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_20160517_0534 | T3 | 1 | train | sideways | all | [
"EWJ"
] | 2016-05-17T00:00:00 | EWJ: 60-day history, VaR(99%)=-0.0280, max drawdown threshold=10%. | Asset: EWJ
Daily returns (past 60 days): mean=0.0015, std=0.0136, worst_day=-0.0325
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2016-05-16] ["Uber China Rival Didi Targets New York IPO In 2017", "With Buffett Betting Big, Is Apple\u2019s Stock a Buy? With Warren Buffet... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0280 (i.e., a 2.80% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0280 = 3.5730, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.027986999999999998,
"expected_loss": 0.027986999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190213_0536 | T3 | 1 | train | sideways | all | [
"XRP-USD"
] | 2019-02-13T00:00:00 | XRP-USD: 60-day history, VaR(99%)=-0.1007, max drawdown threshold=10%. | Asset: XRP-USD
Daily returns (past 60 days): mean=0.0019, std=0.0440, worst_day=-0.1031
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... | 0.9926 | 0.9926 | Step 1: Compute |VaR(99%)| from historical returns = 0.1007 (i.e., a 10.07% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1007 = 0.9926, capped at 1.0.
Maximum position size = 0.9926 (99.3% of portfolio). | {
"var_99": -0.100743,
"expected_loss": 0.100743,
"max_drawdown_threshold": 0.1,
"position_size": 0.9926,
"has_text": false,
"text_chars": 0
} |
T3_all_20200724_0539 | T3 | 1 | train | sideways | all | [
"IVV"
] | 2020-07-24T00:00:00 | IVV: 60-day history, VaR(99%)=-0.0291, max drawdown threshold=10%. | Asset: IVV
Daily returns (past 60 days): mean=0.0025, std=0.0130, worst_day=-0.0328
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-07-23] ["Elon Musk doesn\u2019t want Tesla to be \u2018super profitable\u2019 as it soars toward a $300 billion valuation CEO says he wa... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0291 (i.e., a 2.91% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0291 = 3.4354, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.029109,
"expected_loss": 0.029109,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220930_0542 | T3 | 1 | train | sideways | all | [
"BTC-USD"
] | 2022-09-30T00:00:00 | BTC-USD: 60-day history, VaR(99%)=-0.0959, max drawdown threshold=10%. | Asset: BTC-USD
Daily returns (past 60 days): mean=-0.0025, std=0.0301, worst_day=-0.1006
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-09-29]
Determine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constrai... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0959 (i.e., a 9.59% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0959 = 1.0423, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.095939,
"expected_loss": 0.095939,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 20
} |
T3_all_20221220_0545 | T3 | 1 | train | sideways | all | [
"MATIC-USD"
] | 2022-12-20T00:00:00 | MATIC-USD: 60-day history, VaR(99%)=-0.1859, max drawdown threshold=10%. | Asset: MATIC-USD
Daily returns (past 60 days): mean=0.0023, std=0.0800, worst_day=-0.2144
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-12-19]
Determine the maximum fraction of total portfolio capital that should be allocated to MATIC-USD, given the drawdown const... | 0.5379 | 0.5379 | Step 1: Compute |VaR(99%)| from historical returns = 0.1859 (i.e., a 18.59% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1859 = 0.5379, capped at 1.0.
Maximum position size = 0.5379 (53.8% of portfolio). | {
"var_99": -0.18590199999999998,
"expected_loss": 0.18590199999999998,
"max_drawdown_threshold": 0.1,
"position_size": 0.5379,
"has_text": true,
"text_chars": 20
} |
T3_all_20160714_0550 | T3 | 1 | train | sideways | all | [
"XLI"
] | 2016-07-14T00:00:00 | XLI: 60-day history, VaR(99%)=-0.0278, max drawdown threshold=10%. | Asset: XLI
Daily returns (past 60 days): mean=0.0009, std=0.0097, worst_day=-0.0336
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2016-07-13] ["SAP-APWorks Team Up to Accelerate Industrial 3D Printing Taking another step in its 3D printing initiative, German software sol... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0278 (i.e., a 2.78% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0278 = 3.5950, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.027816,
"expected_loss": 0.027816,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20200914_0553 | T3 | 1 | train | sideways | all | [
"^VIX"
] | 2020-09-14T00:00:00 | ^VIX: 60-day history, VaR(99%)=-0.1003, max drawdown threshold=10%. | Asset: ^VIX
Daily returns (past 60 days): mean=-0.0037, std=0.0644, worst_day=-0.1005
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-09-11] Ambarella Stock Could See Further Downside Ambarella Incorporated stock (NASDAQ: AMBA) is down 22% since the beginning of this ... | 0.9966 | 0.9966 | Step 1: Compute |VaR(99%)| from historical returns = 0.1003 (i.e., a 10.03% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1003 = 0.9966, capped at 1.0.
Maximum position size = 0.9966 (99.7% of portfolio). | {
"var_99": -0.10034000000000001,
"expected_loss": 0.10034000000000001,
"max_drawdown_threshold": 0.1,
"position_size": 0.9966,
"has_text": true,
"text_chars": 3020
} |
T3_all_20200609_0556 | T3 | 1 | train | sideways | all | [
"EFA"
] | 2020-06-09T00:00:00 | EFA: 60-day history, VaR(99%)=-0.0289, max drawdown threshold=10%. | Asset: EFA
Daily returns (past 60 days): mean=0.0035, std=0.0178, worst_day=-0.0289
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-06-08] ["UBS Maintains Buy on Adobe, Raises Price Target to $450", "UBS Maintains Buy on Adobe, Raises Price Target to $450", "3 Top E-C... | 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 = 3.4601, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.028901,
"expected_loss": 0.028901,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190920_0559 | T3 | 1 | train | sideways | all | [
"BTC-USD"
] | 2019-09-20T00:00:00 | BTC-USD: 60-day history, VaR(99%)=-0.0660, max drawdown threshold=10%. | Asset: BTC-USD
Daily returns (past 60 days): mean=-0.0001, std=0.0280, worst_day=-0.0775
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 = 0.0660 (i.e., a 6.60% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0660 = 1.5144, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.066034,
"expected_loss": 0.066034,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20190902_0562 | T3 | 1 | train | sideways | all | [
"XLRE"
] | 2019-09-02T00:00:00 | XLRE: 60-day history, VaR(99%)=-0.0194, max drawdown threshold=10%. | Asset: XLRE
Daily returns (past 60 days): mean=0.0010, std=0.0085, worst_day=-0.0196
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-08-30] ["Nvidia Stock Is a Long-Term Winner Predicting what technologies will be prevalent in ten years is difficult. Who\u2019s to say... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0194 (i.e., a 1.94% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0194 = 5.1570, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.019391,
"expected_loss": 0.019391,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20200828_0565 | T3 | 1 | train | sideways | all | [
"BTC-USD"
] | 2020-08-28T00:00:00 | BTC-USD: 60-day history, VaR(99%)=-0.0478, max drawdown threshold=10%. | Asset: BTC-USD
Daily returns (past 60 days): mean=0.0038, std=0.0228, worst_day=-0.0600
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 = 0.0478 (i.e., a 4.78% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0478 = 2.0903, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.04784,
