A news scan found the headline 'QWIDE91002 swing 3-of-3 train 16bp/side'. This refers to a trading strategy, where 16bp/side means 16 basis points per side, a basis point being one hundredth of a percent. The body of the note mentions Frozen1720/1721, which is a specific trading period, and Same50ETFuniverse, referring to a trading universe with 50 equally traded assets, or etfs, which are exchange-traded funds. The strategy enters a position only when all signs are positive, with a prior stop at 1 and target at 1.5 times the average daily range, or adr, with half of the position plus one times the risk, or r, and breakeven the next day, with a maximum of 5 sessions. Daily open gap ordering is known, otherwise the strategy stops at the first bar with ambiguity, and opening profits are filled conservatively at a certain level. Fees are 1 basis point plus 5 to 15 slip, which refers to the difference between the expected and actual price of a trade. The note also mentions vectorbt, a backtesting library, which reconciles the amount order ledger with custom cash per asset to less than 1e-8, a very small number. Synthetic 9 to 12 and 16 hour slots encode ordering, but observed fill times are not considered, and drawdown, or loss, is sampled and marked with an approximation every 15 minutes overnight, but is unvalidated. The strategy is equally funded in 50 independent sleeves, not pooled, with 100 percent per trade compounding. The note cites two sources, including a stock bars data feed and a research paper from AQR. The full metrics of the strategy are also provided, including a return of -5.3426 percent, a drawdown of -5.3643 percent, and a win rate of 37.09 percent.
The QWIDE91002 swing trading strategy, which is 3-of-3 for the year 2026 with a cost of 6 basis points per side, has been analyzed. This strategy, also known as a trading system that buys and sells stocks based on certain rules, started with a frozen position in 1720/1721 and used the same universe as the 50 ETFs, with the first monthly session only entering long positions when all signs were positive, with a stop loss at 1 times the average daily range and a target at 1.5 times, and half of the position was closed at a profit of 1 times the risk, with a breakeven stop on the next day and a maximum of 5 sessions. The daily open gap was used for ordering, and if there was ambiguity, the stop was placed at the first bar, with opening profits filled conservatively at the specified level. The fees were 1 basis point plus a 5 to 15 slip, and the vectorbt amount order ledger was reconciled with a custom cash per asset of less than 1e-8. The strategy used synthetic 9, 12, and 16 hour slots to encode ordering, but did not observe fill times, and used a drawdown sampled mark approximation, with 15 minute overnight unvalidated data. The strategy was equally funded in 50 independent sleeves, and was not pooled with 100 percent per trade compounding. The data was sourced from 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 for the strategy are: family is swing, era is 2026, cost per side is 0.0006, return is -0.837390516077452, drawdown is -2.6756370346532887, win rate is 52.093023255813954, sample size 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 period is 2.353488372093023, and vectorbt reconciled is true.
The QWIDE91002 swing trading strategy had a return of -3.5853043981237565% during the holdout period. This strategy, also known as a 3-of-3 holdout, uses a 6 basis points per side cost structure. A basis point is a unit of measurement, one hundredth of a percent. The strategy was tested on data from the period starting 1/3/12, with a prior 20-day average daily range stop at 1 and target at 1.5, and half of the average true range plus 1. The daily open gap ordering was known, otherwise the strategy used a stop at the first bar's ambiguity, which refers to uncertainty in the market. Opening profits were filled conservatively at a certain level. The fees were 1 basis point plus 5 to 15 slip, which refers to the difference between expected and actual trading costs. The vectorbt amount order ledger was used to reconcile custom cash per asset to less than 1e-8, a very small number. The strategy used synthetic 9, 12, and 16 hour time slots to encode ordering, but did not observe fill times, which refer to the times when trades are executed. The drawdown, or peak to trough decline, was sampled using a mark to market approximation, which estimates the value of a portfolio, and 15-minute overnight unvalidated data. The strategy was equally funded in 50 independent sleeves, not pooled, with 100% per trade compounding. The source data came from https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all and a research paper from AQR, https://www.aqr.com/-/media/AQR/Documents/Insights/Journal-Article/AQR-JPM-Fall-2017.pdf. The full metrics of the strategy are available, including a win rate of 46.48910411622276%, average win percentage of 1.1366843295470295%, and average loss percentage of 1.2592056317905695%.
