n BIL: current=0.2364, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0218.\nRebalancing threshold: 0.0500.\n0.0218 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0610, transaction cost = 0.000061 (negligible vs. drift).", "metadata": {"current_weights": {"SPY": 0.2718, "BTC-USD": 0.2587, "STIP": 0.2331, "BIL": 0.2364}, "target_weights": {"SPY": 0.25, "BTC-USD": 0.25, "STIP": 0.25, "BIL": 0.25}, "max_deviation": 0.0218, "total_turnover": 0.061013, "transaction_cost": 6.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "SPY", "primary_trade": 0.0218}} +{"id": "T6_all_20250404_0147", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLV", "LINK-USD", "ICSH", "IYR"], "decision_date": "2025-04-04", "context_summary": "Max weight deviation: 0.0113, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLV: current=0.2512, target=0.2500\n LINK-USD: current=0.2536, target=0.2500\n ICSH: current=0.2387, target=0.2500\n IYR: current=0.2565, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0113.\nRebalancing threshold: 0.0500.\n0.0113 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0226, transaction cost = 0.000023 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.2512, "LINK-USD": 0.2536, "ICSH": 0.2387, "IYR": 0.2565}, "target_weights": {"XLV": 0.25, "LINK-USD": 0.25, "ICSH": 0.25, "IYR": 0.25}, "max_deviation": 0.0113, "total_turnover": 0.022625, "transaction_cost": 2.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ICSH", "primary_trade": -0.0113}} +{"id": "T6_all_20251128_0150", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["MTUM", "XRP-USD", "SGOV", "TLH"], "decision_date": "2025-11-28", "context_summary": "Max weight deviation: 0.0303, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n MTUM: current=0.2753, target=0.2500\n XRP-USD: current=0.2895, target=0.2500\n SGOV: current=0.1850, target=0.2500\n TLH: current=0.2502, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of SGOV", "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": {"MTUM": 0.2753, "XRP-USD": 0.2895, "SGOV": 0.185, "TLH": 0.2502}, "target_weights": {"MTUM": 0.25, "XRP-USD": 0.25, "SGOV": 0.25, "TLH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.060567, "transaction_cost": 6.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "SGOV", "primary_trade": -0.065}} +{"id": "T6_all_20250807_0153", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VLUE", "LINK-USD", "CSHI", "IGOV"], "decision_date": "2025-08-07", "context_summary": "Max weight deviation: 0.0299, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VLUE: current=0.2513, target=0.2500\n LINK-USD: current=0.2587, target=0.2500\n CSHI: current=0.2201, target=0.2500\n IGOV: current=0.2700, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0299.\nRebalancing threshold: 0.0500.\n0.0299 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0599, transaction cost = 0.000060 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2513, "LINK-USD": 0.2587, "CSHI": 0.2201, "IGOV": 0.27}, "target_weights": {"VLUE": 0.25, "LINK-USD": 0.25, "CSHI": 0.25, "IGOV": 0.25}, "max_deviation": 0.0299, "total_turnover": 0.059879, "transaction_cost": 6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "CSHI", "primary_trade": -0.0299}} +{"id": "T6_all_20250708_0157", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VTI", "BTC-USD", "ITB", "CSHI"], "decision_date": "2025-07-08", "context_summary": "Max weight deviation: 0.0223, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VTI: current=0.2548, target=0.2500\n BTC-USD: current=0.2651, target=0.2500\n ITB: current=0.2525, target=0.2500\n CSHI: 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 = 0.0447, transaction cost = 0.000045 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2548, "BTC-USD": 0.2651, "ITB": 0.2525, "CSHI": 0.2277}, "target_weights": {"VTI": 0.25, "BTC-USD": 0.25, "ITB": 0.25, "CSHI": 0.25}, "max_deviation": 0.0223, "total_turnover": 0.04468, "transaction_cost": 4.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "CSHI", "primary_trade": -0.0223}} +{"id": "T6_all_20251127_0160", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ETH-USD", "ITB", "BIL"], "decision_date": "2025-11-27", "context_summary": "Max weight deviation: 0.0155, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLB: current=0.2566, target=0.2500\n ETH-USD: current=0.2201, target=0.2500\n ITB: current=0.3149, target=0.2500\n BIL: current=0.2084, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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 ITB", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0155.\nRebalancing threshold: 0.0500.\n0.0155 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0341, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.2566, "ETH-USD": 0.2201, "ITB": 0.3149, "BIL": 0.2084}, "target_weights": {"XLB": 0.25, "ETH-USD": 0.25, "ITB": 0.25, "BIL": 0.25}, "max_deviation": 0.064868, "total_turnover": 0.034084, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "ITB", "primary_trade": 0.0649}} +{"id": "T6_all_20250128_0161", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "AVAX-USD", "VNQ", "SGOV"], "decision_date": "2025-01-28", "context_summary": "Max weight deviation: 0.0249, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2749, target=0.2500\n AVAX-USD: current=0.2537, target=0.2500\n VNQ: current=0.2296, target=0.2500\n SGOV: current=0.2418, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0249.\nRebalancing threshold: 0.0500.\n0.0249 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0572, transaction cost = 0.000057 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2749, "AVAX-USD": 0.2537, "VNQ": 0.2296, "SGOV": 0.2418}, "target_weights": {"XLY": 0.25, "AVAX-USD": 0.25, "VNQ": 0.25, "SGOV": 0.25}, "max_deviation": 0.0249, "total_turnover": 0.057222, "transaction_cost": 5.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9044, "primary_asset": "XLY", "primary_trade": 0.0249}} +{"id": "T6_all_20250305_0167", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ETH-USD", "ICSH", "MORT"], "decision_date": "2025-03-05", "context_summary": "Max weight deviation: 0.0455, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.2324, target=0.2500\n ETH-USD: current=0.2342, target=0.2500\n ICSH: current=0.2955, target=0.2500\n MORT: current=0.2380, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0455.\nRebalancing threshold: 0.0500.\n0.0455 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0910, transaction cost = 0.000091 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2324, "ETH-USD": 0.2342, "ICSH": 0.2955, "MORT": 0.238}, "target_weights": {"XLRE": 0.25, "ETH-USD": 0.25, "ICSH": 0.25, "MORT": 0.25}, "max_deviation": 0.0455, "total_turnover": 0.090967, "transaction_cost": 9.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "ICSH", "primary_trade": 0.0455}} +{"id": "T6_all_20250213_0169", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "DOT-USD", "SCHH", "TIP"], "decision_date": "2025-02-13", "context_summary": "Max weight deviation: 0.0447, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.2053, target=0.2500\n DOT-USD: current=0.2749, target=0.2500\n SCHH: current=0.2554, target=0.2500\n TIP: 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: 0.0447.\nRebalancing threshold: 0.0500.\n0.0447 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0893, transaction cost = 0.000089 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2053, "DOT-USD": 0.2749, "SCHH": 0.2554, "TIP": 0.2644}, "target_weights": {"ACWI": 0.25, "DOT-USD": 0.25, "SCHH": 0.25, "TIP": 0.25}, "max_deviation": 0.0447, "total_turnover": 0.089316, "transaction_cost": 8.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "ACWI", "primary_trade": -0.0447}} +{"id": "T6_all_20250604_0171", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLB", "ETH-USD", "SGOV", "STIP"], "decision_date": "2025-06-04", "context_summary": "Max weight deviation: 0.0295, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLB: current=0.2510, target=0.2500\n ETH-USD: current=0.2205, target=0.2500\n SGOV: current=0.2515, target=0.2500\n STIP: current=0.2770, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0295.\nRebalancing threshold: 0.0500.\n0.0295 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0589, transaction cost = 0.000059 (negligible vs. drift).", "metadata": {"current_weights": {"XLB": 0.251, "ETH-USD": 0.2205, "SGOV": 0.2515, "STIP": 0.277}, "target_weights": {"XLB": 0.25, "ETH-USD": 0.25, "SGOV": 0.25, "STIP": 0.25}, "max_deviation": 0.0295, "total_turnover": 0.058935, "transaction_cost": 5.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ETH-USD", "primary_trade": -0.0295}} +{"id": "T6_all_20250509_0176", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "SOL-USD", "INDS", "ICSH"], "decision_date": "2025-05-09", "context_summary": "Max weight deviation: 0.0417, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.2587, target=0.2500\n SOL-USD: current=0.2134, target=0.2500\n INDS: current=0.3150, target=0.2500\n ICSH: current=0.2129, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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 INDS", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0417.\nRebalancing threshold: 0.0500.\n0.0417 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0947, transaction cost = 0.000095 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2587, "SOL-USD": 0.2134, "INDS": 0.315, "ICSH": 0.2129}, "target_weights": {"IWM": 0.25, "SOL-USD": 0.25, "INDS": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.094727, "transaction_cost": 9.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "INDS", "primary_trade": 0.065}} +{"id": "T6_all_20250312_0179", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "AVAX-USD", "SCHH", "IAU"], "decision_date": "2025-03-12", "context_summary": "Max weight deviation: 0.0126, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.2527, target=0.2500\n AVAX-USD: current=0.2389, target=0.2500\n SCHH: current=0.2626, target=0.2500\n IAU: 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: 0.0126.\nRebalancing threshold: 0.0500.\n0.0126 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0306, transaction cost = 0.000031 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.2527, "AVAX-USD": 0.2389, "SCHH": 0.2626, "IAU": 0.2458}, "target_weights": {"XLP": 0.25, "AVAX-USD": 0.25, "SCHH": 0.25, "IAU": 0.25}, "max_deviation": 0.0126, "total_turnover": 0.030621, "transaction_cost": 3.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "SCHH", "primary_trade": 0.0126}} +{"id": "T6_all_20250722_0181", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["USMV", "SOL-USD", "ITB", "CORN"], "decision_date": "2025-07-22", "context_summary": "Max weight deviation: 0.0295, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.2381, target=0.2500\n SOL-USD: current=0.2710, target=0.2500\n ITB: current=0.2205, target=0.2500\n CORN: current=0.2704, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0295.\nRebalancing threshold: 0.0500.\n0.0295 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0828, transaction cost = 0.000083 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2381, "SOL-USD": 0.271, "ITB": 0.2205, "CORN": 0.2704}, "target_weights": {"USMV": 0.25, "SOL-USD": 0.25, "ITB": 0.25, "CORN": 0.25}, "max_deviation": 0.0295, "total_turnover": 0.082766, "transaction_cost": 8.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ITB", "primary_trade": -0.0295}} +{"id": "T6_all_20251125_0184", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "ADA-USD", "SHV", "SCHH"], "decision_date": "2025-11-25", "context_summary": "Max weight deviation: 0.0217, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n FXI: current=0.2619, target=0.2500\n ADA-USD: current=0.1849, target=0.2500\n SHV: current=0.2796, target=0.2500\n SCHH: current=0.2736, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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 ADA-USD", "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 = 0.0434, transaction cost = 0.000043 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2619, "ADA-USD": 0.1849, "SHV": 0.2796, "SCHH": 0.2736}, "target_weights": {"FXI": 0.25, "ADA-USD": 0.25, "SHV": 0.25, "SCHH": 0.25}, "max_deviation": 0.065055, "total_turnover": 0.043408, "transaction_cost": 4.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "ADA-USD", "primary_trade": -0.0651}} +{"id": "T6_all_20251224_0188", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLV", "LINK-USD", "DBB", "ICSH"], "decision_date": "2025-12-24", "context_summary": "Max weight deviation: 0.0105, 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=0.2822, target=0.2500\n DBB: current=0.2259, target=0.2500\n ICSH: current=0.3070, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0105.\nRebalancing threshold: 0.0500.\n0.0105 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0288, transaction cost = 0.000029 (negligible vs. drift).", "metadata": {"current_weights": {"XLV": 0.185, "LINK-USD": 0.2822, "DBB": 0.2259, "ICSH": 0.307}, "target_weights": {"XLV": 0.25, "LINK-USD": 0.25, "DBB": 0.25, "ICSH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.028766, "transaction_cost": 2.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "XLV", "primary_trade": -0.065}} +{"id": "T6_all_20250106_0189", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "DOT-USD", "XHB", "BIL"], "decision_date": "2025-01-06", "context_summary": "Max weight deviation: 0.0145, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.2355, target=0.2500\n DOT-USD: current=0.2640, target=0.2500\n XHB: current=0.2361, target=0.2500\n BIL: 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: 0.0145.\nRebalancing threshold: 0.0500.\n0.0145 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0568, transaction cost = 0.000057 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2355, "DOT-USD": 0.264, "XHB": 0.2361, "BIL": 0.2644}, "target_weights": {"IWM": 0.25, "DOT-USD": 0.25, "XHB": 0.25, "BIL": 0.25}, "max_deviation": 0.0145, "total_turnover": 0.056814, "transaction_cost": 5.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "IWM", "primary_trade": -0.0145}} +{"id": "T6_all_20251217_0191", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["IWM", "AVAX-USD", "JNK", "SGOV"], "decision_date": "2025-12-17", "context_summary": "Max weight deviation: 0.0375, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.2125, target=0.2500\n AVAX-USD: current=0.2572, target=0.2500\n JNK: current=0.2775, target=0.2500\n SGOV: 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: 0.0375.\nRebalancing threshold: 0.0500.\n0.0375 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0750, transaction cost = 0.000075 (negligible vs. drift).", "metadata": {"current_weights": {"IWM": 0.2125, "AVAX-USD": 0.2572, "JNK": 0.2775, "SGOV": 0.2527}, "target_weights": {"IWM": 0.25, "AVAX-USD": 0.25, "JNK": 0.25, "SGOV": 0.25}, "max_deviation": 0.0375, "total_turnover": 0.075029, "transaction_cost": 7.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "IWM", "primary_trade": -0.0375}} +{"id": "T6_all_20250410_0193", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLRE", "DOT-USD", "VNQI", "VCIT"], "decision_date": "2025-04-10", "context_summary": "Max weight deviation: 0.0369, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.2869, target=0.2500\n DOT-USD: current=0.2177, target=0.2500\n VNQI: current=0.2648, target=0.2500\n VCIT: current=0.2307, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0369.\nRebalancing threshold: 0.0500.\n0.0369 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1033, transaction cost = 0.000103 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2869, "DOT-USD": 0.2177, "VNQI": 0.2648, "VCIT": 0.2307}, "target_weights": {"XLRE": 0.25, "DOT-USD": 0.25, "VNQI": 0.25, "VCIT": 0.25}, "max_deviation": 0.0369, "total_turnover": 0.103307, "transaction_cost": 0.000103, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLRE", "primary_trade": 0.0369}} +{"id": "T6_all_20251010_0194", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLF", "ETH-USD", "LQD", "CSHI"], "decision_date": "2025-10-10", "context_summary": "Max weight deviation: 0.0323, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLF: current=0.1910, target=0.2500\n ETH-USD: current=0.2397, target=0.2500\n LQD: current=0.3150, target=0.2500\n CSHI: current=0.2542, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of LQD", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0323.\nRebalancing threshold: 0.0500.\n0.0323 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0688, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"XLF": 0.191, "ETH-USD": 0.2397, "LQD": 0.315, "CSHI": 0.2542}, "target_weights": {"XLF": 0.25, "ETH-USD": 0.25, "LQD": 0.25, "CSHI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.068827, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LQD", "primary_trade": 0.065}} +{"id": "T6_all_20250808_0195", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLK", "ETH-USD", "SHY", "SCHH"], "decision_date": "2025-08-08", "context_summary": "Max weight deviation: 0.0264, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.2383, target=0.2500\n ETH-USD: current=0.2764, target=0.2500\n SHY: current=0.2284, target=0.2500\n SCHH: current=0.2569, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0264.\nRebalancing threshold: 0.0500.\n0.0264 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0667, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2383, "ETH-USD": 0.2764, "SHY": 0.2284, "SCHH": 0.2569}, "target_weights": {"XLK": 0.25, "ETH-USD": 0.25, "SHY": 0.25, "SCHH": 0.25}, "max_deviation": 0.0264, "total_turnover": 0.06667, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "ETH-USD", "primary_trade": 0.0264}} +{"id": "T6_all_20251120_0197", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["USMV", "AVAX-USD", "INDS", "SGOV"], "decision_date": "2025-11-20", "context_summary": "Max weight deviation: 0.0119, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.2457, target=0.2500\n AVAX-USD: current=0.2619, target=0.2500\n INDS: current=0.2533, target=0.2500\n SGOV: current=0.2391, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0119.\nRebalancing threshold: 0.0500.\n0.0119 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0305, transaction cost = 0.000031 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2457, "AVAX-USD": 0.2619, "INDS": 0.2533, "SGOV": 0.2391}, "target_weights": {"USMV": 0.25, "AVAX-USD": 0.25, "INDS": 0.25, "SGOV": 0.25}, "max_deviation": 0.0119, "total_turnover": 0.030533, "transaction_cost": 3.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "AVAX-USD", "primary_trade": 0.0119}} +{"id": "T6_all_20250623_0201", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLY", "LINK-USD", "IYR", "STIP"], "decision_date": "2025-06-23", "context_summary": "Max weight deviation: 0.0301, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLY: current=0.2709, target=0.2500\n LINK-USD: current=0.2635, target=0.2500\n IYR: current=0.2457, target=0.2500\n STIP: current=0.2199, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (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 = 0.0687, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"XLY": 0.2709, "LINK-USD": 0.2635, "IYR": 0.2457, "STIP": 0.2199}, "target_weights": {"XLY": 0.25, "LINK-USD": 0.25, "IYR": 0.25, "STIP": 0.25}, "max_deviation": 0.0301, "total_turnover": 0.068699, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "STIP", "primary_trade": -0.0301}} +{"id": "T6_all_20251203_0204", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "BNB-USD", "SHY", "CSHI"], "decision_date": "2025-12-03", "context_summary": "Max weight deviation: 0.0170, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n SPY: current=0.1850, target=0.2500\n BNB-USD: current=0.2615, target=0.2500\n SHY: current=0.2496, target=0.2500\n CSHI: current=0.3039, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of SPY", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0170.\nRebalancing threshold: 0.0500.\n0.0170 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0343, transaction cost = 0.000034 (negligible vs. drift).", "metadata": {"current_weights": {"SPY": 0.185, "BNB-USD": 0.2615, "SHY": 0.2496, "CSHI": 0.3039}, "target_weights": {"SPY": 0.25, "BNB-USD": 0.25, "SHY": 0.25, "CSHI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.034275, "transaction_cost": 3.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9046, "primary_asset": "SPY", "primary_trade": -0.065}} +{"id": "T6_all_20250814_0208", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["ACWI", "AVAX-USD", "BIL", "DBA"], "decision_date": "2025-08-14", "context_summary": "Max weight deviation: 0.0405, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.2805, target=0.2500\n AVAX-USD: current=0.2648, target=0.2500\n BIL: current=0.2697, target=0.2500\n DBA: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of DBA", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0405.\nRebalancing threshold: 0.0500.\n0.0405 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0811, transaction cost = 0.000081 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2805, "AVAX-USD": 0.2648, "BIL": 0.2697, "DBA": 0.185}, "target_weights": {"ACWI": 0.25, "AVAX-USD": 0.25, "BIL": 0.25, "DBA": 0.25}, "max_deviation": 0.065, "total_turnover": 0.081074, "transaction_cost": 8.1e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "DBA", "primary_trade": -0.065}} +{"id": "T6_all_20250618_0211", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ETH-USD", "IYR", "ICSH"], "decision_date": "2025-06-18", "context_summary": "Max weight deviation: 0.0345, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QQQ: current=0.2845, target=0.2500\n ETH-USD: current=0.2408, target=0.2500\n IYR: current=0.2398, target=0.2500\n ICSH: 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: 0.0345.\nRebalancing threshold: 0.0500.\n0.0345 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0691, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2845, "ETH-USD": 0.2408, "IYR": 0.2398, "ICSH": 0.2348}, "target_weights": {"QQQ": 0.25, "ETH-USD": 0.25, "IYR": 0.25, "ICSH": 0.25}, "max_deviation": 0.0345, "total_turnover": 0.069087, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "QQQ", "primary_trade": 0.0345}} +{"id": "T6_all_20250513_0213", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLU", "ADA-USD", "TLT", "WEAT"], "decision_date": "2025-05-13", "context_summary": "Max weight deviation: 0.0284, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLU: current=0.2643, target=0.2500\n ADA-USD: current=0.2342, target=0.2500\n TLT: current=0.2231, target=0.2500\n WEAT: 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": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0284.\nRebalancing threshold: 0.0500.\n0.0284 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0854, transaction cost = 0.000085 (negligible vs. drift).", "metadata": {"current_weights": {"XLU": 0.2643, "ADA-USD": 0.2342, "TLT": 0.2231, "WEAT": 0.2784}, "target_weights": {"XLU": 0.25, "ADA-USD": 0.25, "TLT": 0.25, "WEAT": 0.25}, "max_deviation": 0.0284, "total_turnover": 0.085354, "transaction_cost": 8.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "WEAT", "primary_trade": 0.0284}} +{"id": "T6_all_20250429_0216", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLK", "LINK-USD", "REZ", "IEF"], "decision_date": "2025-04-29", "context_summary": "Max weight deviation: 0.0462, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.2684, target=0.2500\n LINK-USD: current=0.1850, target=0.2500\n REZ: current=0.2822, target=0.2500\n IEF: current=0.2644, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0462.\nRebalancing threshold: 0.0500.\n0.0462 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0923, transaction cost = 0.000092 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2684, "LINK-USD": 0.185, "REZ": 0.2822, "IEF": 0.2644}, "target_weights": {"XLK": 0.25, "LINK-USD": 0.25, "REZ": 0.25, "IEF": 0.25}, "max_deviation": 0.065, "total_turnover": 0.092303, "transaction_cost": 9.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "LINK-USD", "primary_trade": -0.065}} +{"id": "T6_all_20250822_0218", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IWM", "BNB-USD", "TLT", "CSHI"], "decision_date": "2025-08-22", "context_summary": "Max weight deviation: 0.0219, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IWM: current=0.2076, target=0.2500\n BNB-USD: current=0.3150, target=0.2500\n TLT: current=0.2461, target=0.2500\n CSHI: current=0.2313, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of BNB-USD", "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": {"IWM": 0.2076, "BNB-USD": 0.315, "TLT": 0.2461, "CSHI": 0.2313}, "target_weights": {"IWM": 0.25, "BNB-USD": 0.25, "TLT": 0.25, "CSHI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.043723, "transaction_cost": 4.4e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": 0.065}} +{"id": "T6_all_20250922_0219", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLK", "ETH-USD", "IGOV", "DBC"], "decision_date": "2025-09-22", "context_summary": "Max weight deviation: 0.0337, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.2837, target=0.2500\n ETH-USD: current=0.2424, target=0.2500\n IGOV: current=0.2307, target=0.2500\n DBC: current=0.2432, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0337.\nRebalancing threshold: 0.0500.\n0.0337 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0675, transaction cost = 0.000067 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.2837, "ETH-USD": 0.2424, "IGOV": 0.2307, "DBC": 0.2432}, "target_weights": {"XLK": 0.25, "ETH-USD": 0.25, "IGOV": 0.25, "DBC": 0.25}, "max_deviation": 0.0337, "total_turnover": 0.067499, "transaction_cost": 6.7e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XLK", "primary_trade": 0.0337}} +{"id": "T6_all_20250912_0220", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["EWJ", "AVAX-USD", "WEAT", "VNQI"], "decision_date": "2025-09-12", "context_summary": "Max weight deviation: 0.0398, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.2740, target=0.2500\n AVAX-USD: current=0.2684, target=0.2500\n WEAT: current=0.2727, target=0.2500\n VNQI: current=0.1850, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of VNQI", "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 = 0.0797, transaction cost = 0.000080 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.274, "AVAX-USD": 0.2684, "WEAT": 0.2727, "VNQI": 0.185}, "target_weights": {"EWJ": 0.25, "AVAX-USD": 0.25, "WEAT": 0.25, "VNQI": 0.25}, "max_deviation": 0.06503, "total_turnover": 0.07968, "transaction_cost": 8e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "VNQI", "primary_trade": -0.065}} +{"id": "T6_all_20250114_0223", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "ETH-USD", "REZ", "TLH"], "decision_date": "2025-01-14", "context_summary": "Max weight deviation: 0.0146, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QQQ: current=0.2628, target=0.2500\n ETH-USD: current=0.2354, target=0.2500\n REZ: current=0.2429, target=0.2500\n TLH: current=0.2589, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0146.\nRebalancing threshold: 0.0500.\n0.0146 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0434, transaction cost = 0.000043 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2628, "ETH-USD": 0.2354, "REZ": 0.2429, "TLH": 0.2589}, "target_weights": {"QQQ": 0.25, "ETH-USD": 0.25, "REZ": 0.25, "TLH": 0.25}, "max_deviation": 0.0146, "total_turnover": 0.043391, "transaction_cost": 4.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "ETH-USD", "primary_trade": -0.0146}} +{"id": "T6_all_20250911_0224", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["XLK", "AVAX-USD", "IYR", "CORN"], "decision_date": "2025-09-11", "context_summary": "Max weight deviation: 0.0261, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLK: current=0.3149, target=0.2500\n AVAX-USD: current=0.2218, target=0.2500\n IYR: current=0.2094, target=0.2500\n CORN: current=0.2539, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0649 of XLK", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0261.\nRebalancing threshold: 0.0500.\n0.0261 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0554, transaction cost = 0.000055 (negligible vs. drift).", "metadata": {"current_weights": {"XLK": 0.3149, "AVAX-USD": 0.2218, "IYR": 0.2094, "CORN": 0.2539}, "target_weights": {"XLK": 0.25, "AVAX-USD": 0.25, "IYR": 0.25, "CORN": 0.25}, "max_deviation": 0.064922, "total_turnover": 0.055369, "transaction_cost": 5.5e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "XLK", "primary_trade": 0.0649}} +{"id": "T6_all_20250829_0228", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QUAL", "ADA-USD", "UNG", "SGOV"], "decision_date": "2025-08-29", "context_summary": "Max weight deviation: 0.0346, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2513, target=0.2500\n ADA-USD: current=0.2789, target=0.2500\n UNG: current=0.1850, target=0.2500\n SGOV: current=0.2848, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of UNG", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0346.\nRebalancing threshold: 0.0500.\n0.0346 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0691, transaction cost = 0.000069 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.2513, "ADA-USD": 0.2789, "UNG": 0.185, "SGOV": 0.2848}, "target_weights": {"QUAL": 0.25, "ADA-USD": 0.25, "UNG": 0.25, "SGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.069112, "transaction_cost": 6.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "UNG", "primary_trade": -0.065}} +{"id": "T6_all_20250116_0230", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BTC-USD", "MORT", "DBC"], "decision_date": "2025-01-16", "context_summary": "Max weight deviation: 0.0343, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VLUE: current=0.2310, target=0.2500\n BTC-USD: current=0.2599, target=0.2500\n MORT: current=0.1941, target=0.2500\n DBC: 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 DBC", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0343.\nRebalancing threshold: 0.0500.\n0.0343 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0790, transaction cost = 0.000079 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.231, "BTC-USD": 0.2599, "MORT": 0.1941, "DBC": 0.315}, "target_weights": {"VLUE": 0.25, "BTC-USD": 0.25, "MORT": 0.25, "DBC": 0.25}, "max_deviation": 0.065, "total_turnover": 0.078996, "transaction_cost": 7.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "DBC", "primary_trade": 0.065}} +{"id": "T6_all_20250403_0234", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EEM", "ADA-USD", "BIL", "SHY"], "decision_date": "2025-04-03", "context_summary": "Max weight deviation: 0.0186, 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=0.2790, target=0.2500\n BIL: current=0.2808, target=0.2500\n SHY: current=0.2552, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0186.\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": {"EEM": 0.185, "ADA-USD": 0.279, "BIL": 0.2808, "SHY": 0.2552}, "target_weights": {"EEM": 0.25, "ADA-USD": 0.25, "BIL": 0.25, "SHY": 0.25}, "max_deviation": 0.065, "total_turnover": 0.037205, "transaction_cost": 3.