"expected_loss": 0.04784,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20210107_0570 | T3 | 1 | train | sideways | all | [
"SCHP"
] | 2021-01-07T00:00:00 | SCHP: 60-day history, VaR(99%)=-0.0034, max drawdown threshold=10%. | Asset: SCHP
Daily returns (past 60 days): mean=0.0002, std=0.0017, worst_day=-0.0041
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 = 0.0034 (i.e., a 0.34% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0034 = 29.3204, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.003411,
"expected_loss": 0.003411,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20160824_0573 | T3 | 1 | train | sideways | all | [
"VTI"
] | 2016-08-24T00:00:00 | VTI: 60-day history, VaR(99%)=-0.0256, max drawdown threshold=10%. | Asset: VTI
Daily returns (past 60 days): mean=0.0009, std=0.0078, worst_day=-0.0335
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2016-08-23] ["Applied Materials' EPS Growing Faster Than Its Stock Price", "Applied Materials' EPS Growing Faster Than Its Stock Price", "Nas... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0256 (i.e., a 2.56% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0256 = 3.9103, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.025573,
"expected_loss": 0.025573,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20180109_0576 | T3 | 1 | train | sideways | all | [
"EWJ"
] | 2018-01-09T00:00:00 | EWJ: 60-day history, VaR(99%)=-0.0104, max drawdown threshold=10%. | Asset: EWJ
Daily returns (past 60 days): mean=0.0017, std=0.0059, worst_day=-0.0106
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2018-01-08] ["Activist shareholders want Apple to help kids kick iPhone addictions Jana, teachers group push for better corporate responsibil... | 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 = 9.6426, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.010371,
"expected_loss": 0.010371,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20160121_0579 | T3 | 1 | train | sideways | all | [
"XLK"
] | 2016-01-21T00:00:00 | XLK: 60-day history, VaR(99%)=-0.0291, max drawdown threshold=10%. | Asset: XLK
Daily returns (past 60 days): mean=-0.0014, std=0.0123, worst_day=-0.0300
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2016-01-20] Commit To Buy American Electric Power Company At $45, Earn 5.7% Using Options Investors considering a purchase of American Elect... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0291 (i.e., a 2.91% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0291 = 3.4309, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.029147,
"expected_loss": 0.029147,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20150217_0582 | T3 | 1 | train | sideways | all | [
"XLK"
] | 2015-02-17T00:00:00 | XLK: 29-day history, VaR(99%)=-0.0254, max drawdown threshold=10%. | Asset: XLK
Daily returns (past 29 days): mean=0.0011, std=0.0113, worst_day=-0.0293
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2015-02-13] ["London wants a piece of New York\u2019s startups U.K. led startup funding in Europe last month, raising $294 million The U.K. g... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0254 (i.e., a 2.54% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0254 = 3.9420, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.025367999999999998,
"expected_loss": 0.025367999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20210729_0585 | T3 | 1 | train | sideways | all | [
"XLK"
] | 2021-07-29T00:00:00 | XLK: 60-day history, VaR(99%)=-0.0268, max drawdown threshold=10%. | Asset: XLK
Daily returns (past 60 days): mean=0.0016, std=0.0102, worst_day=-0.0285
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-07-28] ["LG will reportedly sell iPhones in its South Korean stores LG has confirmed that it will start selling iPhones and other Apple ... | 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 = 3.7337, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.026782999999999998,
"expected_loss": 0.026782999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20191011_0588 | T3 | 1 | train | sideways | all | [
"ETH-USD"
] | 2019-10-11T00:00:00 | ETH-USD: 60-day history, VaR(99%)=-0.1278, max drawdown threshold=10%. | Asset: ETH-USD
Daily returns (past 60 days): mean=-0.0011, std=0.0381, 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 ... | 0.7824 | 0.7824 | Step 1: Compute |VaR(99%)| from historical returns = 0.1278 (i.e., a 12.78% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1278 = 0.7824, capped at 1.0.
Maximum position size = 0.7824 (78.2% of portfolio). | {
"var_99": -0.127804,
"expected_loss": 0.127804,
"max_drawdown_threshold": 0.1,
"position_size": 0.7824,
"has_text": false,
"text_chars": 0
} |
T3_all_20191010_0591 | T3 | 1 | train | sideways | all | [
"FXI"
] | 2019-10-10T00:00:00 | FXI: 60-day history, VaR(99%)=-0.0349, max drawdown threshold=10%. | Asset: FXI
Daily returns (past 60 days): mean=-0.0008, std=0.0115, worst_day=-0.0399
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-10-09] ["Monness Crespi Hardt becomes latest to slash its Netflix price target on competition concerns Monness Crespi Hardt became the ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0349 (i.e., a 3.49% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0349 = 2.8678, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.034870000000000005,
"expected_loss": 0.034870000000000005,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20181016_0594 | T3 | 1 | train | sideways | all | [
"USMV"
] | 2018-10-16T00:00:00 | USMV: 60-day history, VaR(99%)=-0.0235, max drawdown threshold=10%. | Asset: USMV
Daily returns (past 60 days): mean=0.0001, std=0.0058, worst_day=-0.0253
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2018-10-15] ["GoPro to Sell Curated Video Clips to the Adobe Stock Marketplace", "Adobe Sees FY19 Total Adobe Sales Growth ~20% Year Over Ye... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0235 (i.e., a 2.35% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0235 = 4.2496, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.023531999999999997,
"expected_loss": 0.023531999999999997,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220720_0599 | T3 | 1 | train | sideways | all | [
"AVAX-USD"
] | 2022-07-20T00:00:00 | AVAX-USD: 60-day history, VaR(99%)=-0.1355, max drawdown threshold=10%. | Asset: AVAX-USD
Daily returns (past 60 days): mean=-0.0001, std=0.0721, worst_day=-0.1362
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-07-19]
Determine the maximum fraction of total portfolio capital that should be allocated to AVAX-USD, given the drawdown constr... | 0.7382 | 0.7382 | Step 1: Compute |VaR(99%)| from historical returns = 0.1355 (i.e., a 13.55% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1355 = 0.7382, capped at 1.0.
Maximum position size = 0.7382 (73.8% of portfolio). | {
"var_99": -0.13547299999999998,
"expected_loss": 0.13547299999999998,
"max_drawdown_threshold": 0.1,
"position_size": 0.7382000000000001,
"has_text": true,
"text_chars": 20
} |
T3_all_20210728_0602 | T3 | 1 | train | sideways | all | [
"AVAX-USD"
] | 2021-07-28T00:00:00 | AVAX-USD: 60-day history, VaR(99%)=-0.1420, max drawdown threshold=10%. | Asset: AVAX-USD
Daily returns (past 60 days): mean=-0.0038, std=0.0582, worst_day=-0.1912
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 an... | 0.7040 | 0.704 | Step 1: Compute |VaR(99%)| from historical returns = 0.1420 (i.e., a 14.20% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1420 = 0.7040, capped at 1.0.
