id stringlengths 20 20 | template stringclasses 6
values | complexity int64 1 3 | split stringclasses 1
value | market_regime stringclasses 1
value | asset_class stringclasses 1
value | assets listlengths 1 4 | decision_date timestamp[s]date 2015-02-05 00:00:00 2022-12-28 00:00:00 | context_summary stringlengths 52 153 | question stringlengths 245 9.63k | answer stringlengths 2 63 | answer_numeric float64 -3.07 9.2 | explanation stringlengths 100 240 | metadata unknown |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
T3_all_20220707_0169 | T3 | 1 | train | sideways | all | [
"DOT-USD"
] | 2022-07-07T00:00:00 | DOT-USD: 60-day history, VaR(99%)=-0.1923, max drawdown threshold=10%. | Asset: DOT-USD
Daily returns (past 60 days): mean=-0.0086, std=0.0701, worst_day=-0.1989
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-07-06]
Determine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constrai... | 0.5201 | 0.5201 | Step 1: Compute |VaR(99%)| from historical returns = 0.1923 (i.e., a 19.23% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1923 = 0.5201, capped at 1.0.
Maximum position size = 0.5201 (52.0% of portfolio). | {
"var_99": -0.192273,
"expected_loss": 0.192273,
"max_drawdown_threshold": 0.1,
"position_size": 0.5201,
"has_text": true,
"text_chars": 20
} |
T3_all_20180829_0172 | T3 | 1 | train | sideways | all | [
"XLB"
] | 2018-08-29T00:00:00 | XLB: 60-day history, VaR(99%)=-0.0176, max drawdown threshold=10%. | Asset: XLB
Daily returns (past 60 days): mean=0.0002, std=0.0087, worst_day=-0.0185
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2018-08-28] ["Here\u2019s What Blockchain Technology Means for IBM Stock InvestorPlace - Stock Market News, Stock Advice & Trading Tips IBM (... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0176 (i.e., a 1.76% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0176 = 5.6897, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.017575999999999998,
"expected_loss": 0.017575999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20210914_0177 | T3 | 1 | train | sideways | all | [
"DOT-USD"
] | 2021-09-14T00:00:00 | DOT-USD: 60-day history, VaR(99%)=-0.1369, max drawdown threshold=10%. | Asset: DOT-USD
Daily returns (past 60 days): mean=0.0185, std=0.0647, worst_day=-0.1890
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 0.7303 | 0.7303 | Step 1: Compute |VaR(99%)| from historical returns = 0.1369 (i.e., a 13.69% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1369 = 0.7303, capped at 1.0.
Maximum position size = 0.7303 (73.0% of portfolio). | {
"var_99": -0.136936,
"expected_loss": 0.136936,
"max_drawdown_threshold": 0.1,
"position_size": 0.7303000000000001,
"has_text": false,
"text_chars": 0
} |
T3_all_20170615_0182 | T3 | 1 | train | sideways | all | [
"BNDX"
] | 2017-06-15T00:00:00 | BNDX: 60-day history, VaR(99%)=-0.0022, max drawdown threshold=10%. | Asset: BNDX
Daily returns (past 60 days): mean=0.0003, std=0.0013, worst_day=-0.0024
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0022 (i.e., a 0.22% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0022 = 46.0446, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.002172,
"expected_loss": 0.002172,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20220110_0185 | T3 | 1 | train | sideways | all | [
"FXI"
] | 2022-01-10T00:00:00 | FXI: 60-day history, VaR(99%)=-0.0288, max drawdown threshold=10%. | Asset: FXI
Daily returns (past 60 days): mean=-0.0015, std=0.0154, worst_day=-0.0294
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-01-07] ["Tuya Officially Announces Support for Matter Smart Home Standard Tuya Smart (NYSE: TUYA), a leading IoT development platform s... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0288 (i.e., a 2.88% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0288 = 3.4677, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.028838,
"expected_loss": 0.028838,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220117_0188 | T3 | 1 | train | sideways | all | [
"IWM"
] | 2022-01-17T00:00:00 | IWM: 60-day history, VaR(99%)=-0.0355, max drawdown threshold=10%. | Asset: IWM
Daily returns (past 60 days): mean=-0.0009, std=0.0141, worst_day=-0.0371
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-01-14] ["3 Downtrodden Stocks to Sell Before It Gets Worse InvestorPlace - Stock Market News, Stock Advice & Trading Tips Downtrends ar... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0355 (i.e., a 3.55% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0355 = 2.8148, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.035526999999999996,
"expected_loss": 0.035526999999999996,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20210316_0193 | T3 | 1 | train | sideways | all | [
"XLI"
] | 2021-03-16T00:00:00 | XLI: 60-day history, VaR(99%)=-0.0229, max drawdown threshold=10%. | Asset: XLI
Daily returns (past 60 days): mean=0.0016, std=0.0110, worst_day=-0.0245
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-03-15] Cloud Computing's Trillion-Dollar Potential Cloud computing companies not only weathered the storm of the pandemic, they thrived.... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0229 (i.e., a 2.29% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0229 = 4.3660, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.022903999999999997,
"expected_loss": 0.022903999999999997,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20191203_0196 | T3 | 1 | train | sideways | all | [
"^VIX"
] | 2019-12-03T00:00:00 | ^VIX: 60-day history, VaR(99%)=-0.1172, max drawdown threshold=10%. | Asset: ^VIX
Daily returns (past 60 days): mean=-0.0001, std=0.0629, worst_day=-0.1202
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-12-02] ["What\u2019s worth streaming in December? \u2018The Mandalorian,\u2019 \u2018Mrs. Maisel,\u2019 \u2018The Witcher\u2019 and mo... | 0.8530 | 0.853 | Step 1: Compute |VaR(99%)| from historical returns = 0.1172 (i.e., a 11.72% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1172 = 0.8530, capped at 1.0.
Maximum position size = 0.8530 (85.3% of portfolio). | {
"var_99": -0.11723499999999999,
"expected_loss": 0.11723499999999999,
"max_drawdown_threshold": 0.1,
"position_size": 0.853,
"has_text": true,
"text_chars": 3020
} |
T3_all_20201006_0201 | T3 | 1 | train | sideways | all | [
"DOT-USD"
] | 2020-10-06T00:00:00 | DOT-USD: 46-day history, VaR(99%)=-0.1651, max drawdown threshold=10%. | Asset: DOT-USD
Daily returns (past 46 days): mean=0.0072, std=0.0872, worst_day=-0.1989
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 0.6058 | 0.6058 | Step 1: Compute |VaR(99%)| from historical returns = 0.1651 (i.e., a 16.51% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1651 = 0.6058, capped at 1.0.
