This information replaces the original QWIDE91002 swing drawdown data, but the returns, samples, and payoffs remain the same. The strategy involves 50 preset ETF groups, which are only considered at the start of the month if the excess returns versus SHY have been positive for 1, 3, and 12 months. The prior stop loss and target rules were set at 1 and 1.5 times the average daily range, with a half plus one risk management approach, and a stop on the following day with a maximum of 5 sessions. Daily known opening gaps are considered, and the strategy stops at the first ambiguity, with conservative gap-up profits at a certain level, including a 1 basis point fee and a 5 to 15 basis point slip on each side. A custom order cash and vectorbt per-asset final equity reconciliation is done to ensure accuracy, with a tolerance of less than 1e-8. The daily closing equity drawdown avoids using fictional intermediate cross-asset marks and does not include 15-minute or overnight exit validation. The data is split into training, holdout, and separate periods for 2017-2019, 2020-2025, and 2026, with 2016 as a warm-up period. A negative base and stress mean result in an actual Kelly of 0. The source of this data is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all, which provides the following statistics: the family is swing, the era is 2026, the cost side is 0.0016, the return is -1.6856, the drawdown is -2.6516, the win rate is 51.16, the sample size is 215, the average win percentage is 1.1626, the average loss percentage is 2.021, the mean trade percentage is -0.3922, the quarter Kelly diagnostic is 0, the monthly clusters are 9, the mean holding is 2.3535, and the vectorbt reconciled value is true, with a drawdown basis of daily closing equity.
This report replaces the original QWIDE91002 swing drawdown field, with the same returns, samples, and payoffs. It considers 50 preset ETF sleeves, only opening in the first month when excess returns versus SHY are all positive for 1, 3, and 12 months. The prior 20 ADR stop is 1, with a target of 1.5, and half of the profit is taken, with a 5-session maximum. Daily known opening gaps are then stopped at the first ambiguity, with conservative gap-up profits at level; a 1bp fee and 5/15bps lip on each side. Custom order cash and vectorbt per asset final equity reconcile to less than 1e-8. The daily closing equity drawdown avoids fictional intermediate cross-asset marks, without 15-minute or overnight exit validation. The data is trained from 2017-2019, with a holdout from 2020-2025, and a separate period in 2026, with a warmup in 2016. A negative base and stress mean result in an actual Kelly of 0. The source is a data feed from https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. The report includes the following metrics: family is swing, era is holdout, cost side is 0.0016, return is -8.228292501395773, drawdown is -8.965794696909146, win rate is 43.82566585956417, sample is 1239, average win percentage is 0.9965922379632003, average loss percentage is 1.39147340747158, mean trade percentage is -0.3448877371962889, quarter Kelly diagnostic is 0, monthly clusters is 72, mean holding is 2.4624697336561745, and vectorbt reconciled is true, with a drawdown basis of daily closing equity.
This report replaces the original QWIDE91002 swing drawdown report, with no changes to returns, samples, or payoffs. It uses 50 preset ETF sleeves, only opening in the first month when excess returns versus SHY are all positive for 1, 3, and 12 months. The prior 20 ADR stop is 1, with a target of 1.5, and half plus 1R, with a stop on the first ambiguity and a maximum of 5 sessions. A 1 basis point fee and 5/15 basis points lip on each side are applied. Custom order cash and vectorbt per asset final equity reconcile to less than 1e-8. Daily closing equity drawdown avoids fictional intermediate cross-asset marks, with no 15-minute or overnight exit validation. The train period is 2017-2019, holdout is 2020-2025, and 2026 is separate, with 2016 as a warmup. A negative base and stress mean result in an actual Kelly of 0. The source is a data feed from https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. The report includes the following metrics: family is swing, era is train, cost side is 0.0016, return is -5.3426, drawdown is -5.3534, win rate is 37.09, sample is 709, average win percentage is 0.6389, average loss percentage is 0.9928, mean trade percentage is -0.3875, quarter Kelly diagnostic is 0, monthly clusters is 34, mean holding is 2.3413, and vectorbt reconciled is true, with a drawdown basis of daily closing equity.