Maximum position size = 0.7040 (70.4% of portfolio). | {
"var_99": -0.14204899999999998,
"expected_loss": 0.14204899999999998,
"max_drawdown_threshold": 0.1,
"position_size": 0.704,
"has_text": false,
"text_chars": 0
} |
T3_all_20160623_0605 | T3 | 1 | train | sideways | all | [
"VEA"
] | 2016-06-23T00:00:00 | VEA: 60-day history, VaR(99%)=-0.0223, max drawdown threshold=10%. | Asset: VEA
Daily returns (past 60 days): mean=0.0003, std=0.0103, worst_day=-0.0274
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2016-06-22] ["Keep an Eye on These 10 Stocks for June 22, 2016", "A Peek Into The Markets: U.S. Stock Futures Edge Higher Ahead Of Yellen Spe... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0223 (i.e., a 2.23% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0223 = 4.4805, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.022319,
"expected_loss": 0.022319,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20171220_0608 | T3 | 1 | train | sideways | all | [
"VCIT"
] | 2017-12-20T00:00:00 | VCIT: 60-day history, VaR(99%)=-0.0039, max drawdown threshold=10%. | Asset: VCIT
Daily returns (past 60 days): mean=0.0000, std=0.0016, worst_day=-0.0043
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 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 = 25.4155, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.003935,
"expected_loss": 0.003935,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20210929_0611 | T3 | 1 | train | sideways | all | [
"MORT"
] | 2021-09-29T00:00:00 | MORT: 60-day history, VaR(99%)=-0.0263, max drawdown threshold=10%. | Asset: MORT
Daily returns (past 60 days): mean=-0.0002, std=0.0115, worst_day=-0.0327
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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 (... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0263 (i.e., a 2.63% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0263 = 3.7999, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.026317,
"expected_loss": 0.026317,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20200306_0616 | T3 | 1 | train | sideways | all | [
"INDS"
] | 2020-03-06T00:00:00 | INDS: 60-day history, VaR(99%)=-0.0356, max drawdown threshold=10%. | Asset: INDS
Daily returns (past 60 days): mean=0.0001, std=0.0134, worst_day=-0.0391
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 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 = 2.8078, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.035615,
"expected_loss": 0.035615,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20200409_0619 | T3 | 1 | train | sideways | all | [
"BIL"
] | 2020-04-09T00:00:00 | BIL: 60-day history, VaR(99%)=-0.0003, max drawdown threshold=10%. | Asset: BIL
Daily returns (past 60 days): mean=0.0000, std=0.0002, worst_day=-0.0003
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to BIL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0003 (i.e., a 0.03% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0003 = 305.5951, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.000327,
"expected_loss": 0.000327,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20220921_0621 | T3 | 1 | train | sideways | all | [
"XRP-USD"
] | 2022-09-21T00:00:00 | XRP-USD: 60-day history, VaR(99%)=-0.0820, max drawdown threshold=10%. | Asset: XRP-USD
Daily returns (past 60 days): mean=0.0030, std=0.0345, worst_day=-0.0968
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-09-20]
Determine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constrain... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0820 (i.e., a 8.20% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0820 = 1.2200, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.081967,
"expected_loss": 0.081967,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 20
} |
T3_all_20160920_0624 | T3 | 1 | train | sideways | all | [
"USO"
] | 2016-09-20T00:00:00 | USO: 60-day history, VaR(99%)=-0.0494, max drawdown threshold=10%. | Asset: USO
Daily returns (past 60 days): mean=-0.0027, std=0.0243, worst_day=-0.0509
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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.... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0494 (i.e., a 4.94% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0494 = 2.0224, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.049447,
"expected_loss": 0.049447,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20190813_0627 | T3 | 1 | train | sideways | all | [
"MTUM"
] | 2019-08-13T00:00:00 | MTUM: 60-day history, VaR(99%)=-0.0219, max drawdown threshold=10%. | Asset: MTUM
Daily returns (past 60 days): mean=0.0007, std=0.0088, worst_day=-0.0312
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-08-12] ["3 Great Stocks Beaten Down This Earnings Season This article was first published by MyWallSt. Find out more about MyWallSt's m... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0219 (i.e., a 2.19% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0219 = 4.5705, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.021879,
"expected_loss": 0.021879,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20191107_0632 | T3 | 1 | train | sideways | all | [
"XLB"
] | 2019-11-07T00:00:00 | XLB: 60-day history, VaR(99%)=-0.0276, max drawdown threshold=10%. | Asset: XLB
Daily returns (past 60 days): mean=0.0007, std=0.0103, worst_day=-0.0322
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-11-06] ["Robinhood glitch is letting users trade with unlimited amounts of borrowed cash Bug gives traders infinite leverage \u2014 but ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0276 (i.e., a 2.76% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0276 = 3.6198, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.027625999999999998,
"expected_loss": 0.027625999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20170110_0635 | T3 | 1 | train | sideways | all | [
"XLV"
] | 2017-01-10T00:00:00 | XLV: 60-day history, VaR(99%)=-0.0179, max drawdown threshold=10%. | Asset: XLV
Daily returns (past 60 days): mean=0.0002, std=0.0084, worst_day=-0.0219
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2017-01-09] ["The Medicines Co LDL-Lowering Drug Positive in Phase II The Medicines CompanyMDCO announced positive top-line results from a Da... | 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 = 5.5981, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.017863,
"expected_loss": 0.017863,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20150827_0638 | T3 | 1 | train | sideways | all | [
"SLV"
] | 2015-08-27T00:00:00 | SLV: 60-day history, VaR(99%)=-0.0347, max drawdown threshold=10%. | Asset: SLV
Daily returns (past 60 days): mean=-0.0025, std=0.0127, worst_day=-0.0374
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to SLV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0347 (i.e., a 3.47% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0347 = 2.8818, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.034700999999999996,
"expected_loss": 0.034700999999999996,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20201111_0641 | T3 | 1 | train | sideways | all | [
"ADA-USD"
] | 2020-11-11T00:00:00 | ADA-USD: 60-day history, VaR(99%)=-0.0831, max drawdown threshold=10%. | Asset: ADA-USD
Daily returns (past 60 days): mean=0.0024, std=0.0442, worst_day=-0.1007
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 1... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0831 (i.e., a 8.31% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0831 = 1.2039, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.083062,
"expected_loss": 0.083062,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20210908_0644 | T3 | 1 | train | sideways | all | [
"MATIC-USD"
] | 2021-09-08T00:00:00 | MATIC-USD: 60-day history, VaR(99%)=-0.1295, max drawdown threshold=10%. | Asset: MATIC-USD
Daily returns (past 60 days): mean=0.0068, std=0.0747, worst_day=-0.1762
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... | 0.7719 | 0.7719 | Step 1: Compute |VaR(99%)| from historical returns = 0.1295 (i.e., a 12.95% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1295 = 0.7719, capped at 1.0.
Maximum position size = 0.7719 (77.2% of portfolio). | {
"var_99": -0.129543,
"expected_loss": 0.129543,
"max_drawdown_threshold": 0.1,
"position_size": 0.7719,
"has_text": false,
"text_chars": 0
} |
T3_all_20220811_0647 | T3 | 1 | train | sideways | all | [
"XHB"
] | 2022-08-11T00:00:00 | XHB: 60-day history, VaR(99%)=-0.0411, max drawdown threshold=10%. | Asset: XHB
Daily returns (past 60 days): mean=0.0021, std=0.0203, 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 = 0.0411 (i.e., a 4.11% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0411 = 2.4331, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.041100000000000005,
"expected_loss": 0.041100000000000005,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20190614_0650 | T3 | 1 | train | sideways | all | [
"BTC-USD"
] | 2019-06-14T00:00:00 | BTC-USD: 60-day history, VaR(99%)=-0.0642, max drawdown threshold=10%. | Asset: BTC-USD
Daily returns (past 60 days): mean=0.0080, std=0.0372, worst_day=-0.0686
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 = 0.0642 (i.e., a 6.42% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0642 = 1.5585, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.064165,
"expected_loss": 0.064165,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20160509_0653 | T3 | 1 | train | sideways | all | [
"QQQ"
] | 2016-05-09T00:00:00 | QQQ: 60-day history, VaR(99%)=-0.0158, max drawdown threshold=10%. | Asset: QQQ
Daily returns (past 60 days): mean=0.0015, std=0.0098, worst_day=-0.0166
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2016-05-06] FEYE Stock: FireEye Inc Tumbles, But It’s Not Beat InvestorPlaceInvestorPlace - Stock Market News, Stock Advice & Trading Tips He... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0158 (i.e., a 1.58% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0158 = 6.3382, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.015777,
"expected_loss": 0.015777,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20180131_0656 | T3 | 1 | train | sideways | all | [
"BNB-USD"
] | 2018-01-31T00:00:00 | BNB-USD: 60-day history, VaR(99%)=-0.1754, max drawdown threshold=10%. | Asset: BNB-USD
Daily returns (past 60 days): mean=0.0282, std=0.1111, worst_day=-0.1754
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 0.5701 | 0.5701 | Step 1: Compute |VaR(99%)| from historical returns = 0.1754 (i.e., a 17.54% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1754 = 0.5701, capped at 1.0.