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EEM", "primary_trade": -0.065}} +{"id": "T6_all_20250217_0236", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "ADA-USD", "IAU", "IEF"], "decision_date": "2025-02-17", "context_summary": "Max weight deviation: 0.0213, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.1851, target=0.2500\n ADA-USD: current=0.2687, target=0.2500\n IAU: current=0.2635, target=0.2500\n IEF: current=0.2827, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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 QUAL", "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 = 0.0425, transaction cost = 0.000043 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.1851, "ADA-USD": 0.2687, "IAU": 0.2635, "IEF": 0.2827}, "target_weights": {"QUAL": 0.25, "ADA-USD": 0.25, "IAU": 0.25, "IEF": 0.25}, "max_deviation": 0.064944, "total_turnover": 0.042522, "transaction_cost": 4.3e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "QUAL", "primary_trade": -0.0649}} +{"id": "T6_all_20250310_0240", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QQQ", "DOT-USD", "HAUZ", "BIL"], "decision_date": "2025-03-10", "context_summary": "Max weight deviation: 0.0111, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QQQ: current=0.2289, target=0.2500\n DOT-USD: current=0.2160, target=0.2500\n HAUZ: current=0.3150, target=0.2500\n BIL: current=0.2400, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0111.\nRebalancing threshold: 0.0500.\n0.0111 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0221, transaction cost = 0.000022 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2289, "DOT-USD": 0.216, "HAUZ": 0.315, "BIL": 0.24}, "target_weights": {"QQQ": 0.25, "DOT-USD": 0.25, "HAUZ": 0.25, "BIL": 0.25}, "max_deviation": 0.065, "total_turnover": 0.022146, "transaction_cost": 2.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "HAUZ", "primary_trade": 0.065}} +{"id": "T6_all_20251110_0244", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLRE", "ADA-USD", "HYG", "CSHI"], "decision_date": "2025-11-10", "context_summary": "Max weight deviation: 0.0184, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLRE: current=0.2496, target=0.2500\n ADA-USD: current=0.1850, target=0.2500\n HYG: current=0.3030, target=0.2500\n CSHI: current=0.2624, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0184.\nRebalancing threshold: 0.0500.\n0.0184 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0370, transaction cost = 0.000037 (negligible vs. drift).", "metadata": {"current_weights": {"XLRE": 0.2496, "ADA-USD": 0.185, "HYG": 0.303, "CSHI": 0.2624}, "target_weights": {"XLRE": 0.25, "ADA-USD": 0.25, "HYG": 0.25, "CSHI": 0.25}, "max_deviation": 0.065, "total_turnover": 0.037003, "transaction_cost": 3.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "ADA-USD", "primary_trade": -0.065}} +{"id": "T6_all_20251022_0249", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["USMV", "XRP-USD", "SGOV", "HAUZ"], "decision_date": "2025-10-22", "context_summary": "Max weight deviation: 0.0309, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n USMV: current=0.2798, target=0.2500\n XRP-USD: current=0.2191, target=0.2500\n SGOV: current=0.2257, target=0.2500\n HAUZ: current=0.2755, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0309.\nRebalancing threshold: 0.0500.\n0.0309 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.1106, transaction cost = 0.000111 (negligible vs. drift).", "metadata": {"current_weights": {"USMV": 0.2798, "XRP-USD": 0.2191, "SGOV": 0.2257, "HAUZ": 0.2755}, "target_weights": {"USMV": 0.25, "XRP-USD": 0.25, "SGOV": 0.25, "HAUZ": 0.25}, "max_deviation": 0.0309, "total_turnover": 0.110554, "transaction_cost": 0.000111, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "XRP-USD", "primary_trade": -0.0309}} +{"id": "T6_all_20250813_0252", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["FXI", "ETH-USD", "SGOV", "SCHH"], "decision_date": "2025-08-13", "context_summary": "Max weight deviation: 0.0154, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n FXI: current=0.2385, target=0.2500\n ETH-USD: current=0.2528, target=0.2500\n SGOV: current=0.3149, target=0.2500\n SCHH: current=0.1938, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0649 of SGOV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0154.\nRebalancing threshold: 0.0500.\n0.0154 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0320, transaction cost = 0.000032 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2385, "ETH-USD": 0.2528, "SGOV": 0.3149, "SCHH": 0.1938}, "target_weights": {"FXI": 0.25, "ETH-USD": 0.25, "SGOV": 0.25, "SCHH": 0.25}, "max_deviation": 0.064867, "total_turnover": 0.032031, "transaction_cost": 3.2e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "SGOV", "primary_trade": 0.0649}} +{"id": "T6_all_20250207_0254", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["FXI", "BNB-USD", "SGOV", "SCHH"], "decision_date": "2025-02-07", "context_summary": "Max weight deviation: 0.0189, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n FXI: current=0.2325, target=0.2500\n BNB-USD: current=0.3150, target=0.2500\n SGOV: current=0.1998, target=0.2500\n SCHH: current=0.2528, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0189.\nRebalancing threshold: 0.0500.\n0.0189 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0394, transaction cost = 0.000039 (negligible vs. drift).", "metadata": {"current_weights": {"FXI": 0.2325, "BNB-USD": 0.315, "SGOV": 0.1998, "SCHH": 0.2528}, "target_weights": {"FXI": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "SCHH": 0.25}, "max_deviation": 0.065, "total_turnover": 0.039413, "transaction_cost": 3.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9047, "primary_asset": "BNB-USD", "primary_trade": 0.065}} +{"id": "T6_all_20250423_0256", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["XLP", "SOL-USD", "VNQI", "IAU"], "decision_date": "2025-04-23", "context_summary": "Max weight deviation: 0.0499, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.2079, target=0.2500\n SOL-USD: current=0.2372, target=0.2500\n VNQI: current=0.2398, target=0.2500\n IAU: current=0.3150, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0499.\nRebalancing threshold: 0.0500.\n0.0499 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0997, transaction cost = 0.000100 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.2079, "SOL-USD": 0.2372, "VNQI": 0.2398, "IAU": 0.315}, "target_weights": {"XLP": 0.25, "SOL-USD": 0.25, "VNQI": 0.25, "IAU": 0.25}, "max_deviation": 0.065, "total_turnover": 0.099748, "transaction_cost": 0.0001, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "IAU", "primary_trade": 0.065}} +{"id": "T6_all_20250408_0258", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["EEM", "ETH-USD", "BIL", "PPLT"], "decision_date": "2025-04-08", "context_summary": "Max weight deviation: 0.0240, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EEM: current=0.2595, target=0.2500\n ETH-USD: current=0.1850, target=0.2500\n BIL: current=0.2438, target=0.2500\n PPLT: current=0.3117, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0240.\nRebalancing threshold: 0.0500.\n0.0240 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0526, transaction cost = 0.000053 (negligible vs. drift).", "metadata": {"current_weights": {"EEM": 0.2595, "ETH-USD": 0.185, "BIL": 0.2438, "PPLT": 0.3117}, "target_weights": {"EEM": 0.25, "ETH-USD": 0.25, "BIL": 0.25, "PPLT": 0.25}, "max_deviation": 0.065, "total_turnover": 0.052585, "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_20250702_0262", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY", "BNB-USD", "SGOV", "TIP"], "decision_date": "2025-07-02", "context_summary": "Max weight deviation: 0.0201, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n SPY: current=0.2073, target=0.2500\n BNB-USD: current=0.2513, target=0.2500\n SGOV: current=0.3150, target=0.2500\n TIP: current=0.2264, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; sell 0.0650 of SGOV", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0201.\nRebalancing threshold: 0.0500.\n0.0201 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0410, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"SPY": 0.2073, "BNB-USD": 0.2513, "SGOV": 0.315, "TIP": 0.2264}, "target_weights": {"SPY": 0.25, "BNB-USD": 0.25, "SGOV": 0.25, "TIP": 0.25}, "max_deviation": 0.065, "total_turnover": 0.041034, "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_20251215_0263", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EWJ", "ADA-USD", "ICSH", "IAU"], "decision_date": "2025-12-15", "context_summary": "Max weight deviation: 0.0204, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EWJ: current=0.2377, target=0.2500\n ADA-USD: current=0.2455, target=0.2500\n ICSH: current=0.2704, target=0.2500\n IAU: 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: 0.0204.\nRebalancing threshold: 0.0500.\n0.0204 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0408, transaction cost = 0.000041 (negligible vs. drift).", "metadata": {"current_weights": {"EWJ": 0.2377, "ADA-USD": 0.2455, "ICSH": 0.2704, "IAU": 0.2464}, "target_weights": {"EWJ": 0.25, "ADA-USD": 0.25, "ICSH": 0.25, "IAU": 0.25}, "max_deviation": 0.0204, "total_turnover": 0.040849, "transaction_cost": 4.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "ICSH", "primary_trade": 0.0204}} +{"id": "T6_all_20251029_0267", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["IVV", "BTC-USD", "SHV", "DBB"], "decision_date": "2025-10-29", "context_summary": "Max weight deviation: 0.0336, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n IVV: current=0.2440, target=0.2500\n BTC-USD: current=0.2836, target=0.2500\n SHV: current=0.2521, target=0.2500\n DBB: current=0.2202, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0336.\nRebalancing threshold: 0.0500.\n0.0336 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0714, transaction cost = 0.000071 (negligible vs. drift).", "metadata": {"current_weights": {"IVV": 0.244, "BTC-USD": 0.2836, "SHV": 0.2521, "DBB": 0.2202}, "target_weights": {"IVV": 0.25, "BTC-USD": 0.25, "SHV": 0.25, "DBB": 0.25}, "max_deviation": 0.0336, "total_turnover": 0.071448, "transaction_cost": 7.1e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "BTC-USD", "primary_trade": 0.0336}} +{"id": "T6_all_20250501_0269", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["VEA", "ADA-USD", "SOYB", "EMB"], "decision_date": "2025-05-01", "context_summary": "Max weight deviation: 0.0460, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VEA: current=0.2960, target=0.2500\n ADA-USD: current=0.2472, target=0.2500\n SOYB: current=0.2157, target=0.2500\n EMB: current=0.2411, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (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 = 0.0919, transaction cost = 0.000092 (negligible vs. drift).", "metadata": {"current_weights": {"VEA": 0.296, "ADA-USD": 0.2472, "SOYB": 0.2157, "EMB": 0.2411}, "target_weights": {"VEA": 0.25, "ADA-USD": 0.25, "SOYB": 0.25, "EMB": 0.25}, "max_deviation": 0.046, "total_turnover": 0.09194, "transaction_cost": 9.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "VEA", "primary_trade": 0.046}} +{"id": "T6_all_20250127_0270", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["VLUE", "BNB-USD", "REZ", "SGOV"], "decision_date": "2025-01-27", "context_summary": "Max weight deviation: 0.0296, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VLUE: current=0.2142, target=0.2500\n BNB-USD: current=0.2430, target=0.2500\n REZ: current=0.2278, target=0.2500\n SGOV: 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 SGOV", "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 = 0.0592, transaction cost = 0.000059 (negligible vs. drift).", "metadata": {"current_weights": {"VLUE": 0.2142, "BNB-USD": 0.243, "REZ": 0.2278, "SGOV": 0.315}, "target_weights": {"VLUE": 0.25, "BNB-USD": 0.25, "REZ": 0.25, "SGOV": 0.25}, "max_deviation": 0.065, "total_turnover": 0.059248, "transaction_cost": 5.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9044, "primary_asset": "SGOV", "primary_trade": 0.065}} +{"id": "T6_all_20250508_0272", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["QUAL", "SOL-USD", "HAUZ", "SGOV"], "decision_date": "2025-05-08", "context_summary": "Max weight deviation: 0.0349, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QUAL: current=0.2760, target=0.2500\n SOL-USD: current=0.2643, target=0.2500\n HAUZ: current=0.1850, target=0.2500\n SGOV: current=0.2747, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0650 of HAUZ", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0349.\nRebalancing threshold: 0.0500.\n0.0349 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0698, transaction cost = 0.000070 (negligible vs. drift).", "metadata": {"current_weights": {"QUAL": 0.276, "SOL-USD": 0.2643, "HAUZ": 0.185, "SGOV": 0.2747}, "target_weights": {"QUAL": 0.25, "SOL-USD": 0.25, "HAUZ": 0.25, "SGOV": 0.25}, "max_deviation": 0.065034, "total_turnover": 0.069766, "transaction_cost": 7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9045, "primary_asset": "HAUZ", "primary_trade": -0.065}} +{"id": "T6_all_20250828_0273", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["QQQ", "XRP-USD", "JNK", "BNO"], "decision_date": "2025-08-28", "context_summary": "Max weight deviation: 0.0218, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n QQQ: current=0.2587, target=0.2500\n XRP-USD: current=0.2282, target=0.2500\n JNK: current=0.2591, target=0.2500\n BNO: current=0.2540, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0218.\nRebalancing threshold: 0.0500.\n0.0218 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0437, transaction cost = 0.000044 (negligible vs. drift).", "metadata": {"current_weights": {"QQQ": 0.2587, "XRP-USD": 0.2282, "JNK": 0.2591, "BNO": 0.254}, "target_weights": {"QQQ": 0.25, "XRP-USD": 0.25, "JNK": 0.25, "BNO": 0.25}, "max_deviation": 0.0218, "total_turnover": 0.043692, "transaction_cost": 4.4e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9046, "primary_asset": "XRP-USD", "primary_trade": -0.0218}} +{"id": "T6_all_20251002_0275", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["^VIX", "BNB-USD", "BNDX", "BIL"], "decision_date": "2025-10-02", "context_summary": "Max weight deviation: 0.0280, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ^VIX: current=0.2347, target=0.2500\n BNB-USD: current=0.2780, target=0.2500\n BNDX: current=0.2470, target=0.2500\n BIL: current=0.2403, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0280.\nRebalancing threshold: 0.0500.\n0.0280 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0561, transaction cost = 0.000056 (negligible vs. drift).", "metadata": {"current_weights": {"^VIX": 0.2347, "BNB-USD": 0.278, "BNDX": 0.247, "BIL": 0.2403}, "target_weights": {"^VIX": 0.25, "BNB-USD": 0.25, "BNDX": 0.25, "BIL": 0.25}, "max_deviation": 0.028, "total_turnover": 0.05608, "transaction_cost": 5.6e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "BNB-USD", "primary_trade": 0.028}} +{"id": "T6_all_20250526_0277", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "BNB-USD", "REZ", "SHY"], "decision_date": "2025-05-26", "context_summary": "Max weight deviation: 0.0154, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.2367, target=0.2500\n BNB-USD: current=0.2609, target=0.2500\n REZ: current=0.2654, target=0.2500\n SHY: 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": "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 = 0.0526, transaction cost = 0.000053 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.2367, "BNB-USD": 0.2609, "REZ": 0.2654, "SHY": 0.237}, "target_weights": {"XLP": 0.25, "BNB-USD": 0.25, "REZ": 0.25, "SHY": 0.25}, "max_deviation": 0.0154, "total_turnover": 0.052566, "transaction_cost": 5.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "REZ", "primary_trade": 0.0154}} +{"id": "T6_all_20250418_0279", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["ACWI", "XRP-USD", "ICSH", "SCHP"], "decision_date": "2025-04-18", "context_summary": "Max weight deviation: 0.0147, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.2647, target=0.2500\n XRP-USD: current=0.2358, target=0.2500\n ICSH: current=0.2379, target=0.2500\n SCHP: current=0.2617, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bear\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (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 = 0.0527, transaction cost = 0.000053 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2647, "XRP-USD": 0.2358, "ICSH": 0.2379, "SCHP": 0.2617}, "target_weights": {"ACWI": 0.25, "XRP-USD": 0.25, "ICSH": 0.25, "SCHP": 0.25}, "max_deviation": 0.0147, "total_turnover": 0.052711, "transaction_cost": 5.3e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "ACWI", "primary_trade": 0.0147}} +{"id": "T6_all_20250703_0282", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["EFA", "DOT-USD", "GLD", "REZ"], "decision_date": "2025-07-03", "context_summary": "Max weight deviation: 0.0127, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n EFA: current=0.1849, target=0.2500\n DOT-USD: current=0.2141, target=0.2500\n GLD: current=0.3010, target=0.2500\n REZ: current=0.3000, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "yes; buy 0.0651 of EFA", "answer_numeric": 1.0, "explanation": "Maximum absolute deviation: 0.0127.\nRebalancing threshold: 0.0500.\n0.0127 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0395, transaction cost = 0.000039 (negligible vs. drift).", "metadata": {"current_weights": {"EFA": 0.1849, "DOT-USD": 0.2141, "GLD": 0.301, "REZ": 0.3}, "target_weights": {"EFA": 0.25, "DOT-USD": 0.25, "GLD": 0.25, "REZ": 0.25}, "max_deviation": 0.065095, "total_turnover": 0.039493, "transaction_cost": 3.9e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 3020, "primary_asset": "EFA", "primary_trade": -0.0651}} +{"id": "T6_all_20251006_0283", "template": "T6", "complexity": 3, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["VTI", "DOT-USD", "TIP", "ICSH"], "decision_date": "2025-10-06", "context_summary": "Max weight deviation: 0.0325, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n VTI: current=0.2585, target=0.2500\n DOT-USD: current=0.2690, target=0.2500\n TIP: current=0.2175, target=0.2500\n ICSH: current=0.2549, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: bull\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0325.\nRebalancing threshold: 0.0500.\n0.0325 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0649, transaction cost = 0.000065 (negligible vs. drift).", "metadata": {"current_weights": {"VTI": 0.2585, "DOT-USD": 0.269, "TIP": 0.2175, "ICSH": 0.2549}, "target_weights": {"VTI": 0.25, "DOT-USD": 0.25, "TIP": 0.25, "ICSH": 0.25}, "max_deviation": 0.0325, "total_turnover": 0.064913, "transaction_cost": 6.5e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 3020, "primary_asset": "TIP", "primary_trade": -0.0325}} +{"id": "T6_all_20250205_0284", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["XLP", "LINK-USD", "SCHH", "CSHI"], "decision_date": "2025-02-05", "context_summary": "Max weight deviation: 0.0383, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n XLP: current=0.2700, target=0.2500\n LINK-USD: current=0.1850, target=0.2500\n SCHH: current=0.2793, target=0.2500\n CSHI: current=0.2657, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and 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: 0.0383.\nRebalancing threshold: 0.0500.\n0.0383 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0766, transaction cost = 0.000077 (negligible vs. drift).", "metadata": {"current_weights": {"XLP": 0.27, "LINK-USD": 0.185, "SCHH": 0.2793, "CSHI": 0.2657}, "target_weights": {"XLP": 0.25, "LINK-USD": 0.25, "SCHH": 0.25, "CSHI": 0.25}, "max_deviation": 0.065031, "total_turnover": 0.076558, "transaction_cost": 7.7e-05, "threshold": 0.05, "should_rebalance": true, "has_text": true, "text_chars": 9044, "primary_asset": "LINK-USD", "primary_trade": -0.065}} +{"id": "T6_all_20250103_0285", "template": "T6", "complexity": 3, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["ACWI", "ETH-USD", "CORN", "INDS"], "decision_date": "2025-01-03", "context_summary": "Max weight deviation: 0.0309, threshold: 0.05. Decision: no (rebalance).", "question": "Portfolio holdings (current vs. target weights):\n ACWI: current=0.2335, target=0.2500\n ETH-USD: current=0.2459, target=0.2500\n CORN: current=0.2809, target=0.2500\n INDS: current=0.2397, target=0.2500\n\nRebalancing threshold: 5.00%\nTransaction cost (round-trip): 0.10%\nMarket regime: sideways\n\nPart A: Should this portfolio be rebalanced? (yes or no)\nPart B: If yes - identify the asset with the largest deviation from its target weight and specify the required trade as a fraction of portfolio (e.g., 'buy 0.0300 of ASSET' or 'sell 0.0500 of ASSET').", "answer": "no", "answer_numeric": 0.0, "explanation": "Maximum absolute deviation: 0.0309.\nRebalancing threshold: 0.0500.\n0.0309 <= 0.0500 \u2192 decision: 'no'.\nIf rebalanced: total turnover = 0.0618, transaction cost = 0.000062 (negligible vs. drift).", "metadata": {"current_weights": {"ACWI": 0.2335, "ETH-USD": 0.2459, "CORN": 0.2809, "INDS": 0.2397}, "target_weights": {"ACWI": 0.25, "ETH-USD": 0.25, "CORN": 0.25, "INDS": 0.25}, "max_deviation": 0.0309, "total_turnover": 0.061793, "transaction_cost": 6.2e-05, "threshold": 0.05, "should_rebalance": false, "has_text": true, "text_chars": 9045, "primary_asset": "CORN", "primary_trade": 0.0309}} +{"id": "T7_all_20251226_0000", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-26", "context_summary": "Regime: sideways. SPY trailing return: +3.1%, annualized vol: 12.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=664.67, end=685.14, trailing_return=+3.08%\nAnnualized volatility: 12.90%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.6800, t10y3m_spread=0.4600, breakeven_10y=2.2400, hy_oas=2.8400, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.1800, vix=13.4700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.08%\n Annualized volatility: 12.90%\n Macro: fed_funds=3.6400, vix=13.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.030803, "annualized_vol": 0.129039, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251027_0001", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-27", "context_summary": "Regime: bull. SPY trailing return: +9.2%, annualized vol: 11.2%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=616.49, end=673.42, trailing_return=+9.23%\nAnnualized volatility: 11.20%\nMacro indicators: fed_funds_rate=4.1100, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5400, t10y3m_spread=0.0900, breakeven_10y=2.2900, hy_oas=2.8800, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.1900, vix=16.3700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.23%\n Annualized volatility: 11.20%\n Macro: fed_funds=4.1100, vix=16.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.092337, "annualized_vol": 0.11199, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20251209_0002", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-09", "context_summary": "Regime: sideways. SPY trailing return: +3.7%, annualized vol: 12.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=655.35, end=679.76, trailing_return=+3.72%\nAnnualized volatility: 12.40%\nMacro indicators: fed_funds_rate=3.8900, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.6000, t10y3m_spread=0.4400, breakeven_10y=2.2600, hy_oas=2.8900, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.1900, vix=16.6600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.72%\n Annualized volatility: 12.40%\n Macro: fed_funds=3.8900, vix=16.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.037245, "annualized_vol": 0.124027, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250716_0003", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-16", "context_summary": "Regime: bull. SPY trailing return: +18.5%, annualized vol: 13.5%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=520.44, end=616.91, trailing_return=+18.53%\nAnnualized volatility: 13.50%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5500, t10y3m_spread=0.0800, breakeven_10y=2.4100, hy_oas=2.9500, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.7200, vix=17.3800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +18.53%\n Annualized volatility: 13.50%\n Macro: fed_funds=4.3300, vix=17.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.185348, "annualized_vol": 0.134998, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250424_0004", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-24", "context_summary": "Regime: bear. SPY trailing return: -11.2%, annualized vol: 20.6%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=595.88, end=529.35, trailing_return=-11.16%\nAnnualized volatility: 20.55%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5900, t10y3m_spread=0.0700, breakeven_10y=2.2900, hy_oas=3.7500, ig_oas=1.0800, ted_spread=0.0900, mortgage_30y=6.8300, vix=28.4500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -11.16%\n Annualized volatility: 20.55%\n Macro: fed_funds=4.3300, vix=28.5\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.111641, "annualized_vol": 0.205536, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20250711_0006", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-11", "context_summary": "Regime: sideways. SPY trailing return: +16.4%, annualized vol: 14.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=533.01, end=620.56, trailing_return=+16.42%\nAnnualized volatility: 14.45%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.4900, t10y3m_spread=-0.0700, breakeven_10y=2.3400, hy_oas=2.9200, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.7200, vix=15.7800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +16.42%\n Annualized volatility: 14.45%\n Macro: fed_funds=4.3300, vix=15.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.164249, "annualized_vol": 0.144484, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250421_0007", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-21", "context_summary": "Regime: bear. SPY trailing return: -13.4%, annualized vol: 19.4%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=601.03, end=520.44, trailing_return=-13.41%\nAnnualized volatility: 19.36%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5300, t10y3m_spread=0.0000, breakeven_10y=2.2300, hy_oas=4.0200, ig_oas=1.1100, ted_spread=0.0900, mortgage_30y=6.8300, vix=29.6500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -13.41%\n Annualized volatility: 19.36%\n Macro: fed_funds=4.3300, vix=29.6\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.134082, "annualized_vol": 0.193609, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250425_0008", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-25", "context_summary": "Regime: bear. SPY trailing return: -8.9%, annualized vol: 21.0%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=593.20, end=540.49, trailing_return=-8.89%\nAnnualized volatility: 20.97%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5500, t10y3m_spread=0.0000, breakeven_10y=2.3000, hy_oas=3.7300, ig_oas=1.0600, ted_spread=0.0900, mortgage_30y=6.8100, vix=26.4700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -8.89%\n Annualized volatility: 20.97%\n Macro: fed_funds=4.3300, vix=26.5\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.088858, "annualized_vol": 0.209726, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20250521_0010", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-21", "context_summary": "Regime: sideways. SPY trailing return: +0.1%, annualized vol: 21.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=585.74, end=586.13, trailing_return=+0.07%\nAnnualized volatility: 21.45%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5100, t10y3m_spread=0.1000, breakeven_10y=2.3500, hy_oas=3.2000, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=6.8100, vix=18.0900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +0.07%\n Annualized volatility: 21.45%\n Macro: fed_funds=4.3300, vix=18.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.000662, "annualized_vol": 0.214455, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250131_0011", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-31", "context_summary": "Regime: sideways. SPY trailing return: +6.3%, annualized vol: 13.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=560.99, end=596.39, trailing_return=+6.31%\nAnnualized volatility: 13.02%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3400, t10y3m_spread=0.2200, breakeven_10y=2.3800, hy_oas=2.6700, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.9500, vix=15.8400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.31%\n Annualized volatility: 13.02%\n Macro: fed_funds=4.3300, vix=15.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.063107, "annualized_vol": 0.13019, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250228_0012", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-28", "context_summary": "Regime: sideways. SPY trailing return: -2.6%, annualized vol: 13.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=591.94, end=576.68, trailing_return=-2.58%\nAnnualized volatility: 13.16%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2200, t10y3m_spread=-0.0300, breakeven_10y=2.3700, hy_oas=2.8100, ig_oas=0.8500, ted_spread=0.0900, mortgage_30y=6.7600, vix=21.1300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -2.58%\n Annualized volatility: 13.16%\n Macro: fed_funds=4.3300, vix=21.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.025775, "annualized_vol": 0.131557, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250327_0013", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-27", "context_summary": "Regime: sideways. SPY trailing return: -4.2%, annualized vol: 16.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=586.50, end=562.15, trailing_return=-4.15%\nAnnualized volatility: 16.10%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3700, t10y3m_spread=0.0200, breakeven_10y=2.3700, hy_oas=3.1900, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=6.6700, vix=18.3300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -4.15%\n Annualized volatility: 16.10%\n Macro: fed_funds=4.3300, vix=18.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.041528, "annualized_vol": 0.160987, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250225_0014", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-25", "context_summary": "Regime: sideways. SPY trailing return: -0.2%, annualized vol: 12.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=590.08, end=588.67, trailing_return=-0.24%\nAnnualized volatility: 12.86%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2700, t10y3m_spread=0.0900, breakeven_10y=2.4200, hy_oas=2.7800, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.8500, vix=18.9800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -0.24%\n Annualized volatility: 12.86%\n Macro: fed_funds=4.3300, vix=19.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.002381, "annualized_vol": 0.128639, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250520_0015", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-20", "context_summary": "Regime: sideways. SPY trailing return: -0.1%, annualized vol: 21.