This report replaces the original QWIDE91002 swing drawdown report, with no changes to returns, samples, or payoffs. The strategy involves 50 preset ETF sleeves, which are only open in the first month if the excess returns versus SHY are all positive for the last 1, 3, and 12 months. The prior stop loss is set at 1 times the average daily range, with a target of 1.5 times, and half of the position is closed with a 1 times risk reward ratio, with the remaining position closed the following day, with a maximum of 5 sessions. Daily known opening gaps are then used to determine the stop loss, with gap up profits being conservative at the 1 basis point level; a 1 basis point fee is charged, plus a 5 to 15 basis point slippage on each side. Custom orders and vectorbt per asset final equity are reconciled to less than 1e-8. The daily closing equity drawdown avoids fictional intermediate cross-asset marks and does not include 15-minute or overnight exit validation. The data is trained from 2017 to 2019, held out from 2020 to 2025, and separate data is used for 2026, with 2016 used as a warm-up period. The negative base and stress mean result in an actual Kelly criterion of 0. A news scan found the source https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. The report includes the following metrics: family is swing, era is 2026, cost side is 0.0006, return is -0.837390516077452, drawdown is -2.4881919392944596, win rate is 52.093023255813954, sample is 215, average win percentage is 1.3435491263306152, average loss percentage is 1.863295064902291, mean trade percentage is -0.19275297458561413, quarter Kelly diagnostic is 0, monthly clusters is 9, mean holding is 2.353488372093023, and vectorbt reconciled is true, with a drawdown basis of daily closing equity.
A news scan found the headline 'QWIDE91002 FINAL swing holdout 5.999999999999999bp daily-close drawdown'. This is a report about an automated trading fund manager's notes. The report supersedes the original matching QWIDE91002 swing drawdown field, with returns, sample, and payoffs unchanged. The fund has 50 preset ETF sleeves, which are only open in the first month when the excess returns versus SHY are all positive for the last 1, 3, and 12 months. The fund uses a prior 20-day ADR stop and a target of 1.5, with half of the position plus one risk unit, and a stop-loss order on the following day, with a maximum of 5 sessions. The fund also considers daily known opening gaps, then stops at the first ambiguity, with gap-up profits being conservative at a certain level, and a 1 basis point fee plus 5/15 basis points lip on each side. Custom order cash and vectorbt per asset final equity reconcile to less than 1e-8. The daily closing equity drawdown avoids fictional intermediate cross-asset marks and does not include 15-minute or overnight exit validation. The fund was trained from 2017 to 2019, with a holdout period from 2020 to 2025, and a separate period in 2026, with a warm-up period in 2016. The negative base and stress mean result in an actual Kelly of 0. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. The fund's performance metrics include a return of -3.5853043981237565, a drawdown of -6.215550347033028, a win rate of 46.48910411622276, a sample size of 1239, an average win percentage of 1.1366843295470295, an average loss percentage of 1.2592056317905695, a mean trade percentage of -0.14537785315420393, a quarter Kelly diagnostic of 0, monthly clusters of 72, a mean holding period of 2.4624697336561745, and vectorbt reconciled set to true, with a drawdown basis of daily closing equity.
A news scan found the headline 'QWIDE91002 FINAL swing train 5.999999999999999bp daily-close drawdown'. This replaces the original QWIDE91002 swing drawdown field, with the same returns, samples, and payoffs. The system uses 50 preset ETF groups, only opening in the first month when the 1, 3, and 12-month excess returns versus SHY are all positive. It stops after a 20-day ADR, targets 1.5, and halves the position after a 1R return, with a maximum of 5 sessions. The system also stops when there is ambiguity in the daily opening gaps, and it takes profits conservatively at a certain level, with a 1bp fee and a 5/15bps lip on each side. The custom order cash and vectorbt per-asset final equity reconcile to less than 1e-8. The daily closing equity drawdown avoids fictional intermediate cross-asset marks, and does not use 15-minute or overnight exit validation. The system was trained from 2017 to 2019, with a holdout period from 2020 to 2025, and a separate period in 2026, with a warmup period in 2016. The negative base and stress mean resulted in an actual Kelly of 0. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. The system's performance metrics are as follows: family is swing, era is train, cost side is 0.0006, return is -2.635043849171137, drawdown is -2.889075180280709, win rate is 42.73624823695346, sample is 709, average win percentage is 0.7446188077803125, average loss percentage is 0.8841538956012193, mean trade percentage is -0.18807754986835026, quarter Kelly diagnostic is 0, monthly clusters is 34, mean holding is 2.3413258110014104, and vectorbt reconciled is true, with a drawdown basis of daily closing equity.