Maximum position size = 0.5701 (57.0% of portfolio). | {
"var_99": -0.175402,
"expected_loss": 0.175402,
"max_drawdown_threshold": 0.1,
"position_size": 0.5701,
"has_text": false,
"text_chars": 0
} |
T3_all_20180130_0661 | T3 | 1 | train | sideways | all | [
"XLK"
] | 2018-01-30T00:00:00 | XLK: 60-day history, VaR(99%)=-0.0187, max drawdown threshold=10%. | Asset: XLK
Daily returns (past 60 days): mean=0.0015, std=0.0072, worst_day=-0.0223
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2018-01-29] ["Alibaba, Foxconn lead big investment in Chinese electric-car maker Tech companies branch out into burgeoning industry Chinese e... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0187 (i.e., a 1.87% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0187 = 5.3434, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.018715,
"expected_loss": 0.018715,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20170224_0664 | T3 | 1 | train | sideways | all | [
"XLU"
] | 2017-02-24T00:00:00 | XLU: 60-day history, VaR(99%)=-0.0254, max drawdown threshold=10%. | Asset: XLU
Daily returns (past 60 days): mean=0.0014, std=0.0090, worst_day=-0.0320
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2017-02-23] ["Winners And Losers From Apple iPhone 8\u2032s Super Cycle Not all components are created equal. As Apple (AAPL) starts to build... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0254 (i.e., a 2.54% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0254 = 3.9344, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.025417,
"expected_loss": 0.025417,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20200806_0668 | T3 | 1 | train | sideways | all | [
"MORT"
] | 2020-08-06T00:00:00 | MORT: 60-day history, VaR(99%)=-0.0446, max drawdown threshold=10%. | Asset: MORT
Daily returns (past 60 days): mean=0.0030, std=0.0258, worst_day=-0.0446
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0446 (i.e., a 4.46% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0446 = 2.2411, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.044621,
"expected_loss": 0.044621,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20190924_0671 | T3 | 1 | train | sideways | all | [
"LINK-USD"
] | 2019-09-24T00:00:00 | LINK-USD: 60-day history, VaR(99%)=-0.0840, max drawdown threshold=10%. | Asset: LINK-USD
Daily returns (past 60 days): mean=-0.0038, std=0.0407, worst_day=-0.0981
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 = 0.0840 (i.e., a 8.40% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0840 = 1.1903, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.08401399999999999,
"expected_loss": 0.08401399999999999,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20190606_0674 | T3 | 1 | train | sideways | all | [
"TLH"
] | 2019-06-06T00:00:00 | TLH: 60-day history, VaR(99%)=-0.0079, max drawdown threshold=10%. | Asset: TLH
Daily returns (past 60 days): mean=0.0009, std=0.0041, worst_day=-0.0102
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0079 (i.e., a 0.79% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0079 = 12.6706, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.007892,
"expected_loss": 0.007892,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20180119_0678 | T3 | 1 | train | sideways | all | [
"ICSH"
] | 2018-01-19T00:00:00 | ICSH: 60-day history, VaR(99%)=-0.0004, max drawdown threshold=10%. | Asset: ICSH
Daily returns (past 60 days): mean=0.0000, std=0.0002, worst_day=-0.0004
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 = 0.0004 (i.e., a 0.04% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0004 = 250.1990, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.0004,
"expected_loss": 0.0004,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20170308_0681 | T3 | 1 | train | sideways | all | [
"IVV"
] | 2017-03-08T00:00:00 | IVV: 60-day history, VaR(99%)=-0.0079, max drawdown threshold=10%. | Asset: IVV
Daily returns (past 60 days): mean=0.0010, std=0.0041, worst_day=-0.0082
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2017-03-07] ["LG Electronics Soars On Firm LCD Pricing, But Smartphone Business Drags LG Electronics (066570.Korea) soared 4.2% on Tuesday am... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0079 (i.e., a 0.79% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0079 = 12.7307, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.007855,
"expected_loss": 0.007855,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20210715_0684 | T3 | 1 | train | sideways | all | [
"ADA-USD"
] | 2021-07-15T00:00:00 | ADA-USD: 60-day history, VaR(99%)=-0.1761, max drawdown threshold=10%. | Asset: ADA-USD
Daily returns (past 60 days): mean=-0.0045, std=0.0742, 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 ... | 0.5678 | 0.5678 | Step 1: Compute |VaR(99%)| from historical returns = 0.1761 (i.e., a 17.61% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1761 = 0.5678, capped at 1.0.
Maximum position size = 0.5678 (56.8% of portfolio). | {
"var_99": -0.17612000000000003,
"expected_loss": 0.17612000000000003,
"max_drawdown_threshold": 0.1,
"position_size": 0.5678000000000001,
"has_text": false,
"text_chars": 0
} |
T3_all_20181017_0687 | T3 | 1 | train | sideways | all | [
"VTI"
] | 2018-10-17T00:00:00 | VTI: 60-day history, VaR(99%)=-0.0260, max drawdown threshold=10%. | Asset: VTI
Daily returns (past 60 days): mean=-0.0001, std=0.0074, worst_day=-0.0324
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2018-10-16] ["12 Stocks To Watch For October 16, 2018", "Barclays Maintains Overweight on Adobe, Raises Price Target to $304", "Adobe shares... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0260 (i.e., a 2.60% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0260 = 3.8481, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.025987,
"expected_loss": 0.025987,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20181011_0690 | T3 | 1 | train | sideways | all | [
"BTC-USD"
] | 2018-10-11T00:00:00 | BTC-USD: 60-day history, VaR(99%)=-0.0546, max drawdown threshold=10%. | Asset: BTC-USD
Daily returns (past 60 days): mean=0.0010, std=0.0202, worst_day=-0.0773
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 = 0.0546 (i.e., a 5.46% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0546 = 1.8321, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.054581,
"expected_loss": 0.054581,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20220328_0693 | T3 | 1 | train | sideways | all | [
"ACWI"
] | 2022-03-28T00:00:00 | ACWI: 60-day history, VaR(99%)=-0.0242, max drawdown threshold=10%. | Asset: ACWI
Daily returns (past 60 days): mean=-0.0012, std=0.0126, worst_day=-0.0309
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-03-25] ["Europe says yes to messaging interoperability as it agrees major new regime for big tech Late Thursday the European Union sec... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0242 (i.e., a 2.42% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0242 = 4.1286, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.024221,
"expected_loss": 0.024221,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20160428_0698 | T3 | 1 | train | sideways | all | [
"XLF"
] | 2016-04-28T00:00:00 | XLF: 60-day history, VaR(99%)=-0.0293, max drawdown threshold=10%. | Asset: XLF
Daily returns (past 60 days): mean=0.0015, std=0.0129, worst_day=-0.0310
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2016-04-27] ["TSMC Will Meet Its Sales Target Despite Apple\u2019s Fiscal Q2 Miss: Bernstein Bernstein Research cut its second-quarter revenu... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0293 (i.e., a 2.93% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0293 = 3.4098, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.029328,
"expected_loss": 0.029328,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20211103_0702 | T3 | 1 | train | sideways | all | [
"DOT-USD"
] | 2021-11-03T00:00:00 | DOT-USD: 60-day history, VaR(99%)=-0.1779, max drawdown threshold=10%. | Asset: DOT-USD
Daily returns (past 60 days): mean=0.0096, std=0.0714, worst_day=-0.1890
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-11-02]
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_20210720_0704 | T3 | 1 | train | sideways | all | [
"USMV"
] | 2021-07-20T00:00:00 | USMV: 60-day history, VaR(99%)=-0.0137, max drawdown threshold=10%. | Asset: USMV
Daily returns (past 60 days): mean=0.0006, std=0.0059, worst_day=-0.0166