Maximum position size = 0.6058 (60.6% of portfolio). | {
"var_99": -0.165067,
"expected_loss": 0.165067,
"max_drawdown_threshold": 0.1,
"position_size": 0.6058,
"has_text": false,
"text_chars": 0
} |
T3_all_20191114_0204 | T3 | 1 | train | sideways | all | [
"MATIC-USD"
] | 2019-11-14T00:00:00 | MATIC-USD: 60-day history, VaR(99%)=-0.0917, max drawdown threshold=10%. | Asset: MATIC-USD
Daily returns (past 60 days): mean=0.0034, std=0.0489, worst_day=-0.0959
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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 a... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0917 (i.e., a 9.17% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0917 = 1.0908, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.09167499999999999,
"expected_loss": 0.09167499999999999,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20160719_0209 | T3 | 1 | train | sideways | all | [
"FXI"
] | 2016-07-19T00:00:00 | FXI: 60-day history, VaR(99%)=-0.0341, max drawdown threshold=10%. | Asset: FXI
Daily returns (past 60 days): mean=0.0010, std=0.0144, worst_day=-0.0438
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2016-07-18] ["Corporate profits brace for fourth straight losing quarter Investors will look for signs that economy not in negative territory... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0341 (i.e., a 3.41% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0341 = 2.9345, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.034078,
"expected_loss": 0.034078,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20170104_0212 | T3 | 1 | train | sideways | all | [
"XLV"
] | 2017-01-04T00:00:00 | XLV: 60-day history, VaR(99%)=-0.0233, max drawdown threshold=10%. | Asset: XLV
Daily returns (past 60 days): mean=-0.0006, std=0.0089, worst_day=-0.0254
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2017-01-03] ["Seven highly valued tech startups that could IPO in 2017 Unicorns like Snap and Spotify are expected to reach Wall Street in 2... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0233 (i.e., a 2.33% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0233 = 4.2874, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.023323999999999998,
"expected_loss": 0.023323999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20171215_0217 | T3 | 1 | train | sideways | all | [
"IVV"
] | 2017-12-15T00:00:00 | IVV: 60-day history, VaR(99%)=-0.0050, max drawdown threshold=10%. | Asset: IVV
Daily returns (past 60 days): mean=0.0010, std=0.0034, worst_day=-0.0054
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2017-12-14] ["Net neutrality repeal gets the internet all wrong, founders claim Signatories calling for FCC to wait on open-internet repeal i... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0050 (i.e., a 0.50% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0050 = 20.0467, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.004987999999999999,
"expected_loss": 0.004987999999999999,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20200819_0224 | T3 | 1 | train | sideways | all | [
"SCHP"
] | 2020-08-19T00:00:00 | SCHP: 60-day history, VaR(99%)=-0.0039, max drawdown threshold=10%. | Asset: SCHP
Daily returns (past 60 days): mean=0.0007, std=0.0021, worst_day=-0.0046
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0039 (i.e., a 0.39% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0039 = 25.9272, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.0038569999999999998,
"expected_loss": 0.0038569999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20211015_0227 | T3 | 1 | train | sideways | all | [
"MATIC-USD"
] | 2021-10-15T00:00:00 | MATIC-USD: 60-day history, VaR(99%)=-0.1567, max drawdown threshold=10%. | Asset: MATIC-USD
Daily returns (past 60 days): mean=-0.0004, std=0.0653, worst_day=-0.1762
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-10-12]
Determine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown cons... | 0.6382 | 0.6382 | Step 1: Compute |VaR(99%)| from historical returns = 0.1567 (i.e., a 15.67% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1567 = 0.6382, capped at 1.0.
Maximum position size = 0.6382 (63.8% of portfolio). | {
"var_99": -0.156693,
"expected_loss": 0.156693,
"max_drawdown_threshold": 0.1,
"position_size": 0.6382,
"has_text": true,
"text_chars": 20
} |
T3_all_20211018_0230 | T3 | 1 | train | sideways | all | [
"DOT-USD"
] | 2021-10-18T00:00:00 | DOT-USD: 60-day history, VaR(99%)=-0.1779, max drawdown threshold=10%. | Asset: DOT-USD
Daily returns (past 60 days): mean=0.0122, std=0.0757, worst_day=-0.1890
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-10-15]
Determine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constrain... | 0.5623 | 0.5623 | Step 1: Compute |VaR(99%)| from historical returns = 0.1779 (i.e., a 17.79% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1779 = 0.5623, capped at 1.0.
Maximum position size = 0.5623 (56.2% of portfolio). | {
"var_99": -0.17785499999999999,
"expected_loss": 0.17785499999999999,
"max_drawdown_threshold": 0.1,
"position_size": 0.5623,
"has_text": true,
"text_chars": 20
} |
T3_all_20160129_0233 | T3 | 1 | train | sideways | all | [
"WEAT"
] | 2016-01-29T00:00:00 | WEAT: 60-day history, VaR(99%)=-0.0265, max drawdown threshold=10%. | Asset: WEAT
Daily returns (past 60 days): mean=-0.0013, std=0.0118, worst_day=-0.0346
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to WEAT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0265 (i.e., a 2.65% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0265 = 3.7795, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.026459,
"expected_loss": 0.026459,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20190104_0238 | T3 | 1 | train | sideways | all | [
"VLUE"
] | 2019-01-04T00:00:00 | VLUE: 60-day history, VaR(99%)=-0.0356, max drawdown threshold=10%. | Asset: VLUE
Daily returns (past 60 days): mean=-0.0033, std=0.0146, worst_day=-0.0356
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-01-03] ["Apple cuts holiday sales forecast on iPhone and China weakness, stock falls 8% CEO Tim Cook cites weaker-than-expected iPhone... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0356 (i.e., a 3.56% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0356 = 2.8129, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.035551,
"expected_loss": 0.035551,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20221028_0242 | T3 | 1 | train | sideways | all | [
"XLK"
] | 2022-10-28T00:00:00 | XLK: 60-day history, VaR(99%)=-0.0427, max drawdown threshold=10%. | Asset: XLK
Daily returns (past 60 days): mean=-0.0025, std=0.0180, worst_day=-0.0427
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-10-27] ["Apple (AAPL) Q4 2022 Earnings Call Transcript Image source: The Motley Fool. Apple (NASDAQ: AAPL) Q4 2022 Earnings Call Oct 27... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0427 (i.e., a 4.27% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0427 = 2.3410, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.042717,
"expected_loss": 0.042717,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20191224_0247 | T3 | 1 | train | sideways | all | [
"LINK-USD"
] | 2019-12-24T00:00:00 | LINK-USD: 60-day history, VaR(99%)=-0.0928, max drawdown threshold=10%. | Asset: LINK-USD
Daily returns (past 60 days): mean=-0.0057, std=0.0370, worst_day=-0.1137
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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 an... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0928 (i.e., a 9.28% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0928 = 1.0776, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.09279899999999999,
"expected_loss": 0.09279899999999999,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20200729_0250 | T3 | 1 | train | sideways | all | [
"XRP-USD"
] | 2020-07-29T00:00:00 | XRP-USD: 60-day history, VaR(99%)=-0.0468, max drawdown threshold=10%. | Asset: XRP-USD
Daily returns (past 60 days): mean=0.0028, std=0.0251, worst_day=-0.0629
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0468 (i.e., a 4.68% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0468 = 2.1377, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.04678,
"expected_loss": 0.04678,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20210705_0253 | T3 | 1 | train | sideways | all | [
"BTC-USD"
] | 2021-07-05T00:00:00 | BTC-USD: 60-day history, VaR(99%)=-0.1328, max drawdown threshold=10%. | Asset: BTC-USD
Daily returns (past 60 days): mean=-0.0066, std=0.0536, worst_day=-0.1328
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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 ... | 0.7528 | 0.7528 | Step 1: Compute |VaR(99%)| from historical returns = 0.1328 (i.e., a 13.28% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1328 = 0.7528, capped at 1.0.