A news scan found the headline 'QWIDE91002 swing 3-of-3 train 6bp/side'. The Frozen1720/1721 strategy, also known as a trading plan, uses a Same50ETFuniverse approach, which is a type of trading universe, meaning a set of rules to select stocks. This strategy enters a position only on the first monthly session with all excess signs positive, with a prior 20-day average daily range stop at 1 and a target at 1.5, and half of the position size plus one risk unit. The position is set to breakeven the next day, with a maximum of 5 sessions. The daily open gap ordering is known, otherwise a stop is set at the first bar with ambiguity, which means uncertainty. Opening profits are filled conservatively at a certain level. Fees are 1 basis point plus 5 to 15 slip, which refers to a small percentage of the trade value. The vectorbt amount order ledger reconciles custom cash per asset to less than 1e-8, which is a very small number. Synthetic 9, 12, and 16 hour slots encode ordering, but observed fill times are not considered. Drawdown, which is a measure of loss, is sampled and marked with an approximation, with 15-minute overnight unvalidated data. The strategy is equally funded in 50 independent sleeves, which are like separate accounts, and not pooled at 100 percent per trade compounding, which means the returns are not combined. The source of this information is 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 train, cost side is 0.0006, return is -2.635043849171137, drawdown is -2.943814217606766, 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 are 34, mean holding is 2.3413258110014104, and vectorbt reconciled is true.
A news scan found the headline 'QWIDE91002 monthly passive 2026 16bp/side'. This refers to a monthly report on an automated trading fund, QWIDE91002, with a 16 basis points per side fee. The fund uses a strategy called 'passive', meaning it does not actively try to beat the market. The fund has 50 predetermined cash ETF sleeves, which were set up in 2016 and trained from 2017 to 2019, and then held from 2020 to 2025. The fund's performance is measured against the SHY index, which is a type of bond index. The fund's return is calculated at the end of each month, and it is a mix of positive and negative returns. The fund does not select specific stocks, but instead uses a full sleeve approach, meaning it invests in all the available ETFs. The fund has fees of 1 basis point and slippage of 5 to 15 basis points. The fund also has a feature called'vector bt position episodes', which refers to the way the fund adjusts its positions over time. The fund does not use a risk balancing strategy, unlike some other funds, such as those offered by AQR. The fund's metrics are as follows: it has a return of 13.72%, a drawdown of -8.12%, a win rate of 86%, and an average win percentage of 17.07%. The fund's annual return is 20.67%, and its mean daily percentage is 0.0788%. The fund's volatility is 14.22% per year, and its Sharpe ratio, which measures risk-adjusted return, is 1.40. The fund currently has no open positions. The data for this report comes from 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 QWIDE91002 monthly passive holdout had a return of 16 basis points per side. The fund uses 50 predetermined cash ETF sleeves, which were warmed up in 2016, trained from 2017 to 2019, and held out from 2020 to 2025, with a separate period in 2026. The month-end return is calculated by subtracting the SHY return, which is a type of bond fund. The fund has a mix of positive fractions and components diagnostics, but no selection is made, and the full sleeve is held passively. The next session will open with a monthly target weight within independently compounding sleeves, with 1 basis point fees and 5 to 15 slippage, and the final era will close with costed liquidation. The fund also has vector bt position episodes that aggregate partial resizes, and correlated positions that are not independent and identically distributed, which means they are not random and do not have the same distribution. Inactive cash is zero, and expenses are embedded in prices. This is a long cash adaptation, not a risk-balanced short futures strategy like the one used by AQR, and it does not have mandatory ADR exits. The source of the data is 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 monthly, signal is passive, cost per side is 0.0016, era is holdout, return is 77.39577595673421, drawdown is -29.686335533123042, win rate is 94, sample is 50, average win percentage is 82.91660269182037, average loss percentage is 8.96818326635472, quarter Kelly diagnostic is 0.23337761383573194, annual return is 10.031989087023785, mean daily percentage is 0.04343735205773449, annual volatility percentage is 16.481427168339913, Sharpe ratio with zero cash is 0.6641544210186046, and open positions is 0.