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=588.67, end=588.11, trailing_return=-0.10%\nAnnualized volatility: 21.45%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4900, t10y3m_spread=0.0700, breakeven_10y=2.3600, hy_oas=3.2100, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.8100, vix=18.1400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -0.10%\n Annualized volatility: 21.45%\n Macro: fed_funds=4.3300, vix=18.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.000956, "annualized_vol": 0.214538, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250725_0017", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-25", "context_summary": "Regime: bull. SPY trailing return: +14.8%, annualized vol: 10.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=548.04, end=629.08, trailing_return=+14.79%\nAnnualized volatility: 10.86%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5200, t10y3m_spread=0.0100, breakeven_10y=2.4500, hy_oas=2.8200, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.7400, vix=15.3900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +14.79%\n Annualized volatility: 10.86%\n Macro: fed_funds=4.3300, vix=15.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.147885, "annualized_vol": 0.108574, "has_text": true, "text_chars": 9047}} +{"id": "T7_all_20250917_0018", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-17", "context_summary": "Regime: bull. SPY trailing return: +10.0%, annualized vol: 9.1%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=595.10, end=654.45, trailing_return=+9.97%\nAnnualized volatility: 9.15%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5300, t10y3m_spread=0.0000, breakeven_10y=2.3700, hy_oas=2.7900, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3500, vix=16.3600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.97%\n Annualized volatility: 9.15%\n Macro: fed_funds=4.3300, vix=16.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.099725, "annualized_vol": 0.091469, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250221_0019", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-21", "context_summary": "Regime: sideways. SPY trailing return: +2.8%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=585.03, end=601.65, trailing_return=+2.84%\nAnnualized volatility: 12.32%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2200, t10y3m_spread=0.1700, breakeven_10y=2.4500, hy_oas=2.6600, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.8500, vix=15.6600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.84%\n Annualized volatility: 12.32%\n Macro: fed_funds=4.3300, vix=15.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.02842, "annualized_vol": 0.12318, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20250317_0020", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-17", "context_summary": "Regime: bear. SPY trailing return: -6.9%, annualized vol: 16.5%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=596.11, end=554.76, trailing_return=-6.94%\nAnnualized volatility: 16.49%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2900, t10y3m_spread=-0.0200, breakeven_10y=2.3000, hy_oas=3.2500, ig_oas=0.9400, ted_spread=0.0900, mortgage_30y=6.6500, vix=21.7700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -6.94%\n Annualized volatility: 16.49%\n Macro: fed_funds=4.3300, vix=21.8\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.069358, "annualized_vol": 0.164858, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250324_0022", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-24", "context_summary": "Regime: sideways. SPY trailing return: -4.9%, annualized vol: 15.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=586.19, end=557.59, trailing_return=-4.88%\nAnnualized volatility: 15.71%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3100, t10y3m_spread=-0.0800, breakeven_10y=2.3300, hy_oas=3.2100, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.6700, vix=19.2800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -4.88%\n Annualized volatility: 15.71%\n Macro: fed_funds=4.3300, vix=19.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.048787, "annualized_vol": 0.157055, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250206_0023", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-06", "context_summary": "Regime: sideways. SPY trailing return: +1.8%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=585.12, end=595.58, trailing_return=+1.79%\nAnnualized volatility: 12.33%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2600, t10y3m_spread=0.1000, breakeven_10y=2.4200, hy_oas=2.6900, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.9500, vix=15.7700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.79%\n Annualized volatility: 12.33%\n Macro: fed_funds=4.3300, vix=15.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.01787, "annualized_vol": 0.123289, "has_text": true, "text_chars": 9047}} +{"id": "T7_all_20251111_0025", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-11", "context_summary": "Regime: bull. SPY trailing return: +6.2%, annualized vol: 11.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=637.89, end=677.58, trailing_return=+6.22%\nAnnualized volatility: 11.27%\nMacro indicators: fed_funds_rate=3.8700, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.1800, breakeven_10y=2.2900, hy_oas=3.0200, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.2200, vix=17.6000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.22%\n Annualized volatility: 11.27%\n Macro: fed_funds=3.8700, vix=17.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.062225, "annualized_vol": 0.112735, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250203_0026", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-03", "context_summary": "Regime: sideways. SPY trailing return: +6.0%, annualized vol: 13.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=559.78, end=593.21, trailing_return=+5.97%\nAnnualized volatility: 13.07%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3600, t10y3m_spread=0.2700, breakeven_10y=2.4200, hy_oas=2.6800, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.9500, vix=16.4300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.97%\n Annualized volatility: 13.07%\n Macro: fed_funds=4.3300, vix=16.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.059731, "annualized_vol": 0.130677, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20251008_0028", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-08", "context_summary": "Regime: bull. SPY trailing return: +7.8%, annualized vol: 8.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=616.91, end=665.33, trailing_return=+7.85%\nAnnualized volatility: 8.67%\nMacro indicators: fed_funds_rate=4.0900, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5700, t10y3m_spread=0.1300, breakeven_10y=2.3500, hy_oas=2.8200, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3400, vix=17.2400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.85%\n Annualized volatility: 8.67%\n Macro: fed_funds=4.0900, vix=17.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.078495, "annualized_vol": 0.086681, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250108_0029", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-08", "context_summary": "Regime: sideways. SPY trailing return: +1.9%, annualized vol: 12.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=569.38, end=580.21, trailing_return=+1.90%\nAnnualized volatility: 12.37%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3700, t10y3m_spread=0.3200, breakeven_10y=2.3800, hy_oas=2.7900, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.9100, vix=17.8200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.90%\n Annualized volatility: 12.37%\n Macro: fed_funds=4.3300, vix=17.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.019033, "annualized_vol": 0.123667, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250212_0030", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-12", "context_summary": "Regime: sideways. SPY trailing return: +1.7%, annualized vol: 12.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=586.68, end=596.65, trailing_return=+1.70%\nAnnualized volatility: 12.43%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2500, t10y3m_spread=0.1900, breakeven_10y=2.4600, hy_oas=2.6600, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.8900, vix=16.0200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.70%\n Annualized volatility: 12.43%\n Macro: fed_funds=4.3300, vix=16.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.017009, "annualized_vol": 0.124339, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20251105_0031", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-05", "context_summary": "Regime: sideways. SPY trailing return: +5.4%, annualized vol: 10.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=637.28, end=671.42, trailing_return=+5.36%\nAnnualized volatility: 10.80%\nMacro indicators: fed_funds_rate=3.8700, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5200, t10y3m_spread=0.1400, breakeven_10y=2.2900, hy_oas=3.1300, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.1700, vix=19.0000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.36%\n Annualized volatility: 10.80%\n Macro: fed_funds=3.8700, vix=19.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.053559, "annualized_vol": 0.107992, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251106_0033", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-06", "context_summary": "Regime: sideways. SPY trailing return: +5.4%, annualized vol: 10.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=639.47, end=673.74, trailing_return=+5.36%\nAnnualized volatility: 10.63%\nMacro indicators: fed_funds_rate=3.8700, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5400, t10y3m_spread=0.2100, breakeven_10y=2.3000, hy_oas=3.0500, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.1700, vix=18.0100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.36%\n Annualized volatility: 10.63%\n Macro: fed_funds=3.8700, vix=18.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.053604, "annualized_vol": 0.106276, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250318_0035", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-18", "context_summary": "Regime: sideways. SPY trailing return: -5.8%, annualized vol: 16.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=593.65, end=559.04, trailing_return=-5.83%\nAnnualized volatility: 16.55%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2500, t10y3m_spread=-0.0300, breakeven_10y=2.2900, hy_oas=3.1800, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.6500, vix=20.5100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -5.83%\n Annualized volatility: 16.55%\n Macro: fed_funds=4.3300, vix=20.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.058302, "annualized_vol": 0.16548, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251121_0036", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-21", "context_summary": "Regime: sideways. SPY trailing return: +0.8%, annualized vol: 12.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=643.46, end=648.84, trailing_return=+0.84%\nAnnualized volatility: 12.05%\nMacro indicators: fed_funds_rate=3.8800, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.1600, breakeven_10y=2.2400, hy_oas=3.1700, ig_oas=0.8500, ted_spread=0.0900, mortgage_30y=6.2600, vix=26.4200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +0.84%\n Annualized volatility: 12.05%\n Macro: fed_funds=3.8800, vix=26.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.008351, "annualized_vol": 0.120531, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250326_0037", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-26", "context_summary": "Regime: sideways. SPY trailing return: -4.0%, annualized vol: 15.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=592.74, end=568.94, trailing_return=-4.02%\nAnnualized volatility: 15.93%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3500, t10y3m_spread=-0.0200, breakeven_10y=2.3500, hy_oas=3.0900, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=6.6700, vix=17.1500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -4.02%\n Annualized volatility: 15.93%\n Macro: fed_funds=4.3300, vix=17.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.040159, "annualized_vol": 0.159316, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250529_0039", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-29", "context_summary": "Regime: sideways. SPY trailing return: +2.2%, annualized vol: 21.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=568.61, end=581.07, trailing_return=+2.19%\nAnnualized volatility: 21.41%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5100, t10y3m_spread=0.1200, breakeven_10y=2.3200, hy_oas=3.2300, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=6.8600, vix=19.3100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.19%\n Annualized volatility: 21.41%\n Macro: fed_funds=4.3300, vix=19.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.021908, "annualized_vol": 0.214114, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20251205_0040", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-05", "context_summary": "Regime: sideways. SPY trailing return: +4.4%, annualized vol: 12.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=652.10, end=680.52, trailing_return=+4.36%\nAnnualized volatility: 12.47%\nMacro indicators: fed_funds_rate=3.8900, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5900, t10y3m_spread=0.4000, breakeven_10y=2.2600, hy_oas=2.8800, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.1900, vix=15.7800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.36%\n Annualized volatility: 12.47%\n Macro: fed_funds=3.8900, vix=15.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.043577, "annualized_vol": 0.124748, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251020_0041", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-20", "context_summary": "Regime: bull. SPY trailing return: +4.6%, annualized vol: 10.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=631.74, end=660.63, trailing_return=+4.57%\nAnnualized volatility: 10.91%\nMacro indicators: fed_funds_rate=4.1100, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5600, t10y3m_spread=0.0200, breakeven_10y=2.2700, hy_oas=3.0400, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.2700, vix=20.7800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.57%\n Annualized volatility: 10.91%\n Macro: fed_funds=4.1100, vix=20.8\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.045726, "annualized_vol": 0.109113, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251031_0043", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-31", "context_summary": "Regime: bull. SPY trailing return: +7.8%, annualized vol: 10.6%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=626.93, end=675.98, trailing_return=+7.82%\nAnnualized volatility: 10.56%\nMacro indicators: fed_funds_rate=3.8700, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5000, t10y3m_spread=0.1900, breakeven_10y=2.2900, hy_oas=2.8500, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.1700, vix=16.9100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.82%\n Annualized volatility: 10.56%\n Macro: fed_funds=3.8700, vix=16.9\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.078236, "annualized_vol": 0.105627, "has_text": true, "text_chars": 9047}} +{"id": "T7_all_20250422_0044", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-22", "context_summary": "Regime: bear. SPY trailing return: -15.2%, annualized vol: 19.8%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=599.28, end=508.06, trailing_return=-15.22%\nAnnualized volatility: 19.79%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.6700, t10y3m_spread=0.0800, breakeven_10y=2.2200, hy_oas=4.1600, ig_oas=1.1200, ted_spread=0.0900, mortgage_30y=6.8300, vix=33.8200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -15.22%\n Annualized volatility: 19.79%\n Macro: fed_funds=4.3300, vix=33.8\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.152218, "annualized_vol": 0.197911, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250603_0045", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-03", "context_summary": "Regime: sideways. SPY trailing return: +3.2%, annualized vol: 20.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=567.69, end=585.99, trailing_return=+3.22%\nAnnualized volatility: 20.88%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5200, t10y3m_spread=0.0200, breakeven_10y=2.3300, hy_oas=3.2700, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=6.8900, vix=18.3600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.22%\n Annualized volatility: 20.88%\n Macro: fed_funds=4.3300, vix=18.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.032249, "annualized_vol": 0.208763, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250430_0046", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-30", "context_summary": "Regime: bear. SPY trailing return: -7.0%, annualized vol: 21.0%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=589.22, end=548.04, trailing_return=-6.99%\nAnnualized volatility: 21.05%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5400, t10y3m_spread=-0.1200, breakeven_10y=2.2300, hy_oas=3.7400, ig_oas=1.0600, ted_spread=0.0900, mortgage_30y=6.8100, vix=24.1700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -6.99%\n Annualized volatility: 21.05%\n Macro: fed_funds=4.3300, vix=24.2\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.069897, "annualized_vol": 0.210484, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251218_0047", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-18", "context_summary": "Regime: sideways. SPY trailing return: +1.6%, annualized vol: 12.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=657.36, end=667.60, trailing_return=+1.56%\nAnnualized volatility: 12.74%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.6700, t10y3m_spread=0.5200, breakeven_10y=2.2400, hy_oas=2.9900, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.2200, vix=17.6200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.56%\n Annualized volatility: 12.74%\n Macro: fed_funds=3.6400, vix=17.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.01558, "annualized_vol": 0.127354, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250303_0048", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-03", "context_summary": "Regime: sideways. SPY trailing return: -1.2%, annualized vol: 13.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=593.00, end=585.68, trailing_return=-1.23%\nAnnualized volatility: 13.48%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2500, t10y3m_spread=-0.0800, breakeven_10y=2.3800, hy_oas=2.8700, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=6.7600, vix=19.6300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -1.23%\n Annualized volatility: 13.48%\n Macro: fed_funds=4.3300, vix=19.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.012343, "annualized_vol": 0.134848, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251017_0049", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-17", "context_summary": "Regime: bull. SPY trailing return: +4.4%, annualized vol: 10.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=629.08, end=656.90, trailing_return=+4.42%\nAnnualized volatility: 10.86%\nMacro indicators: fed_funds_rate=4.1100, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5800, t10y3m_spread=-0.0300, breakeven_10y=2.2800, hy_oas=3.0400, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.2700, vix=25.3100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.42%\n Annualized volatility: 10.86%\n Macro: fed_funds=4.1100, vix=25.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.044216, "annualized_vol": 0.108648, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251009_0051", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-09", "context_summary": "Regime: bull. SPY trailing return: +8.1%, annualized vol: 8.6%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=618.97, end=669.30, trailing_return=+8.13%\nAnnualized volatility: 8.65%\nMacro indicators: fed_funds_rate=4.1000, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.1200, breakeven_10y=2.3500, hy_oas=2.8400, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3400, vix=16.3000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.13%\n Annualized volatility: 8.65%\n Macro: fed_funds=4.1000, vix=16.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.081311, "annualized_vol": 0.086458, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250602_0052", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-02", "context_summary": "Regime: sideways. SPY trailing return: +3.2%, annualized vol: 21.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=564.52, end=582.71, trailing_return=+3.22%\nAnnualized volatility: 21.17%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5200, t10y3m_spread=0.0500, breakeven_10y=2.3400, hy_oas=3.3200, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.8900, vix=18.5700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.22%\n Annualized volatility: 21.17%\n Macro: fed_funds=4.3300, vix=18.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.032221, "annualized_vol": 0.211728, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250523_0053", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-23", "context_summary": "Regime: sideways. SPY trailing return: -0.0%, annualized vol: 21.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=576.68, end=576.48, trailing_return=-0.04%\nAnnualized volatility: 21.69%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5400, t10y3m_spread=0.1700, breakeven_10y=2.3400, hy_oas=3.3200, ig_oas=0.9200, ted_spread=0.0900, mortgage_30y=6.8600, vix=20.2800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -0.04%\n Annualized volatility: 21.69%\n Macro: fed_funds=4.3300, vix=20.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.000352, "annualized_vol": 0.216937, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251216_0055", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-16", "context_summary": "Regime: sideways. SPY trailing return: +2.1%, annualized vol: 12.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=663.06, end=676.88, trailing_return=+2.08%\nAnnualized volatility: 12.59%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.6700, t10y3m_spread=0.5300, breakeven_10y=2.2500, hy_oas=2.9100, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.2200, vix=16.5000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.08%\n Annualized volatility: 12.59%\n Macro: fed_funds=3.6400, vix=16.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.02083, "annualized_vol": 0.125903, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250109_0056", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-09", "context_summary": "Regime: sideways. SPY trailing return: +1.2%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=574.03, end=581.06, trailing_return=+1.22%\nAnnualized volatility: 12.31%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3900, t10y3m_spread=0.3200, breakeven_10y=2.4000, hy_oas=2.8400, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.9100, vix=17.7000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.22%\n Annualized volatility: 12.31%\n Macro: fed_funds=4.3300, vix=17.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.012243, "annualized_vol": 0.123143, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251223_0057", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-23", "context_summary": "Regime: sideways. SPY trailing return: +3.5%, annualized vol: 12.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=659.92, end=682.96, trailing_return=+3.49%\nAnnualized volatility: 12.89%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.7300, t10y3m_spread=0.5300, breakeven_10y=2.2300, hy_oas=2.8800, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.2100, vix=14.0800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.49%\n Annualized volatility: 12.89%\n Macro: fed_funds=3.6400, vix=14.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.034917, "annualized_vol": 0.128886, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250924_0058", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-24", "context_summary": "Regime: bull. SPY trailing return: +7.6%, annualized vol: 8.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=612.65, end=659.46, trailing_return=+7.64%\nAnnualized volatility: 8.86%\nMacro indicators: fed_funds_rate=4.0900, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5900, t10y3m_spread=0.1200, breakeven_10y=2.3700, hy_oas=2.7100, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.2600, vix=16.6400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.64%\n Annualized volatility: 8.86%\n Macro: fed_funds=4.0900, vix=16.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.076392, "annualized_vol": 0.08857, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250721_0060", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-21", "context_summary": "Regime: bull. SPY trailing return: +17.6%, annualized vol: 11.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=529.35, end=622.30, trailing_return=+17.56%\nAnnualized volatility: 11.77%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5600, t10y3m_spread=0.0400, breakeven_10y=2.4100, hy_oas=2.9300, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.7500, vix=16.4100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +17.56%\n Annualized volatility: 11.77%\n Macro: fed_funds=4.3300, vix=16.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.175592, "annualized_vol": 0.117695, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250319_0062", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-19", "context_summary": "Regime: bear. SPY trailing return: -4.0%, annualized vol: 16.7%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=575.96, end=553.00, trailing_return=-3.99%\nAnnualized volatility: 16.66%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2500, t10y3m_spread=-0.0500, breakeven_10y=2.3000, hy_oas=3.2300, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.6500, vix=21.7000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -3.99%\n Annualized volatility: 16.66%\n Macro: fed_funds=4.3300, vix=21.7\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.039865, "annualized_vol": 0.166592, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250804_0063", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-04", "context_summary": "Regime: bull. SPY trailing return: +11.1%, annualized vol: 10.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=554.79, end=616.49, trailing_return=+11.12%\nAnnualized volatility: 10.93%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5400, t10y3m_spread=-0.1200, breakeven_10y=2.3300, hy_oas=3.1300, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.7200, vix=20.3800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +11.12%\n Annualized volatility: 10.93%\n Macro: fed_funds=4.3300, vix=20.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.111214, "annualized_vol": 0.109284, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250826_0065", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-26", "context_summary": "Regime: bull. SPY trailing return: +9.3%, annualized vol: 9.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=582.71, end=637.07, trailing_return=+9.33%\nAnnualized volatility: 9.71%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5500, t10y3m_spread=-0.0100, breakeven_10y=2.4100, hy_oas=2.8000, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.5800, vix=14.7900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.33%\n Annualized volatility: 9.71%\n Macro: fed_funds=4.3300, vix=14.8\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.093282, "annualized_vol": 0.097078, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251030_0067", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-30", "context_summary": "Regime: bull. SPY trailing return: +8.9%, annualized vol: 10.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=627.46, end=683.50, trailing_return=+8.93%\nAnnualized volatility: 10.32%\nMacro indicators: fed_funds_rate=4.1200, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.4900, t10y3m_spread=0.1500, breakeven_10y=2.3000, hy_oas=2.7600, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.1900, vix=16.9200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.93%\n Annualized volatility: 10.32%\n Macro: fed_funds=4.1200, vix=16.9\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.089313, "annualized_vol": 0.103249, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20250709_0069", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-09", "context_summary": "Regime: sideways. SPY trailing return: +18.6%, annualized vol: 16.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=518.63, end=615.12, trailing_return=+18.60%\nAnnualized volatility: 16.00%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5200, t10y3m_spread=0.0000, breakeven_10y=2.3500, hy_oas=2.9200, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.6700, vix=16.8100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +18.60%\n Annualized volatility: 16.00%\n Macro: fed_funds=4.3300, vix=16.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.186042, "annualized_vol": 0.159968, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250120_0070", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-20", "context_summary": "Regime: sideways. SPY trailing return: +2.8%, annualized vol: 13.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=573.05, end=589.04, trailing_return=+2.79%\nAnnualized volatility: 13.15%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3400, t10y3m_spread=0.2700, breakeven_10y=2.4100, hy_oas=2.6600, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=7.0400, vix=15.9700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.79%\n Annualized volatility: 13.15%\n Macro: fed_funds=4.3300, vix=16.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.027894, "annualized_vol": 0.131545, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251229_0071", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-29", "context_summary": "Regime: sideways. SPY trailing return: +3.0%, annualized vol: 12.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=665.43, end=685.14, trailing_return=+2.96%\nAnnualized volatility: 12.89%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.6800, t10y3m_spread=0.5000, breakeven_10y=2.2300, hy_oas=2.8600, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.1800, vix=13.6000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.96%\n Annualized volatility: 12.89%\n Macro: fed_funds=3.6400, vix=13.