Maximum position size = 0.7528 (75.3% of portfolio). | {
"var_99": -0.13283699999999998,
"expected_loss": 0.13283699999999998,
"max_drawdown_threshold": 0.1,
"position_size": 0.7528,
"has_text": false,
"text_chars": 0
} |
T3_all_20151008_0256 | T3 | 1 | train | sideways | all | [
"XLY"
] | 2015-10-08T00:00:00 | XLY: 60-day history, VaR(99%)=-0.0351, max drawdown threshold=10%. | Asset: XLY
Daily returns (past 60 days): mean=-0.0004, std=0.0136, worst_day=-0.0388
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2015-10-07] ["Fast Money Picks For October 7", "Susquehanna Maintains Positive on Adobe Systems, Raises PT to $97.00", "Benzinga's Top #PreM... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0351 (i.e., a 3.51% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0351 = 2.8476, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.035116999999999995,
"expected_loss": 0.035116999999999995,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20171201_0259 | T3 | 1 | train | sideways | all | [
"VEA"
] | 2017-12-01T00:00:00 | VEA: 60-day history, VaR(99%)=-0.0065, max drawdown threshold=10%. | Asset: VEA
Daily returns (past 60 days): mean=0.0008, std=0.0039, worst_day=-0.0068
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2017-11-30] ["High-flying tech stocks fall back toward earth, chip makers suffer worst day of year Tech stocks lead S&P 500 to a loss despite... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0065 (i.e., a 0.65% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0065 = 15.4266, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.006482,
"expected_loss": 0.006482,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20170406_0261 | T3 | 1 | train | sideways | all | [
"XLB"
] | 2017-04-06T00:00:00 | XLB: 60-day history, VaR(99%)=-0.0133, max drawdown threshold=10%. | Asset: XLB
Daily returns (past 60 days): mean=0.0006, std=0.0071, worst_day=-0.0169
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2017-04-05] ["ADP Posts Another Blowout Jobs Number to 263K Wednesday, April 5, 2017 For the second straight month, Automated Data Processing... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0133 (i.e., a 1.33% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0133 = 7.5411, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.013261,
"expected_loss": 0.013261,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190314_0268 | T3 | 1 | train | sideways | all | [
"XLV"
] | 2019-03-14T00:00:00 | XLV: 60-day history, VaR(99%)=-0.0264, max drawdown threshold=10%. | Asset: XLV
Daily returns (past 60 days): mean=-0.0002, std=0.0115, worst_day=-0.0294
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-03-13] ["How your internet surfing could make you money in the coming blockchain revolution Decentralized internet will give people onl... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0264 (i.e., a 2.64% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0264 = 3.7926, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.026366999999999998,
"expected_loss": 0.026366999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220315_0271 | T3 | 1 | train | sideways | all | [
"XLU"
] | 2022-03-15T00:00:00 | XLU: 60-day history, VaR(99%)=-0.0206, max drawdown threshold=10%. | Asset: XLU
Daily returns (past 60 days): mean=-0.0000, std=0.0101, worst_day=-0.0256
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-03-14] ["Foxconn closes Shenzhen factories after fresh COVID outbreak Foxconn and Unimicron have announced temporary shutdowns to deal ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0206 (i.e., a 2.06% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0206 = 4.8571, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.020589,
"expected_loss": 0.020589,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190117_0274 | T3 | 1 | train | sideways | all | [
"ETH-USD"
] | 2019-01-17T00:00:00 | ETH-USD: 60-day history, VaR(99%)=-0.1514, max drawdown threshold=10%. | Asset: ETH-USD
Daily returns (past 60 days): mean=-0.0037, std=0.0686, worst_day=-0.1575
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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 ... | 0.6607 | 0.6607 | Step 1: Compute |VaR(99%)| from historical returns = 0.1514 (i.e., a 15.14% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1514 = 0.6607, capped at 1.0.
Maximum position size = 0.6607 (66.1% of portfolio). | {
"var_99": -0.151353,
"expected_loss": 0.151353,
"max_drawdown_threshold": 0.1,
"position_size": 0.6607000000000001,
"has_text": false,
"text_chars": 0
} |
T3_all_20160505_0277 | T3 | 1 | train | sideways | all | [
"EFA"
] | 2016-05-05T00:00:00 | EFA: 60-day history, VaR(99%)=-0.0179, max drawdown threshold=10%. | Asset: EFA
Daily returns (past 60 days): mean=0.0014, std=0.0110, worst_day=-0.0199
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2016-05-04] ["Fitbit wins ruling in Jawbone patent dispute Patents invalidated, but trade-secret claims may continue A fight between two of t... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0179 (i.e., a 1.79% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0179 = 5.5775, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.017929,
"expected_loss": 0.017929,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20221214_0284 | T3 | 1 | train | sideways | all | [
"XRP-USD"
] | 2022-12-14T00:00:00 | XRP-USD: 60-day history, VaR(99%)=-0.1492, max drawdown threshold=10%. | Asset: XRP-USD
Daily returns (past 60 days): mean=-0.0024, std=0.0488, worst_day=-0.1798
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-12-13]
Determine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constrai... | 0.6701 | 0.6701 | Step 1: Compute |VaR(99%)| from historical returns = 0.1492 (i.e., a 14.92% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1492 = 0.6701, capped at 1.0.
Maximum position size = 0.6701 (67.0% of portfolio). | {
"var_99": -0.14923799999999998,
"expected_loss": 0.14923799999999998,
"max_drawdown_threshold": 0.1,
"position_size": 0.6701,
"has_text": true,
"text_chars": 20
} |
T3_all_20170824_0287 | T3 | 1 | train | sideways | all | [
"XLI"
] | 2017-08-24T00:00:00 | XLI: 60-day history, VaR(99%)=-0.0147, max drawdown threshold=10%. | Asset: XLI
Daily returns (past 60 days): mean=0.0001, std=0.0057, worst_day=-0.0175
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2017-08-23] ["Apple\u2019s $1 billion TV move pits company against Spotify, not Netflix Apple\u2019s investment in producing and acquiring TV... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0147 (i.e., a 1.47% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0147 = 6.8054, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.014693999999999999,
"expected_loss": 0.014693999999999999,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20170301_0294 | T3 | 1 | train | sideways | all | [
"HYG"
] | 2017-03-01T00:00:00 | HYG: 60-day history, VaR(99%)=-0.0050, max drawdown threshold=10%. | Asset: HYG
Daily returns (past 60 days): mean=0.0007, std=0.0020, worst_day=-0.0075
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to HYG, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0050 (i.e., a 0.50% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0050 = 20.1203, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.0049700000000000005,
"expected_loss": 0.0049700000000000005,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20200217_0297 | T3 | 1 | train | sideways | all | [
"QQQ"
] | 2020-02-17T00:00:00 | QQQ: 60-day history, VaR(99%)=-0.0180, max drawdown threshold=10%. | Asset: QQQ
Daily returns (past 60 days): mean=0.0024, std=0.0077, worst_day=-0.0209
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-02-14] ["Applied Materials (AMAT): Strong Industry, Solid Earnings Estimate Revisions", "Tiger Management Buys Amazon.com Inc, NXP Semic... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0180 (i.e., a 1.80% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0180 = 5.5590, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.017988999999999998,
"expected_loss": 0.017988999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20210512_0300 | T3 | 1 | train | sideways | all | [
"XLU"
] | 2021-05-12T00:00:00 | XLU: 60-day history, VaR(99%)=-0.0191, max drawdown threshold=10%. | Asset: XLU
Daily returns (past 60 days): mean=0.0010, std=0.0097, worst_day=-0.0197
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-05-11] ["2 Stocks to Invest in Virtual and Augmented Reality Augmented reality (AR) and virtual reality (VR) promise to change the world... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0191 (i.e., a 1.91% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0191 = 5.2334, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.019108,
"expected_loss": 0.019108,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20201013_0303 | T3 | 1 | train | sideways | all | [
"LINK-USD"
] | 2020-10-13T00:00:00 | LINK-USD: 60-day history, VaR(99%)=-0.1681, max drawdown threshold=10%. | Asset: LINK-USD
Daily returns (past 60 days): mean=-0.0059, std=0.0746, worst_day=-0.1934
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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 an... | 0.5948 | 0.5948 | Step 1: Compute |VaR(99%)| from historical returns = 0.1681 (i.e., a 16.81% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1681 = 0.5948, capped at 1.0.
Maximum position size = 0.5948 (59.5% of portfolio). | {
"var_99": -0.168134,
"expected_loss": 0.168134,
"max_drawdown_threshold": 0.1,
"position_size": 0.5948,
"has_text": false,
"text_chars": 0
} |
T3_all_20210309_0306 | T3 | 1 | train | sideways | all | [
"LINK-USD"
] | 2021-03-09T00:00:00 | LINK-USD: 60-day history, VaR(99%)=-0.1669, max drawdown threshold=10%. | Asset: LINK-USD
Daily returns (past 60 days): mean=0.0145, std=0.0800, worst_day=-0.1817
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 0.5990 | 0.599 | Step 1: Compute |VaR(99%)| from historical returns = 0.1669 (i.e., a 16.69% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1669 = 0.5990, capped at 1.0.
