Notes

A news scan found the following data: a descriptive trade-mark replay, not executable validation, shows the results of a trading simulation. The simulation used the following parameters: phase is holdout known calendar, block is 3, sample is 1, paths is 20000, opportunities is 20, cash percentiles are 272.05464052287596, 272.05464052287596, and 272.05464052287596, loss probability percent is 0, median drawdown percent is 0, cash below ticket percent is 0, mean tickets is 20, and p95 loss streak is 0. This simulation used vectorbt return and drawdown with one contract per event and a $1000 initial investment, with normalized reinvest permitting fractional contracts, which are not available live. The simulation also used MC25USD constant all-in exposure, scaling empirical costed returns, not quoted 20 premium plus 5 cost, and a block 3 circular bootstrap. The known-calendar holdout is not an independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A news scan found the following data: the phase is holdout known calendar, block 1, sample 1, with 20000 paths and 20 opportunities. The cash percentiles are 272.05464052287596, 272.05464052287596, and 272.05464052287596. The loss probability percentage is 0, the median drawdown percentage is 0, and the cash below ticket percentage is 0. The mean tickets are 20 and the 95th percentile loss streak is 0. This is a descriptive trade mark replay, not an executable validation, using vectorbt return and drawdown with one contract per event and a $1000 initial investment. The returns are normalized and reinvested, allowing for fractional contracts, but this is not available in live trading. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. This uses a block 3 circular bootstrap method. The known-calendar holdout is not an independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade replay for SFIX shows the following statistics: the model is in the train phase, block 3, sample 6, with 20,000 paths and 20 opportunities. The cash percentiles are 85.36, 123.58, and 165.36. The loss probability is 18.56% and the median drawdown is 15.60%. The mean number of tickets is 20 and the 95th percentile loss streak is 4. This data is based on a vectorbt return and drawdown analysis, with one contract per event and an initial investment of $1000. The analysis uses a normalized reinvest approach, allowing for fractional contracts, and assumes a constant all-in exposure of $25 USD, with empirical costed returns. Note that the block 3 circular bootstrap method is used, and the known-calendar holdout is not independent. Additionally, near-zero floating returns may affect the loss streak figure, so it should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A news scan found the following data: this is a descriptive trade mark replay, not an executable validation. It uses a vectorbt return and drawdown with one contract per event and a $1000 initial investment, with normalized reinvest that permits fractional contracts, which are unavailable live. The data includes the following information: the phase is train, the block is 1, the sample is 6, the paths are 20000, the opportunities are 20, the cash percentiles are 66.44055749128917, 123.58341463414632, and 185.01198606271785, the loss probability percentage is 26.790000000000003, the median drawdown percentage is 19.58480219349784, the cash below ticket percentage is 0.305, the mean tickets are 19.98885, and the 95th percentile loss streak is 7. The MC25USD has a constant all-in exposure that scales empirical costed returns, not quoted 20 premium plus 5 cost. The block 3 circular bootstrap is used. The known-calendar holdout is not independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A news scan found the following data line: a descriptive trade-mark replay, not executable validation, shows the results of a trading strategy. The strategy has a group called RSI_ge50, which means a measure of how overbought or oversold a stock is, and it has a sample size of 4. The return is -2.4, the drawdown, which is the largest decrease in value, is 2.64, and the win rate, which is the percentage of winning trades, is 0. The mean ticket return percentage, which is the average return per trade, is -14.63, and the normalized reinvest return percentage, which is the return if the profits were reinvested, is -51.12. The normalized drawdown percentage, which is the largest decrease in value if the profits were reinvested, is 51.12. There were 0 close 4x hits, which means the trade did not close with a profit 4 times the initial investment, and 0 close half hits, which means the trade did not close with a profit half the size of the initial investment. The trade was affordable 1 time. The results are based on a $1000 initial investment, with one contract per event, and the returns are normalized to permit fractional contracts, which are not available in live trading. The exposure is scaled to $25 USD constant, and the returns are costed, meaning they include the cost of trading, not just the quoted price plus a 20% premium and a 5% cost. The results also use a block 3 circular bootstrap, which is a method of estimating the results. The known-calendar holdout, which is a way of testing the strategy, is not independent discovery. The near-zero floating returns may affect the loss streak, so the loss streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A news scan found the following data: a group called RSI_lt50 has a sample size of 2, a return of 1.5, a drawdown of 0.296589223924848, and a win rate of 100. The mean ticket return percentage is 42.85714285714286, the normalized reinvest return percentage is 100.08163265306122, and the normalized drawdown percentage is 0. There are 0 close 4x hits and 0 close half hits, with 2 normal affordable instances. This is a descriptive trade-mark replay, not an executable validation, using vectorbt return and drawdown with one contract per event and a $1000 initial investment. The normalized reinvest permits fractional contracts, which are unavailable live. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. It uses a block 3 circular bootstrap. The known-calendar holdout is not an independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade replay for SFIX, not for validation, shows the following results: the group is below 50, the sample size is 2, the return is 1.5, and the drawdown is 0.296589223924848. The win rate is 100, the mean ticket return percentage is 42.85714285714286, the normalized reinvest return percentage is 100.08163265306122, and the normalized drawdown percentage is 0. There are 0 close 4x hits and 0 close half hits, with 2 normal affordable trades. This data is based on a vectorbt return and drawdown calculation, using one contract per event and a $1000 initial investment, with normalized reinvest allowing for fractional contracts, which are not available in live trading. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. A block 3 circular bootstrap was used, and the known-calendar holdout is not an independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade replay for SFIX, which is not executable validation, shows the following results: the group is above 50, the sample size is 4, the return is -2.4, the drawdown is 2.6433915211969694, the win rate is 0, the mean ticket return percentage is -14.634146341463413, the normalized reinvest return percentage is -51.1219512195122, and the normalized drawdown percentage is 51.1219512195122. There are 0 close 4x hits and 0 close half hits, and it is normally affordable. This replay uses vectorbt return and drawdown with one contract per event, a $1000 initial investment, and normalized reinvest, which allows for fractional contracts that are not available live. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. A block 3 circular bootstrap is used, and the known-calendar holdout is not independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade replay, not executable validation, shows the following results: the group is all, the sample size is 6, the return is -0.9, the drawdown is 2.86, the win rate is 33.33%, the mean ticket return percentage is 4.53, the normalized reinvest return percentage is -2.20, and the normalized drawdown percentage is 51.12. The number of close 4x hits is 0, and the number of close half hits is 0, with 3 normal affordable instances. This replay uses a vectorbt return and drawdown calculation, with one contract per event and an initial investment of $1000. The normalized reinvest return allows for fractional contracts, which are not available in live trading. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. A block 3 circular bootstrap is used, and the known-calendar holdout is not independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade replay for SFIX, which is not executable, shows the following results: the lag is 5, the phase is train_common, the cost is 0.1, the sample is 6, the return is -4.3, and the drawdown is 4.985044865403776. The win rate is 0, the mean ticket return percentage is -21.175947114162224, the normalized reinvest return percentage is -87.24007561436673, and the normalized drawdown percentage is 87.24007561436673. There are 0 close 4x hits and 0 close half hits, with 4 normal affordable instances. This data is based on a vectorbt return and drawdown calculation, with one contract per event and an initial investment of $1000. The normalized reinvest return allows for fractional contracts, which are not available in live trading. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. A block 3 circular bootstrap was used, and the known-calendar holdout is not independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade mark replay, not executable validation, shows the following results: the lag is 5, the phase is train common, the cost is 0.05, the sample is 6, the return is -1.3, the drawdown is 2.486325211337659, the win rate is 50, the mean ticket return percentage is -5.645198718054145, the normalized reinvest return percentage is -52.86987615940042, and the normalized drawdown percentage is 63.41463414634146. There are 0 close 4x hits and 0 close half hits, with 4 normal affordable instances. This data is based on a vectorbt return and drawdown of one contract per event, with an initial investment of $1000. The normalized reinvest return permits fractional contracts, which are not available in live trading. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. A block 3 circular bootstrap was used, and the known-calendar holdout is not independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade mark replay for SFIX, which is not executable validation, shows the following results: the lag is 5, the phase is holdout known calendar, the cost is 0.1, the sample is 1, the return is 1.6, the drawdown is 1.0000000000000009, the win rate is 100, the mean ticket return percentage is 19.047619047619047, the normalized reinvest return percentage is 19.047619047619047, and the normalized drawdown percentage is 0. The close 4x hits and close half hits are both 0, and the normal affordable is 0. This data is based on a vectorbt return and drawdown of one contract per event, with an initial investment of $1000. The normalized reinvest permits fractional contracts, which are not available live. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. The block 3 circular bootstrap is used. The known-calendar holdout is not independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade replay for SFIX shows the following results: the lag is 5, the phase is holdout known calendar, the cost is 0.05, the sample is 1, the return is 2.1, the drawdown is 0.9975062344139696, the win rate is 100, the mean ticket return percentage is 25.766871165644172, the normalized reinvest return percentage is 25.76687116564418, and the normalized drawdown percentage is 0. The close 4x hits and close half hits are both 0, and the normal affordable is 0. This is a descriptive trade-mark replay, not an executable validation, using vectorbt return and drawdown with one contract per event and a $1000 initial investment. The normalized reinvest permits fractional contracts, which are unavailable live. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. The block 3 circular bootstrap is used. The known-calendar holdout is not an independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade mark replay, not executable validation, shows the following results: the lag is 5, the phase is train, the cost is 0.1, the sample is 7, the return is -5.5, the drawdown is 6.181455633100685, the win rate is 0, the mean ticket return percentage is -23.04877099581251, the normalized reinvest return percentage is -91.61490683229813, and the normalized drawdown percentage is 91.61490683229813. The number of close 4x hits is 0 and the number of close half hits is 0. This data is based on a vectorbt return and drawdown calculation, with one contract per event and an initial investment of $1000. The normalized reinvest return percentage allows for fractional contracts, which are not available in live trading. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. A block 3 circular bootstrap was used, and the known-calendar holdout is not an independent discovery. Note that near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade replay for SFIX shows the following results: the lag is 5, the phase is train, the cost is 0.05, the sample size is 7, the return is -2, and the drawdown is 3.182496270512214. The win rate is 42.857142857142854 percent, the mean ticket return percentage is -7.9156648352552, the normalized reinvest return percentage is -63.020979755837246, and the normalized drawdown percentage is 70.92673520583371. There are 0 close 4x hits and 0 close half hits, with 4 normal affordable trades. This is a descriptive trade-mark replay, not an executable validation, using vectorbt return and drawdown with one contract per event and a $1000 initial investment. The normalized reinvest return permits fractional contracts, which are not available live. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. A block 3 circular bootstrap was used. The known-calendar holdout is not an independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade mark replay, not executable validation, shows the following results: the lag is 3, the phase is train common, the cost is 0.1, the sample is 6, the return is -3.9, the drawdown is 5.153617443012903, the win rate is 16.666666666666664, the mean ticket return percentage is -15.218253968253967, the normalized reinvest return percentage is -76.18214285714285, and the normalized drawdown percentage is 81.67857142857142. There are 0 close 4x hits and 0 close half hits, with 3 normal affordable instances. This data is based on a vectorbt return and drawdown of one contract per event, with a $1000 initial investment, and normalized reinvest permits fractional contracts, which are unavailable live. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost, using a block 3 circular bootstrap method. The known-calendar holdout is not independent discovery, and near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade mark replay, not executable validation, shows the following results: the lag is 3, the phase is train common, the cost is 0.05, the sample is 6, the return is -0.9, the drawdown is 2.86, and the win rate is 33.33%. The mean ticket return percentage is 4.53, the normalized reinvest return percentage is -2.20, and the normalized drawdown percentage is 51.12. There are 0 close 4x hits and 0 close half hits, with 3 normal affordable instances. This data is based on a vectorbt return and drawdown of one contract per event, with a $1000 initial investment. The normalized reinvest permits fractional contracts, which are not available live. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. A block 3 circular bootstrap was used. The known-calendar holdout is not independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade mark replay for SFIX, which is not executable validation, shows the following results: the lag is 3, the phase is holdout known calendar, the cost is 0.1, the sample is 1, the return is 2.1, the drawdown is 0, and the win rate is 100. The mean ticket return percentage is 26.58227848101266, the normalized reinvest return percentage is 26.582278481012665, and the normalized drawdown percentage is 0. There are 0 close 4x hits and 0 close half hits, and the normal affordable amount is 0. This data is based on a vectorbt return and drawdown of one contract per event, with an initial investment of $1000. The normalized reinvest return allows for fractional contracts, which are not available in live trading. The MC25USD constant all-in exposure scales empirical costed returns, which does not include a 20 premium and 5 cost. A block 3 circular bootstrap was used. The known-calendar holdout is not an independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A news scan found the following data line: a descriptive trade-mark replay for SFIX, not executable validation. The replay has the following parameters: a lag of 3, a phase of holdout known calendar, a cost of 0.05, a sample of 1, a return of 2.6, a drawdown of 0, a win rate of 100, a mean ticket return percentage of 33.98692810457517, a normalized reinvest return percentage of 33.98692810457518, a normalized drawdown percentage of 0, close 4x hits of 0, and close half hits of 0. The replay uses a vectorbt return and drawdown of one contract per event, with an initial investment of $1000. The normalized reinvest return permits fractional contracts, which are not available in live trading. The MC25USD has a constant all-in exposure that scales empirical costed returns, not quoted 20 premium plus 5 cost. The block 3 circular bootstrap is used. The known-calendar holdout is not an independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A news scan found the following trade data: the lag is 3, the phase is train, the cost is 0.1, the sample is 6, the return is -3.9, the drawdown is 5.153617443012903, the win rate is 16.666666666666664, the mean ticket return percentage is -15.218253968253967, the normalized reinvest return percentage is -76.18214285714285, and the normalized drawdown percentage is 81.67857142857142. This data also includes the number of close 4x hits, which is 0, and the number of close half hits, which is 0, and the number of normal affordable trades, which is 3. This is a descriptive trade-mark replay, not an executable validation, using vectorbt return and drawdown with one contract per event and a $1000 initial investment. The normalized reinvest return permits fractional contracts, which are not available in live trading. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. The block 3 circular bootstrap is used. The known-calendar holdout is not independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade replay for SFIX, which is not executable validation, shows the following results: the lag is 3, the phase is train, the cost is 0.05, and the sample is 6. The return is -0.9, the drawdown is 2.86, and the win rate is 33.33%. The mean ticket return percentage is 4.53, the normalized reinvest return percentage is -2.20, and the normalized drawdown percentage is 51.12. There are 0 close 4x hits and 0 close half hits, with 3 normal affordable instances. This data is based on a vectorbt return and drawdown calculation, with one contract per event and a $1000 initial investment. The normalized reinvest return allows for fractional contracts, which are not available in live trading. The MC25USD constant all-in exposure scales the empirical costed returns, which does not include a 20% premium and 5% cost. A block 3 circular bootstrap was used, and the known-calendar holdout is not independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A news scan found the following data line: a trading fund manager's notes show a grid row with specific values. The notes include a lag of 2, a phase of train_common, a cost of 0.1, a sample of 6, a return of -5.3, and a drawdown of 4.82412060301507. The win rate is 0, the mean ticket return percentage is -27.77540296515629, and the normalized reinvest return percentage is -91.30862022228246. The normalized drawdown percentage is 91.30862022228246, with 0 close 4x hits and 0 close half hits. The notes also mention 2 normal affordable instances. This is a descriptive trade-mark replay, not an executable validation, using vectorbt return and drawdown with one contract per event and a $1000 initial investment. The normalized reinvest permits fractional contracts, which are unavailable live. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. A block 3 circular bootstrap is used, and the known-calendar holdout is not independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade-mark replay, not executable validation, shows the following results: the lag is 2, the phase is train_common, the cost is 0.05, the sample is 6, the return is -2.3, the drawdown is 2.05513784461151, the win rate is 16.666666666666664, the mean ticket return percentage is -14.277006088546418, the normalized reinvest return percentage is -69.00924904889678, and the normalized drawdown percentage is 69.00924904889678. The close 4x hits and close half hits are both 0, and the normal affordable is 2. This data is based on a vectorbt return and drawdown of one contract per event, with an initial investment of $1000. The normalized reinvest return percentage allows for fractional contracts, which are not available in live trading. The MC25USD constant all-in exposure scales empirical costed returns, and does not include a 20 premium and 5 cost. A block 3 circular bootstrap was used, and the known-calendar holdout is not an independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A news scan found the following data: the lag is 2, the phase is holdout known calendar, the cost is 0.1, the sample is 2, the return is 0.6, the drawdown is 1.3725490196078494, the win rate is 50, the mean ticket return percentage is 6.9, the normalized reinvest return percentage is 11.00000000000001, the normalized drawdown percentage is 11.199999999999989, close 4x hits is 0, close half hits is 0, and normal affordable is 0. This is a descriptive trade mark replay, not an executable validation, using vectorbt return and drawdown with one contract per event and a $1000 initial investment. The normalized reinvest permits fractional contracts, which are unavailable live. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost. The block 3 circular bootstrap is used. The known-calendar holdout is not an independent discovery. Near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306

A descriptive trade replay for SFIX shows the following results: the lag is 2, the phase is holdout known calendar, the cost is 0.05, the sample is 2, the return is 1.5999999999999988, the drawdown is 0.8780487804877946, the win rate is 50, the mean ticket return percentage is 12.455562870309414, the normalized reinvest return percentage is 22.54114549045425, and the normalized drawdown percentage is 7.346938775510214. The close 4x hits and close half hits are both 0, and the normal affordable is 0. This replay is not executable validation, but rather a descriptive trade mark replay. The vectorbt return and drawdown are calculated for one contract per event, with a $1000 initial investment, and normalized reinvest permits fractional contracts, which are not available live. The MC25USD constant all-in exposure scales empirical costed returns, not quoted 20 premium plus 5 cost, and uses a block 3 circular bootstrap. The known-calendar holdout is not independent discovery, and near-zero floating returns may affect the loss streak, so the streak figure should not be used. https://runway.adityaperswal.workers.dev/data/option-bars ; research/study.py R91306