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.029617, "annualized_vol": 0.128919, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250812_0072", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-12", "context_summary": "Regime: bull. SPY trailing return: +8.0%, annualized vol: 10.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=583.77, end=630.57, trailing_return=+8.02%\nAnnualized volatility: 10.69%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5100, t10y3m_spread=-0.0700, breakeven_10y=2.4000, hy_oas=2.9400, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.6300, vix=16.2500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.02%\n Annualized volatility: 10.69%\n Macro: fed_funds=4.3300, vix=16.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.080175, "annualized_vol": 0.106877, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250915_0074", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-15", "context_summary": "Regime: bull. SPY trailing return: +10.4%, annualized vol: 9.1%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=590.67, end=651.88, trailing_return=+10.36%\nAnnualized volatility: 9.14%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5000, t10y3m_spread=-0.0200, breakeven_10y=2.3600, hy_oas=2.7900, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3500, vix=14.7600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.36%\n Annualized volatility: 9.14%\n Macro: fed_funds=4.3300, vix=14.8\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.103631, "annualized_vol": 0.091405, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250819_0075", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-19", "context_summary": "Regime: bull. SPY trailing return: +10.7%, annualized vol: 10.1%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=576.48, end=637.89, trailing_return=+10.65%\nAnnualized volatility: 10.08%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5700, t10y3m_spread=0.0100, breakeven_10y=2.3800, hy_oas=2.8800, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.5800, vix=14.9900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.65%\n Annualized volatility: 10.08%\n Macro: fed_funds=4.3300, vix=15.0\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.106522, "annualized_vol": 0.100797, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250130_0077", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-30", "context_summary": "Regime: sideways. SPY trailing return: +6.2%, annualized vol: 13.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=558.63, end=593.20, trailing_return=+6.19%\nAnnualized volatility: 13.67%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3400, t10y3m_spread=0.2400, breakeven_10y=2.4000, hy_oas=2.6800, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.9600, vix=16.5600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.19%\n Annualized volatility: 13.67%\n Macro: fed_funds=4.3300, vix=16.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.061894, "annualized_vol": 0.136701, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250630_0079", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-30", "context_summary": "Regime: sideways. SPY trailing return: +9.2%, annualized vol: 18.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=558.12, end=609.74, trailing_return=+9.25%\nAnnualized volatility: 18.76%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5600, t10y3m_spread=-0.1000, breakeven_10y=2.2900, hy_oas=3.0200, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=6.7700, vix=16.3200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.25%\n Annualized volatility: 18.76%\n Macro: fed_funds=4.3300, vix=16.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.092482, "annualized_vol": 0.18757, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250307_0080", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-07", "context_summary": "Regime: sideways. SPY trailing return: -5.5%, annualized vol: 14.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=597.11, end=564.52, trailing_return=-5.46%\nAnnualized volatility: 14.70%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3300, t10y3m_spread=-0.0500, breakeven_10y=2.3400, hy_oas=2.9900, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=6.6300, vix=24.8700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -5.46%\n Annualized volatility: 14.70%\n Macro: fed_funds=4.3300, vix=24.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.054577, "annualized_vol": 0.146999, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250512_0081", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-12", "context_summary": "Regime: sideways. SPY trailing return: -7.2%, annualized vol: 21.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=601.01, end=557.94, trailing_return=-7.17%\nAnnualized volatility: 21.27%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4900, t10y3m_spread=0.0300, breakeven_10y=2.2900, hy_oas=3.5300, ig_oas=1.0200, ted_spread=0.0900, mortgage_30y=6.7600, vix=21.9000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -7.17%\n Annualized volatility: 21.27%\n Macro: fed_funds=4.3300, vix=21.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.071658, "annualized_vol": 0.212704, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250530_0083", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-30", "context_summary": "Regime: sideways. SPY trailing return: +1.5%, annualized vol: 21.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=574.72, end=583.36, trailing_return=+1.50%\nAnnualized volatility: 21.29%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5100, t10y3m_spread=0.0700, breakeven_10y=2.3200, hy_oas=3.2200, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=6.8900, vix=19.1800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.50%\n Annualized volatility: 21.29%\n Macro: fed_funds=4.3300, vix=19.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.015033, "annualized_vol": 0.212875, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250129_0084", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-29", "context_summary": "Regime: sideways. SPY trailing return: +4.6%, annualized vol: 13.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=569.80, end=595.88, trailing_return=+4.58%\nAnnualized volatility: 13.65%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3600, t10y3m_spread=0.2400, breakeven_10y=2.4200, hy_oas=2.6600, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.9600, vix=16.4100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.58%\n Annualized volatility: 13.65%\n Macro: fed_funds=4.3300, vix=16.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.045766, "annualized_vol": 0.136498, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20250402_0085", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-02", "context_summary": "Regime: bear. SPY trailing return: -4.9%, annualized vol: 16.4%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=583.49, end=554.61, trailing_return=-4.95%\nAnnualized volatility: 16.40%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.3000, t10y3m_spread=-0.1500, breakeven_10y=2.3300, hy_oas=3.5000, ig_oas=0.9800, ted_spread=0.0900, mortgage_30y=6.6500, vix=21.7700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -4.95%\n Annualized volatility: 16.40%\n Macro: fed_funds=4.3300, vix=21.8\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.049485, "annualized_vol": 0.164048, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251118_0086", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-18", "context_summary": "Regime: sideways. SPY trailing return: +3.9%, annualized vol: 11.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=637.07, end=661.90, trailing_return=+3.90%\nAnnualized volatility: 11.52%\nMacro indicators: fed_funds_rate=3.8800, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5300, t10y3m_spread=0.1600, breakeven_10y=2.2800, hy_oas=3.1300, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.2400, vix=22.3800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.90%\n Annualized volatility: 11.52%\n Macro: fed_funds=3.8800, vix=22.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.038983, "annualized_vol": 0.115157, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250609_0088", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-09", "context_summary": "Regime: sideways. SPY trailing return: +9.0%, annualized vol: 20.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=543.54, end=592.35, trailing_return=+8.98%\nAnnualized volatility: 20.11%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4700, t10y3m_spread=0.0800, breakeven_10y=2.3100, hy_oas=3.0900, ig_oas=0.8700, ted_spread=0.0900, mortgage_30y=6.8500, vix=16.7700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.98%\n Annualized volatility: 20.11%\n Macro: fed_funds=4.3300, vix=16.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.089809, "annualized_vol": 0.201091, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250909_0089", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-09", "context_summary": "Regime: bull. SPY trailing return: +7.8%, annualized vol: 9.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=596.91, end=643.37, trailing_return=+7.78%\nAnnualized volatility: 9.77%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5600, t10y3m_spread=-0.0500, breakeven_10y=2.3500, hy_oas=2.8400, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.5000, vix=15.1100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.78%\n Annualized volatility: 9.77%\n Macro: fed_funds=4.3300, vix=15.1\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.077844, "annualized_vol": 0.097748, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251231_0090", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-31", "context_summary": "Regime: sideways. SPY trailing return: +2.6%, annualized vol: 12.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=667.81, end=685.14, trailing_return=+2.60%\nAnnualized volatility: 12.92%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.6900, t10y3m_spread=0.4900, breakeven_10y=2.2400, hy_oas=2.8400, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.1800, vix=14.3300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.60%\n Annualized volatility: 12.92%\n Macro: fed_funds=3.6400, vix=14.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.025953, "annualized_vol": 0.129237, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251024_0092", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-24", "context_summary": "Regime: bull. SPY trailing return: +6.6%, annualized vol: 11.1%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=626.76, end=667.96, trailing_return=+6.57%\nAnnualized volatility: 11.15%\nMacro indicators: fed_funds_rate=4.1100, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5300, t10y3m_spread=0.0600, breakeven_10y=2.3000, hy_oas=2.9600, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.1900, vix=17.3000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.57%\n Annualized volatility: 11.15%\n Macro: fed_funds=4.1100, vix=17.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.065723, "annualized_vol": 0.111493, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20251113_0094", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-13", "context_summary": "Regime: sideways. SPY trailing return: +7.4%, annualized vol: 11.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=632.74, end=679.51, trailing_return=+7.39%\nAnnualized volatility: 11.19%\nMacro indicators: fed_funds_rate=3.8700, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5200, t10y3m_spread=0.1300, breakeven_10y=2.2700, hy_oas=3.0200, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.2200, vix=17.5100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.39%\n Annualized volatility: 11.19%\n Macro: fed_funds=3.8700, vix=17.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.073913, "annualized_vol": 0.11193, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250528_0096", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-28", "context_summary": "Regime: sideways. SPY trailing return: +1.6%, annualized vol: 21.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=575.42, end=584.45, trailing_return=+1.57%\nAnnualized volatility: 21.68%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5100, t10y3m_spread=0.0800, breakeven_10y=2.3200, hy_oas=3.2400, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=6.8600, vix=18.9600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.57%\n Annualized volatility: 21.68%\n Macro: fed_funds=4.3300, vix=19.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.015688, "annualized_vol": 0.216806, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250101_0098", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-01", "context_summary": "Regime: sideways. SPY trailing return: +3.6%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=557.80, end=577.70, trailing_return=+3.57%\nAnnualized volatility: 12.19%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=317.6040, unemployment=4.1000, gdp_growth_qoq=23586.5420, t10y2y_spread=0.3300, t10y3m_spread=0.2100, breakeven_10y=2.3400, hy_oas=2.9200, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.8500, vix=17.3500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.57%\n Annualized volatility: 12.19%\n Macro: fed_funds=4.3300, vix=17.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.035668, "annualized_vol": 0.121896, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251124_0099", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-24", "context_summary": "Regime: sideways. SPY trailing return: +2.5%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=639.62, end=655.30, trailing_return=+2.45%\nAnnualized volatility: 12.20%\nMacro indicators: fed_funds_rate=3.8800, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.1600, breakeven_10y=2.2400, hy_oas=3.1900, ig_oas=0.8600, ted_spread=0.0900, mortgage_30y=6.2600, vix=23.4300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.45%\n Annualized volatility: 12.20%\n Macro: fed_funds=3.8800, vix=23.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.024505, "annualized_vol": 0.121985, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20251015_0100", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-15", "context_summary": "Regime: bull. SPY trailing return: +5.6%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=623.57, end=658.48, trailing_return=+5.60%\nAnnualized volatility: 10.84%\nMacro indicators: fed_funds_rate=4.1000, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.0100, breakeven_10y=2.3000, hy_oas=3.1100, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.3000, vix=20.8100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.60%\n Annualized volatility: 10.84%\n Macro: fed_funds=4.1000, vix=20.8\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.055984, "annualized_vol": 0.108401, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250227_0102", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-27", "context_summary": "Regime: sideways. SPY trailing return: -1.0%, annualized vol: 12.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=591.94, end=586.04, trailing_return=-1.00%\nAnnualized volatility: 12.85%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2000, t10y3m_spread=-0.0600, breakeven_10y=2.3600, hy_oas=2.8100, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.8500, vix=19.1000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -1.00%\n Annualized volatility: 12.85%\n Macro: fed_funds=4.3300, vix=19.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.009973, "annualized_vol": 0.128459, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250613_0104", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-13", "context_summary": "Regime: sideways. SPY trailing return: +6.8%, annualized vol: 19.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=559.02, end=596.91, trailing_return=+6.78%\nAnnualized volatility: 19.32%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4600, t10y3m_spread=-0.1000, breakeven_10y=2.2500, hy_oas=3.1700, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=6.8400, vix=18.0200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.78%\n Annualized volatility: 19.32%\n Macro: fed_funds=4.3300, vix=18.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.067773, "annualized_vol": 0.193236, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250121_0106", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-21", "context_summary": "Regime: sideways. SPY trailing return: +2.8%, annualized vol: 13.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=573.05, end=589.04, trailing_return=+2.79%\nAnnualized volatility: 13.15%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3400, t10y3m_spread=0.2700, breakeven_10y=2.4100, hy_oas=2.6600, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=7.0400, vix=15.9700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.79%\n Annualized volatility: 13.15%\n Macro: fed_funds=4.3300, vix=16.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.027894, "annualized_vol": 0.131545, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250926_0108", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-26", "context_summary": "Regime: bull. SPY trailing return: +6.4%, annualized vol: 8.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=615.23, end=654.32, trailing_return=+6.35%\nAnnualized volatility: 8.95%\nMacro indicators: fed_funds_rate=4.0900, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5400, t10y3m_spread=0.1400, breakeven_10y=2.3800, hy_oas=2.7600, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3000, vix=16.7400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.35%\n Annualized volatility: 8.95%\n Macro: fed_funds=4.0900, vix=16.7\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.063542, "annualized_vol": 0.089486, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251204_0109", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-04", "context_summary": "Regime: sideways. SPY trailing return: +5.1%, annualized vol: 12.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=646.72, end=680.02, trailing_return=+5.15%\nAnnualized volatility: 12.48%\nMacro indicators: fed_funds_rate=3.8900, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5700, t10y3m_spread=0.3400, breakeven_10y=2.2400, hy_oas=2.8900, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.2300, vix=16.0800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.15%\n Annualized volatility: 12.48%\n Macro: fed_funds=3.8900, vix=16.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.05148, "annualized_vol": 0.124817, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250417_0110", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-17", "context_summary": "Regime: bear. SPY trailing return: -13.1%, annualized vol: 19.4%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=597.77, end=519.70, trailing_return=-13.06%\nAnnualized volatility: 19.42%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5200, t10y3m_spread=-0.0400, breakeven_10y=2.1700, hy_oas=4.1600, ig_oas=1.1300, ted_spread=0.0900, mortgage_30y=6.6200, vix=32.6400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -13.06%\n Annualized volatility: 19.42%\n Macro: fed_funds=4.3300, vix=32.6\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.130596, "annualized_vol": 0.194151, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251104_0111", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-04", "context_summary": "Regime: bull. SPY trailing return: +7.8%, annualized vol: 10.5%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=630.57, end=679.47, trailing_return=+7.75%\nAnnualized volatility: 10.48%\nMacro indicators: fed_funds_rate=3.8700, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5300, t10y3m_spread=0.1500, breakeven_10y=2.3100, hy_oas=3.0400, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.1700, vix=17.1700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.75%\n Annualized volatility: 10.48%\n Macro: fed_funds=3.8700, vix=17.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.077548, "annualized_vol": 0.104766, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250801_0112", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-01", "context_summary": "Regime: bull. SPY trailing return: +13.4%, annualized vol: 10.5%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=552.47, end=626.76, trailing_return=+13.45%\nAnnualized volatility: 10.47%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.4300, t10y3m_spread=-0.0400, breakeven_10y=2.3900, hy_oas=2.8600, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.7200, vix=16.7200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +13.45%\n Annualized volatility: 10.47%\n Macro: fed_funds=4.3300, vix=16.7\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.134482, "annualized_vol": 0.104687, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251014_0114", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-14", "context_summary": "Regime: bull. SPY trailing return: +5.7%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=623.48, end=659.29, trailing_return=+5.74%\nAnnualized volatility: 10.83%\nMacro indicators: fed_funds_rate=4.1000, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5300, t10y3m_spread=0.0300, breakeven_10y=2.3000, hy_oas=3.1800, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.3000, vix=19.0300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.74%\n Annualized volatility: 10.83%\n Macro: fed_funds=4.1000, vix=19.0\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.057427, "annualized_vol": 0.108327, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250617_0116", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-17", "context_summary": "Regime: sideways. SPY trailing return: +6.9%, annualized vol: 19.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=557.59, end=595.85, trailing_return=+6.86%\nAnnualized volatility: 19.44%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4900, t10y3m_spread=0.0300, breakeven_10y=2.3000, hy_oas=3.1000, ig_oas=0.8700, ted_spread=0.0900, mortgage_30y=6.8400, vix=19.1100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.86%\n Annualized volatility: 19.44%\n Macro: fed_funds=4.3300, vix=19.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.068619, "annualized_vol": 0.194408, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250522_0118", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-22", "context_summary": "Regime: sideways. SPY trailing return: -1.7%, annualized vol: 21.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=586.04, end=576.25, trailing_return=-1.67%\nAnnualized volatility: 21.69%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5800, t10y3m_spread=0.2200, breakeven_10y=2.3500, hy_oas=3.2500, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=6.8100, vix=20.8700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -1.67%\n Annualized volatility: 21.69%\n Macro: fed_funds=4.3300, vix=20.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.016696, "annualized_vol": 0.216939, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250314_0119", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-14", "context_summary": "Regime: bear. SPY trailing return: -8.4%, annualized vol: 15.9%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=593.57, end=543.54, trailing_return=-8.43%\nAnnualized volatility: 15.87%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3300, t10y3m_spread=-0.0700, breakeven_10y=2.2900, hy_oas=3.4000, ig_oas=0.9700, ted_spread=0.0900, mortgage_30y=6.6500, vix=24.6600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -8.43%\n Annualized volatility: 15.87%\n Macro: fed_funds=4.3300, vix=24.7\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.084299, "annualized_vol": 0.158658, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250218_0121", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-18", "context_summary": "Regime: sideways. SPY trailing return: +3.6%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=579.91, end=600.98, trailing_return=+3.63%\nAnnualized volatility: 12.32%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2100, t10y3m_spread=0.1300, breakeven_10y=2.4300, hy_oas=2.6600, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.8700, vix=14.7700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.63%\n Annualized volatility: 12.32%\n Macro: fed_funds=4.3300, vix=14.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.036341, "annualized_vol": 0.123179, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250516_0122", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-16", "context_summary": "Regime: sideways. SPY trailing return: -3.0%, annualized vol: 21.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=601.65, end=583.77, trailing_return=-2.97%\nAnnualized volatility: 21.69%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4900, t10y3m_spread=0.0700, breakeven_10y=2.3400, hy_oas=3.2000, ig_oas=0.9400, ted_spread=0.0900, mortgage_30y=6.8100, vix=17.8300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -2.97%\n Annualized volatility: 21.69%\n Macro: fed_funds=4.3300, vix=17.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.029725, "annualized_vol": 0.216851, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250825_0123", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-25", "context_summary": "Regime: bull. SPY trailing return: +9.7%, annualized vol: 9.6%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=583.36, end=639.88, trailing_return=+9.69%\nAnnualized volatility: 9.64%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5800, t10y3m_spread=-0.0100, breakeven_10y=2.4100, hy_oas=2.8800, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.5800, vix=14.2200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.69%\n Annualized volatility: 9.64%\n Macro: fed_funds=4.3300, vix=14.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.096886, "annualized_vol": 0.096424, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250328_0124", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-28", "context_summary": "Regime: sideways. SPY trailing return: -3.3%, annualized vol: 16.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=579.81, end=560.65, trailing_return=-3.30%\nAnnualized volatility: 15.98%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.4100, t10y3m_spread=0.0500, breakeven_10y=2.3900, hy_oas=3.2700, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=6.6500, vix=18.6900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -3.30%\n Annualized volatility: 15.98%\n Macro: fed_funds=4.3300, vix=18.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.033039, "annualized_vol": 0.159762, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250710_0125", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-10", "context_summary": "Regime: sideways. SPY trailing return: +17.2%, annualized vol: 14.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=527.89, end=618.81, trailing_return=+17.22%\nAnnualized volatility: 14.78%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.4800, t10y3m_spread=-0.0800, breakeven_10y=2.3300, hy_oas=2.9400, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.6700, vix=15.9400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +17.22%\n Annualized volatility: 14.78%\n Macro: fed_funds=4.3300, vix=15.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.172238, "annualized_vol": 0.147832, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251219_0127", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-19", "context_summary": "Regime: sideways. SPY trailing return: +2.8%, annualized vol: 12.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=654.32, end=672.64, trailing_return=+2.80%\nAnnualized volatility: 12.80%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.6600, t10y3m_spread=0.5000, breakeven_10y=2.2400, hy_oas=2.9500, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.2100, vix=16.8700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.80%\n Annualized volatility: 12.80%\n Macro: fed_funds=3.6400, vix=16.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.027992, "annualized_vol": 0.128025, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250506_0128", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-06", "context_summary": "Regime: sideways. SPY trailing return: -5.9%, annualized vol: 21.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=592.18, end=557.12, trailing_return=-5.92%\nAnnualized volatility: 21.26%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5300, t10y3m_spread=0.0300, breakeven_10y=2.2800, hy_oas=3.6000, ig_oas=1.0500, ted_spread=0.0900, mortgage_30y=6.7600, vix=23.6400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -5.92%\n Annualized volatility: 21.26%\n Macro: fed_funds=4.3300, vix=23.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.059199, "annualized_vol": 0.212574, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250107_0130", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-07", "context_summary": "Regime: sideways. SPY trailing return: +3.7%, annualized vol: 12.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=565.99, end=586.85, trailing_return=+3.69%\nAnnualized volatility: 12.13%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3400, t10y3m_spread=0.2700, breakeven_10y=2.3400, hy_oas=2.7600, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.9100, vix=16.0400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.69%\n Annualized volatility: 12.13%\n Macro: fed_funds=4.3300, vix=16.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.036856, "annualized_vol": 0.121306, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250918_0132", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-18", "context_summary": "Regime: bull. SPY trailing return: +8.6%, annualized vol: 9.0%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=601.68, end=653.64, trailing_return=+8.64%\nAnnualized volatility: 9.01%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5400, t10y3m_spread=0.0400, breakeven_10y=2.3800, hy_oas=2.7900, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3500, vix=15.7200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.64%\n Annualized volatility: 9.01%\n Macro: fed_funds=4.3300, vix=15.7\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.086358, "annualized_vol": 0.090095, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250306_0133", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-06", "context_summary": "Regime: sideways. SPY trailing return: -3.6%, annualized vol: 14.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=595.98, end=574.72, trailing_return=-3.57%\nAnnualized volatility: 14.27%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2900, t10y3m_spread=-0.0700, breakeven_10y=2.3400, hy_oas=2.8800, ig_oas=0.8700, ted_spread=0.0900, mortgage_30y=6.7600, vix=21.9300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -3.57%\n Annualized volatility: 14.27%\n Macro: fed_funds=4.3300, vix=21.