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-07-19] This Segment of Tech Stocks Will Outpace the Rest Over the Next 4 Years Technology stocks have been the must-own sector for more... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0137 (i.e., a 1.37% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0137 = 7.3201, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.013661,
"expected_loss": 0.013661,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190718_0705 | T3 | 1 | train | sideways | all | [
"XLP"
] | 2019-07-18T00:00:00 | XLP: 60-day history, VaR(99%)=-0.0152, max drawdown threshold=10%. | Asset: XLP
Daily returns (past 60 days): mean=0.0010, std=0.0069, worst_day=-0.0165
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-07-17] ["Netflix Reports Earnings Today. Here\u2019s What to Expect. Management will likely face questions about competition from other ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0152 (i.e., a 1.52% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0152 = 6.5620, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.015238999999999999,
"expected_loss": 0.015238999999999999,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20210701_0707 | T3 | 1 | train | sideways | all | [
"XLB"
] | 2021-07-01T00:00:00 | XLB: 60-day history, VaR(99%)=-0.0237, max drawdown threshold=10%. | Asset: XLB
Daily returns (past 60 days): mean=0.0004, std=0.0104, worst_day=-0.0255
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-06-30] ["Ably raises $70 million for its developer platform that enables realtime features Ably is a Pub/Sub messaging platform that com... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0237 (i.e., a 2.37% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0237 = 4.2109, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.023748,
"expected_loss": 0.023748,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190122_0709 | T3 | 1 | train | sideways | all | [
"BTC-USD"
] | 2019-01-22T00:00:00 | BTC-USD: 60-day history, VaR(99%)=-0.0961, max drawdown threshold=10%. | Asset: BTC-USD
Daily returns (past 60 days): mean=-0.0024, std=0.0435, worst_day=-0.1073
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 = 0.0961 (i.e., a 9.61% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0961 = 1.0407, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.096089,
"expected_loss": 0.096089,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20210215_0711 | T3 | 1 | train | sideways | all | [
"XLY"
] | 2021-02-15T00:00:00 | XLY: 60-day history, VaR(99%)=-0.0268, max drawdown threshold=10%. | Asset: XLY
Daily returns (past 60 days): mean=0.0016, std=0.0103, worst_day=-0.0313
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-02-12] ["Which is better, the 2021 Toyota RAV4 or the 2021 Honda CR-V? The Toyota RAV4 and Honda CR-V are two popular, reliable, compact... | 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 = 3.7360, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.026767,
"expected_loss": 0.026767,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20180801_0713 | T3 | 1 | train | sideways | all | [
"TIP"
] | 2018-08-01T00:00:00 | TIP: 60-day history, VaR(99%)=-0.0015, max drawdown threshold=10%. | Asset: TIP
Daily returns (past 60 days): mean=0.0001, std=0.0007, worst_day=-0.0016
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0015 (i.e., a 0.15% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0015 = 66.9937, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.001493,
"expected_loss": 0.001493,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20221021_0715 | T3 | 1 | train | sideways | all | [
"DOT-USD"
] | 2022-10-21T00:00:00 | DOT-USD: 60-day history, VaR(99%)=-0.0875, max drawdown threshold=10%. | Asset: DOT-USD
Daily returns (past 60 days): mean=-0.0034, std=0.0305, worst_day=-0.0875
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-10-20]
Determine the maximum fraction of total portfolio capital that should be allocated to DOT-USD, given the drawdown constrai... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0875 (i.e., a 8.75% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0875 = 1.1433, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.087465,
"expected_loss": 0.087465,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 20
} |
T3_all_20171115_0717 | T3 | 1 | train | sideways | all | [
"MTUM"
] | 2017-11-15T00:00:00 | MTUM: 60-day history, VaR(99%)=-0.0107, max drawdown threshold=10%. | Asset: MTUM
Daily returns (past 60 days): mean=0.0017, std=0.0051, worst_day=-0.0126
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2017-11-14] ["Amazon selling its cloud-computing business in China Beijing Sinnet Technology says it\u2019s buying unit for up to $300 milli... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0107 (i.e., a 1.07% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0107 = 9.3293, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.010719,
"expected_loss": 0.010719,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20170901_0719 | T3 | 1 | train | sideways | all | [
"EEM"
] | 2017-09-01T00:00:00 | EEM: 60-day history, VaR(99%)=-0.0174, max drawdown threshold=10%. | Asset: EEM
Daily returns (past 60 days): mean=0.0013, std=0.0076, worst_day=-0.0240
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2017-08-31] ["3 Must Read Stories: Trump Blasts North Korea, Apple\u2019s Market Cap Approaches $1 Trillion, Alibaba Pictures", "Toshiba cont... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0174 (i.e., a 1.74% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0174 = 5.7403, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.017421,
"expected_loss": 0.017421,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220623_0721 | T3 | 1 | train | sideways | all | [
"FXI"
] | 2022-06-23T00:00:00 | FXI: 60-day history, VaR(99%)=-0.0438, max drawdown threshold=10%. | Asset: FXI
Daily returns (past 60 days): mean=0.0004, std=0.0246, worst_day=-0.0438
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-06-22] ["Market Sell-Off: 1 Tech Stock to Buy Hand Over Fist Right Now Shares of contract electronics manufacturer Jabil (NYSE: JBL) wer... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0438 (i.e., a 4.38% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0438 = 2.2811, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.043838999999999996,
"expected_loss": 0.043838999999999996,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20200709_0723 | T3 | 1 | train | sideways | all | [
"BIL"
] | 2020-07-09T00:00:00 | BIL: 60-day history, VaR(99%)=-0.0002, max drawdown threshold=10%. | Asset: BIL
Daily returns (past 60 days): mean=-0.0000, std=0.0001, worst_day=-0.0002
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to BIL, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0002 (i.e., a 0.02% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0002 = 457.7642, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.00021799999999999999,
"expected_loss": 0.00021799999999999999,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20190726_0725 | T3 | 1 | train | sideways | all | [
"XLY"
] | 2019-07-26T00:00:00 | XLY: 60-day history, VaR(99%)=-0.0214, max drawdown threshold=10%. | Asset: XLY
Daily returns (past 60 days): mean=0.0005, std=0.0088, worst_day=-0.0302
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-07-25] ["Asian markets little changed as investors await central bank decisions Stocks in Japan, Hong Kong rise slightly Asian markets w... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0214 (i.e., a 2.14% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0214 = 4.6730, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.021398999999999998,
"expected_loss": 0.021398999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20180316_0727 | T3 | 1 | train | sideways | all | [
"BNDX"
] | 2018-03-16T00:00:00 | BNDX: 60-day history, VaR(99%)=-0.0020, max drawdown threshold=10%. | Asset: BNDX
Daily returns (past 60 days): mean=0.0001, std=0.0012, worst_day=-0.0022
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 = 0.0020 (i.e., a 0.20% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0020 = 50.1620, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.001994,
"expected_loss": 0.001994,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20190801_0729 | T3 | 1 | train | sideways | all | [
"BTC-USD"
] | 2019-08-01T00:00:00 | BTC-USD: 60-day history, VaR(99%)=-0.1312, max drawdown threshold=10%. | Asset: BTC-USD
Daily returns (past 60 days): mean=0.0043, std=0.0526, 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 1... | 0.7621 | 0.7621 | Step 1: Compute |VaR(99%)| from historical returns = 0.1312 (i.e., a 13.12% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1312 = 0.7621, capped at 1.0.