Maximum position size = 0.5990 (59.9% of portfolio). | {
"var_99": -0.16694299999999998,
"expected_loss": 0.16694299999999998,
"max_drawdown_threshold": 0.1,
"position_size": 0.599,
"has_text": false,
"text_chars": 0
} |
T3_all_20190211_0309 | T3 | 1 | train | sideways | all | [
"VLUE"
] | 2019-02-11T00:00:00 | VLUE: 60-day history, VaR(99%)=-0.0302, max drawdown threshold=10%. | Asset: VLUE
Daily returns (past 60 days): mean=-0.0012, std=0.0132, worst_day=-0.0356
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-02-08] ["If you own Apple, Amazon, Facebook or AMD, look out below Those shares have been bid up by the average investor, but buying c... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0302 (i.e., a 3.02% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0302 = 3.3154, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.030161999999999998,
"expected_loss": 0.030161999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190201_0312 | T3 | 1 | train | sideways | all | [
"EEM"
] | 2019-02-01T00:00:00 | EEM: 60-day history, VaR(99%)=-0.0236, max drawdown threshold=10%. | Asset: EEM
Daily returns (past 60 days): mean=0.0013, std=0.0134, worst_day=-0.0263
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-01-31] ["Apple may soup up cameras, boost AR capabilities in new iPhones: report With iPhone growth slowing, Apple Inc. hopes to reboot ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0236 (i.e., a 2.36% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0236 = 4.2306, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.023637,
"expected_loss": 0.023637,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20210907_0317 | T3 | 1 | train | sideways | all | [
"QQQ"
] | 2021-09-07T00:00:00 | QQQ: 60-day history, VaR(99%)=-0.0102, max drawdown threshold=10%. | Asset: QQQ
Daily returns (past 60 days): mean=0.0019, std=0.0064, worst_day=-0.0111
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-09-03] ["Zip acquisition of Payflex means Africa is ripe for BNPL disruption Australian buy now, pay later (BNPL) company Zip this week ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0102 (i.e., a 1.02% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0102 = 9.7575, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.010249,
"expected_loss": 0.010249,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20180503_0322 | T3 | 1 | train | sideways | all | [
"ACWI"
] | 2018-05-03T00:00:00 | ACWI: 60-day history, VaR(99%)=-0.0268, max drawdown threshold=10%. | Asset: ACWI
Daily returns (past 60 days): mean=0.0001, std=0.0109, worst_day=-0.0309
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2018-05-02] ["AMD the underdog bites back, as Intel and Qualcomm struggle in their own ways The chip companies\u2019 quarterly reports show ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0268 (i.e., a 2.68% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0268 = 3.7271, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.026830999999999997,
"expected_loss": 0.026830999999999997,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220114_0325 | T3 | 1 | train | sideways | all | [
"ETH-USD"
] | 2022-01-14T00:00:00 | ETH-USD: 60-day history, VaR(99%)=-0.0789, max drawdown threshold=10%. | Asset: ETH-USD
Daily returns (past 60 days): mean=-0.0051, std=0.0390, worst_day=-0.0847
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-01-13]
Determine the maximum fraction of total portfolio capital that should be allocated to ETH-USD, given the drawdown constrai... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0789 (i.e., a 7.89% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0789 = 1.2675, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.07889399999999999,
"expected_loss": 0.07889399999999999,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 20
} |
T3_all_20200228_0328 | T3 | 1 | train | sideways | all | [
"XLP"
] | 2020-02-28T00:00:00 | XLP: 60-day history, VaR(99%)=-0.0240, max drawdown threshold=10%. | Asset: XLP
Daily returns (past 60 days): mean=-0.0004, std=0.0067, worst_day=-0.0250
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-02-27] ["Apple's stock drops 2.8% premarket, after rising 1.6% Wednesday to snap 4-day losing streak", "With Microsoft\u2019s coronavir... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0240 (i.e., a 2.40% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0240 = 4.1637, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.024017,
"expected_loss": 0.024017,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20221010_0331 | T3 | 1 | train | sideways | all | [
"XLF"
] | 2022-10-10T00:00:00 | XLF: 60-day history, VaR(99%)=-0.0332, max drawdown threshold=10%. | Asset: XLF
Daily returns (past 60 days): mean=0.0002, std=0.0154, worst_day=-0.0372
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-10-07] ["US STOCKS-Wall Street slips as jobs growth boosts rate hike bets For a Reuters live blog on U.S., UK and European stock markets... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0332 (i.e., a 3.32% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0332 = 3.0139, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.033179,
"expected_loss": 0.033179,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220418_0334 | T3 | 1 | train | sideways | all | [
"XLV"
] | 2022-04-18T00:00:00 | XLV: 60-day history, VaR(99%)=-0.0203, max drawdown threshold=10%. | Asset: XLV
Daily returns (past 60 days): mean=0.0008, std=0.0109, worst_day=-0.0206
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-04-14] ["Mercury Systems (MRCY) Clinches $14M SiP Assemblies Contract Mercury Systems MRCY has been awarded a $14-million contract by a ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0203 (i.e., a 2.03% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0203 = 4.9232, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.020312,
"expected_loss": 0.020312,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20201005_0337 | T3 | 1 | train | sideways | all | [
"SOL-USD"
] | 2020-10-05T00:00:00 | SOL-USD: 60-day history, VaR(99%)=-0.1932, max drawdown threshold=10%. | Asset: SOL-USD
Daily returns (past 60 days): mean=0.0093, std=0.1022, worst_day=-0.2453
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 0.5177 | 0.5177 | Step 1: Compute |VaR(99%)| from historical returns = 0.1932 (i.e., a 19.32% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1932 = 0.5177, capped at 1.0.
Maximum position size = 0.5177 (51.8% of portfolio). | {
"var_99": -0.193159,
"expected_loss": 0.193159,
"max_drawdown_threshold": 0.1,
"position_size": 0.5177,
"has_text": false,
"text_chars": 0
} |
T3_all_20170103_0342 | T3 | 1 | train | sideways | all | [
"XLI"
] | 2017-01-03T00:00:00 | XLI: 60-day history, VaR(99%)=-0.0115, max drawdown threshold=10%. | Asset: XLI
Daily returns (past 60 days): mean=0.0012, std=0.0073, worst_day=-0.0129
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2016-12-30] ["Which Wall Street Firm Made The Best Stock Picks Of 2016?", "Which Wall Street Firm Made The Best Stock Picks Of 2016?", "7 Sto... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0115 (i.e., a 1.15% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0115 = 8.6885, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.011509,
"expected_loss": 0.011509,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20151026_0344 | T3 | 1 | train | sideways | all | [
"BTC-USD"
] | 2015-10-26T00:00:00 | BTC-USD: 60-day history, VaR(99%)=-0.0268, max drawdown threshold=10%. | Asset: BTC-USD
Daily returns (past 60 days): mean=0.0039, std=0.0141, worst_day=-0.0332
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0268 (i.e., a 2.68% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0268 = 3.7310, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.026803,
"expected_loss": 0.026803,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20221202_0347 | T3 | 1 | train | sideways | all | [
"WEAT"
] | 2022-12-02T00:00:00 | WEAT: 60-day history, VaR(99%)=-0.0379, max drawdown threshold=10%. | Asset: WEAT
Daily returns (past 60 days): mean=-0.0014, std=0.0191, worst_day=-0.0405
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to WEAT, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0379 (i.e., a 3.79% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0379 = 2.6397, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.037883,
"expected_loss": 0.037883,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20181212_0350 | T3 | 1 | train | sideways | all | [
"DBB"
] | 2018-12-12T00:00:00 | DBB: 60-day history, VaR(99%)=-0.0202, max drawdown threshold=10%. | Asset: DBB
Daily returns (past 60 days): mean=0.0008, std=0.0107, worst_day=-0.0243
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to DBB, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0202 (i.e., a 2.02% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0202 = 4.9532, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.020189,
"expected_loss": 0.020189,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20201203_0353 | T3 | 1 | train | sideways | all | [
"SOL-USD"
] | 2020-12-03T00:00:00 | SOL-USD: 60-day history, VaR(99%)=-0.1697, max drawdown threshold=10%. | Asset: SOL-USD
Daily returns (past 60 days): mean=-0.0014, std=0.0743, worst_day=-0.1811
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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 ... | 0.5894 | 0.5894 | Step 1: Compute |VaR(99%)| from historical returns = 0.1697 (i.e., a 16.97% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1697 = 0.5894, capped at 1.0.