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.035667, "annualized_vol": 0.142654, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250401_0134", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-01", "context_summary": "Regime: bear. SPY trailing return: -4.0%, annualized vol: 16.4%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=576.28, end=553.05, trailing_return=-4.03%\nAnnualized volatility: 16.39%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3400, t10y3m_spread=-0.0900, breakeven_10y=2.3800, hy_oas=3.5500, ig_oas=0.9700, ted_spread=0.0900, mortgage_30y=6.6500, vix=22.2800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -4.03%\n Annualized volatility: 16.39%\n Macro: fed_funds=4.3300, vix=22.3\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.040311, "annualized_vol": 0.163929, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250407_0136", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-07", "context_summary": "Regime: bear. SPY trailing return: -14.0%, annualized vol: 17.8%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=581.06, end=499.55, trailing_return=-14.03%\nAnnualized volatility: 17.78%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.3300, t10y3m_spread=-0.2700, breakeven_10y=2.1800, hy_oas=4.4500, ig_oas=1.1400, ted_spread=0.0900, mortgage_30y=6.6400, vix=43.3500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -14.03%\n Annualized volatility: 17.78%\n Macro: fed_funds=4.3300, vix=43.3\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.140274, "annualized_vol": 0.177829, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250514_0137", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-14", "context_summary": "Regime: sideways. SPY trailing return: -3.7%, annualized vol: 21.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=602.75, end=580.19, trailing_return=-3.74%\nAnnualized volatility: 21.67%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4700, t10y3m_spread=0.0800, breakeven_10y=2.3200, hy_oas=3.0900, ig_oas=0.9400, ted_spread=0.0900, mortgage_30y=6.7600, vix=18.2200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -3.74%\n Annualized volatility: 21.67%\n Macro: fed_funds=4.3300, vix=18.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.037424, "annualized_vol": 0.216724, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250527_0138", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-27", "context_summary": "Regime: sideways. SPY trailing return: -2.2%, annualized vol: 21.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=585.68, end=572.55, trailing_return=-2.24%\nAnnualized volatility: 21.49%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5100, t10y3m_spread=0.1500, breakeven_10y=2.3300, hy_oas=3.4000, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.8600, vix=22.2900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -2.24%\n Annualized volatility: 21.49%\n Macro: fed_funds=4.3300, vix=22.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.022431, "annualized_vol": 0.214944, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251112_0139", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-12", "context_summary": "Regime: bull. SPY trailing return: +7.0%, annualized vol: 11.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=634.43, end=679.13, trailing_return=+7.05%\nAnnualized volatility: 11.27%\nMacro indicators: fed_funds_rate=3.8700, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.1800, breakeven_10y=2.2900, hy_oas=3.0200, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.2200, vix=17.2800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.05%\n Annualized volatility: 11.27%\n Macro: fed_funds=3.8700, vix=17.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.070464, "annualized_vol": 0.112736, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251028_0140", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-28", "context_summary": "Regime: bull. SPY trailing return: +8.9%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=625.86, end=681.36, trailing_return=+8.87%\nAnnualized volatility: 10.78%\nMacro indicators: fed_funds_rate=4.1200, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5300, t10y3m_spread=0.1200, breakeven_10y=2.2800, hy_oas=2.8000, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.1900, vix=15.7900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.87%\n Annualized volatility: 10.78%\n Macro: fed_funds=4.1200, vix=15.8\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.088676, "annualized_vol": 0.107783, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20250414_0142", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-14", "context_summary": "Regime: bear. SPY trailing return: -9.5%, annualized vol: 19.1%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=583.18, end=527.89, trailing_return=-9.48%\nAnnualized volatility: 19.10%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5200, t10y3m_spread=0.1400, breakeven_10y=2.2000, hy_oas=4.2600, ig_oas=1.1800, ted_spread=0.0900, mortgage_30y=6.6200, vix=37.5600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -9.48%\n Annualized volatility: 19.10%\n Macro: fed_funds=4.3300, vix=37.6\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.094811, "annualized_vol": 0.190992, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250219_0144", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-19", "context_summary": "Regime: sideways. SPY trailing return: +3.9%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=580.10, end=602.75, trailing_return=+3.90%\nAnnualized volatility: 12.31%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2600, t10y3m_spread=0.2100, breakeven_10y=2.4500, hy_oas=2.6600, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.8700, vix=15.3500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.90%\n Annualized volatility: 12.31%\n Macro: fed_funds=4.3300, vix=15.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.039031, "annualized_vol": 0.123114, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250115_0145", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-15", "context_summary": "Regime: sideways. SPY trailing return: +0.3%, annualized vol: 12.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=572.10, end=573.87, trailing_return=+0.31%\nAnnualized volatility: 12.49%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.4100, t10y3m_spread=0.4200, breakeven_10y=2.4400, hy_oas=2.8000, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.9300, vix=18.7100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +0.31%\n Annualized volatility: 12.49%\n Macro: fed_funds=4.3300, vix=18.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.00309, "annualized_vol": 0.124886, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250827_0146", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-27", "context_summary": "Regime: bull. SPY trailing return: +9.2%, annualized vol: 9.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=585.99, end=639.73, trailing_return=+9.17%\nAnnualized volatility: 9.71%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.6500, t10y3m_spread=-0.0200, breakeven_10y=2.4200, hy_oas=2.7800, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.5800, vix=14.6200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.17%\n Annualized volatility: 9.71%\n Macro: fed_funds=4.3300, vix=14.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.09171, "annualized_vol": 0.097082, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250304_0148", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-04", "context_summary": "Regime: sideways. SPY trailing return: -3.0%, annualized vol: 13.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=593.28, end=575.42, trailing_return=-3.01%\nAnnualized volatility: 13.95%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2000, t10y3m_spread=-0.1900, breakeven_10y=2.3600, hy_oas=2.9400, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=6.7600, vix=22.7800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -3.01%\n Annualized volatility: 13.95%\n Macro: fed_funds=4.3300, vix=22.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.030096, "annualized_vol": 0.139485, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251126_0149", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-26", "context_summary": "Regime: sideways. SPY trailing return: +5.1%, annualized vol: 12.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=638.33, end=671.20, trailing_return=+5.15%\nAnnualized volatility: 12.48%\nMacro indicators: fed_funds_rate=3.8800, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5800, t10y3m_spread=0.1100, breakeven_10y=2.2200, hy_oas=3.1000, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.2600, vix=18.5600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.15%\n Annualized volatility: 12.48%\n Macro: fed_funds=3.8800, vix=18.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.051498, "annualized_vol": 0.124824, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250818_0150", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-18", "context_summary": "Regime: bull. SPY trailing return: +10.7%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=576.25, end=638.03, trailing_return=+10.72%\nAnnualized volatility: 10.78%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5800, t10y3m_spread=0.0300, breakeven_10y=2.3800, hy_oas=2.8800, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.5800, vix=15.0900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.72%\n Annualized volatility: 10.78%\n Macro: fed_funds=4.3300, vix=15.1\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.107199, "annualized_vol": 0.107778, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250320_0152", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-20", "context_summary": "Regime: sideways. SPY trailing return: -2.9%, annualized vol: 15.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=575.78, end=559.02, trailing_return=-2.91%\nAnnualized volatility: 15.91%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2600, t10y3m_spread=-0.0800, breakeven_10y=2.3100, hy_oas=3.1900, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=6.6500, vix=19.9000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -2.91%\n Annualized volatility: 15.91%\n Macro: fed_funds=4.3300, vix=19.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.02911, "annualized_vol": 0.159104, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250616_0153", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-16", "context_summary": "Regime: sideways. SPY trailing return: +5.9%, annualized vol: 19.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=557.40, end=590.23, trailing_return=+5.89%\nAnnualized volatility: 19.37%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4500, t10y3m_spread=-0.0400, breakeven_10y=2.2800, hy_oas=3.1800, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=6.8400, vix=20.8200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.89%\n Annualized volatility: 19.37%\n Macro: fed_funds=4.3300, vix=20.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.058897, "annualized_vol": 0.193688, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250610_0155", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-10", "context_summary": "Regime: sideways. SPY trailing return: +6.9%, annualized vol: 19.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=554.76, end=592.88, trailing_return=+6.87%\nAnnualized volatility: 19.89%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4800, t10y3m_spread=0.0500, breakeven_10y=2.3100, hy_oas=3.1200, ig_oas=0.8700, ted_spread=0.0900, mortgage_30y=6.8500, vix=17.1600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.87%\n Annualized volatility: 19.89%\n Macro: fed_funds=4.3300, vix=17.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.068716, "annualized_vol": 0.198883, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250704_0156", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-04", "context_summary": "Regime: sideways. SPY trailing return: +26.3%, annualized vol: 16.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=490.85, end=620.08, trailing_return=+26.33%\nAnnualized volatility: 16.74%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.4700, t10y3m_spread=-0.0700, breakeven_10y=2.3300, hy_oas=2.8000, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.6700, vix=16.3800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +26.33%\n Annualized volatility: 16.74%\n Macro: fed_funds=4.3300, vix=16.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.263271, "annualized_vol": 0.16739, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251225_0157", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-25", "context_summary": "Regime: sideways. SPY trailing return: +3.1%, annualized vol: 12.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=664.67, end=685.14, trailing_return=+3.08%\nAnnualized volatility: 12.90%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.6800, t10y3m_spread=0.4600, breakeven_10y=2.2400, hy_oas=2.8400, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.1800, vix=13.4700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.08%\n Annualized volatility: 12.90%\n Macro: fed_funds=3.6400, vix=13.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.030803, "annualized_vol": 0.129039, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250701_0159", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-01", "context_summary": "Regime: sideways. SPY trailing return: +15.5%, annualized vol: 18.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=530.62, end=612.65, trailing_return=+15.46%\nAnnualized volatility: 18.74%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5200, t10y3m_spread=-0.1700, breakeven_10y=2.2900, hy_oas=2.9600, ig_oas=0.8600, ted_spread=0.0900, mortgage_30y=6.7700, vix=16.7300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +15.46%\n Annualized volatility: 18.74%\n Macro: fed_funds=4.3300, vix=16.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.154605, "annualized_vol": 0.187417, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250214_0161", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-14", "context_summary": "Regime: sideways. SPY trailing return: +4.4%, annualized vol: 12.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=575.44, end=601.01, trailing_return=+4.44%\nAnnualized volatility: 12.55%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2100, t10y3m_spread=0.1800, breakeven_10y=2.4400, hy_oas=2.6600, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.8700, vix=15.1000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.44%\n Annualized volatility: 12.55%\n Macro: fed_funds=4.3300, vix=15.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.044442, "annualized_vol": 0.125485, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250910_0163", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-10", "context_summary": "Regime: bull. SPY trailing return: +9.3%, annualized vol: 9.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=590.23, end=644.86, trailing_return=+9.26%\nAnnualized volatility: 9.76%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5400, t10y3m_spread=-0.0200, breakeven_10y=2.3600, hy_oas=2.8700, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.5000, vix=15.0400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.26%\n Annualized volatility: 9.76%\n Macro: fed_funds=4.3300, vix=15.0\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.09255, "annualized_vol": 0.097615, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251003_0164", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-03", "context_summary": "Regime: bull. SPY trailing return: +7.2%, annualized vol: 8.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=620.56, end=665.43, trailing_return=+7.23%\nAnnualized volatility: 8.65%\nMacro indicators: fed_funds_rate=4.0900, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.0800, breakeven_10y=2.3400, hy_oas=2.8100, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3400, vix=16.6300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.23%\n Annualized volatility: 8.65%\n Macro: fed_funds=4.0900, vix=16.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.072314, "annualized_vol": 0.086536, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250908_0166", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-08", "context_summary": "Regime: bull. SPY trailing return: +7.9%, annualized vol: 9.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=594.54, end=641.80, trailing_return=+7.95%\nAnnualized volatility: 9.81%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5900, t10y3m_spread=0.0300, breakeven_10y=2.3700, hy_oas=2.8300, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.5000, vix=15.1800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.95%\n Annualized volatility: 9.81%\n Macro: fed_funds=4.3300, vix=15.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.079475, "annualized_vol": 0.098089, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251201_0167", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-01", "context_summary": "Regime: sideways. SPY trailing return: +5.9%, annualized vol: 12.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=641.80, end=679.52, trailing_return=+5.88%\nAnnualized volatility: 12.45%\nMacro indicators: fed_funds_rate=3.8900, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.1400, breakeven_10y=2.2300, hy_oas=2.9200, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.2300, vix=16.3500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.88%\n Annualized volatility: 12.45%\n Macro: fed_funds=3.8900, vix=16.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.05878, "annualized_vol": 0.124499, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250606_0169", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-06", "context_summary": "Regime: sideways. SPY trailing return: +6.4%, annualized vol: 20.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=550.88, end=586.33, trailing_return=+6.44%\nAnnualized volatility: 20.04%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4800, t10y3m_spread=-0.0400, breakeven_10y=2.2900, hy_oas=3.1800, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=6.8500, vix=18.4800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.44%\n Annualized volatility: 20.04%\n Macro: fed_funds=4.3300, vix=18.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.064351, "annualized_vol": 0.200363, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250717_0171", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-17", "context_summary": "Regime: bull. SPY trailing return: +21.8%, annualized vol: 13.5%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=508.06, end=618.97, trailing_return=+21.83%\nAnnualized volatility: 13.50%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5800, t10y3m_spread=0.0500, breakeven_10y=2.4100, hy_oas=3.0000, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.7200, vix=17.1600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +21.83%\n Annualized volatility: 13.50%\n Macro: fed_funds=4.3300, vix=17.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.21831, "annualized_vol": 0.134985, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250626_0172", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-26", "context_summary": "Regime: sideways. SPY trailing return: +8.9%, annualized vol: 18.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=553.05, end=602.01, trailing_return=+8.85%\nAnnualized volatility: 18.73%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5500, t10y3m_spread=-0.0900, breakeven_10y=2.2800, hy_oas=3.0400, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=6.8100, vix=16.7600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.85%\n Annualized volatility: 18.73%\n Macro: fed_funds=4.3300, vix=16.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.088533, "annualized_vol": 0.187286, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250627_0173", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-27", "context_summary": "Regime: sideways. SPY trailing return: +9.4%, annualized vol: 18.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=554.61, end=606.72, trailing_return=+9.40%\nAnnualized volatility: 18.74%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5600, t10y3m_spread=-0.1300, breakeven_10y=2.2800, hy_oas=3.0400, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=6.7700, vix=16.5900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.40%\n Annualized volatility: 18.74%\n Macro: fed_funds=4.3300, vix=16.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.09396, "annualized_vol": 0.187438, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250313_0175", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-13", "context_summary": "Regime: bear. SPY trailing return: -7.2%, annualized vol: 15.7%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=593.69, end=550.88, trailing_return=-7.21%\nAnnualized volatility: 15.69%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3100, t10y3m_spread=-0.0300, breakeven_10y=2.3300, hy_oas=3.2000, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.6300, vix=24.2300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -7.21%\n Annualized volatility: 15.69%\n Macro: fed_funds=4.3300, vix=24.2\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.072111, "annualized_vol": 0.156884, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250916_0176", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-16", "context_summary": "Regime: bull. SPY trailing return: +11.2%, annualized vol: 9.2%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=589.28, end=655.35, trailing_return=+11.21%\nAnnualized volatility: 9.16%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5100, t10y3m_spread=-0.0100, breakeven_10y=2.3700, hy_oas=2.7500, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3500, vix=15.6900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +11.21%\n Annualized volatility: 9.16%\n Macro: fed_funds=4.3300, vix=15.7\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.112119, "annualized_vol": 0.091633, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250625_0178", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-25", "context_summary": "Regime: sideways. SPY trailing return: +9.5%, annualized vol: 19.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=549.36, end=601.68, trailing_return=+9.52%\nAnnualized volatility: 19.24%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5500, t10y3m_spread=-0.0800, breakeven_10y=2.2900, hy_oas=3.0600, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=6.8100, vix=17.4800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.52%\n Annualized volatility: 19.24%\n Macro: fed_funds=4.3300, vix=17.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.095227, "annualized_vol": 0.1924, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250821_0179", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-21", "context_summary": "Regime: bull. SPY trailing return: +8.3%, annualized vol: 10.1%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=584.45, end=632.74, trailing_return=+8.26%\nAnnualized volatility: 10.07%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5500, t10y3m_spread=-0.0100, breakeven_10y=2.3500, hy_oas=2.9400, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.5800, vix=15.6900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.26%\n Annualized volatility: 10.07%\n Macro: fed_funds=4.3300, vix=15.7\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.082629, "annualized_vol": 0.100694, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250707_0180", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-07", "context_summary": "Regime: sideways. SPY trailing return: +26.3%, annualized vol: 16.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=490.85, end=620.08, trailing_return=+26.33%\nAnnualized volatility: 16.74%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.4700, t10y3m_spread=-0.0700, breakeven_10y=2.3300, hy_oas=2.8000, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.6700, vix=16.3800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +26.33%\n Annualized volatility: 16.74%\n Macro: fed_funds=4.3300, vix=16.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.263271, "annualized_vol": 0.16739, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250624_0181", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-24", "context_summary": "Regime: sideways. SPY trailing return: +6.1%, annualized vol: 19.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=560.65, end=595.10, trailing_return=+6.14%\nAnnualized volatility: 19.13%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5000, t10y3m_spread=-0.0400, breakeven_10y=2.3000, hy_oas=3.1200, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=6.8100, vix=19.8300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.14%\n Annualized volatility: 19.13%\n Macro: fed_funds=4.3300, vix=19.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.061445, "annualized_vol": 0.191346, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251016_0182", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-16", "context_summary": "Regime: bull. SPY trailing return: +5.2%, annualized vol: 10.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=628.88, end=661.40, trailing_return=+5.17%\nAnnualized volatility: 10.86%\nMacro indicators: fed_funds_rate=4.1000, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.0200, breakeven_10y=2.2900, hy_oas=2.9500, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.3000, vix=20.6400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.17%\n Annualized volatility: 10.86%\n Macro: fed_funds=4.1000, vix=20.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.051724, "annualized_vol": 0.108627, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251211_0183", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-11", "context_summary": "Regime: sideways. SPY trailing return: +4.6%, annualized vol: 12.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=653.64, end=683.68, trailing_return=+4.60%\nAnnualized volatility: 12.42%\nMacro indicators: fed_funds_rate=3.8900, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5900, t10y3m_spread=0.4400, breakeven_10y=2.2500, hy_oas=2.9100, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.1900, vix=15.7700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.60%\n Annualized volatility: 12.42%\n Macro: fed_funds=3.8900, vix=15.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.045961, "annualized_vol": 0.12423, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250724_0184", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-24", "context_summary": "Regime: bull. SPY trailing return: +15.5%, annualized vol: 10.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=544.61, end=628.88, trailing_return=+15.47%\nAnnualized volatility: 10.86%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5200, t10y3m_spread=-0.0100, breakeven_10y=2.3700, hy_oas=2.8300, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.7500, vix=15.3700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +15.47%\n Annualized volatility: 10.86%\n Macro: fed_funds=4.3300, vix=15.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.154733, "annualized_vol": 0.10857, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250404_0185", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-04", "context_summary": "Regime: bear. SPY trailing return: -8.5%, annualized vol: 17.1%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=580.21, end=530.62, trailing_return=-8.55%\nAnnualized volatility: 17.08%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.3500, t10y3m_spread=-0.2500, breakeven_10y=2.2800, hy_oas=4.0100, ig_oas=1.0600, ted_spread=0.0900, mortgage_30y=6.6400, vix=30.0200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -8.55%\n Annualized volatility: 17.08%\n Macro: fed_funds=4.3300, vix=30.0\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.085479, "annualized_vol": 0.170775, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251001_0187", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-01", "context_summary": "Regime: bull. SPY trailing return: +7.7%, annualized vol: 8.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=615.12, end=662.41, trailing_return=+7.69%\nAnnualized volatility: 8.71%\nMacro indicators: fed_funds_rate=4.0900, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5600, t10y3m_spread=0.1400, breakeven_10y=2.3600, hy_oas=2.8000, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3000, vix=16.2800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.69%\n Annualized volatility: 8.71%\n Macro: fed_funds=4.0900, vix=16.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.076872, "annualized_vol": 0.087053, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251128_0188", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-28", "context_summary": "Regime: sideways. SPY trailing return: +5.0%, annualized vol: 12.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=643.66, end=675.83, trailing_return=+5.00%\nAnnualized volatility: 12.51%\nMacro indicators: fed_funds_rate=3.8800, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.0800, breakeven_10y=2.2300, hy_oas=3.0000, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.2300, vix=17.1900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.00%\n Annualized volatility: 12.51%\n Macro: fed_funds=3.8800, vix=17.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.049982, "annualized_vol": 0.125086, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250807_0189", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-07", "context_summary": "Regime: bull. SPY trailing return: +8.9%, annualized vol: 11.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=576.38, end=627.46, trailing_return=+8.86%\nAnnualized volatility: 11.35%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5300, t10y3m_spread=-0.1000, breakeven_10y=2.3400, hy_oas=2.9800, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.7200, vix=16.7700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.86%\n Annualized volatility: 11.35%\n Macro: fed_funds=4.3300, vix=16.8\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.088613, "annualized_vol": 0.113461, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250311_0190", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-11", "context_summary": "Regime: sideways. SPY trailing return: -6.7%, annualized vol: 15.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=592.19, end=552.56, trailing_return=-6.69%\nAnnualized volatility: 15.67%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3300, t10y3m_spread=-0.1100, breakeven_10y=2.3100, hy_oas=3.1600, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=6.6300, vix=27.8600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -6.69%\n Annualized volatility: 15.67%\n Macro: fed_funds=4.3300, vix=27.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.06691, "annualized_vol": 0.156748, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250708_0191", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-08", "context_summary": "Regime: sideways. SPY trailing return: +13.5%, annualized vol: 16.