Maximum position size = 0.7621 (76.2% of portfolio). | {
"var_99": -0.131222,
"expected_loss": 0.131222,
"max_drawdown_threshold": 0.1,
"position_size": 0.7621,
"has_text": false,
"text_chars": 0
} |
T3_all_20160406_0731 | T3 | 1 | train | sideways | all | [
"USMV"
] | 2016-04-06T00:00:00 | USMV: 60-day history, VaR(99%)=-0.0157, max drawdown threshold=10%. | Asset: USMV
Daily returns (past 60 days): mean=0.0013, std=0.0082, worst_day=-0.0159
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2016-04-05] ["Apple is about to get a lot more of your money Average user predicted to top $100 on services like Apple Music by 2020, an 85%... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0157 (i.e., a 1.57% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0157 = 6.3537, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.015739,
"expected_loss": 0.015739,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20201211_0734 | T3 | 1 | train | sideways | all | [
"XRP-USD"
] | 2020-12-11T00:00:00 | XRP-USD: 60-day history, VaR(99%)=-0.1355, max drawdown threshold=10%. | Asset: XRP-USD
Daily returns (past 60 days): mean=0.0145, std=0.0760, worst_day=-0.1612
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... | 0.7383 | 0.7383 | Step 1: Compute |VaR(99%)| from historical returns = 0.1355 (i.e., a 13.55% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1355 = 0.7383, capped at 1.0.
Maximum position size = 0.7383 (73.8% of portfolio). | {
"var_99": -0.135453,
"expected_loss": 0.135453,
"max_drawdown_threshold": 0.1,
"position_size": 0.7383000000000001,
"has_text": false,
"text_chars": 0
} |
T3_all_20170403_0736 | T3 | 1 | train | sideways | all | [
"XHB"
] | 2017-04-03T00:00:00 | XHB: 60-day history, VaR(99%)=-0.0139, max drawdown threshold=10%. | Asset: XHB
Daily returns (past 60 days): mean=0.0012, std=0.0082, worst_day=-0.0158
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 = 0.0139 (i.e., a 1.39% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0139 = 7.2070, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.013875,
"expected_loss": 0.013875,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20160624_0738 | T3 | 1 | train | sideways | all | [
"MORT"
] | 2016-06-24T00:00:00 | MORT: 60-day history, VaR(99%)=-0.0192, max drawdown threshold=10%. | Asset: MORT
Daily returns (past 60 days): mean=0.0010, std=0.0077, worst_day=-0.0282
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0192 (i.e., a 1.92% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0192 = 5.1996, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.019232,
"expected_loss": 0.019232,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20191218_0740 | T3 | 1 | train | sideways | all | [
"ETH-USD"
] | 2019-12-18T00:00:00 | ETH-USD: 60-day history, VaR(99%)=-0.0816, max drawdown threshold=10%. | Asset: ETH-USD
Daily returns (past 60 days): mean=-0.0053, std=0.0313, worst_day=-0.0824
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 ... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0816 (i.e., a 8.16% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0816 = 1.2257, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.081589,
"expected_loss": 0.081589,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20200224_0742 | T3 | 1 | train | sideways | all | [
"XLY"
] | 2020-02-24T00:00:00 | XLY: 60-day history, VaR(99%)=-0.0152, max drawdown threshold=10%. | Asset: XLY
Daily returns (past 60 days): mean=0.0014, std=0.0067, worst_day=-0.0154
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-02-21] ["Notable ETF Inflow Detected - MGK, ADBE, MCD, UNP Looking today at week-over-week shares outstanding changes among the universe... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0152 (i.e., a 1.52% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0152 = 6.5873, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.015181,
"expected_loss": 0.015181,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220607_0744 | T3 | 1 | train | sideways | all | [
"VNQ"
] | 2022-06-07T00:00:00 | VNQ: 60-day history, VaR(99%)=-0.0339, max drawdown threshold=10%. | Asset: VNQ
Daily returns (past 60 days): mean=-0.0005, std=0.0146, worst_day=-0.0339
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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.... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0339 (i.e., a 3.39% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0339 = 2.9528, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.033866,
"expected_loss": 0.033866,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20221122_0746 | T3 | 1 | train | sideways | all | [
"XLRE"
] | 2022-11-22T00:00:00 | XLRE: 60-day history, VaR(99%)=-0.0351, max drawdown threshold=10%. | Asset: XLRE
Daily returns (past 60 days): mean=-0.0027, std=0.0169, worst_day=-0.0375
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-11-21] ["Should Vanguard Mega Cap ETF (MGC) Be on Your Investing Radar? If you're interested in broad exposure to the Large Cap Blend ... | 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 = 2.8513, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.035072,
"expected_loss": 0.035072,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20200908_0749 | T3 | 1 | train | sideways | all | [
"VLUE"
] | 2020-09-08T00:00:00 | VLUE: 60-day history, VaR(99%)=-0.0289, max drawdown threshold=10%. | Asset: VLUE
Daily returns (past 60 days): mean=0.0011, std=0.0123, worst_day=-0.0315
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-09-04] ["Asian markets slide, following Wall Street\u2019s tumble Stocks fall in Tokyo, Hong Kong, Seoul Asian markets skidded Friday a... | 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 = 3.4649, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.028860999999999998,
"expected_loss": 0.028860999999999998,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20180907_0751 | T3 | 1 | train | sideways | all | [
"FXI"
] | 2018-09-07T00:00:00 | FXI: 60-day history, VaR(99%)=-0.0319, max drawdown threshold=10%. | Asset: FXI
Daily returns (past 60 days): mean=-0.0022, std=0.0149, worst_day=-0.0356
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2018-09-06] ["7 Lucrative Biotech Stocks With Up to 300% Upside InvestorPlace - Stock Market News, Stock Advice & Trading Tips Forget market... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0319 (i.e., a 3.19% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0319 = 3.1344, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.031904,
"expected_loss": 0.031904,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20151005_0753 | T3 | 1 | train | sideways | all | [
"XLU"
] | 2015-10-05T00:00:00 | XLU: 60-day history, VaR(99%)=-0.0323, max drawdown threshold=10%. | Asset: XLU
Daily returns (past 60 days): mean=0.0005, std=0.0116, worst_day=-0.0339
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2015-10-02] ["Micron Jumps On Q4 Beat But Is Down From Year Ago", "Analog Devices' Rating Upped by Citi; Target Price Reiterated", "Micron Ju... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0323 (i.e., a 3.23% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0323 = 3.0987, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.032271,
"expected_loss": 0.032271,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220902_0755 | T3 | 1 | train | sideways | all | [
"VNQ"
] | 2022-09-02T00:00:00 | VNQ: 60-day history, VaR(99%)=-0.0294, max drawdown threshold=10%. | Asset: VNQ
Daily returns (past 60 days): mean=-0.0006, std=0.0137, worst_day=-0.0339
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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.... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0294 (i.e., a 2.94% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0294 = 3.4018, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.029396,
"expected_loss": 0.029396,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20190218_0757 | T3 | 1 | train | sideways | all | [
"ETH-USD"
] | 2019-02-18T00:00:00 | ETH-USD: 60-day history, VaR(99%)=-0.1287, max drawdown threshold=10%. | Asset: ETH-USD
Daily returns (past 60 days): mean=0.0059, std=0.0572, worst_day=-0.1471
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... | 0.7770 | 0.777 | Step 1: Compute |VaR(99%)| from historical returns = 0.1287 (i.e., a 12.87% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1287 = 0.7770, capped at 1.0.