Maximum position size = 0.5894 (58.9% of portfolio). | {
"var_99": -0.169651,
"expected_loss": 0.169651,
"max_drawdown_threshold": 0.1,
"position_size": 0.5894,
"has_text": false,
"text_chars": 0
} |
T3_all_20210420_0356 | T3 | 1 | train | sideways | all | [
"^VIX"
] | 2021-04-20T00:00:00 | ^VIX: 60-day history, VaR(99%)=-0.1809, max drawdown threshold=10%. | Asset: ^VIX
Daily returns (past 60 days): mean=-0.0078, std=0.0828, worst_day=-0.1825
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-04-19] ["The Station: A chat with Scale AI's Alexandr Wang, the NYC scooter winners and TuSimple goes public The Station is a weekly n... | 0.5528 | 0.5528 | Step 1: Compute |VaR(99%)| from historical returns = 0.1809 (i.e., a 18.09% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1809 = 0.5528, capped at 1.0.
Maximum position size = 0.5528 (55.3% of portfolio). | {
"var_99": -0.18090699999999998,
"expected_loss": 0.18090699999999998,
"max_drawdown_threshold": 0.1,
"position_size": 0.5528000000000001,
"has_text": true,
"text_chars": 3020
} |
T3_all_20150409_0359 | T3 | 1 | train | sideways | all | [
"EWJ"
] | 2015-04-09T00:00:00 | EWJ: 60-day history, VaR(99%)=-0.0183, max drawdown threshold=10%. | Asset: EWJ
Daily returns (past 60 days): mean=0.0025, std=0.0084, worst_day=-0.0198
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2015-04-08] ["Jabil a Buy Even if Business With Apple Ebbs Raymond James is upgrading the electronics supplier to Outperform with a price tar... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0183 (i.e., a 1.83% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0183 = 5.4701, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.018281,
"expected_loss": 0.018281,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20160308_0364 | T3 | 1 | train | sideways | all | [
"SCHH"
] | 2016-03-08T00:00:00 | SCHH: 60-day history, VaR(99%)=-0.0289, max drawdown threshold=10%. | Asset: SCHH
Daily returns (past 60 days): mean=0.0005, std=0.0129, worst_day=-0.0299
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to SCHH, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0289 (i.e., a 2.89% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0289 = 3.4627, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.028879,
"expected_loss": 0.028879,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20221124_0367 | T3 | 1 | train | sideways | all | [
"FXI"
] | 2022-11-24T00:00:00 | FXI: 60-day history, VaR(99%)=-0.0434, max drawdown threshold=10%. | Asset: FXI
Daily returns (past 60 days): mean=-0.0019, std=0.0243, worst_day=-0.0438
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-11-23] ["Paramount (PARA) to Stream Top Gun: Maverick on Paramount+ Paramount Global PARA recently announced that it will be streaming ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0434 (i.e., a 4.34% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0434 = 2.3066, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.043354,
"expected_loss": 0.043354,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20180320_0369 | T3 | 1 | train | sideways | all | [
"ADA-USD"
] | 2018-03-20T00:00:00 | ADA-USD: 60-day history, VaR(99%)=-0.1586, max drawdown threshold=10%. | Asset: ADA-USD
Daily returns (past 60 days): mean=-0.0173, std=0.0775, worst_day=-0.1761
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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 ... | 0.6304 | 0.6304 | Step 1: Compute |VaR(99%)| from historical returns = 0.1586 (i.e., a 15.86% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1586 = 0.6304, capped at 1.0.
Maximum position size = 0.6304 (63.0% of portfolio). | {
"var_99": -0.158636,
"expected_loss": 0.158636,
"max_drawdown_threshold": 0.1,
"position_size": 0.6304000000000001,
"has_text": false,
"text_chars": 0
} |
T3_all_20150707_0372 | T3 | 1 | train | sideways | all | [
"XLF"
] | 2015-07-07T00:00:00 | XLF: 60-day history, VaR(99%)=-0.0199, max drawdown threshold=10%. | Asset: XLF
Daily returns (past 60 days): mean=0.0003, std=0.0078, worst_day=-0.0244
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2015-07-06] The Zacks Analyst Blog Highlights: Automatic Data Processing, Marriott Vacations Worldwide, Carnival and SkyWest - Press Releases... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0199 (i.e., a 1.99% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0199 = 5.0158, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.019937,
"expected_loss": 0.019937,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20221107_0375 | T3 | 1 | train | sideways | all | [
"BTC-USD"
] | 2022-11-07T00:00:00 | BTC-USD: 60-day history, VaR(99%)=-0.0588, max drawdown threshold=10%. | Asset: BTC-USD
Daily returns (past 60 days): mean=0.0017, std=0.0258, worst_day=-0.0927
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-11-06]
Determine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constrain... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0588 (i.e., a 5.88% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0588 = 1.7018, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.058762999999999996,
"expected_loss": 0.058762999999999996,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 20
} |
T3_all_20221026_0378 | T3 | 1 | train | sideways | all | [
"EEM"
] | 2022-10-26T00:00:00 | EEM: 60-day history, VaR(99%)=-0.0325, max drawdown threshold=10%. | Asset: EEM
Daily returns (past 60 days): mean=-0.0024, std=0.0131, worst_day=-0.0341
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-10-25] ["Why Is Everyone Talking About Apple? Apple's (NASDAQ: AAPL) stock has fallen about 10% since mid-September. The leading causes... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0325 (i.e., a 3.25% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0325 = 3.0808, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.032459,
"expected_loss": 0.032459,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220628_0383 | T3 | 1 | train | sideways | all | [
"VTI"
] | 2022-06-28T00:00:00 | VTI: 60-day history, VaR(99%)=-0.0335, max drawdown threshold=10%. | Asset: VTI
Daily returns (past 60 days): mean=-0.0025, std=0.0177, worst_day=-0.0335
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-06-27] ["CEOs will look past abortion bans, too Reuters Reuters NEW YORK (Reuters Breakingviews) - The demolition of the constitutional... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0335 (i.e., a 3.35% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0335 = 2.9889, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.033457,
"expected_loss": 0.033457,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20200904_0386 | T3 | 1 | train | sideways | all | [
"BNO"
] | 2020-09-04T00:00:00 | BNO: 60-day history, VaR(99%)=-0.0373, max drawdown threshold=10%. | Asset: BNO
Daily returns (past 60 days): mean=0.0023, std=0.0157, worst_day=-0.0504
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0373 (i.e., a 3.73% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0373 = 2.6815, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.037293,
"expected_loss": 0.037293,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20210922_0391 | T3 | 1 | train | sideways | all | [
"XLE"
] | 2021-09-22T00:00:00 | XLE: 60-day history, VaR(99%)=-0.0350, max drawdown threshold=10%. | Asset: XLE
Daily returns (past 60 days): mean=-0.0024, std=0.0184, worst_day=-0.0360
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-09-21] ["Over 2 Billion Devices Will be Shipped with a Dedicated Chipset for Ambient Sound or Natural Language Processing By 2026 Natur... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0350 (i.e., a 3.50% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0350 = 2.8547, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.035030000000000006,
"expected_loss": 0.035030000000000006,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20201027_0394 | T3 | 1 | train | sideways | all | [
"XLB"
] | 2020-10-27T00:00:00 | XLB: 60-day history, VaR(99%)=-0.0314, max drawdown threshold=10%. | Asset: XLB
Daily returns (past 60 days): mean=0.0012, std=0.0133, worst_day=-0.0337