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=542.40, end=615.46, trailing_return=+13.47%\nAnnualized volatility: 16.44%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5000, t10y3m_spread=-0.0200, breakeven_10y=2.3500, hy_oas=2.8600, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.6700, vix=17.7900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +13.47%\n Annualized volatility: 16.44%\n Macro: fed_funds=4.3300, vix=17.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.134692, "annualized_vol": 0.164389, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250729_0192", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-29", "context_summary": "Regime: bull. SPY trailing return: +14.4%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=552.14, end=631.58, trailing_return=+14.39%\nAnnualized volatility: 10.84%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5100, t10y3m_spread=0.0200, breakeven_10y=2.4400, hy_oas=2.8200, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.7400, vix=15.0300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +14.39%\n Annualized volatility: 10.84%\n Macro: fed_funds=4.3300, vix=15.0\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.143881, "annualized_vol": 0.108379, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250409_0193", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-09", "context_summary": "Regime: bear. SPY trailing return: -14.3%, annualized vol: 17.8%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=573.08, end=490.85, trailing_return=-14.35%\nAnnualized volatility: 17.79%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5500, t10y3m_spread=-0.0500, breakeven_10y=2.2200, hy_oas=4.5700, ig_oas=1.1800, ted_spread=0.0900, mortgage_30y=6.6400, vix=43.3500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -14.35%\n Annualized volatility: 17.79%\n Macro: fed_funds=4.3300, vix=43.3\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.143478, "annualized_vol": 0.177853, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251007_0195", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-07", "context_summary": "Regime: bull. SPY trailing return: +7.8%, annualized vol: 8.6%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=619.55, end=667.81, trailing_return=+7.79%\nAnnualized volatility: 8.61%\nMacro indicators: fed_funds_rate=4.0900, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5800, t10y3m_spread=0.1600, breakeven_10y=2.3400, hy_oas=2.7600, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3400, vix=16.3700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.79%\n Annualized volatility: 8.61%\n Macro: fed_funds=4.0900, vix=16.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.077883, "annualized_vol": 0.086086, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251127_0196", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-27", "context_summary": "Regime: sideways. SPY trailing return: +5.0%, annualized vol: 12.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=643.66, end=675.83, trailing_return=+5.00%\nAnnualized volatility: 12.51%\nMacro indicators: fed_funds_rate=3.8800, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.0800, breakeven_10y=2.2300, hy_oas=3.0000, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.2300, vix=17.1900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.00%\n Annualized volatility: 12.51%\n Macro: fed_funds=3.8800, vix=17.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.049982, "annualized_vol": 0.125086, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250128_0198", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-28", "context_summary": "Regime: sideways. SPY trailing return: +3.4%, annualized vol: 13.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=571.53, end=590.80, trailing_return=+3.37%\nAnnualized volatility: 13.55%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3600, t10y3m_spread=0.2100, breakeven_10y=2.4000, hy_oas=2.6600, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.9600, vix=17.9000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.37%\n Annualized volatility: 13.55%\n Macro: fed_funds=4.3300, vix=17.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.03372, "annualized_vol": 0.135526, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20251107_0199", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-07", "context_summary": "Regime: sideways. SPY trailing return: +4.2%, annualized vol: 10.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=639.53, end=666.51, trailing_return=+4.22%\nAnnualized volatility: 10.88%\nMacro indicators: fed_funds_rate=3.8700, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5400, t10y3m_spread=0.1800, breakeven_10y=2.2800, hy_oas=3.1300, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.2200, vix=19.5000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.22%\n Annualized volatility: 10.88%\n Macro: fed_funds=3.8700, vix=19.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.042202, "annualized_vol": 0.108811, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250123_0200", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-23", "context_summary": "Regime: sideways. SPY trailing return: +5.0%, annualized vol: 13.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=569.04, end=597.77, trailing_return=+5.05%\nAnnualized volatility: 13.15%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3100, t10y3m_spread=0.2400, breakeven_10y=2.4000, hy_oas=2.6600, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=7.0400, vix=15.1000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.05%\n Annualized volatility: 13.15%\n Macro: fed_funds=4.3300, vix=15.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.050482, "annualized_vol": 0.131524, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20250416_0201", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-16", "context_summary": "Regime: bear. SPY trailing return: -10.6%, annualized vol: 19.1%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=594.43, end=531.52, trailing_return=-10.58%\nAnnualized volatility: 19.09%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5100, t10y3m_spread=0.0200, breakeven_10y=2.1900, hy_oas=4.0900, ig_oas=1.1400, ted_spread=0.0900, mortgage_30y=6.6200, vix=30.1200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -10.58%\n Annualized volatility: 19.09%\n Macro: fed_funds=4.3300, vix=30.1\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.105833, "annualized_vol": 0.190916, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250102_0203", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-02", "context_summary": "Regime: sideways. SPY trailing return: +3.6%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=557.80, end=577.70, trailing_return=+3.57%\nAnnualized volatility: 12.19%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3300, t10y3m_spread=0.2100, breakeven_10y=2.3400, hy_oas=2.9200, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.8500, vix=17.3500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.57%\n Annualized volatility: 12.19%\n Macro: fed_funds=4.3300, vix=17.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.035668, "annualized_vol": 0.121896, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250305_0204", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-05", "context_summary": "Regime: sideways. SPY trailing return: -4.7%, annualized vol: 14.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=596.96, end=568.61, trailing_return=-4.75%\nAnnualized volatility: 14.14%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2600, t10y3m_spread=-0.1200, breakeven_10y=2.3500, hy_oas=2.9900, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=6.7600, vix=23.5100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -4.75%\n Annualized volatility: 14.14%\n Macro: fed_funds=4.3300, vix=23.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.047491, "annualized_vol": 0.141428, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250220_0205", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-20", "context_summary": "Regime: sideways. SPY trailing return: +3.6%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=583.22, end=604.17, trailing_return=+3.59%\nAnnualized volatility: 12.32%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2500, t10y3m_spread=0.1900, breakeven_10y=2.4500, hy_oas=2.6800, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.8700, vix=15.2700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.59%\n Annualized volatility: 12.32%\n Macro: fed_funds=4.3300, vix=15.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.035917, "annualized_vol": 0.123159, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250213_0206", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-13", "context_summary": "Regime: sideways. SPY trailing return: +2.0%, annualized vol: 12.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=582.90, end=594.73, trailing_return=+2.03%\nAnnualized volatility: 12.46%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2600, t10y3m_spread=0.2700, breakeven_10y=2.4600, hy_oas=2.6600, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.8900, vix=15.8900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.03%\n Annualized volatility: 12.46%\n Macro: fed_funds=4.3300, vix=15.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.020293, "annualized_vol": 0.124553, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20251023_0208", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-23", "context_summary": "Regime: bull. SPY trailing return: +5.5%, annualized vol: 11.1%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=629.12, end=664.02, trailing_return=+5.55%\nAnnualized volatility: 11.11%\nMacro indicators: fed_funds_rate=4.1100, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5200, t10y3m_spread=0.0100, breakeven_10y=2.2900, hy_oas=3.0100, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.2700, vix=18.6000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.55%\n Annualized volatility: 11.11%\n Macro: fed_funds=4.1100, vix=18.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.055467, "annualized_vol": 0.111111, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251013_0209", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-13", "context_summary": "Regime: sideways. SPY trailing return: +4.3%, annualized vol: 10.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=622.30, end=649.32, trailing_return=+4.34%\nAnnualized volatility: 10.42%\nMacro indicators: fed_funds_rate=4.1000, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5300, t10y3m_spread=0.0300, breakeven_10y=2.3000, hy_oas=3.1800, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.3000, vix=21.6600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.34%\n Annualized volatility: 10.42%\n Macro: fed_funds=4.1000, vix=21.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.043421, "annualized_vol": 0.10421, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250604_0211", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-04", "context_summary": "Regime: sideways. SPY trailing return: +6.7%, annualized vol: 20.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=552.56, end=589.33, trailing_return=+6.65%\nAnnualized volatility: 20.88%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5000, t10y3m_spread=0.0300, breakeven_10y=2.3200, hy_oas=3.1900, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=6.8900, vix=17.6900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.65%\n Annualized volatility: 20.88%\n Macro: fed_funds=4.3300, vix=17.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.066544, "annualized_vol": 0.208773, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250122_0213", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-22", "context_summary": "Regime: sideways. SPY trailing return: +4.7%, annualized vol: 13.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=567.81, end=594.43, trailing_return=+4.69%\nAnnualized volatility: 13.27%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2800, t10y3m_spread=0.2100, breakeven_10y=2.3800, hy_oas=2.6600, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=7.0400, vix=15.0600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.69%\n Annualized volatility: 13.27%\n Macro: fed_funds=4.3300, vix=15.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.046869, "annualized_vol": 0.132721, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250806_0215", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-06", "context_summary": "Regime: bull. SPY trailing return: +11.6%, annualized vol: 11.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=557.94, end=622.69, trailing_return=+11.60%\nAnnualized volatility: 11.30%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5000, t10y3m_spread=-0.1200, breakeven_10y=2.3600, hy_oas=2.9800, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.7200, vix=17.8500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +11.60%\n Annualized volatility: 11.30%\n Macro: fed_funds=4.3300, vix=17.9\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.116041, "annualized_vol": 0.11296, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250901_0217", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-01", "context_summary": "Regime: bull. SPY trailing return: +9.1%, annualized vol: 9.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=586.33, end=639.62, trailing_return=+9.09%\nAnnualized volatility: 9.76%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.6400, t10y3m_spread=0.0000, breakeven_10y=2.4100, hy_oas=2.8400, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.5600, vix=15.3600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.09%\n Annualized volatility: 9.76%\n Macro: fed_funds=4.3300, vix=15.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.090898, "annualized_vol": 0.097571, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250929_0219", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-29", "context_summary": "Regime: bull. SPY trailing return: +6.1%, annualized vol: 9.0%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=620.08, end=658.07, trailing_return=+6.13%\nAnnualized volatility: 8.97%\nMacro indicators: fed_funds_rate=4.0900, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5700, t10y3m_spread=0.1800, breakeven_10y=2.3800, hy_oas=2.7500, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3000, vix=15.2900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.13%\n Annualized volatility: 8.97%\n Macro: fed_funds=4.0900, vix=15.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.06127, "annualized_vol": 0.089713, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250502_0220", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-02", "context_summary": "Regime: bear. SPY trailing return: -7.3%, annualized vol: 21.0%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=595.58, end=552.14, trailing_return=-7.29%\nAnnualized volatility: 21.03%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5500, t10y3m_spread=-0.0600, breakeven_10y=2.2500, hy_oas=3.7800, ig_oas=1.0900, ted_spread=0.0900, mortgage_30y=6.7600, vix=24.6000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -7.29%\n Annualized volatility: 21.03%\n Macro: fed_funds=4.3300, vix=24.6\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.072937, "annualized_vol": 0.210293, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250509_0221", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-09", "context_summary": "Regime: sideways. SPY trailing return: -6.1%, annualized vol: 21.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=594.73, end=558.66, trailing_return=-6.07%\nAnnualized volatility: 21.27%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4700, t10y3m_spread=0.0300, breakeven_10y=2.2900, hy_oas=3.5100, ig_oas=1.0200, ted_spread=0.0900, mortgage_30y=6.7600, vix=22.4800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -6.07%\n Annualized volatility: 21.27%\n Macro: fed_funds=4.3300, vix=22.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.06066, "annualized_vol": 0.212743, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251114_0223", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-14", "context_summary": "Regime: sideways. SPY trailing return: +6.0%, annualized vol: 11.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=630.20, end=668.24, trailing_return=+6.03%\nAnnualized volatility: 11.75%\nMacro indicators: fed_funds_rate=3.8800, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5300, t10y3m_spread=0.1500, breakeven_10y=2.2800, hy_oas=3.0900, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.2400, vix=20.0000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.03%\n Annualized volatility: 11.75%\n Macro: fed_funds=3.8800, vix=20.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.060346, "annualized_vol": 0.117547, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251202_0225", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-02", "context_summary": "Regime: sideways. SPY trailing return: +5.1%, annualized vol: 12.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=643.37, end=676.42, trailing_return=+5.14%\nAnnualized volatility: 12.48%\nMacro indicators: fed_funds_rate=3.8900, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.2800, breakeven_10y=2.2400, hy_oas=2.9400, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.2300, vix=17.2400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.14%\n Annualized volatility: 12.48%\n Macro: fed_funds=3.8900, vix=17.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.051363, "annualized_vol": 0.124765, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250312_0226", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-12", "context_summary": "Regime: sideways. SPY trailing return: -8.2%, annualized vol: 15.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=596.77, end=547.97, trailing_return=-8.18%\nAnnualized volatility: 15.74%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3400, t10y3m_spread=-0.0600, breakeven_10y=2.3100, hy_oas=3.2200, ig_oas=0.9400, ted_spread=0.0900, mortgage_30y=6.6300, vix=26.9200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -8.18%\n Annualized volatility: 15.74%\n Macro: fed_funds=4.3300, vix=26.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.081765, "annualized_vol": 0.157392, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250722_0228", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-22", "context_summary": "Regime: bull. SPY trailing return: +15.4%, annualized vol: 11.5%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=540.49, end=623.48, trailing_return=+15.35%\nAnnualized volatility: 11.47%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5300, t10y3m_spread=-0.0300, breakeven_10y=2.4000, hy_oas=2.8900, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.7500, vix=16.6500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +15.35%\n Annualized volatility: 11.47%\n Macro: fed_funds=4.3300, vix=16.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.15354, "annualized_vol": 0.114727, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251125_0229", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-25", "context_summary": "Regime: sideways. SPY trailing return: +4.7%, annualized vol: 12.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=634.88, end=664.94, trailing_return=+4.73%\nAnnualized volatility: 12.47%\nMacro indicators: fed_funds_rate=3.8800, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5800, t10y3m_spread=0.1300, breakeven_10y=2.2300, hy_oas=3.1500, ig_oas=0.8500, ted_spread=0.0900, mortgage_30y=6.2600, vix=20.5200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.73%\n Annualized volatility: 12.47%\n Macro: fed_funds=3.8800, vix=20.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.047346, "annualized_vol": 0.124723, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20251119_0230", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-19", "context_summary": "Regime: sideways. SPY trailing return: +2.6%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=639.73, end=656.34, trailing_return=+2.60%\nAnnualized volatility: 11.62%\nMacro indicators: fed_funds_rate=3.8800, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5400, t10y3m_spread=0.1800, breakeven_10y=2.2700, hy_oas=3.2000, ig_oas=0.8500, ted_spread=0.0900, mortgage_30y=6.2400, vix=24.6900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.60%\n Annualized volatility: 11.62%\n Macro: fed_funds=3.8800, vix=24.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.025963, "annualized_vol": 0.11619, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250715_0232", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-15", "context_summary": "Regime: bull. SPY trailing return: +19.2%, annualized vol: 14.4%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=519.70, end=619.55, trailing_return=+19.21%\nAnnualized volatility: 14.38%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5300, t10y3m_spread=0.0100, breakeven_10y=2.3900, hy_oas=2.9500, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.7200, vix=17.2000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +19.21%\n Annualized volatility: 14.38%\n Macro: fed_funds=4.3300, vix=17.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.192134, "annualized_vol": 0.143813, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250718_0233", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-18", "context_summary": "Regime: bull. SPY trailing return: +19.5%, annualized vol: 12.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=521.27, end=622.76, trailing_return=+19.47%\nAnnualized volatility: 12.31%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5600, t10y3m_spread=0.0600, breakeven_10y=2.4300, hy_oas=2.9100, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.7500, vix=16.5200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +19.47%\n Annualized volatility: 12.31%\n Macro: fed_funds=4.3300, vix=16.5\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.194683, "annualized_vol": 0.123134, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250820_0235", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-20", "context_summary": "Regime: bull. SPY trailing return: +10.8%, annualized vol: 10.2%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=572.55, end=634.43, trailing_return=+10.81%\nAnnualized volatility: 10.18%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5500, t10y3m_spread=0.0000, breakeven_10y=2.3500, hy_oas=2.9000, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.5800, vix=15.5700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.81%\n Annualized volatility: 10.18%\n Macro: fed_funds=4.3300, vix=15.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.108082, "annualized_vol": 0.101822, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250805_0236", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-05", "context_summary": "Regime: bull. SPY trailing return: +12.0%, annualized vol: 11.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=558.66, end=625.86, trailing_return=+12.03%\nAnnualized volatility: 11.26%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5300, t10y3m_spread=-0.1300, breakeven_10y=2.3700, hy_oas=3.0200, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.7200, vix=17.5200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +12.03%\n Annualized volatility: 11.26%\n Macro: fed_funds=4.3300, vix=17.5\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.120298, "annualized_vol": 0.112603, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20251224_0238", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-24", "context_summary": "Regime: sideways. SPY trailing return: +3.4%, annualized vol: 12.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=662.41, end=685.14, trailing_return=+3.43%\nAnnualized volatility: 12.91%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.7000, t10y3m_spread=0.5300, breakeven_10y=2.2400, hy_oas=2.8300, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.2100, vix=14.0000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.43%\n Annualized volatility: 12.91%\n Macro: fed_funds=3.6400, vix=14.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.034315, "annualized_vol": 0.129063, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250106_0239", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-06", "context_summary": "Regime: sideways. SPY trailing return: +2.9%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=566.98, end=583.49, trailing_return=+2.91%\nAnnualized volatility: 12.15%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3200, t10y3m_spread=0.2600, breakeven_10y=2.3400, hy_oas=2.8100, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.9100, vix=16.1300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.91%\n Annualized volatility: 12.15%\n Macro: fed_funds=4.3300, vix=16.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.029113, "annualized_vol": 0.121541, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251222_0240", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-22", "context_summary": "Regime: sideways. SPY trailing return: +3.1%, annualized vol: 12.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=658.07, end=678.74, trailing_return=+3.14%\nAnnualized volatility: 12.88%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.6800, t10y3m_spread=0.5400, breakeven_10y=2.2400, hy_oas=2.9000, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.2100, vix=14.9100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.14%\n Annualized volatility: 12.88%\n Macro: fed_funds=3.6400, vix=14.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.0314, "annualized_vol": 0.128798, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251217_0241", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-17", "context_summary": "Regime: sideways. SPY trailing return: +2.4%, annualized vol: 12.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=659.46, end=675.03, trailing_return=+2.36%\nAnnualized volatility: 12.57%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.6700, t10y3m_spread=0.5100, breakeven_10y=2.2300, hy_oas=2.9800, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.2200, vix=16.4800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.36%\n Annualized volatility: 12.57%\n Macro: fed_funds=3.6400, vix=16.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.023612, "annualized_vol": 0.125743, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251117_0242", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-17", "context_summary": "Regime: sideways. SPY trailing return: +4.4%, annualized vol: 11.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=639.88, end=668.13, trailing_return=+4.41%\nAnnualized volatility: 11.71%\nMacro indicators: fed_funds_rate=3.8800, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5200, t10y3m_spread=0.1900, breakeven_10y=2.2800, hy_oas=3.0700, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.2400, vix=19.8300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.41%\n Annualized volatility: 11.71%\n Macro: fed_funds=3.8800, vix=19.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.044138, "annualized_vol": 0.117122, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250410_0243", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-10", "context_summary": "Regime: bear. SPY trailing return: -5.5%, annualized vol: 18.4%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=573.87, end=542.40, trailing_return=-5.48%\nAnnualized volatility: 18.36%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4300, t10y3m_spread=-0.0100, breakeven_10y=2.2700, hy_oas=4.3700, ig_oas=1.2100, ted_spread=0.0900, mortgage_30y=6.6400, vix=33.6200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -5.48%\n Annualized volatility: 18.36%\n Macro: fed_funds=4.3300, vix=33.6\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.054827, "annualized_vol": 0.183617, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251010_0244", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-10", "context_summary": "Regime: bull. SPY trailing return: +7.2%, annualized vol: 8.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=622.76, end=667.36, trailing_return=+7.16%\nAnnualized volatility: 8.68%\nMacro indicators: fed_funds_rate=4.1000, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5400, t10y3m_spread=0.1100, breakeven_10y=2.3400, hy_oas=2.9500, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3000, vix=16.4300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.16%\n Annualized volatility: 8.68%\n Macro: fed_funds=4.1000, vix=16.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.071621, "annualized_vol": 0.086793, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250808_0246", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-08", "context_summary": "Regime: bull. SPY trailing return: +8.1%, annualized vol: 10.6%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=580.19, end=626.93, trailing_return=+8.06%\nAnnualized volatility: 10.64%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5100, t10y3m_spread=-0.0900, breakeven_10y=2.3500, hy_oas=2.9500, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.6300, vix=16.5700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.06%\n Annualized volatility: 10.64%\n Macro: fed_funds=4.3300, vix=16.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.080566, "annualized_vol": 0.106376, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251120_0248", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-20", "context_summary": "Regime: sideways. SPY trailing return: +2.8%, annualized vol: 11.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=641.19, end=658.88, trailing_return=+2.76%\nAnnualized volatility: 11.61%\nMacro indicators: fed_funds_rate=3.8800, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.1800, breakeven_10y=2.2700, hy_oas=3.1700, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.2400, vix=23.6600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.76%\n Annualized volatility: 11.61%\n Macro: fed_funds=3.8800, vix=23.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.027585, "annualized_vol": 0.116148, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250903_0249", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-03", "context_summary": "Regime: bull. SPY trailing return: +7.2%, annualized vol: 9.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=592.35, end=634.88, trailing_return=+7.18%\nAnnualized volatility: 9.84%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.6200, t10y3m_spread=0.0800, breakeven_10y=2.4100, hy_oas=2.9200, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.5600, vix=17.1700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.18%\n Annualized volatility: 9.84%\n Macro: fed_funds=4.3300, vix=17.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.071808, "annualized_vol": 0.098417, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250919_0251", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-19", "context_summary": "Regime: bull. SPY trailing return: +9.1%, annualized vol: 8.