A news scan found the headline about Evolution Petroleum's earnings. The automated trading fund manager made some decisions about buying and selling the company's stock, which is traded as EPM. The manager looked at the stock's performance before and after the company announced its earnings on the actual issuer date, which was 19625. The manager decided to buy the stock at the opening price three days before the announcement and sell it at the closing price one day before the announcement, with a preferred stop at 1 prior to 20 ADR and a target at 1.5 ADR. The manager used data from 2024 for training and from May 2026 for testing, with an adjusted SIP. The manager also considered fees of 5 basis points per side and a slip of 10 basis points for the base case and 25 basis points for the stress case. The manager used a daily high and low stop, and a gap stop at the minimum of the open and stop prices, with a conservative target. The manager used a system called Vectorbt to reproduce the costed ledger, with two fill observations per event. The manager found that the preferred training return was -5.422920% for the base case and -6.551066% for the stress case. The holdout return was +5.708773% for the base case and +3.823032% for the stress case, with the stress case winning 4 out of 6 times, with an average win of 2.643210% and an average loss of 3.262591%. The manager also found that the mean return was 0.674609%, with a 95% confidence interval of [-1.778946, 3.065121]%. The manager found that the event-close drawdown was 3.668236%, and the Vectorbt sampled drawdown was 3.956487%. The manager concluded that the strategy should be rejected for live trading, with a raw holdout quarter Kelly of 0.063806, because it failed the training, uncertainty, and execution tests. The manager noted that a strong counterargument is that the royalty mix may have changed, which could make the 2024 data stale, and that prospective proof is needed, not retrospective deletion. The manager verified the dates retrospectively and found that the advance announcement, early news, and dividend execution were complete, but that there was a gap in the audit. The manager used data from https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=EPM&feed=sip&adjustment=all&timeframe=1Day and https://ir.evolutionpetroleum.com/news-events/news-releases, and found a future announcement scheduled for September 15 AM at https://ir.evolutionpetroleum.com/news-releases/news-release-details/evolution-petroleum-schedules-fiscal-q4-and-full-year-2026.
The QWIDE91002 monthly passive train had a return of 16 basis points per side. The system used 50 predetermined cash ETF sleeves, with data from 2016 used for warmup, 2017-2019 for training, 2020-2025 for holdout, and 2026 for separate testing. The system's performance was measured by month-end returns minus the SHY index. The results showed a positive mix of fractions with no selection, using a full sleeve passive approach. For the next session, the system will open with a monthly target weight within independently compounding sleeves, with 1 basis point fees and 5-15 slippage, and final era close costed liquidation. The system also used vectorized backtest position episodes with aggregate partial resizes, and correlated positions that were not independent and identically distributed, giving it an edge. Inactive cash was set to zero, with expenses embedded in prices. This is a long cash adaptation, not a risk-balanced short futures strategy like AQR's, and does not require mandatory ADR exits. The system's metrics are as follows: family is monthly, signal is passive, cost per side is 0.0016, era is train, return is 33.04901076986295, drawdown is -17.822829741004465, win rate is 98, sample size is 50, average win percentage is 33.94444098527958, average loss percentage is 10.661824731701195, quarter Kelly diagnostic is 0.24342951829191636, annual return is 10.021907782507732, mean daily percentage is 0.039939242162321704, annual volatility percentage is 10.187884991733197, Sharpe ratio with zero cash is 0.987907601339425, and open positions is 0. 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.