Maximum position size = 0.7770 (77.7% of portfolio). | {
"var_99": -0.128707,
"expected_loss": 0.128707,
"max_drawdown_threshold": 0.1,
"position_size": 0.777,
"has_text": false,
"text_chars": 0
} |
T3_all_20200417_0759 | T3 | 1 | train | sideways | all | [
"ADA-USD"
] | 2020-04-17T00:00:00 | ADA-USD: 60-day history, VaR(99%)=-0.1446, max drawdown threshold=10%. | Asset: ADA-USD
Daily returns (past 60 days): mean=-0.0028, std=0.0645, 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 ... | 0.6918 | 0.6918 | Step 1: Compute |VaR(99%)| from historical returns = 0.1446 (i.e., a 14.46% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1446 = 0.6918, capped at 1.0.
Maximum position size = 0.6918 (69.2% of portfolio). | {
"var_99": -0.14455099999999999,
"expected_loss": 0.14455099999999999,
"max_drawdown_threshold": 0.1,
"position_size": 0.6918000000000001,
"has_text": false,
"text_chars": 0
} |
T3_all_20210817_0761 | T3 | 1 | train | sideways | all | [
"ACWI"
] | 2021-08-17T00:00:00 | ACWI: 60-day history, VaR(99%)=-0.0141, max drawdown threshold=10%. | Asset: ACWI
Daily returns (past 60 days): mean=0.0008, std=0.0056, worst_day=-0.0153
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-08-16] ["C3 Global Services & IKG Global Consultants Form Strategic Partnership to Promote Healthcare Education and Exports The mission... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0141 (i.e., a 1.41% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0141 = 7.0780, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.014128,
"expected_loss": 0.014128,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20220701_0763 | T3 | 1 | train | sideways | all | [
"DBC"
] | 2022-07-01T00:00:00 | DBC: 60-day history, VaR(99%)=-0.0293, max drawdown threshold=10%. | Asset: DBC
Daily returns (past 60 days): mean=0.0001, std=0.0146, worst_day=-0.0293
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0293 (i.e., a 2.93% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0293 = 3.4171, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.029265,
"expected_loss": 0.029265,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20210201_0766 | T3 | 1 | train | sideways | all | [
"SOL-USD"
] | 2021-02-01T00:00:00 | SOL-USD: 60-day history, VaR(99%)=-0.1934, max drawdown threshold=10%. | Asset: SOL-USD
Daily returns (past 60 days): mean=0.0156, std=0.0994, worst_day=-0.1969
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... | 0.5171 | 0.5171 | Step 1: Compute |VaR(99%)| from historical returns = 0.1934 (i.e., a 19.34% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1934 = 0.5171, capped at 1.0.
Maximum position size = 0.5171 (51.7% of portfolio). | {
"var_99": -0.193385,
"expected_loss": 0.193385,
"max_drawdown_threshold": 0.1,
"position_size": 0.5171,
"has_text": false,
"text_chars": 0
} |
T3_all_20220125_0768 | T3 | 1 | train | sideways | all | [
"VTI"
] | 2022-01-25T00:00:00 | VTI: 60-day history, VaR(99%)=-0.0219, max drawdown threshold=10%. | Asset: VTI
Daily returns (past 60 days): mean=-0.0008, std=0.0102, worst_day=-0.0219
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-01-24] ["Buy Smart With Software Stocks on the Dip InvestorPlace - Stock Market News, Stock Advice & Trading Tips Technology stocks are... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0219 (i.e., a 2.19% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0219 = 4.5664, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.021899,
"expected_loss": 0.021899,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20201002_0770 | T3 | 1 | train | sideways | all | [
"USO"
] | 2020-10-02T00:00:00 | USO: 60-day history, VaR(99%)=-0.0478, max drawdown threshold=10%. | Asset: USO
Daily returns (past 60 days): mean=-0.0013, std=0.0181, worst_day=-0.0617
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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.... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0478 (i.e., a 4.78% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0478 = 2.0919, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.047804,
"expected_loss": 0.047804,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20220412_0772 | T3 | 1 | train | sideways | all | [
"ADA-USD"
] | 2022-04-12T00:00:00 | ADA-USD: 60-day history, VaR(99%)=-0.1034, max drawdown threshold=10%. | Asset: ADA-USD
Daily returns (past 60 days): mean=-0.0027, std=0.0464, worst_day=-0.1071
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-04-11]
Determine the maximum fraction of total portfolio capital that should be allocated to ADA-USD, given the drawdown constrai... | 0.9671 | 0.9671 | Step 1: Compute |VaR(99%)| from historical returns = 0.1034 (i.e., a 10.34% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1034 = 0.9671, capped at 1.0.
Maximum position size = 0.9671 (96.7% of portfolio). | {
"var_99": -0.10340099999999999,
"expected_loss": 0.10340099999999999,
"max_drawdown_threshold": 0.1,
"position_size": 0.9671000000000001,
"has_text": true,
"text_chars": 20
} |
T3_all_20211101_0773 | T3 | 1 | train | sideways | all | [
"XRP-USD"
] | 2021-11-01T00:00:00 | XRP-USD: 60-day history, VaR(99%)=-0.1519, max drawdown threshold=10%. | Asset: XRP-USD
Daily returns (past 60 days): mean=-0.0005, std=0.0490, worst_day=-0.1902
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2021-10-29]
Determine the maximum fraction of total portfolio capital that should be allocated to XRP-USD, given the drawdown constrai... | 0.6585 | 0.6585 | Step 1: Compute |VaR(99%)| from historical returns = 0.1519 (i.e., a 15.19% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1519 = 0.6585, capped at 1.0.
Maximum position size = 0.6585 (65.8% of portfolio). | {
"var_99": -0.151871,
"expected_loss": 0.151871,
"max_drawdown_threshold": 0.1,
"position_size": 0.6585000000000001,
"has_text": true,
"text_chars": 20
} |
T3_all_20190522_0775 | T3 | 1 | train | sideways | all | [
"UNG"
] | 2019-05-22T00:00:00 | UNG: 60-day history, VaR(99%)=-0.0270, max drawdown threshold=10%. | Asset: UNG
Daily returns (past 60 days): mean=-0.0014, std=0.0124, worst_day=-0.0297
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.... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0270 (i.e., a 2.70% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0270 = 3.6997, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.027028999999999997,
"expected_loss": 0.027028999999999997,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20220411_0777 | T3 | 1 | train | sideways | all | [
"SLV"
] | 2022-04-11T00:00:00 | SLV: 60-day history, VaR(99%)=-0.0308, max drawdown threshold=10%. | Asset: SLV
Daily returns (past 60 days): mean=0.0013, std=0.0148, worst_day=-0.0322
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine the maximum fraction of total portfolio capital that should be allocated to SLV, given the drawdown constraint. Report as a decimal between 0.00 and 1.00 (e.g... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0308 (i.e., a 3.08% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0308 = 3.2507, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.030763,
"expected_loss": 0.030763,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20200916_0779 | T3 | 1 | train | sideways | all | [
"BNB-USD"
] | 2020-09-16T00:00:00 | BNB-USD: 60-day history, VaR(99%)=-0.1428, max drawdown threshold=10%. | Asset: BNB-USD
Daily returns (past 60 days): mean=0.0091, std=0.0509, worst_day=-0.1649
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Determine 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... | 0.7001 | 0.7001 | Step 1: Compute |VaR(99%)| from historical returns = 0.1428 (i.e., a 14.28% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1428 = 0.7001, capped at 1.0.