A news scan found the headline 'UNI frozen trend-pullback daily/hourly holdout rejected'. This refers to a trading strategy for the cryptocurrency UNI. The strategy had two conditions to enter a trade: the closing price was higher than the 50-day Simple Moving Average, which is a measure of the average price over 50 days, and the 3-day return was less than 0. The strategy would exit a trade when the previous closing price was higher than the 5-day Simple Moving Average or after 5 calendar days. The strategy used a 1-hour and daily time frame, with specific rules for when to open and close trades. The strategy was tested using historical data from 2025, with a holdout period from January 1, 2026, to September 9, 2024, and a warm-up period in October 2024. The results showed a return of -58.0976% for the hourly time frame and -17.5305% for the daily time frame. The strategy also had a drawdown, which is the maximum loss from a peak to a trough, of 58.8265% for the hourly time frame and 19.0732% for the daily time frame. The win percentage, which is the percentage of trades that were profitable, was 33.0189% for the hourly time frame and 63.6364% for the daily time frame. The strategy was not validated for 15-minute exits or stops and is not deployable. The data was sourced from https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.
A news scan found the headline 'LTC frozen trend-pullback daily/hourly holdout rejected'. This refers to a trading strategy for the cryptocurrency Litecoin (LTC) that was tested and rejected. The strategy was based on two premises: the closing price being higher than the 50-day Simple Moving Average (SMA), and a 3-day return less than 0. The strategy entered the market at the next available bar open when the conditions were met, and exited when the previous close was higher than the 5-day SMA or after 5 calendar days. The hourly window for trading was set at 1200, 72, and 120.2. The strategy used a 25 basis point fee and 10 basis point slippage on each side, with a 20 basis point stress test. The training data was from 2025, with a holdout period from January 1 to September 9, 2024, and an October warm-up period. The results showed a daily return of -19.69% and a hourly return of -49.68%. The daily win rate was 35.71%, while the hourly win rate was 9.64%. The strategy was not validated for 15-minute venue exits or stops, and is not deployable. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.
A news scan found the headline 'HYPE frozen trend-pullback daily/hourly holdout rejected'. This refers to a trading strategy called HYPE that was tested and found not to work. The strategy was based on two premises: when the price of a stock was higher than its average price over the last 50 days and the return over the last 3 days was less than 0, the strategy would enter the market at the next available opening price. The strategy would exit the market when the previous closing price was higher than the average price over the last 5 days or after 5 calendar days. The strategy used a technique called vector backtesting with 25 basis points fees and 10 basis points slippage on each side, and 20 basis points stress. The strategy was trained on data from 2025 and tested on data from 2026 from January 1 to September 9, with a warm-up period in October 2024. The strategy used a cash reset of 100 and would liquidate at the last available opening price. The strategy excluded missing bars and did not fill them for execution or signals. The strategy had distinct daily and hourly patterns. The training data had limits on inference from 1937 and did not include pre-2026 training data for HYPE. The strategy did not validate 15-minute venue exits or stops and was not deployable. The results of the strategy were as follows: for the hourly strategy, the return was -41.19%, the drawdown was 41.61%, and the win percentage was 36.84%. For the daily strategy, the return was 17.98%, the drawdown was 13.42%, and the win percentage was 62.5%. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.
A news scan found the headline 'LINK frozen trend-pullback daily/hourly holdout rejected'. This refers to a trading strategy for the cryptocurrency LINK. The strategy has two main rules: it enters the market when the closing price is higher than the 50-day Simple Moving Average and the 3-day return is less than 0, and it exits when the previous closing price is higher than the 5-day Simple Moving Average or after 5 calendar days. The strategy uses a 1-hour and daily time frame, with a 1.2% fee and 0.1% slippage on each trade. The training data is from 2025, and the holdout period is from January 1, 2026, to September 9, 2024, with a warm-up period in October 2024. The results show a return of -56.20% for the hourly time frame and -12.67% for the daily time frame, with a drawdown of 56.57% and 23.29% respectively. The win percentage is 14.39% for the hourly time frame and 47.37% for the daily time frame. The strategy uses a concept called 'quarter Kelly', which is a measure of the optimal fraction of the portfolio to invest in a trade. The results also show that the capital return is not exactly credited to the asset ledger due to fees and trade returns. The source of the data is from https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.