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=602.01, end=656.69, trailing_return=+9.08%\nAnnualized volatility: 8.82%\nMacro indicators: fed_funds_rate=4.0800, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5400, t10y3m_spread=0.0800, breakeven_10y=2.3800, hy_oas=2.7100, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.2600, vix=15.7000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.08%\n Annualized volatility: 8.82%\n Macro: fed_funds=4.0800, vix=15.7\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.090822, "annualized_vol": 0.088182, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250623_0252", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-23", "context_summary": "Regime: sideways. SPY trailing return: +4.8%, annualized vol: 19.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=562.15, end=589.28, trailing_return=+4.83%\nAnnualized volatility: 19.21%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4800, t10y3m_spread=-0.0100, breakeven_10y=2.3300, hy_oas=3.1300, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=6.8100, vix=20.6200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.83%\n Annualized volatility: 19.21%\n Macro: fed_funds=4.3300, vix=20.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.048272, "annualized_vol": 0.192071, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251230_0254", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-30", "context_summary": "Regime: sideways. SPY trailing return: +3.0%, annualized vol: 12.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=665.42, end=685.14, trailing_return=+2.96%\nAnnualized volatility: 12.92%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.6700, t10y3m_spread=0.4400, breakeven_10y=2.2200, hy_oas=2.8700, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.1800, vix=14.2000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.96%\n Annualized volatility: 12.92%\n Macro: fed_funds=3.6400, vix=14.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.029632, "annualized_vol": 0.129193, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250224_0255", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-24", "context_summary": "Regime: sideways. SPY trailing return: +0.7%, annualized vol: 12.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=587.01, end=591.36, trailing_return=+0.74%\nAnnualized volatility: 12.84%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2300, t10y3m_spread=0.1000, breakeven_10y=2.4200, hy_oas=2.7800, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.8500, vix=18.2100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +0.74%\n Annualized volatility: 12.84%\n Macro: fed_funds=4.3300, vix=18.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.007412, "annualized_vol": 0.128438, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250714_0257", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-14", "context_summary": "Regime: bull. SPY trailing return: +16.3%, annualized vol: 14.4%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=531.52, end=618.37, trailing_return=+16.34%\nAnnualized volatility: 14.42%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5300, t10y3m_spread=0.0200, breakeven_10y=2.3700, hy_oas=2.9700, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.7200, vix=16.4000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +16.34%\n Annualized volatility: 14.42%\n Macro: fed_funds=4.3300, vix=16.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.163415, "annualized_vol": 0.144189, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251203_0258", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-03", "context_summary": "Regime: sideways. SPY trailing return: +5.1%, annualized vol: 12.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=644.86, end=677.67, trailing_return=+5.09%\nAnnualized volatility: 12.47%\nMacro indicators: fed_funds_rate=3.8900, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5800, t10y3m_spread=0.3200, breakeven_10y=2.2400, hy_oas=2.9200, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.2300, vix=16.5900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.09%\n Annualized volatility: 12.47%\n Macro: fed_funds=3.8900, vix=16.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.050881, "annualized_vol": 0.124738, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250612_0259", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-12", "context_summary": "Regime: sideways. SPY trailing return: +7.5%, annualized vol: 19.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=553.00, end=594.54, trailing_return=+7.51%\nAnnualized volatility: 19.46%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4700, t10y3m_spread=-0.0400, breakeven_10y=2.2700, hy_oas=3.1200, ig_oas=0.8700, ted_spread=0.0900, mortgage_30y=6.8500, vix=17.2600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.51%\n Annualized volatility: 19.46%\n Macro: fed_funds=4.3300, vix=17.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.075129, "annualized_vol": 0.194618, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250814_0261", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-14", "context_summary": "Regime: bull. SPY trailing return: +8.7%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=588.11, end=639.47, trailing_return=+8.73%\nAnnualized volatility: 10.79%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5700, t10y3m_spread=-0.0500, breakeven_10y=2.3700, hy_oas=2.9000, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.6300, vix=14.4900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.73%\n Annualized volatility: 10.79%\n Macro: fed_funds=4.3300, vix=14.5\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.087327, "annualized_vol": 0.107918, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250618_0262", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-18", "context_summary": "Regime: sideways. SPY trailing return: +4.1%, annualized vol: 19.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=567.57, end=590.76, trailing_return=+4.08%\nAnnualized volatility: 19.53%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4500, t10y3m_spread=-0.0300, breakeven_10y=2.3100, hy_oas=3.1700, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=6.8400, vix=21.6000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.08%\n Annualized volatility: 19.53%\n Macro: fed_funds=4.3300, vix=21.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.040848, "annualized_vol": 0.195344, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250513_0264", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-13", "context_summary": "Regime: sideways. SPY trailing return: -4.1%, annualized vol: 21.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=600.98, end=576.38, trailing_return=-4.09%\nAnnualized volatility: 21.62%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4700, t10y3m_spread=0.0300, breakeven_10y=2.2900, hy_oas=3.1500, ig_oas=0.9700, ted_spread=0.0900, mortgage_30y=6.7600, vix=18.3900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -4.09%\n Annualized volatility: 21.62%\n Macro: fed_funds=4.3300, vix=18.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.040932, "annualized_vol": 0.216164, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250429_0266", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-29", "context_summary": "Regime: bear. SPY trailing return: -8.2%, annualized vol: 21.0%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=593.21, end=544.61, trailing_return=-8.19%\nAnnualized volatility: 21.00%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5600, t10y3m_spread=-0.0900, breakeven_10y=2.2500, hy_oas=3.7300, ig_oas=1.0400, ted_spread=0.0900, mortgage_30y=6.8100, vix=25.1500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -8.19%\n Annualized volatility: 21.00%\n Macro: fed_funds=4.3300, vix=25.1\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.08194, "annualized_vol": 0.209997, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250822_0268", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-22", "context_summary": "Regime: bull. SPY trailing return: +8.5%, annualized vol: 9.3%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=581.07, end=630.20, trailing_return=+8.46%\nAnnualized volatility: 9.33%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5400, t10y3m_spread=0.0100, breakeven_10y=2.3900, hy_oas=2.9500, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.5800, vix=16.6000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.46%\n Annualized volatility: 9.33%\n Macro: fed_funds=4.3300, vix=16.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.084561, "annualized_vol": 0.09331, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250922_0269", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-22", "context_summary": "Regime: bull. SPY trailing return: +8.8%, annualized vol: 8.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=606.72, end=659.94, trailing_return=+8.77%\nAnnualized volatility: 8.84%\nMacro indicators: fed_funds_rate=4.0800, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5700, t10y3m_spread=0.1100, breakeven_10y=2.3900, hy_oas=2.7200, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.2600, vix=15.4500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.77%\n Annualized volatility: 8.84%\n Macro: fed_funds=4.0800, vix=15.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.087715, "annualized_vol": 0.088448, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251208_0270", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-08", "context_summary": "Regime: sideways. SPY trailing return: +4.6%, annualized vol: 12.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=651.88, end=681.81, trailing_return=+4.59%\nAnnualized volatility: 12.38%\nMacro indicators: fed_funds_rate=3.8900, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5800, t10y3m_spread=0.4300, breakeven_10y=2.2600, hy_oas=2.8500, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.1900, vix=15.4100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.59%\n Annualized volatility: 12.38%\n Macro: fed_funds=3.8900, vix=15.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.045909, "annualized_vol": 0.123807, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250912_0272", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-12", "context_summary": "Regime: bull. SPY trailing return: +10.4%, annualized vol: 9.4%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=590.76, end=652.10, trailing_return=+10.38%\nAnnualized volatility: 9.37%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.4900, t10y3m_spread=-0.0700, breakeven_10y=2.3400, hy_oas=2.7800, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.3500, vix=14.7100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +10.38%\n Annualized volatility: 9.37%\n Macro: fed_funds=4.3300, vix=14.7\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.103834, "annualized_vol": 0.0937, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250923_0273", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-23", "context_summary": "Regime: bull. SPY trailing return: +8.7%, annualized vol: 8.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=609.74, end=663.06, trailing_return=+8.75%\nAnnualized volatility: 8.77%\nMacro indicators: fed_funds_rate=4.0900, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5400, t10y3m_spread=0.1500, breakeven_10y=2.3700, hy_oas=2.6900, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.2600, vix=16.1000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.75%\n Annualized volatility: 8.77%\n Macro: fed_funds=4.0900, vix=16.1\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.087458, "annualized_vol": 0.08774, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250114_0274", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-14", "context_summary": "Regime: sideways. SPY trailing return: +0.2%, annualized vol: 12.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=572.05, end=573.08, trailing_return=+0.18%\nAnnualized volatility: 12.52%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3900, t10y3m_spread=0.4200, breakeven_10y=2.4500, hy_oas=2.8500, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.9300, vix=19.1900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +0.18%\n Annualized volatility: 12.52%\n Macro: fed_funds=4.3300, vix=19.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.001798, "annualized_vol": 0.125169, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250911_0276", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-11", "context_summary": "Regime: bull. SPY trailing return: +8.5%, annualized vol: 9.4%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=595.85, end=646.72, trailing_return=+8.54%\nAnnualized volatility: 9.41%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5000, t10y3m_spread=-0.0500, breakeven_10y=2.3500, hy_oas=2.8400, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.5000, vix=15.3500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.54%\n Annualized volatility: 9.41%\n Macro: fed_funds=4.3300, vix=15.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.085382, "annualized_vol": 0.0941, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250605_0278", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-05", "context_summary": "Regime: sideways. SPY trailing return: +7.5%, annualized vol: 20.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=547.97, end=589.18, trailing_return=+7.52%\nAnnualized volatility: 20.09%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5000, t10y3m_spread=-0.0700, breakeven_10y=2.3100, hy_oas=3.2300, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=6.8900, vix=17.6100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.52%\n Annualized volatility: 20.09%\n Macro: fed_funds=4.3300, vix=17.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.075196, "annualized_vol": 0.200909, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250902_0279", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-02", "context_summary": "Regime: bull. SPY trailing return: +9.1%, annualized vol: 9.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=586.33, end=639.62, trailing_return=+9.09%\nAnnualized volatility: 9.76%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.6400, t10y3m_spread=0.0000, breakeven_10y=2.4100, hy_oas=2.8400, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.5600, vix=15.3600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.09%\n Annualized volatility: 9.76%\n Macro: fed_funds=4.3300, vix=15.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.090898, "annualized_vol": 0.097571, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250829_0280", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-29", "context_summary": "Regime: bull. SPY trailing return: +9.2%, annualized vol: 9.6%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=589.18, end=643.46, trailing_return=+9.21%\nAnnualized volatility: 9.64%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.6000, t10y3m_spread=-0.0400, breakeven_10y=2.4100, hy_oas=2.7500, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.5600, vix=14.4300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.21%\n Annualized volatility: 9.64%\n Macro: fed_funds=4.3300, vix=14.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.092139, "annualized_vol": 0.096428, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250116_0281", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-16", "context_summary": "Regime: sideways. SPY trailing return: +1.7%, annualized vol: 13.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=574.30, end=584.30, trailing_return=+1.74%\nAnnualized volatility: 13.02%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3900, t10y3m_spread=0.3100, breakeven_10y=2.4200, hy_oas=2.7200, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.9300, vix=16.1200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.74%\n Annualized volatility: 13.02%\n Macro: fed_funds=4.3300, vix=16.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.017423, "annualized_vol": 0.130214, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250117_0283", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-17", "context_summary": "Regime: sideways. SPY trailing return: +1.7%, annualized vol: 13.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=573.36, end=583.18, trailing_return=+1.71%\nAnnualized volatility: 13.01%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3800, t10y3m_spread=0.2700, breakeven_10y=2.4200, hy_oas=2.7300, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=7.0400, vix=16.6000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.71%\n Annualized volatility: 13.01%\n Macro: fed_funds=4.3300, vix=16.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.017136, "annualized_vol": 0.130088, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251212_0285", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-12", "context_summary": "Regime: sideways. SPY trailing return: +4.3%, annualized vol: 12.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=656.69, end=685.14, trailing_return=+4.33%\nAnnualized volatility: 12.42%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.6200, t10y3m_spread=0.4800, breakeven_10y=2.2500, hy_oas=2.8800, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.2200, vix=14.8500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.33%\n Annualized volatility: 12.42%\n Macro: fed_funds=3.6400, vix=14.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.043322, "annualized_vol": 0.124203, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250331_0286", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-31", "context_summary": "Regime: bear. SPY trailing return: -4.9%, annualized vol: 16.3%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=577.70, end=549.36, trailing_return=-4.91%\nAnnualized volatility: 16.33%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3800, t10y3m_spread=-0.0600, breakeven_10y=2.3700, hy_oas=3.4700, ig_oas=0.9400, ted_spread=0.0900, mortgage_30y=6.6500, vix=21.6500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -4.91%\n Annualized volatility: 16.33%\n Macro: fed_funds=4.3300, vix=21.6\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.049052, "annualized_vol": 0.163299, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250925_0288", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-25", "context_summary": "Regime: bull. SPY trailing return: +7.3%, annualized vol: 8.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=612.46, end=657.36, trailing_return=+7.33%\nAnnualized volatility: 8.87%\nMacro indicators: fed_funds_rate=4.0900, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5900, t10y3m_spread=0.1400, breakeven_10y=2.3800, hy_oas=2.7000, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.2600, vix=16.1800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.33%\n Annualized volatility: 8.87%\n Macro: fed_funds=4.0900, vix=16.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.073315, "annualized_vol": 0.088742, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250403_0289", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-03", "context_summary": "Regime: bear. SPY trailing return: -4.9%, annualized vol: 16.2%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=586.85, end=558.12, trailing_return=-4.89%\nAnnualized volatility: 16.24%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.2900, t10y3m_spread=-0.1200, breakeven_10y=2.3200, hy_oas=3.4200, ig_oas=0.9600, ted_spread=0.0900, mortgage_30y=6.6500, vix=21.5100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -4.89%\n Annualized volatility: 16.24%\n Macro: fed_funds=4.3300, vix=21.5\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.048948, "annualized_vol": 0.162438, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250217_0290", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-17", "context_summary": "Regime: sideways. SPY trailing return: +4.0%, annualized vol: 12.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=577.80, end=600.98, trailing_return=+4.01%\nAnnualized volatility: 12.23%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2100, t10y3m_spread=0.1300, breakeven_10y=2.4300, hy_oas=2.6600, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.8700, vix=14.7700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.01%\n Annualized volatility: 12.23%\n Macro: fed_funds=4.3300, vix=14.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.040129, "annualized_vol": 0.122327, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251103_0291", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-03", "context_summary": "Regime: bull. SPY trailing return: +7.3%, annualized vol: 10.6%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=631.82, end=678.20, trailing_return=+7.34%\nAnnualized volatility: 10.56%\nMacro indicators: fed_funds_rate=3.8600, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5100, t10y3m_spread=0.2200, breakeven_10y=2.3000, hy_oas=2.9400, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.1700, vix=17.4400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.34%\n Annualized volatility: 10.56%\n Macro: fed_funds=3.8600, vix=17.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.073403, "annualized_vol": 0.105617, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250310_0293", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-10", "context_summary": "Regime: sideways. SPY trailing return: -4.4%, annualized vol: 14.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=594.03, end=567.69, trailing_return=-4.44%\nAnnualized volatility: 14.75%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3300, t10y3m_spread=-0.0200, breakeven_10y=2.3300, hy_oas=2.9700, ig_oas=0.8900, ted_spread=0.0900, mortgage_30y=6.6300, vix=23.3700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -4.44%\n Annualized volatility: 14.75%\n Macro: fed_funds=4.3300, vix=23.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.044357, "annualized_vol": 0.147488, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250619_0295", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-19", "context_summary": "Regime: sideways. SPY trailing return: +3.8%, annualized vol: 19.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=568.94, end=590.67, trailing_return=+3.82%\nAnnualized volatility: 19.20%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4400, t10y3m_spread=-0.0400, breakeven_10y=2.3100, hy_oas=3.1600, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=6.8100, vix=20.1400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.82%\n Annualized volatility: 19.20%\n Macro: fed_funds=4.3300, vix=20.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.038196, "annualized_vol": 0.192047, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250620_0297", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-20", "context_summary": "Regime: sideways. SPY trailing return: +3.8%, annualized vol: 19.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=568.94, end=590.67, trailing_return=+3.82%\nAnnualized volatility: 19.20%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4400, t10y3m_spread=-0.0400, breakeven_10y=2.3100, hy_oas=3.1600, ig_oas=0.8800, ted_spread=0.0900, mortgage_30y=6.8100, vix=20.1400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.82%\n Annualized volatility: 19.20%\n Macro: fed_funds=4.3300, vix=20.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.038196, "annualized_vol": 0.192047, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251110_0299", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-11-10", "context_summary": "Regime: sideways. SPY trailing return: +4.6%, annualized vol: 10.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=638.03, end=667.17, trailing_return=+4.57%\nAnnualized volatility: 10.88%\nMacro indicators: fed_funds_rate=3.8700, cpi_yoy=325.0630, unemployment=4.5000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5600, t10y3m_spread=0.1900, breakeven_10y=2.2800, hy_oas=3.1500, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.2200, vix=19.0800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.57%\n Annualized volatility: 10.88%\n Macro: fed_funds=3.8700, vix=19.1\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.045677, "annualized_vol": 0.108805, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250519_0301", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-19", "context_summary": "Regime: sideways. SPY trailing return: -0.7%, annualized vol: 21.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=591.36, end=587.47, trailing_return=-0.66%\nAnnualized volatility: 21.72%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4500, t10y3m_spread=0.0600, breakeven_10y=2.3400, hy_oas=3.1600, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.8100, vix=17.2400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -0.66%\n Annualized volatility: 21.72%\n Macro: fed_funds=4.3300, vix=17.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.006588, "annualized_vol": 0.217248, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250505_0303", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-05", "context_summary": "Regime: sideways. SPY trailing return: -6.2%, annualized vol: 21.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=597.65, end=560.34, trailing_return=-6.24%\nAnnualized volatility: 21.26%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5000, t10y3m_spread=0.0000, breakeven_10y=2.2700, hy_oas=3.6000, ig_oas=1.0600, ted_spread=0.0900, mortgage_30y=6.7600, vix=22.6800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -6.24%\n Annualized volatility: 21.26%\n Macro: fed_funds=4.3300, vix=22.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.062434, "annualized_vol": 0.212597, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250113_0304", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-13", "context_summary": "Regime: sideways. SPY trailing return: +0.5%, annualized vol: 12.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=569.57, end=572.19, trailing_return=+0.46%\nAnnualized volatility: 12.62%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3700, t10y3m_spread=0.4100, breakeven_10y=2.4300, hy_oas=2.8100, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.9300, vix=19.5400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +0.46%\n Annualized volatility: 12.62%\n Macro: fed_funds=4.3300, vix=19.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.004594, "annualized_vol": 0.126165, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250415_0305", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-15", "context_summary": "Regime: bear. SPY trailing return: -9.5%, annualized vol: 19.2%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=589.04, end=533.01, trailing_return=-9.51%\nAnnualized volatility: 19.24%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5400, t10y3m_spread=0.0500, breakeven_10y=2.2300, hy_oas=4.1400, ig_oas=1.1500, ted_spread=0.0900, mortgage_30y=6.6200, vix=30.8900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -9.51%\n Annualized volatility: 19.24%\n Macro: fed_funds=4.3300, vix=30.9\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.095114, "annualized_vol": 0.192425, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251022_0307", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-22", "context_summary": "Regime: bull. SPY trailing return: +6.0%, annualized vol: 11.1%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=629.92, end=667.49, trailing_return=+5.96%\nAnnualized volatility: 11.06%\nMacro indicators: fed_funds_rate=4.1100, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5300, t10y3m_spread=0.0200, breakeven_10y=2.2800, hy_oas=2.9700, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.2700, vix=17.8700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.96%\n Annualized volatility: 11.06%\n Macro: fed_funds=4.1100, vix=17.9\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.059646, "annualized_vol": 0.110632, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250813_0308", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-13", "context_summary": "Regime: bull. SPY trailing return: +8.5%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=587.47, end=637.28, trailing_return=+8.48%\nAnnualized volatility: 10.83%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5700, t10y3m_spread=-0.0400, breakeven_10y=2.3800, hy_oas=2.9300, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.6300, vix=14.7300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.48%\n Annualized volatility: 10.83%\n Macro: fed_funds=4.3300, vix=14.7\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.084803, "annualized_vol": 0.108311, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250207_0309", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-07", "context_summary": "Regime: sideways. SPY trailing return: +1.7%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=587.66, end=597.65, trailing_return=+1.70%\nAnnualized volatility: 12.25%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2400, t10y3m_spread=0.1100, breakeven_10y=2.4200, hy_oas=2.6600, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.8900, vix=15.5000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.70%\n Annualized volatility: 12.25%\n Macro: fed_funds=4.3300, vix=15.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.017002, "annualized_vol": 0.122531, "has_text": true, "text_chars": 9047}} +{"id": "T7_all_20250423_0311", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-23", "context_summary": "Regime: bear. SPY trailing return: -11.8%, annualized vol: 20.4%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=590.80, end=521.27, trailing_return=-11.77%\nAnnualized volatility: 20.38%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.6500, t10y3m_spread=0.0800, breakeven_10y=2.2700, hy_oas=3.9900, ig_oas=1.1100, ted_spread=0.0900, mortgage_30y=6.8300, vix=30.5700\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -11.77%\n Annualized volatility: 20.38%\n Macro: fed_funds=4.3300, vix=30.6\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.11768, "annualized_vol": 0.203795, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250408_0313", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-08", "context_summary": "Regime: bear. SPY trailing return: -12.8%, annualized vol: 17.8%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=572.19, end=498.66, trailing_return=-12.85%\nAnnualized volatility: 17.77%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4200, t10y3m_spread=-0.1400, breakeven_10y=2.1900, hy_oas=4.6100, ig_oas=1.2000, ted_spread=0.0900, mortgage_30y=6.6400, vix=43.3500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -12.85%\n Annualized volatility: 17.77%\n Macro: fed_funds=4.3300, vix=43.3\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.128499, "annualized_vol": 0.177718, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250204_0315", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-04", "context_summary": "Regime: sideways. SPY trailing return: +4.0%, annualized vol: 13.