A news scan found the headline 'QWIDE91002 monthly passive 2026 6bp/side'. The fund manager's notes are about a trading strategy. The strategy uses 50 predetermined cash ETF sleeves, which were set up in 2016 and tested from 2017 to 2019, and then not changed from 2020 to 2025. In 2026, the strategy is separate. At the end of each month, the strategy looks at the return minus the return of SHY, which is a type of low-risk investment. The strategy mixes the positive fractions of the return and does diagnostics on the components, but does not select any. The strategy is passive and uses the full sleeve. The next session will open with a monthly target weight within independently compounding sleeves, with 1bp fees and 5/15 slippage, and the final era close will be costed with liquidation. The strategy also looks at vector bt position episodes and aggregate partial resizes, and notes that correlated positions are not independent, which is called an IID edge. Inactive cash is zero, and expenses are embedded in prices. This strategy is a long cash adaptation, not a risk-balanced short futures strategy like AQR's. There are no mandatory ADR exits, so it is unapproved. The source of the data is 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 monthly, signal is passive, cost side is 0.0006, era is 2026, return is 13.952572096657988, drawdown is -8.119084725235936, win rate is 86, sample is 50, average win percentage is 17.302009882450044, average loss percentage is 6.612579607424165, quarter Kelly diagnostic is 0.20162350282815392, annual return is 21.024684009024732, mean daily percentage is 0.07995452287652759, vol annual percentage is 14.214391569886033, Sharpe zero cash is 1.4174746534751963, and open positions is 0.
The QWIDE91002 monthly passive holdout had a 6 basis points per side performance. The system uses 50 predetermined cash ETF sleeves, which were warmed up in 2016, trained from 2017 to 2019, and are being held out from 2020 to 2025, with 2026 being separate. The month-end return is calculated by subtracting the SHY return, and the mix has a positive fraction with three components and diagnostics, but no selection is made. The passive full sleeve is used. For the next session, the open monthly target weight is within independently compounding sleeves, with 1 basis point fees and 5 to 15 basis points slippage, and the final era close is costed with liquidation. The system also considers vector bt position episodes with aggregate partial resizes, and correlated positions are not independently and identically distributed, which means they are not random and unconnected. Inactive cash is zero, and expenses are embedded in prices. This is a long cash adaptation, not an AQR risk-balanced short futures strategy, and there are no mandatory ADR exits, hence it is unapproved. The source data can be found at 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 monthly, signal is passive, cost side is 0.0006, era is holdout, return is 77.75092292197321, drawdown is -29.68633553312302, win rate is 94, sample is 50, average win percentage is 83.28282239156854, average loss percentage is 8.785917230151693, quarter Kelly diagnostic is 0.23341757574169797, annual return is 10.06869769989811, mean daily percentage is 0.04356934609810567, volatility annual percentage is 16.48038216244716, Sharpe zero cash is 0.6662148431084862, and open positions are 0.
A news scan found the headline 'QWIDE91002 monthly passive train 6bp/side'. The fund manager's notes mention Frozen1720/1721/1724, which refers to a set of frozen or fixed positions. The manager uses fifty predetermined cash ETF sleeves, which are groups of exchange-traded funds that track a specific index or sector, with a warm-up period in 2016, training from 2017 to 2019, a holdout period from 2020 to 2025, and a separate period in 2026. The manager calculates the return minus the SHY, which is a type of bond fund, and signs, or indications, of positive or negative returns. The manager mixes the positive fraction, or part, of the return with three components and diagnostics, without selecting specific securities, and uses a passive full sleeve approach, meaning all securities are included without active management. The next session will open with a monthly target weight within independently compounding sleeves, with 1 basis point fees, which is a unit of measurement for interest rates or fees, and 5 to 15 basis points slippage, which refers to the difference between expected and actual prices. The manager also mentions vector bt position episodes, which refers to a type of statistical analysis, and aggregate partial resizes, which means adjusting the size of positions. The manager notes that correlated positions, or positions that move together, are not independent and identically distributed, or IID, which is a statistical concept, and that there is no edge, or advantage. Inactive cash is set to zero, and expenses are embedded in prices. This is a long cash adaptation, not an AQR risk-balanced short futures strategy, which means the manager is focusing on long-term cash investments rather than short-term futures contracts. The manager also mentions that there are no mandatory ADR exits, which refers to American Depositary Receipts, and that this strategy is unapproved. The source of the data is 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 monthly, signal is passive, cost side is 0.0006, era is train, return is 33.315375355762036, drawdown is -17.822829741004387, win rate is 98, sample is 50, average win percentage is 34.21261824564346, average loss percentage is 10.482949371648012, quarter Kelly diagnostic is 0.2434679703119502, annual return is 10.095532305485566, mean daily percentage is 0.04020459105128569, volatility annual percentage is 10.187861252772898, Sharpe zero cash is 0.9944733927512432, and open positions is 0.