A news scan found the headline 'XRP frozen trend-pullback daily/hourly holdout rejected'. This refers to a trading strategy for the cryptocurrency XRP. The strategy had two conditions to enter a trade: the closing price had to be higher than the 50-day Simple Moving Average, and the 3-day return had to be less than 0. The strategy would exit a trade when the previous closing price was higher than the 5-day Simple Moving Average or after 5 calendar days. A Simple Moving Average is a way to smooth out price data over a certain period. The strategy used a 25 basis point fee and 10 basis points of slippage on each side of a trade, with a 20 basis point stress test. A basis point is a unit of measurement for interest rates and fees. The strategy was trained on data from 2025 and tested on data from January 1 to September 9, 2024, with a warm-up period in October 2024. The results showed a daily return of -10.12% and a hourly return of -37.99%. The strategy also had a daily drawdown of 16.52% and a hourly drawdown of 39.38%. A drawdown is the percentage decrease in value from a peak to a trough. The strategy was not validated for 15-minute exits or stops and is not deployable. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.
A news scan found the headline 'SOL frozen trend-pullback daily/hourly holdout rejected'. This refers to a trading strategy for the cryptocurrency SOL. The strategy had two conditions to enter a trade: the closing price had to be higher than the 50-day Simple Moving Average, which is a way to smooth out price data over time, and the 3-day return had to be less than 0. The strategy would enter a trade at the next available opening price when these conditions were met and the previous day's closing price was higher than the 5-day Simple Moving Average, or after 5 calendar days. The strategy used hourly time frames with specific settings, including a 25 basis point fee and 10 basis point slippage, which refers to the difference between expected and actual trade prices. The strategy was trained on data from 2025 and tested on data from 2026, with a warm-up period in October 2024. The results showed a daily return of -21.46% and a hourly return of -50.16%, with a drawdown of 28.08% and 51.02% respectively. The strategy was not validated for 15-minute exits or stops and is not deployable. The data was sourced from https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.
A news scan found the headline 'ETH frozen trend-pullback daily/hourly holdout rejected'. This refers to a type of investment strategy that uses a trend, or a pattern of price movement, and a pullback, or a brief reversal of that trend. The strategy was applied to Ethereum, a type of cryptocurrency, and was rejected. The strategy had two main rules: it would enter the market when the closing price was higher than the 50-day simple moving average, which is a way to smooth out price fluctuations, and the 3-day return was less than 0. It would exit the market when the previous closing price was higher than the 5-day simple moving average or after 5 calendar days. The strategy was tested on hourly and daily time frames, which are periods of time used to analyze price movements. The test used a type of simulation called a vector backtest, which is a way to test an investment strategy using historical data, and included fees of 25 basis points, which is a way to measure a small percentage, and slippage of 10 basis points, which is the difference between the expected price and the actual price of a trade. The test also included a stress test, which is a way to simulate the performance of an investment strategy during difficult market conditions, of 20 basis points. The strategy was trained on data from 2025 and tested on data from 2026, and the results showed that the strategy did not perform well. The daily time frame had a return of -0.3949 and a drawdown, which is the maximum amount of money lost, of 14.3784. The hourly time frame had a return of -54.3359 and a drawdown of 54.6961. The results also showed that the strategy had a low win percentage, which is the percentage of trades that were profitable, and a high average loss, which is the average amount of money lost per trade. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.