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=566.55, end=589.22, trailing_return=+4.00%\nAnnualized volatility: 13.15%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2800, t10y3m_spread=0.2000, breakeven_10y=2.4500, hy_oas=2.7300, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.9500, vix=18.6200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +4.00%\n Annualized volatility: 13.15%\n Macro: fed_funds=4.3300, vix=18.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.040024, "annualized_vol": 0.131475, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20250730_0317", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-30", "context_summary": "Regime: bull. SPY trailing return: +12.4%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=560.34, end=629.92, trailing_return=+12.42%\nAnnualized volatility: 10.83%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.4800, t10y3m_spread=-0.0600, breakeven_10y=2.4300, hy_oas=2.8600, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.7400, vix=15.9800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +12.42%\n Annualized volatility: 10.83%\n Macro: fed_funds=4.3300, vix=16.0\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.124176, "annualized_vol": 0.10833, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20250124_0318", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-24", "context_summary": "Regime: sideways. SPY trailing return: +5.7%, annualized vol: 13.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=568.85, end=601.03, trailing_return=+5.66%\nAnnualized volatility: 13.18%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3600, t10y3m_spread=0.2900, breakeven_10y=2.4200, hy_oas=2.6600, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.9600, vix=15.0200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.66%\n Annualized volatility: 13.18%\n Macro: fed_funds=4.3300, vix=15.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.05658, "annualized_vol": 0.131836, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20250702_0319", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-02", "context_summary": "Regime: sideways. SPY trailing return: +22.6%, annualized vol: 17.8%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=499.55, end=612.46, trailing_return=+22.60%\nAnnualized volatility: 17.77%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.4800, t10y3m_spread=-0.1400, breakeven_10y=2.2900, hy_oas=2.9100, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.7700, vix=16.8300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +22.60%\n Annualized volatility: 17.77%\n Macro: fed_funds=4.3300, vix=16.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.226005, "annualized_vol": 0.177744, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250210_0321", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-10", "context_summary": "Regime: sideways. SPY trailing return: +0.7%, annualized vol: 12.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=588.22, end=592.18, trailing_return=+0.67%\nAnnualized volatility: 12.38%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2000, t10y3m_spread=0.1400, breakeven_10y=2.4200, hy_oas=2.6700, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.8900, vix=16.5400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +0.67%\n Annualized volatility: 12.38%\n Macro: fed_funds=4.3300, vix=16.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.006734, "annualized_vol": 0.123809, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20251215_0323", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-15", "context_summary": "Regime: sideways. SPY trailing return: +2.7%, annualized vol: 12.6%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=659.94, end=677.90, trailing_return=+2.72%\nAnnualized volatility: 12.62%\nMacro indicators: fed_funds_rate=3.6400, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.6700, t10y3m_spread=0.5600, breakeven_10y=2.2600, hy_oas=2.9100, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.2200, vix=15.7400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.72%\n Annualized volatility: 12.62%\n Macro: fed_funds=3.6400, vix=15.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.027211, "annualized_vol": 0.126174, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250811_0325", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-11", "context_summary": "Regime: bull. SPY trailing return: +8.8%, annualized vol: 10.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=580.93, end=631.82, trailing_return=+8.76%\nAnnualized volatility: 10.66%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5100, t10y3m_spread=-0.0500, breakeven_10y=2.3900, hy_oas=2.9400, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.6300, vix=15.1500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.76%\n Annualized volatility: 10.66%\n Macro: fed_funds=4.3300, vix=15.1\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.087601, "annualized_vol": 0.106649, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250411_0326", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-11", "context_summary": "Regime: bear. SPY trailing return: -11.2%, annualized vol: 19.1%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=584.30, end=518.63, trailing_return=-11.24%\nAnnualized volatility: 19.11%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5600, t10y3m_spread=0.0600, breakeven_10y=2.1900, hy_oas=4.4200, ig_oas=1.1800, ted_spread=0.0900, mortgage_30y=6.6200, vix=40.7200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -11.24%\n Annualized volatility: 19.11%\n Macro: fed_funds=4.3300, vix=40.7\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.112389, "annualized_vol": 0.191142, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251029_0327", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-29", "context_summary": "Regime: bull. SPY trailing return: +9.7%, annualized vol: 10.4%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=622.69, end=683.17, trailing_return=+9.71%\nAnnualized volatility: 10.41%\nMacro indicators: fed_funds_rate=4.1200, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5200, t10y3m_spread=0.1000, breakeven_10y=2.2800, hy_oas=2.8200, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.1900, vix=16.4200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.71%\n Annualized volatility: 10.41%\n Macro: fed_funds=4.1200, vix=16.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.09713, "annualized_vol": 0.104121, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250501_0329", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-01", "context_summary": "Regime: bear. SPY trailing return: -7.6%, annualized vol: 21.0%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=593.18, end=548.26, trailing_return=-7.57%\nAnnualized volatility: 21.02%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5700, t10y3m_spread=-0.1400, breakeven_10y=2.2300, hy_oas=3.9400, ig_oas=1.0900, ted_spread=0.0900, mortgage_30y=6.8100, vix=24.7000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -7.57%\n Annualized volatility: 21.02%\n Macro: fed_funds=4.3300, vix=24.7\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.075728, "annualized_vol": 0.21023, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250127_0330", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-27", "context_summary": "Regime: sideways. SPY trailing return: +5.0%, annualized vol: 13.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=570.60, end=599.28, trailing_return=+5.02%\nAnnualized volatility: 13.20%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3600, t10y3m_spread=0.2800, breakeven_10y=2.4300, hy_oas=2.6600, ig_oas=0.8000, ted_spread=0.0900, mortgage_30y=6.9600, vix=14.8500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.02%\n Annualized volatility: 13.20%\n Macro: fed_funds=4.3300, vix=14.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.050249, "annualized_vol": 0.132045, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20250508_0332", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-08", "context_summary": "Regime: sideways. SPY trailing return: -7.0%, annualized vol: 21.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=596.65, end=554.79, trailing_return=-7.02%\nAnnualized volatility: 21.21%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4800, t10y3m_spread=-0.0800, breakeven_10y=2.2500, hy_oas=3.6700, ig_oas=1.0500, ted_spread=0.0900, mortgage_30y=6.7600, vix=23.5500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -7.02%\n Annualized volatility: 21.21%\n Macro: fed_funds=4.3300, vix=23.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.070166, "annualized_vol": 0.2121, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250428_0334", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-28", "context_summary": "Regime: bear. SPY trailing return: -8.7%, annualized vol: 21.0%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=596.39, end=544.40, trailing_return=-8.72%\nAnnualized volatility: 21.05%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5500, t10y3m_spread=-0.0300, breakeven_10y=2.2700, hy_oas=3.6700, ig_oas=1.0400, ted_spread=0.0900, mortgage_30y=6.8100, vix=24.8400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -8.72%\n Annualized volatility: 21.05%\n Macro: fed_funds=4.3300, vix=24.8\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.087174, "annualized_vol": 0.210453, "has_text": true, "text_chars": 9047}} +{"id": "T7_all_20250828_0336", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-28", "context_summary": "Regime: bull. SPY trailing return: +8.8%, annualized vol: 9.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=589.33, end=641.19, trailing_return=+8.80%\nAnnualized volatility: 9.67%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.6500, t10y3m_spread=-0.0200, breakeven_10y=2.4300, hy_oas=2.7800, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.5800, vix=14.8500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +8.80%\n Annualized volatility: 9.67%\n Macro: fed_funds=4.3300, vix=14.9\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.087993, "annualized_vol": 0.096726, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20251210_0337", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-12-10", "context_summary": "Regime: sideways. SPY trailing return: +3.8%, annualized vol: 12.4%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=654.45, end=679.17, trailing_return=+3.78%\nAnnualized volatility: 12.37%\nMacro indicators: fed_funds_rate=3.8900, cpi_yoy=326.0310, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5700, t10y3m_spread=0.4500, breakeven_10y=2.2600, hy_oas=2.8900, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.1900, vix=16.9300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +3.78%\n Annualized volatility: 12.37%\n Macro: fed_funds=3.8900, vix=16.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.037778, "annualized_vol": 0.123692, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20251002_0338", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-02", "context_summary": "Regime: bull. SPY trailing return: +7.4%, annualized vol: 8.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=618.81, end=664.67, trailing_return=+7.41%\nAnnualized volatility: 8.71%\nMacro indicators: fed_funds_rate=4.0900, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5700, t10y3m_spread=0.1100, breakeven_10y=2.3500, hy_oas=2.8100, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3000, vix=16.2900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.41%\n Annualized volatility: 8.71%\n Macro: fed_funds=4.0900, vix=16.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.074101, "annualized_vol": 0.087085, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250526_0339", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-26", "context_summary": "Regime: sideways. SPY trailing return: -2.2%, annualized vol: 21.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=585.68, end=572.55, trailing_return=-2.24%\nAnnualized volatility: 21.49%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5100, t10y3m_spread=0.1500, breakeven_10y=2.3300, hy_oas=3.4000, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.8600, vix=22.2900\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -2.24%\n Annualized volatility: 21.49%\n Macro: fed_funds=4.3300, vix=22.3\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.022431, "annualized_vol": 0.214944, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250731_0341", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-31", "context_summary": "Regime: bull. SPY trailing return: +12.9%, annualized vol: 10.5%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=557.12, end=629.12, trailing_return=+12.92%\nAnnualized volatility: 10.52%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.4400, t10y3m_spread=-0.0300, breakeven_10y=2.4200, hy_oas=2.8900, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.7400, vix=15.4800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +12.92%\n Annualized volatility: 10.52%\n Macro: fed_funds=4.3300, vix=15.5\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.129236, "annualized_vol": 0.105214, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250515_0343", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-15", "context_summary": "Regime: sideways. SPY trailing return: -3.8%, annualized vol: 21.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=604.17, end=580.93, trailing_return=-3.85%\nAnnualized volatility: 21.66%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4800, t10y3m_spread=0.1200, breakeven_10y=2.3700, hy_oas=3.1000, ig_oas=0.9300, ted_spread=0.0900, mortgage_30y=6.7600, vix=18.6200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -3.85%\n Annualized volatility: 21.66%\n Macro: fed_funds=4.3300, vix=18.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.038459, "annualized_vol": 0.216623, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250815_0345", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-08-15", "context_summary": "Regime: bull. SPY trailing return: +9.1%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=586.13, end=639.53, trailing_return=+9.11%\nAnnualized volatility: 10.80%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=323.2910, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5500, t10y3m_spread=-0.0100, breakeven_10y=2.3900, hy_oas=2.8900, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.5800, vix=14.8300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +9.11%\n Annualized volatility: 10.80%\n Macro: fed_funds=4.3300, vix=14.8\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.091097, "annualized_vol": 0.10795, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250905_0347", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-05", "context_summary": "Regime: bull. SPY trailing return: +8.0%, annualized vol: 9.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=596.24, end=643.66, trailing_return=+7.95%\nAnnualized volatility: 9.81%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5800, t10y3m_spread=0.0100, breakeven_10y=2.3800, hy_oas=2.8400, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.5000, vix=15.3000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.95%\n Annualized volatility: 9.81%\n Macro: fed_funds=4.3300, vix=15.3\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.079523, "annualized_vol": 0.098118, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250418_0349", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bear", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-04-18", "context_summary": "Regime: bear. SPY trailing return: -13.4%, annualized vol: 19.4%. Allocation: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=601.03, end=520.44, trailing_return=-13.41%\nAnnualized volatility: 19.36%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.3020, unemployment=4.2000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5300, t10y3m_spread=0.0000, breakeven_10y=2.2300, hy_oas=4.0200, ig_oas=1.1100, ted_spread=0.0900, mortgage_30y=6.8300, vix=29.6500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bear; Allocations: equities: decrease, bonds: increase, commodities: neutral, real_estate: decrease, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -13.41%\n Annualized volatility: 19.36%\n Macro: fed_funds=4.3300, vix=29.6\n \u2192 Regime: bear\n\nAllocation rationale for bear regime:\n Equities: decrease ()\n Bonds: increase (defensive)\n Commodities: neutral ()\n Real_Estate: decrease ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "bear", "allocation_adjustments": {"equities": "decrease", "bonds": "increase", "commodities": "neutral", "real_estate": "decrease", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.134082, "annualized_vol": 0.193609, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250904_0351", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-04", "context_summary": "Regime: bull. SPY trailing return: +7.7%, annualized vol: 9.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=592.88, end=638.33, trailing_return=+7.66%\nAnnualized volatility: 9.70%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.6100, t10y3m_spread=0.0400, breakeven_10y=2.4000, hy_oas=2.8800, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.5600, vix=16.3500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.66%\n Annualized volatility: 9.70%\n Macro: fed_funds=4.3300, vix=16.4\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.076646, "annualized_vol": 0.097045, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250703_0353", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-03", "context_summary": "Regime: sideways. SPY trailing return: +23.4%, annualized vol: 16.7%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=498.66, end=615.23, trailing_return=+23.38%\nAnnualized volatility: 16.72%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5200, t10y3m_spread=-0.1100, breakeven_10y=2.3000, hy_oas=2.8800, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.7700, vix=16.6400\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +23.38%\n Annualized volatility: 16.72%\n Macro: fed_funds=4.3300, vix=16.6\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.233761, "annualized_vol": 0.167197, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251006_0354", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-06", "context_summary": "Regime: bull. SPY trailing return: +7.6%, annualized vol: 8.7%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=618.37, end=665.42, trailing_return=+7.61%\nAnnualized volatility: 8.65%\nMacro indicators: fed_funds_rate=4.0900, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5500, t10y3m_spread=0.1000, breakeven_10y=2.3300, hy_oas=2.8000, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3400, vix=16.6500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.61%\n Annualized volatility: 8.65%\n Macro: fed_funds=4.0900, vix=16.6\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.076081, "annualized_vol": 0.086506, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250226_0356", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-26", "context_summary": "Regime: sideways. SPY trailing return: -0.4%, annualized vol: 12.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=588.29, end=585.74, trailing_return=-0.43%\nAnnualized volatility: 12.86%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2300, t10y3m_spread=0.0000, breakeven_10y=2.3800, hy_oas=2.8400, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.8500, vix=19.4300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -0.43%\n Annualized volatility: 12.86%\n Macro: fed_funds=4.3300, vix=19.4\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.004325, "annualized_vol": 0.128604, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250205_0357", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-05", "context_summary": "Regime: sideways. SPY trailing return: +2.2%, annualized vol: 13.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=580.63, end=593.18, trailing_return=+2.16%\nAnnualized volatility: 13.00%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3100, t10y3m_spread=0.1900, breakeven_10y=2.4400, hy_oas=2.7100, ig_oas=0.8200, ted_spread=0.0900, mortgage_30y=6.9500, vix=17.2100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.16%\n Annualized volatility: 13.00%\n Macro: fed_funds=4.3300, vix=17.2\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.021598, "annualized_vol": 0.129984, "has_text": true, "text_chars": 9044}} +{"id": "T7_all_20250103_0359", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-03", "context_summary": "Regime: sideways. SPY trailing return: +2.3%, annualized vol: 12.0%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=563.08, end=576.28, trailing_return=+2.34%\nAnnualized volatility: 12.04%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3200, t10y3m_spread=0.2100, breakeven_10y=2.3400, hy_oas=2.8800, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.9100, vix=17.9300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +2.34%\n Annualized volatility: 12.04%\n Macro: fed_funds=4.3300, vix=17.9\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.023444, "annualized_vol": 0.120438, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250723_0361", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-23", "context_summary": "Regime: bull. SPY trailing return: +14.5%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=544.40, end=623.57, trailing_return=+14.54%\nAnnualized volatility: 10.83%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5200, t10y3m_spread=-0.0600, breakeven_10y=2.3900, hy_oas=2.9000, ig_oas=0.8100, ted_spread=0.0900, mortgage_30y=6.7500, vix=16.5000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +14.54%\n Annualized volatility: 10.83%\n Macro: fed_funds=4.3300, vix=16.5\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.145429, "annualized_vol": 0.108287, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250211_0363", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-02-11", "context_summary": "Regime: sideways. SPY trailing return: +1.7%, annualized vol: 12.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=586.39, end=596.20, trailing_return=+1.67%\nAnnualized volatility: 12.45%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.6790, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2300, t10y3m_spread=0.1600, breakeven_10y=2.4400, hy_oas=2.6600, ig_oas=0.8400, ted_spread=0.0900, mortgage_30y=6.8900, vix=15.8100\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.67%\n Annualized volatility: 12.45%\n Macro: fed_funds=4.3300, vix=15.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.016729, "annualized_vol": 0.124536, "has_text": true, "text_chars": 9046}} +{"id": "T7_all_20250321_0365", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-21", "context_summary": "Regime: sideways. SPY trailing return: -4.3%, annualized vol: 15.9%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=582.70, end=557.40, trailing_return=-4.34%\nAnnualized volatility: 15.92%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.2900, t10y3m_spread=-0.0900, breakeven_10y=2.3100, hy_oas=3.1700, ig_oas=0.9100, ted_spread=0.0900, mortgage_30y=6.6700, vix=19.8000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -4.34%\n Annualized volatility: 15.92%\n Macro: fed_funds=4.3300, vix=19.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.043407, "annualized_vol": 0.159179, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250110_0366", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-01-10", "context_summary": "Regime: sideways. SPY trailing return: +1.2%, annualized vol: 12.3%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=574.03, end=581.06, trailing_return=+1.22%\nAnnualized volatility: 12.31%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=318.9610, unemployment=4.0000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.4100, t10y3m_spread=0.3300, breakeven_10y=2.3900, hy_oas=2.8200, ig_oas=0.8300, ted_spread=0.0900, mortgage_30y=6.9300, vix=17.7000\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +1.22%\n Annualized volatility: 12.31%\n Macro: fed_funds=4.3300, vix=17.7\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.012243, "annualized_vol": 0.123143, "has_text": true, "text_chars": 9045}} +{"id": "T7_all_20250728_0367", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-07-28", "context_summary": "Regime: bull. SPY trailing return: +15.2%, annualized vol: 10.8%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=548.26, end=631.74, trailing_return=+15.23%\nAnnualized volatility: 10.83%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=322.1690, unemployment=4.3000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.4900, t10y3m_spread=-0.0200, breakeven_10y=2.4400, hy_oas=2.8400, ig_oas=0.7800, ted_spread=0.0900, mortgage_30y=6.7400, vix=14.9300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +15.23%\n Annualized volatility: 10.83%\n Macro: fed_funds=4.3300, vix=14.9\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.152277, "annualized_vol": 0.108325, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250611_0369", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-06-11", "context_summary": "Regime: sideways. SPY trailing return: +6.7%, annualized vol: 19.5%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=559.04, end=596.24, trailing_return=+6.66%\nAnnualized volatility: 19.50%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=321.4350, unemployment=4.1000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.4600, t10y3m_spread=0.0200, breakeven_10y=2.2900, hy_oas=3.1200, ig_oas=0.8700, ted_spread=0.0900, mortgage_30y=6.8500, vix=16.9500\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +6.66%\n Annualized volatility: 19.50%\n Macro: fed_funds=4.3300, vix=17.0\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": 0.066551, "annualized_vol": 0.195004, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250930_0371", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-09-30", "context_summary": "Regime: bull. SPY trailing return: +7.2%, annualized vol: 8.9%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=615.46, end=659.92, trailing_return=+7.22%\nAnnualized volatility: 8.87%\nMacro indicators: fed_funds_rate=4.0900, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24026.8340, t10y2y_spread=0.5200, t10y3m_spread=0.1100, breakeven_10y=2.3500, hy_oas=2.7400, ig_oas=0.7700, ted_spread=0.0900, mortgage_30y=6.3000, vix=16.1200\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +7.22%\n Annualized volatility: 8.87%\n Macro: fed_funds=4.0900, vix=16.1\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.072243, "annualized_vol": 0.088687, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250507_0372", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-05-07", "context_summary": "Regime: sideways. SPY trailing return: -7.3%, annualized vol: 21.2%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=596.20, end=552.47, trailing_return=-7.34%\nAnnualized volatility: 21.25%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=320.6200, unemployment=4.3000, gdp_growth_qoq=23770.9760, t10y2y_spread=0.5200, t10y3m_spread=-0.0300, breakeven_10y=2.2600, hy_oas=3.6600, ig_oas=1.0500, ted_spread=0.0900, mortgage_30y=6.7600, vix=24.7600\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -7.34%\n Annualized volatility: 21.25%\n Macro: fed_funds=4.3300, vix=24.8\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.073355, "annualized_vol": 0.212454, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20250325_0373", "template": "T7", "complexity": 4, "split": "test", "market_regime": "sideways", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-03-25", "context_summary": "Regime: sideways. SPY trailing return: -4.2%, annualized vol: 16.1%. Allocation: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase.", "question": "Market indicator: SPY\nPrice history (60 days): start=592.70, end=567.57, trailing_return=-4.24%\nAnnualized volatility: 16.10%\nMacro indicators: fed_funds_rate=4.3300, cpi_yoy=319.7850, unemployment=4.2000, gdp_growth_qoq=23548.2100, t10y2y_spread=0.3000, t10y3m_spread=0.0100, breakeven_10y=2.3600, hy_oas=3.0500, ig_oas=0.9000, ted_spread=0.0900, mortgage_30y=6.6700, vix=17.4800\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: sideways; Allocations: equities: neutral, bonds: neutral, commodities: neutral, real_estate: neutral, cryptocurrency: decrease, cash: increase", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: -4.24%\n Annualized volatility: 16.10%\n Macro: fed_funds=4.3300, vix=17.5\n \u2192 Regime: sideways\n\nAllocation rationale for sideways regime:\n Equities: neutral ()\n Bonds: neutral ()\n Commodities: neutral ()\n Real_Estate: neutral ()\n Cryptocurrency: decrease ()\n Cash: increase (defensive)", "metadata": {"detected_regime": "sideways", "allocation_adjustments": {"equities": "neutral", "bonds": "neutral", "commodities": "neutral", "real_estate": "neutral", "cryptocurrency": "decrease", "cash": "increase"}, "trailing_return": -0.042396, "annualized_vol": 0.161009, "has_text": true, "text_chars": 3020}} +{"id": "T7_all_20251021_0374", "template": "T7", "complexity": 4, "split": "test", "market_regime": "bull", "asset_class": "all", "assets": ["SPY"], "decision_date": "2025-10-21", "context_summary": "Regime: bull. SPY trailing return: +5.7%, annualized vol: 11.1%. Allocation: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease.", "question": "Market indicator: SPY\nPrice history (60 days): start=631.58, end=667.50, trailing_return=+5.69%\nAnnualized volatility: 11.06%\nMacro indicators: fed_funds_rate=4.1100, cpi_yoy=324.2450, unemployment=4.4000, gdp_growth_qoq=24055.7490, t10y2y_spread=0.5400, t10y3m_spread=0.0300, breakeven_10y=2.2600, hy_oas=2.9900, ig_oas=0.7900, ted_spread=0.0900, mortgage_30y=6.2700, vix=18.2300\n\nPart A: Identify the current market regime. Choose from: bull, bear, sideways, crisis.\n\nPart B: For each of the six asset classes (Equities, Bonds, Commodities, Real Estate, Cryptocurrency, Cash), recommend whether to increase, decrease, or maintain the current allocation.", "answer": "Regime: bull; Allocations: equities: increase, bonds: decrease, commodities: neutral, real_estate: increase, cryptocurrency: increase, cash: decrease", "answer_numeric": null, "explanation": "Regime classification:\n Trailing 60-day return: +5.69%\n Annualized volatility: 11.06%\n Macro: fed_funds=4.1100, vix=18.2\n \u2192 Regime: bull\n\nAllocation rationale for bull regime:\n Equities: increase (risk-on)\n Bonds: decrease ()\n Commodities: neutral ()\n Real_Estate: increase (risk-on)\n Cryptocurrency: increase (risk-on)\n Cash: decrease ()", "metadata": {"detected_regime": "bull", "allocation_adjustments": {"equities": "increase", "bonds": "decrease", "commodities": "neutral", "real_estate": "increase", "cryptocurrency": "increase", "cash": "decrease"}, "trailing_return": 0.056867, "annualized_vol": 0.110642, "has_text": true, "text_chars": 3020}}