Maximum position size = 0.7001 (70.0% of portfolio). | {
"var_99": -0.142836,
"expected_loss": 0.142836,
"max_drawdown_threshold": 0.1,
"position_size": 0.7001000000000001,
"has_text": false,
"text_chars": 0
} |
T3_all_20220509_0781 | T3 | 1 | train | sideways | all | [
"BTC-USD"
] | 2022-05-09T00:00:00 | BTC-USD: 60-day history, VaR(99%)=-0.0698, max drawdown threshold=10%. | Asset: BTC-USD
Daily returns (past 60 days): mean=-0.0031, std=0.0281, worst_day=-0.0787
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2022-05-08]
Determine the maximum fraction of total portfolio capital that should be allocated to BTC-USD, given the drawdown constrai... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0698 (i.e., a 6.98% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0698 = 1.4327, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.069799,
"expected_loss": 0.069799,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 20
} |
T3_all_20171229_0785 | T3 | 1 | train | sideways | all | [
"DBB"
] | 2017-12-29T00:00:00 | DBB: 60-day history, VaR(99%)=-0.0216, max drawdown threshold=10%. | Asset: DBB
Daily returns (past 60 days): mean=0.0009, std=0.0087, worst_day=-0.0230
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 = 0.0216 (i.e., a 2.16% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0216 = 4.6319, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.02159,
"expected_loss": 0.02159,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": false,
"text_chars": 0
} |
T3_all_20201113_0787 | T3 | 1 | train | sideways | all | [
"VTI"
] | 2020-11-13T00:00:00 | VTI: 60-day history, VaR(99%)=-0.0335, max drawdown threshold=10%. | Asset: VTI
Daily returns (past 60 days): mean=0.0010, std=0.0130, worst_day=-0.0335
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-11-12] ["Better Buy: Slack vs. Adobe Slack (NYSE: WORK) and Adobe (NASDAQ: ADBE) are both forward-thinking companies that are changing h... | 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_20171023_0789 | T3 | 1 | train | sideways | all | [
"BTC-USD"
] | 2017-10-23T00:00:00 | BTC-USD: 60-day history, VaR(99%)=-0.1021, max drawdown threshold=10%. | Asset: BTC-USD
Daily returns (past 60 days): mean=0.0072, std=0.0449, 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 1... | 0.9798 | 0.9798 | Step 1: Compute |VaR(99%)| from historical returns = 0.1021 (i.e., a 10.21% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1021 = 0.9798, capped at 1.0.
Maximum position size = 0.9798 (98.0% of portfolio). | {
"var_99": -0.10206599999999999,
"expected_loss": 0.10206599999999999,
"max_drawdown_threshold": 0.1,
"position_size": 0.9798,
"has_text": false,
"text_chars": 0
} |
T3_all_20151113_0791 | T3 | 1 | train | sideways | all | [
"VTI"
] | 2015-11-13T00:00:00 | VTI: 60-day history, VaR(99%)=-0.0313, max drawdown threshold=10%. | Asset: VTI
Daily returns (past 60 days): mean=-0.0004, std=0.0131, worst_day=-0.0335
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2015-11-12] How NVIDIA Corporation Gained 15% in October NVDA data by YCharts . What: Shares of NVIDIA gained 15% in October, according to d... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0313 (i.e., a 3.13% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0313 = 3.1955, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.031293999999999995,
"expected_loss": 0.031293999999999995,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20170920_0793 | T3 | 1 | train | sideways | all | [
"^VIX"
] | 2017-09-20T00:00:00 | ^VIX: 60-day history, VaR(99%)=-0.1635, max drawdown threshold=10%. | Asset: ^VIX
Daily returns (past 60 days): mean=-0.0014, std=0.0789, worst_day=-0.1825
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2017-09-19] ["18 Stocks to Capture the Next Tech Boom Janus Henderson Global Technology trounces its peers with big stocks like Alphabet an... | 0.6118 | 0.6118 | Step 1: Compute |VaR(99%)| from historical returns = 0.1635 (i.e., a 16.35% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1635 = 0.6118, capped at 1.0.
Maximum position size = 0.6118 (61.2% of portfolio). | {
"var_99": -0.163455,
"expected_loss": 0.163455,
"max_drawdown_threshold": 0.1,
"position_size": 0.6118,
"has_text": true,
"text_chars": 3020
} |
T3_all_20200529_0795 | T3 | 1 | train | sideways | all | [
"FXI"
] | 2020-05-29T00:00:00 | FXI: 60-day history, VaR(99%)=-0.0438, max drawdown threshold=10%. | Asset: FXI
Daily returns (past 60 days): mean=0.0005, std=0.0249, worst_day=-0.0438
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-05-28] ["Tweedy Browne's \u2014\u2026\u2014\u2026 Annual Letter to Shareholders", "The Momentum Trade Driving Stocks Higher May Be About... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0438 (i.e., a 4.38% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0438 = 2.2811, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.043838999999999996,
"expected_loss": 0.043838999999999996,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20200630_0797 | T3 | 1 | train | sideways | all | [
"IWM"
] | 2020-06-30T00:00:00 | IWM: 60-day history, VaR(99%)=-0.0371, max drawdown threshold=10%. | Asset: IWM
Daily returns (past 60 days): mean=0.0035, std=0.0238, worst_day=-0.0371
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2020-06-29] ["Notable Monday Option Activity: NKE, AMD, HLT Among the underlying components of the S&P 500 index, we saw noteworthy options t... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0371 (i.e., a 3.71% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0371 = 2.6978, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.037066999999999996,
"expected_loss": 0.037066999999999996,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20190114_0799 | T3 | 1 | train | sideways | all | [
"MTUM"
] | 2019-01-14T00:00:00 | MTUM: 60-day history, VaR(99%)=-0.0353, max drawdown threshold=10%. | Asset: MTUM
Daily returns (past 60 days): mean=-0.0014, std=0.0179, worst_day=-0.0383
Maximum acceptable portfolio drawdown: 10%
Market regime: sideways
Recent filing/news:
[Kaggle 2019-01-11] ["Friday's ETF with Unusual Volume: SIZE The iShares Edge MSCI USA Size Factor ETF is seeing unusually high volume in afternoon... | 1.0000 | 1 | Step 1: Compute |VaR(99%)| from historical returns = 0.0353 (i.e., a 3.53% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.0353 = 2.8303, capped at 1.0.
Maximum position size = 1.0000 (100.0% of portfolio). | {
"var_99": -0.035331999999999995,
"expected_loss": 0.035331999999999995,
"max_drawdown_threshold": 0.1,
"position_size": 1,
"has_text": true,
"text_chars": 3020
} |
T3_all_20210104_0801 | T3 | 1 | train | sideways | all | [
"MATIC-USD"
] | 2021-01-04T00:00:00 | MATIC-USD: 60-day history, VaR(99%)=-0.1731, max drawdown threshold=10%. | Asset: MATIC-USD
Daily returns (past 60 days): mean=0.0103, std=0.0653, worst_day=-0.1846
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... | 0.5778 | 0.5778 | Step 1: Compute |VaR(99%)| from historical returns = 0.1731 (i.e., a 17.31% loss in the worst 1% of days).
Step 2: Fixed-fractional formula: f* = 10% / 0.1731 = 0.5778, capped at 1.0.
Maximum position size = 0.5778 (57.8% of portfolio). | {
"var_99": -0.173072,
"expected_loss": 0.173072,
"max_drawdown_threshold": 0.1,
"position_size": 0.5778,
"has_text": false,
"text_chars": 0
} |
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