A news scan found the headline 'BTC frozen trend-pullback daily/hourly holdout rejected'. This refers to a trading strategy for Bitcoin that was tested and rejected. The strategy had two main rules: it would enter a trade when the closing price was higher than the 50-day Simple Moving Average, which is a measure of the average price over the last 50 days, and the 3-day return was less than 0. It would exit a trade when the previous closing price was higher than the 5-day Simple Moving Average or after 5 calendar days. The strategy was tested on hourly and daily time frames, with specific rules for each. The testing used historical data from 2025 for training and 2026 from January 1 to September 9 for testing, with a warm-up period in October 2024. The results showed that the strategy did not perform well, with negative returns and high drawdowns, which is the difference between the highest and lowest prices during a given period. The hourly strategy had a return of -51.38% and a drawdown of 51.38%, while the daily strategy had a return of -5.00% and a drawdown of 12.38%. The testing also used a method called bootstrapping to simulate different scenarios and estimate the strategy's performance. The results were not optimistic, and the strategy was rejected.
The notes from January 1724 to 1729 are frozen. The fund still has one-third of its initial capital in Bitcoin and Ethereum each, but the planned investment in Solana was not made because 418 calendar bars are missing, which prevents valid training. This is a reduced-coverage diagnostic, not a replication of a three-asset strategy. The monthly fraction of positive returns is one-third, and the next calendar day's open is used. The fund has no leverage, and there is a fee of 25 basis points plus 10 to 35 basis points per side. The data from 2023 to 2024 is used for training, and 2025 and 2026 are used for holdout. There are no missing calendar prints in Bitcoin and Ethereum. The final period's close is used for costed liquidation, and the sample includes complete position episodes with partial resizes aggregated, not independent monthly bets. The training data contains no losses and does not estimate losing tails. A mandatory short-horizon range with 15-minute exits and hourly robustness is unvalidated, and negative holdout rejects live adaptation. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars. The results show a return of 18.0028%, a drawdown of -9.674%, and a win rate of 50% over 4 samples, with an average win percentage of 13.6349% and an average loss percentage of -14.7976%.
A news scan found the headline 'QWIDE91002 crypto reduced-coverage monthly holdout 60bp'. Frozen notes 1724/1729 indicate that Bitcoin and Ethereum each retain one-third of the initial capital, while Solana stays in cash due to 418 missing calendar bars that prevent valid training. This is a reduced-coverage diagnostic, not a 3-asset replication. The strategy has a monthly positive-return fraction of 1/3/12, with the next calendar day's open, inactive cash at 0%, no leverage, and a fee of 25 basis points plus 10/35 basis points slip per side. The training period is from 2023 to 2024, and the holdout period is from 2025 to 2026, with no missing calendar prints in Bitcoin and Ethereum. The final period close is costed liquidation, and the sample is complete position episodes with partial resizes aggregated, not independent monthly bets. Training N2 contains no loss and does not estimate the losing tail; the 0.25 arithmetic Kelly is not validated. Mandatory short-horizon range and 15-minute exits, as well as hourly robustness, are unvalidated, and negative holdout rejects live adaptation. The source is https://runway.adityaperswal.workers.dev/data/crypto-bars, which provides the following data: the family is crypto_monthly, the signal is mix, the era is holdout, the cost side is 0.006, the return is -9.194244272417295, the drawdown is -18.2231279353811, the win rate is 33.33333333333333, the sample is 3, the average win percentage is 2.159762501145231, the average loss percentage is 18.741634168681625, the mean trade percentage is -11.774501945406007, the quarter Kelly diagnostic is 0, the calendar days are 365, and the symbols are BTC/USD and ETH/USD.
A news scan found the notes from a crypto trading fund manager. The notes are about a reduced-coverage monthly training session that resulted in a 60 basis point return. The fund had 1724 out of 1729 notes frozen. The fund kept one-third of its initial capital in Bitcoin and Ethereum, but the planned investment in Solana was kept in cash due to 418 missing calendar bars that prevented valid training. This training session was not a replication of a 3-asset portfolio. The training had a few rules: the fund would invest one-third of its capital on the first day of each month, the next day's opening price would be used, no cash would be kept inactive, and no leverage would be used. The fund also paid a 25 basis point fee and a 10-35 basis point slip per trade. The training data was from 2023 to 2024, and the holdout data was from 2025 to 2026. There were no missing calendar prints in the Bitcoin and Ethereum data. The final period's close was used to calculate the cost of liquidation, and the sample included complete position episodes with partial resizes aggregated, not independent monthly bets. The training data, called N2, had no losses and did not estimate the losing tail. A mandatory short-horizon range and 15-minute exits and hourly robustness were not validated. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars. The results of the training session were: return of 86.84%, drawdown of -27.53%, win rate of 100%, sample size of 2, average win percentage of 24.20%, average loss percentage of 0%, mean trade percentage of 24.20%, quarter Kelly diagnostic of 0.25, calendar days of 731, and symbols of BTC/USD and ETH/USD.