The QWIDE91002 monthly report for December 2026 shows a 16 basis points per side performance. The fund uses 50 predetermined cash ETF sleeves, which were warmed up in 2016, trained from 2017 to 2019, and held out from 2020 to 2025, with a separate period in 2026. The month-end return is calculated by subtracting the SHY return, with a mix of positive fractions and component diagnostics, but no selection, and a passive full sleeve approach. The next session will open with a monthly target weight within independently compounding sleeves, with 1 basis point fees and 5/15 slippage, and final era close costed liquidation. The fund also uses vector bt position episodes with aggregate partial resizes, and correlated positions that are not independently and identically distributed, which means they are not random and unrelated. Inactive cash is set to zero, and expenses are embedded in prices. This is a long cash adaptation strategy, not a risk-balanced short futures strategy like AQR, and it does not require mandatory ADR exits. The source data is from 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 monthly, signal is 12, cost per side is 0.0016, era is 2026, return is 12.652638875446364, drawdown is -7.9762544242265925, win rate is 65, sample is 60, average win percentage is 18.27104928228229, average loss percentage is 3.786189909436414, quarter Kelly diagnostic is 0.1443679479236617, annual return is 19.012928221907654, mean daily percentage is 0.07311567997987553, volatility annual percentage is 13.917123248215363, Sharpe ratio with zero cash is 1.323919536121903, and open positions is 0.
A news scan found the headline 'QWIDE91002 monthly 12 holdout 16bp/side'. This refers to a trading fund's monthly report, where 12 represents the signal and 16bp/side is the cost per side, with bp meaning basis points, or a unit of measurement for interest rates and investment returns. The fund has a frozen set of 50 cash ETF sleeves, which are groups of investments, and uses data from 2016 as a warm-up, 2017-2019 for training, 2020-2025 as a holdout, and 2026 as a separate period. The fund's return is calculated at the end of each month, minus the return of the SHY investment, which is a type of bond. The fund has a mix of positive fractions and diagnostics, but does not select specific investments. Instead, it uses a passive full sleeve approach. The next session will open with a monthly target weight within independently compounding sleeves, with 1bp fees and 5/15 slippage, which refers to the difference between the expected and actual price of a trade. The fund also has vector bt position episodes, which are periods of buying or selling, and aggregate partial resizes, which means adjusting the size of the investments. The fund's expenses are embedded in the prices, and it is a long cash adaptation, meaning it focuses on holding cash for an extended period. This is different from an AQR risk-balanced short futures approach, which involves selling investments to reduce risk. The fund does not have mandatory ADR exits, which are rules for exiting investments. The source of this information is 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 monthly, signal is 12, cost side is 0.0016, era is holdout, return is 31.297330195582873, drawdown is -15.795237483747048, win rate is 43.66197183098591, sample is 284, avg win pct is 22.28359889309118, avg loss pct is 6.8880149180692545, quarter kelly diagnostic is 0.06561874178027188, annual return is 4.646044077827849, mean daily pct is 0.01977521205153735, vol annual pct is 9.295417883603923, sharpe zero cash is 0.5361085966643298, and open positions is 0.