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-10-26] ["Apple, Amazon, Boeing, Visa, Pfizer, and Other Stocks to Watch This Week Microsoft, Apple, Alphabet, Facebook, Amazon, AMD, Cat... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0314 (i.e., a 3.14% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0314 = 3.1835, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.031411999999999995,
"expected_loss": 0.031411999999999995,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190926_0397 | T3 | 1 | train | sideways | all | [
"BTC-USD"
] | 2019-09-26T00:00:00 | BTC-USD: 60-day history, VaR(99%)=-0.0924, max drawdown threshold=10%. | Asset: BTC-USD
Daily returns (past 60 days): mean=-0.0014, std=0.0310, worst_day=-0.1140
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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 ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0924 (i.e., a 9.24% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0924 = 1.0819, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.092432,
"expected_loss": 0.092432,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20150602_0400 | T3 | 1 | train | sideways | all | [
"CPER"
] | 2015-06-02T00:00:00 | CPER: 60-day history, VaR(99%)=-0.0297, max drawdown threshold=10%. | Asset: CPER
Daily returns (past 60 days): mean=-0.0000, std=0.0149, worst_day=-0.0313
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to CPER, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0297 (i.e., a 2.97% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0297 = 3.3726, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.029651,
"expected_loss": 0.029651,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20171009_0403 | T3 | 1 | train | sideways | all | [
"XLRE"
] | 2017-10-09T00:00:00 | XLRE: 60-day history, VaR(99%)=-0.0104, max drawdown threshold=10%. | Asset: XLRE
Daily returns (past 60 days): mean=0.0004, std=0.0057, worst_day=-0.0108
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2017-10-06] ["IYW, ADBE, CRM, CTSH: Large Outflows Detected at ETF Looking today at week-over-week shares outstanding changes among the univ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0104 (i.e., a 1.04% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0104 = 9.6220, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.010393,
"expected_loss": 0.010393,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220126_0408 | T3 | 1 | train | sideways | all | [
"XLE"
] | 2022-01-26T00:00:00 | XLE: 60-day history, VaR(99%)=-0.0403, max drawdown threshold=10%. | Asset: XLE
Daily returns (past 60 days): mean=0.0022, std=0.0174, worst_day=-0.0411
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-01-25] ["7 Best Technology Stocks to Buy After the Big Dip InvestorPlace - Stock Market News, Stock Advice & Trading Tips So far, 2022 i... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0403 (i.e., a 4.03% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0403 = 2.4800, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.040322,
"expected_loss": 0.040322,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20170207_0411 | T3 | 1 | train | sideways | all | [
"XLRE"
] | 2017-02-07T00:00:00 | XLRE: 60-day history, VaR(99%)=-0.0198, max drawdown threshold=10%. | Asset: XLRE
Daily returns (past 60 days): mean=0.0003, std=0.0093, worst_day=-0.0227
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2017-02-06] ["Apple, Google among nearly 100 tech firms fighting Trump\u2019s travel ban in court Companies claim president\u2019s immigrati... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0198 (i.e., a 1.98% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0198 = 5.0601, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.019762,
"expected_loss": 0.019762,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220721_0414 | T3 | 1 | train | sideways | all | [
"XLF"
] | 2022-07-21T00:00:00 | XLF: 60-day history, VaR(99%)=-0.0358, max drawdown threshold=10%. | Asset: XLF
Daily returns (past 60 days): mean=-0.0016, std=0.0175, worst_day=-0.0368
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-07-20] ["US STOCKS-Nasdaq rises on positive earnings signals as inflation concerns loom By Echo Wang July 20 (Reuters) - The tech-heavy... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0358 (i.e., a 3.58% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0358 = 2.7966, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.035758,
"expected_loss": 0.035758,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20221020_0417 | T3 | 1 | train | sideways | all | [
"ICSH"
] | 2022-10-20T00:00:00 | ICSH: 60-day history, VaR(99%)=-0.0006, max drawdown threshold=10%. | Asset: ICSH
Daily returns (past 60 days): mean=0.0001, std=0.0003, worst_day=-0.0006
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0006 (i.e., a 0.06% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0006 = 166.9237, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.0005989999999999999,
"expected_loss": 0.0005989999999999999,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20210810_0420 | T3 | 1 | train | sideways | all | [
"UNG"
] | 2021-08-10T00:00:00 | UNG: 60-day history, VaR(99%)=-0.0384, max drawdown threshold=10%. | Asset: UNG
Daily returns (past 60 days): mean=0.0045, std=0.0188, worst_day=-0.0432
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0384 (i.e., a 3.84% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0384 = 2.6027, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.038422,
"expected_loss": 0.038422,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20200612_0423 | T3 | 1 | train | sideways | all | [
"IVV"
] | 2020-06-12T00:00:00 | IVV: 60-day history, VaR(99%)=-0.0328, max drawdown threshold=10%. | Asset: IVV
Daily returns (past 60 days): mean=0.0016, std=0.0187, worst_day=-0.0328
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-06-11] ["Can the all-new Cadillac CT5 take on its European competitors? Review: It\u2019s meant to compete with European big boys like t... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0328 (i.e., a 3.28% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0328 = 3.0503, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.032784,
"expected_loss": 0.032784,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20200625_0430 | T3 | 1 | train | sideways | all | [
"MATIC-USD"
] | 2020-06-25T00:00:00 | MATIC-USD: 60-day history, VaR(99%)=-0.1267, max drawdown threshold=10%. | Asset: MATIC-USD
Daily returns (past 60 days): mean=0.0082, std=0.0595, worst_day=-0.1465
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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 a... | 0.7892 | 0.7892 | Step 1: Compute |VaR(99%)| from historical returns = 0.1267 (i.e., a 12.67% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1267 = 0.7892, capped at 1.0.
Maximum position size = 0.7892 (78.9% of portfolio). | {
"var_99": -0.126708,
"expected_loss": 0.126708,
"max_drawdown_threshold": 0.1,
"position_size": 0.7892,
"has_text": false,
"text_chars": 0
} |
T3_all_20221116_0432 | T3 | 1 | train | sideways | all | [
"DOT-USD"
] | 2022-11-16T00:00:00 | DOT-USD: 60-day history, VaR(99%)=-0.1259, max drawdown threshold=10%. | Asset: DOT-USD
Daily returns (past 60 days): mean=-0.0018, std=0.0397, worst_day=-0.1400
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-11-15]
Determine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constrai... | 0.7942 | 0.7942 | Step 1: Compute |VaR(99%)| from historical returns = 0.1259 (i.e., a 12.59% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1259 = 0.7942, capped at 1.0.
Maximum position size = 0.7942 (79.4% of portfolio). | {
"var_99": -0.125919,
"expected_loss": 0.125919,
"max_drawdown_threshold": 0.1,
"position_size": 0.7942,
"has_text": true,
"text_chars": 20
} |
T3_all_20210217_0435 | T3 | 1 | train | sideways | all | [
"LINK-USD"
] | 2021-02-17T00:00:00 | LINK-USD: 60-day history, VaR(99%)=-0.1547, max drawdown threshold=10%. | Asset: LINK-USD
Daily returns (past 60 days): mean=0.0175, std=0.0800, worst_day=-0.1567
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 0.6463 | 0.6463 | Step 1: Compute |VaR(99%)| from historical returns = 0.1547 (i.e., a 15.47% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1547 = 0.6463, capped at 1.0.