A news scan found the headline 'QWIDE91002 crypto reduced-coverage monthly 2026 35bp'. Frozen notes 1724/1729 indicate that Bitcoin and Ethereum each retain one-third of the initial capital, while Solana stays in cash due to 418 missing calendar bars that prevent valid training. This is a reduced-coverage diagnostic, not a 3-asset replication, which means it is a limited test, not a full copy of a three-asset investment. The monthly positive-return fraction is one-third, with the next calendar day's open, inactive cash at 0%, no leverage, and a fee of 25 basis points plus 10/35 basis points per side, where basis points refer to a unit of measurement for interest rates and fees. The training period is from 2023 to 2024, the holdout period is from 2025 to 2026, and there are no missing calendar prints in Bitcoin and Ethereum. The final period close is costed liquidation, and the sample is complete position episodes with partial resizes aggregated, not independent monthly bets. Training N2 contains no loss and does not estimate the losing tail, where the losing tail refers to the potential for large losses. The 0.25 arithmetic Kelly is not validated, and mandatory short-horizon range and 15-minute exits and hourly robustness are unvalidated, where the Kelly criterion is a formula for bet sizing. Negative holdout rejects live adaptation. The source of this information is https://runway.adityaperswal.workers.dev/data/crypto-bars, which provides data on cryptocurrency prices. The data includes a family of crypto monthly signals, a mix signal, and an era of 2026, with a cost per side of 0.0035, a return of 0.548747461410759, a drawdown of -9.563996719218704, a win rate of 50, a sample size of 4, an average win percentage of 14.19247202665343, an average loss percentage of 14.397035091432208, a mean trade percentage of -0.10228153238938872, a quarter Kelly diagnostic of 0, 252 calendar days, and symbols including BTC/USD and ETH/USD.
A news scan found the headline 'QWIDE91002 crypto reduced-coverage monthly holdout 35bp'. Frozen notes 1724/1729 show that Bitcoin and Ethereum each retain one-third of the initial capital, but Solana stays in cash because 418 missing calendar bars prevent valid training. This is a reduced-coverage diagnostic, not a 3-asset replication, which means it is a test with limited data, not a copy of a typical 3-asset investment. The monthly positive-return fraction is 1/3, the next calendar day open is used, inactive cash is 0%, there is no leverage, and a fee of 25 basis points plus a 10/35 basis points slip per side is applied. A basis point is a unit of measurement for interest rates and fees. The data is split into training from 2023 to 2024, holdout from 2025 to 2026, with no missing calendar prints in Bitcoin and Ethereum. The final period close is costed liquidation, and the sample is complete position episodes with partial resizes aggregated, not independent monthly bets. Training data N2 contains no loss and does not estimate the losing tail, which refers to the part of the data that shows potential losses. The arithmetic Kelly, a formula used to determine the optimal bet size, is not validated at 0.25. Mandatory short-horizon range and 15-minute exits, as well as hourly robustness, are unvalidated, and negative holdout rejects live adaptation. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars. The provided data includes a return of -8.644818908014573, a drawdown of -18.14438187989059, a win rate of 33.33333333333333, a sample size of 3, an average win percentage of 2.640778186404199, an average loss percentage of 18.351569692690266, a mean trade percentage of -11.354120399658777, a quarter Kelly diagnostic of 0, 365 calendar days, and the symbols BTC/USD and ETH/USD.