Maximum position size = 0.6463 (64.6% of portfolio). | {
"var_99": -0.154738,
"expected_loss": 0.154738,
"max_drawdown_threshold": 0.1,
"position_size": 0.6463,
"has_text": false,
"text_chars": 0
} |
T3_all_20200128_0438 | T3 | 1 | train | sideways | all | [
"XRP-USD"
] | 2020-01-28T00:00:00 | XRP-USD: 60-day history, VaR(99%)=-0.0773, max drawdown threshold=10%. | Asset: XRP-USD
Daily returns (past 60 days): mean=0.0011, std=0.0344, worst_day=-0.1135
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0773 (i.e., a 7.73% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0773 = 1.2945, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.07725000000000001,
"expected_loss": 0.07725000000000001,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20220809_0441 | T3 | 1 | train | sideways | all | [
"XLY"
] | 2022-08-09T00:00:00 | XLY: 60-day history, VaR(99%)=-0.0388, max drawdown threshold=10%. | Asset: XLY
Daily returns (past 60 days): mean=0.0025, std=0.0219, worst_day=-0.0388
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-08-08] ["US STOCKS-Wall St set for higher open after selloff on jobs data By Bansari Mayur Kamdar and Aniruddha Ghosh Aug 8 (Reuters) - ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0388 (i.e., a 3.88% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0388 = 2.5763, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.038815999999999996,
"expected_loss": 0.038815999999999996,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20151221_0444 | T3 | 1 | train | sideways | all | [
"USMV"
] | 2015-12-21T00:00:00 | USMV: 60-day history, VaR(99%)=-0.0168, max drawdown threshold=10%. | Asset: USMV
Daily returns (past 60 days): mean=0.0006, std=0.0083, worst_day=-0.0203
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2015-12-18] Adobe (ADBE) Attains a New 52-Week High on Solid Earnings Shares of Adobe Systems Inc.ADBE attained a new 52-week high of $96.42... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0168 (i.e., a 1.68% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0168 = 5.9466, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.016815999999999998,
"expected_loss": 0.016815999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20191112_0449 | T3 | 1 | train | sideways | all | [
"HYG"
] | 2019-11-12T00:00:00 | HYG: 60-day history, VaR(99%)=-0.0051, max drawdown threshold=10%. | Asset: HYG
Daily returns (past 60 days): mean=0.0003, std=0.0022, worst_day=-0.0059
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to HYG, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0051 (i.e., a 0.51% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0051 = 19.5016, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.005128,
"expected_loss": 0.005128,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20191231_0453 | T3 | 1 | train | sideways | all | [
"QQQ"
] | 2019-12-31T00:00:00 | QQQ: 60-day history, VaR(99%)=-0.0123, max drawdown threshold=10%. | Asset: QQQ
Daily returns (past 60 days): mean=0.0022, std=0.0064, worst_day=-0.0151
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-12-30] Is North America Contribution To Amazon's Total Revenue 60%, 70%, Or 80%? Amazon‘s (NASDAQ:AMZN) North America business, consisti... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0123 (i.e., a 1.23% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0123 = 8.1560, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.012261,
"expected_loss": 0.012261,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190702_0456 | T3 | 1 | train | sideways | all | [
"ETH-USD"
] | 2019-07-02T00:00:00 | ETH-USD: 60-day history, VaR(99%)=-0.1059, max drawdown threshold=10%. | Asset: ETH-USD
Daily returns (past 60 days): mean=0.0112, std=0.0501, worst_day=-0.1262
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 0.9447 | 0.9447 | Step 1: Compute |VaR(99%)| from historical returns = 0.1059 (i.e., a 10.59% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1059 = 0.9447, capped at 1.0.
Maximum position size = 0.9447 (94.5% of portfolio). | {
"var_99": -0.10585399999999999,
"expected_loss": 0.10585399999999999,
"max_drawdown_threshold": 0.1,
"position_size": 0.9447000000000001,
"has_text": false,
"text_chars": 0
} |
T3_all_20200521_0459 | T3 | 1 | train | sideways | all | [
"ACWI"
] | 2020-05-21T00:00:00 | ACWI: 60-day history, VaR(99%)=-0.0309, max drawdown threshold=10%. | Asset: ACWI
Daily returns (past 60 days): mean=-0.0006, std=0.0210, worst_day=-0.0309
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-05-20] ["Earnings Scheduled For May 20, 2020", "Analog Devices Q2 Adj. EPS $1.080 Beats $1.040 Estimate, Sales $1.317B Miss $1.330B Es... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0309 (i.e., a 3.09% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0309 = 3.2314, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.030947,
"expected_loss": 0.030947,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20160729_0461 | T3 | 1 | train | sideways | all | [
"QQQ"
] | 2016-07-29T00:00:00 | QQQ: 60-day history, VaR(99%)=-0.0282, max drawdown threshold=10%. | Asset: QQQ
Daily returns (past 60 days): mean=0.0015, std=0.0097, worst_day=-0.0399
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2016-07-28] ["3M Stock Seen Edging Up to $186 Second-quarter margins expanded by about 50 basis points year-over-year, and should accelerate ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0282 (i.e., a 2.82% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0282 = 3.5470, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.028193,
"expected_loss": 0.028193,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190111_0464 | T3 | 1 | train | sideways | all | [
"XLRE"
] | 2019-01-11T00:00:00 | XLRE: 60-day history, VaR(99%)=-0.0375, max drawdown threshold=10%. | Asset: XLRE
Daily returns (past 60 days): mean=0.0008, std=0.0136, worst_day=-0.0375
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-01-10] ["Apple's stock slips 0.7% premarket, after rising 3.6% the past 2 sessions", "The stock market is too damaged for a sustained r... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0375 (i.e., a 3.75% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0375 = 2.6646, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.037529,
"expected_loss": 0.037529,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20210203_0467 | T3 | 1 | train | sideways | all | [
"XHB"
] | 2021-02-03T00:00:00 | XHB: 60-day history, VaR(99%)=-0.0284, max drawdown threshold=10%. | Asset: XHB
Daily returns (past 60 days): mean=0.0019, std=0.0138, worst_day=-0.0411
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0284 (i.e., a 2.84% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0284 = 3.5263, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.028359,
"expected_loss": 0.028359,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20210614_0470 | T3 | 1 | train | sideways | all | [
"EMB"
] | 2021-06-14T00:00:00 | EMB: 60-day history, VaR(99%)=-0.0069, max drawdown threshold=10%. | Asset: EMB
Daily returns (past 60 days): mean=0.0009, std=0.0038, worst_day=-0.0091
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0069 (i.e., a 0.69% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0069 = 14.4529, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.006919,
"expected_loss": 0.006919,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20210514_0473 | T3 | 1 | train | sideways | all | [
"AVAX-USD"
] | 2021-05-14T00:00:00 | AVAX-USD: 60-day history, VaR(99%)=-0.1510, max drawdown threshold=10%. | Asset: AVAX-USD
Daily returns (past 60 days): mean=0.0062, std=0.0799, worst_day=-0.1550
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 0.6623 | 0.6623 | Step 1: Compute |VaR(99%)| from historical returns = 0.1510 (i.e., a 15.10% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1510 = 0.6623, capped at 1.0.
Maximum position size = 0.6623 (66.2% of portfolio). | {
"var_99": -0.15098599999999998,
"expected_loss": 0.15098599999999998,
"max_drawdown_threshold": 0.1,
"position_size": 0.6623,
"has_text": false,
"text_chars": 0
} |
T3_all_20210216_0476 | T3 | 1 | train | sideways | all | [
"LINK-USD"
] | 2021-02-16T00:00:00 | LINK-USD: 60-day history, VaR(99%)=-0.1547, max drawdown threshold=10%. | Asset: LINK-USD
Daily returns (past 60 days): mean=0.0179, std=0.0799, worst_day=-0.1567
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 0.6463 | 0.6463 | Step 1: Compute |VaR(99%)| from historical returns = 0.1547 (i.e., a 15.47% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1547 = 0.6463, capped at 1.0.
Maximum position size = 0.6463 (64.6% of portfolio). | {
"var_99": -0.154738,
"expected_loss": 0.154738,
"max_drawdown_threshold": 0.1,
"position_size": 0.6463,
"has_text": false,
"text_chars": 0
} |
T3_all_20181123_0481 | T3 | 1 | train | sideways | all | [
"ETH-USD"
] | 2018-11-23T00:00:00 | ETH-USD: 60-day history, VaR(99%)=-0.1583, max drawdown threshold=10%. | Asset: ETH-USD
Daily returns (past 60 days): mean=-0.0099, std=0.0438, worst_day=-0.1593
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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 ... | 0.6319 | 0.6319 | Step 1: Compute |VaR(99%)| from historical returns = 0.1583 (i.e., a 15.83% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1583 = 0.6319, capped at 1.0.