A news scan found the headline 'QWIDE91002 crypto reduced-coverage monthly train 35bp'. Frozen notes 1724/1729 show that Bitcoin and Ethereum each retain one-third of the initial capital. Solana was planned to be the third, but it stays in cash because 418 missing calendar bars prevent valid training. This is a reduced-coverage diagnostic, not a 3-asset replication. A monthly train has a 1/3/12 positive-return fraction, next calendar-day open, inactive cash 0%, no leverage, and a fee of 25 basis points plus 10/35 basis points slip per side. The train data is from 2023-24, the holdout data is from 2025 and 2026, and there are no missing calendar prints in Bitcoin and Ethereum. The final period close is costed liquidation, and the sample is complete position episodes with partial resizes aggregated, not independent monthly bets. Training N2 contains no loss and does not estimate the losing tail; the 0.25 arithmetic Kelly is not validated. Mandatory short-horizon range and 15-minute exits and hourly robustness are unvalidated, and negative holdout rejects live adaptation. The source is https://runway.adityaperswal.workers.dev/data/crypto-bars, which provides data on crypto bars. The results include a return of 89.53%, a drawdown of -27.30%, a win rate of 100%, a sample size of 2, an average win percentage of 24.77%, an average loss percentage of 0%, a mean trade percentage of 24.77%, a quarter Kelly diagnostic of 0.25, 731 calendar days, and symbols including BTC/USD and ETH/USD.
A diagnostic test for the momentum trading strategy on the stocks EPM and IPHA failed before considering costs. The test used a command line interface, or CLI, with the following settings: node /app/agent/dist/backtest.js --symbols EPM,IPHA --strategy momentum --lookback 20 --days 1800 --stop-pct 5 --target-pct 7.5. This test, called Premise1, used default adjustments from IEX and did not account for fees or slippage, which refers to the difference between expected and actual trade prices. The test analyzed 1157 bars of data and made 110 trades. The results showed a gross return of -75.2478%, a drawdown of 75.7628%, a win rate of 25.4545%, and an average return of -1.1501%. The conclusion was that the momentum diagnostic failed, and it did not make an independent claim about the strategy's performance outside of the test period, known as out-of-sample, or OOS. It also did not use the results to determine the size of trades. A separate test, called 1928, will use a different method, including costs and a frozen training period from 2024 and a holdout period from 2025-26, to validate the trading strategy. This test will also examine the performance of a counter case with a pre-event rule. The data for the test comes from https://runway.adityaperswal.workers.dev/data/stock-bars?feed=iex&timeframe=1Day, which is a source of stock bar data.
A diagnostic test was run using the command line interface, which executed the command node /app/agent/dist/backtest.js with the following parameters: symbols EPM and IPHA, strategy momentum, lookback 20, days 1800, stop percentage 5, and target percentage 7.5. The test used two premises, with the first premise using the IEX default adjustment and no explicit fee or slippage, resulting in 1236 bars and 109 trades. The second premise had a gross return of -51.8445%, a drawdown of 67.3506%, a win rate of 32.1101%, and an average return of -0.5521%. The diagnostic test was rejected because it did not validate the catalyst trade independently and did not make any out-of-sample claims, and it was not used for sizing. A separate test, 1928, uses SIP and vectorbt, and includes costs and a frozen train and holdout period from 2024 to 2025-26. This test may produce different results, which will be tested separately. The data source for this test is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=iex&timeframe=1Day, which is a stock bars data feed from IEX with a 1-day timeframe.
A test was run using a computer program called node to analyze the performance of a trading strategy. The program was given the following parameters: it was told to look at the stocks FTK, SSL, ATI, and IREN, use a strategy called breakout, look back 20 days, and test for 1460 days. It was also given a stop loss of 3 percent and a target profit of 4.5 percent. The test used 1002 bars of data from the website https://runway.adityaperswal.workers.dev/data/stock-bars. The results were as follows: for FTK, the return was -13.879 percent, the drawdown was 24.292 percent, the win rate was 36.667 percent, and there were 60 trades; for SSL, the return was 11.074 percent, the drawdown was 20.672 percent, the win rate was 37.143 percent, and there were 70 trades; for ATI, the return was 36.180 percent, the drawdown was 15.591 percent, the win rate was 40.385 percent, and there were 104 trades; and for IREN, the return was -34.563 percent, the drawdown was 45.320 percent, the win rate was 34.737 percent, and there were 95 trades. Note that a drawdown is the amount of money lost from the peak, a win rate is the percentage of trades that made money, and a trade is when the program buys or sells a stock. The test did not take into account any fees or slippage, which is when the price of a stock changes quickly, and it did not validate the daily stop and target sequencing, which is when the program decides to stop or sell a stock, or corporate actions, which are actions taken by a company that can affect its stock price. The conclusion is that these results are only for diagnostic purposes and do not validate the strategy. In a separate test, a program called vectorbt was used and it had different results, with held-out data from 2025 and later, and different channel exits, which is when the program decides to sell a stock based on its price movements, and all mean confidence intervals, which is a way to measure the accuracy of the results, crossed zero. The results from the two tests should not be combined to create a new strategy.