Maximum position size = 0.6319 (63.2% of portfolio). | {
"var_99": -0.158264,
"expected_loss": 0.158264,
"max_drawdown_threshold": 0.1,
"position_size": 0.6319,
"has_text": false,
"text_chars": 0
} |
T3_all_20220425_0484 | T3 | 1 | train | sideways | all | [
"XLY"
] | 2022-04-25T00:00:00 | XLY: 60-day history, VaR(99%)=-0.0360, max drawdown threshold=10%. | Asset: XLY
Daily returns (past 60 days): mean=-0.0001, std=0.0204, worst_day=-0.0388
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-04-22] ["Smart Speaker Market: 20.87% Y-O-Y Growth Rate in 2021 | By End-user (residential users and commercial users) and Geography | ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0360 (i.e., a 3.60% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0360 = 2.7802, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.035969,
"expected_loss": 0.035969,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20180403_0491 | T3 | 1 | train | sideways | all | [
"IGOV"
] | 2018-04-03T00:00:00 | IGOV: 60-day history, VaR(99%)=-0.0084, max drawdown threshold=10%. | Asset: IGOV
Daily returns (past 60 days): mean=0.0008, std=0.0041, worst_day=-0.0096
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to IGOV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0084 (i.e., a 0.84% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0084 = 11.8837, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.008414999999999999,
"expected_loss": 0.008414999999999999,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20200206_0496 | T3 | 1 | train | sideways | all | [
"MATIC-USD"
] | 2020-02-06T00:00:00 | MATIC-USD: 60-day history, VaR(99%)=-0.1741, max drawdown threshold=10%. | Asset: MATIC-USD
Daily returns (past 60 days): mean=0.0005, std=0.0728, worst_day=-0.2144
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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 a... | 0.5745 | 0.5745 | Step 1: Compute |VaR(99%)| from historical returns = 0.1741 (i.e., a 17.41% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1741 = 0.5745, capped at 1.0.
Maximum position size = 0.5745 (57.5% of portfolio). | {
"var_99": -0.17407599999999998,
"expected_loss": 0.17407599999999998,
"max_drawdown_threshold": 0.1,
"position_size": 0.5745,
"has_text": false,
"text_chars": 0
} |
T3_all_20220810_0501 | T3 | 1 | train | sideways | all | [
"^VIX"
] | 2022-08-10T00:00:00 | ^VIX: 60-day history, VaR(99%)=-0.0969, max drawdown threshold=10%. | Asset: ^VIX
Daily returns (past 60 days): mean=-0.0063, std=0.0583, worst_day=-0.0986
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-08-09] ["Down 47% in a Year, Time to Buy This Growth Stock? With a market cap of $8.3 billion, Cognex Corporation (NASDAQ: CGNX) is no... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0969 (i.e., a 9.69% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0969 = 1.0319, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.096908,
"expected_loss": 0.096908,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190521_0504 | T3 | 1 | train | sideways | all | [
"FXI"
] | 2019-05-21T00:00:00 | FXI: 60-day history, VaR(99%)=-0.0307, max drawdown threshold=10%. | Asset: FXI
Daily returns (past 60 days): mean=-0.0015, std=0.0127, worst_day=-0.0327
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-05-20] Credit Suisse Absolutely Is Right to Double Down on Pfizer Stock After upgrading Pfizer (NYSE:) to “Outperform” in January and r... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0307 (i.e., a 3.07% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0307 = 3.2527, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.030743,
"expected_loss": 0.030743,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20200311_0507 | T3 | 1 | train | sideways | all | [
"XLY"
] | 2020-03-11T00:00:00 | XLY: 60-day history, VaR(99%)=-0.0388, max drawdown threshold=10%. | Asset: XLY
Daily returns (past 60 days): mean=-0.0010, std=0.0148, worst_day=-0.0388
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-03-10] ["123 Biggest Movers From Yesterday", "UBS Maintains Buy on Apple, Lowers Price Target to $335", "Shares of several technology c... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0388 (i.e., a 3.88% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0388 = 2.5763, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.038815999999999996,
"expected_loss": 0.038815999999999996,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190306_0510 | T3 | 1 | train | sideways | all | [
"CPER"
] | 2019-03-06T00:00:00 | CPER: 60-day history, VaR(99%)=-0.0245, max drawdown threshold=10%. | Asset: CPER
Daily returns (past 60 days): mean=0.0014, std=0.0114, worst_day=-0.0292
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to CPER, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0245 (i.e., a 2.45% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0245 = 4.0845, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.024482999999999998,
"expected_loss": 0.024482999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20190225_0513 | T3 | 1 | train | sideways | all | [
"QQQ"
] | 2019-02-25T00:00:00 | QQQ: 60-day history, VaR(99%)=-0.0358, max drawdown threshold=10%. | Asset: QQQ
Daily returns (past 60 days): mean=0.0008, std=0.0161, worst_day=-0.0391
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-02-22] ["Pinnacle West's (PNW) Q4 Earnings Beat Estimates, Up Y/Y Pinnacle West Capital CorporationPNW delivered adjusted earnings per s... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0358 (i.e., a 3.58% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0358 = 2.7899, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.035844,
"expected_loss": 0.035844,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220706_0516 | T3 | 1 | train | sideways | all | [
"XLK"
] | 2022-07-06T00:00:00 | XLK: 60-day history, VaR(99%)=-0.0427, max drawdown threshold=10%. | Asset: XLK
Daily returns (past 60 days): mean=-0.0028, std=0.0232, worst_day=-0.0427
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-07-05] ["EU lawmakers pass landmark tech rules, but enforcement a worry By Foo Yun Chee BRUSSELS, July 5 (Reuters) - EU lawmakers gave ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0427 (i.e., a 4.27% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0427 = 2.3410, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.042717,
"expected_loss": 0.042717,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190207_0519 | T3 | 1 | train | sideways | all | [
"SCHH"
] | 2019-02-07T00:00:00 | SCHH: 60-day history, VaR(99%)=-0.0340, max drawdown threshold=10%. | Asset: SCHH
Daily returns (past 60 days): mean=0.0010, std=0.0120, worst_day=-0.0340
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to SCHH, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0340 (i.e., a 3.40% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0340 = 2.9369, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.034048999999999996,
"expected_loss": 0.034048999999999996,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20210824_0522 | T3 | 1 | train | sideways | all | [
"MATIC-USD"
] | 2021-08-24T00:00:00 | MATIC-USD: 60-day history, VaR(99%)=-0.1015, max drawdown threshold=10%. | Asset: MATIC-USD
Daily returns (past 60 days): mean=0.0070, std=0.0651, worst_day=-0.1305
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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 a... | 0.9852 | 0.9852 | Step 1: Compute |VaR(99%)| from historical returns = 0.1015 (i.e., a 10.15% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1015 = 0.9852, capped at 1.0.
Maximum position size = 0.9852 (98.5% of portfolio). | {
"var_99": -0.101507,
"expected_loss": 0.101507,
"max_drawdown_threshold": 0.1,
"position_size": 0.9852000000000001,
"has_text": false,
"text_chars": 0
} |
T3_all_20160510_0527 | T3 | 1 | train | sideways | all | [
"ACWI"
] | 2016-05-10T00:00:00 | ACWI: 60-day history, VaR(99%)=-0.0146, max drawdown threshold=10%. | Asset: ACWI
Daily returns (past 60 days): mean=0.0020, std=0.0090, worst_day=-0.0149
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2016-05-09] Drug Stocks Reporting on May 10: XON, ARIA, CPRX & More How is the Earnings Picture Evolving now that a large part of the first-... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0146 (i.e., a 1.46% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0146 = 6.8337, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.014633,
"expected_loss": 0.014633,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
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