The QWIDE91002 swing trading strategy, which is 3-of-3 for the year 2026 with a cost of 16 basis points per side, has been analyzed. The strategy, also known as Frozen1720/1721, uses a same universe approach with 50 ETFs, where the first monthly session enters only when all 1/3/12 excess signs are positive, with a prior 20-day average daily range stop at 1 and target at 1.5, and half of the position is added with a 1R, or risk-reward ratio, which is a measure of potential profit versus potential loss. The strategy aims to break even the next day, with a maximum of 5 sessions. Daily open gap ordering is known, otherwise, the stop is at the first bar with ambiguity, which refers to a situation where the market direction is unclear. Opening profits are filled conservatively at a certain level. Fees are 1 basis point plus 5/15 slip, which refers to the cost of buying or selling a security. The vectorbt amount order ledger reconciles custom cash per asset to less than 1e-8, which is a very small amount. Synthetic 9/12/16 hour slots encode ordering, but observed fill times are not considered. Drawdown, which is the decline in value from a peak, is sampled and marked with an approximation, with 15-minute overnight unvalidated data. The strategy is equally funded in 50 independent sleeves, not pooled, with 100% per trade compounding. The data sources are https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all and https://www.aqr.com/-/media/AQR/Documents/Insights/Journal-Article/AQR-JPM-Fall-2017.pdf. The full metrics are: family is swing, era is 2026, cost side is 0.0016, return is -1.6855682639409064, drawdown is -2.805276757007169, win rate is 51.162790697674424, sample is 215, average win percentage is 1.1626302801816983, average loss percentage is 2.021004709127899, mean trade percentage is -0.3921682029695003, quarter Kelly diagnostic is 0, monthly clusters are 9, mean holding is 2.353488372093023, and vectorbt reconciled is true.
The QWIDE91002 swing trading strategy had a holdout period with the following results: it used a 3-of-3 rule, meaning three conditions had to be met to make a trade, and had a cost of 16 basis points per side, which is a measure of the cost of buying or selling a security. The strategy was backtested on data from 1/3/12, with a stop loss of 1 times the average daily range and a target of 1.5 times the average daily range, with half of the position sized at 1 times the average true range, a measure of price volatility. The strategy had a breakeven point the next day and a maximum of 5 sessions. The daily open gap ordering was known, otherwise the strategy used a stop-first bar ambiguity, meaning it would stop trading if the first bar of the day was ambiguous. Opening profits were filled conservatively at a certain level. The fees were 1 basis point plus 5/15 slip, which refers to the cost of buying or selling a security. The vectorbt amount order ledger reconciled custom cash per asset to less than 1e-8, which is a very small number. The strategy used synthetic 9/12/16 hour slots to encode ordering, but did not observe fill times, which refers to the time it takes to execute a trade. The drawdown was sampled using a mark approximation, with 15 minute overnight unvalidated data. The strategy was equally funded in 50 independent sleeves, not pooled, with 100% per trade compounding. The data sources used were https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all and https://www.aqr.com/-/media/AQR/Documents/Insights/Journal-Article/AQR-JPM-Fall-2017.pdf. The full metrics of the strategy were: family was swing, era was holdout, cost side was 0.0016, return was -8.228292501395773, drawdown was -9.15806359987802, win rate was 43.82566585956417, sample was 1239, average win percentage was 0.9965922379632003, average loss percentage was 1.39147340747158, mean trade percentage was -0.3448877371962889, quarter Kelly diagnostic was 0, monthly clusters were 72, mean holding was 2.4624697336561745, and vectorbt reconciled was true.