The system known as QWIDE91002 has been analyzed. It uses a method called Frozen1720/1721/1724, which involves fifty predetermined cash ETF sleeves. The data was divided into periods: 2016 for warmup, 2017–19 for training, 2020–25 for holdout, and 2026 for a separate evaluation. The return at the end of each month is calculated by subtracting the return of SHY, which is a type of low-risk investment. The system mixes a positive fraction of the components with diagnostics but does not select any particular component; instead, it uses a passive full sleeve approach. For the next session, the system will open with a monthly target weight within independently compounding sleeves, considering 1 basis point fees and 5/15 slippage, and will finalize with a costed liquidation at the end. The system also aggregates partial resizes of vector bt position episodes and acknowledges that correlated positions do not have independent and identically distributed edges. Inactive cash is set to zero, with expenses embedded in prices. This system is a long cash adaptation and does not involve short futures like AQR risk-balanced strategies, and it does not require mandatory ADR exits. The data sources include https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all and a research paper from AQR. The full metrics of the system are provided, showing details such as return, drawdown, win rate, and average win and loss percentages.
A news scan found the headline 'QWIDE91002 monthly 12 2026 6bp/side'. The fund manager's notes for QWIDE91002 mention that certain positions, referred to as Frozen1720/1721/1724, were frozen. The fund has fifty predetermined cash ETF sleeves, which were set up in 2016 as a warmup, trained from 2017 to 2019, held out from 2020 to 2025, and are separate for 2026. The fund's return at the end of each month is compared to the return of SHY, a type of bond fund, and the results are used to adjust the mix of investments. The fund's components are diagnosed, but no selection is made, and the full sleeve is used passively. For the next session, the monthly target weight will be set within independently compounding sleeves, with fees of 1 basis point and slippage of 5 to 15 basis points. The final liquidation will be costed at the end of the era. The fund's vector bt position episodes will be aggregated and partially resized. Correlated positions are not independent and identically distributed, which means they are not random and do not have the same distribution, and are referred to as an edge. Inactive cash is set to zero, and expenses are embedded in prices. This is a long cash adaptation, not a risk-balanced short futures strategy like the one used by AQR, and does not require mandatory ADR exits. The data sources for this information 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 for the fund are also provided, including a family of monthly, a signal of 12, a cost side of 0.0006, an era of 2026, a return of 12.9164524179755, a drawdown of -7.969869188682088, a win rate of 66.66666666666666, a sample of 60, an average win percentage of 18.049197418516112, an average loss percentage of 3.781317519453858, a quarter Kelly diagnostic of 0.14920828411473333, an annual return of 19.420340712904572, a mean daily percentage of 0.07447154968361418, a volatility annual percentage of 13.907936465750502, a Sharpe ratio of 1.3493612489879947, and zero open positions.
The QWIDE91002 monthly report for the 12 holdout period with a 6 basis points per side fee is as follows. The system uses 50 predetermined cash ETF sleeves, with data from 2016 used for warmup, 2017-2019 for training, 2020-2025 for holdout, and 2026 for separate testing. The month-end return is calculated by subtracting the SHY return, with a mix of positive fractions and component diagnostics, but no selection. The system uses a passive full sleeve approach. For the next session, the open monthly target weight is determined within independently compounding sleeves, with 1 basis point fees and 5/15 slippage, and final era close costed liquidation. The system also considers vector bt position episodes and aggregate partial resizes, with correlated positions not being independently and identically distributed, which is referred to as an edge in trading, meaning an advantage. Inactive cash is set to zero, with expenses embedded in prices. This is a long cash adaptation strategy, not a risk-balanced short futures strategy like the one used by AQR. There are no mandatory ADR exits, hence it is unapproved. 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 monthly, signal is 12, cost per side is 0.0006, era is holdout, return is 32.714881480437356, drawdown is -15.527755926989506, win rate is 44.36619718309859, sample size is 284, average win percentage is 22.170973223244573, average loss percentage is 6.7865232234357515, quarter Kelly diagnostic is 0.06834179862516034, annual return is 4.833632844144531, mean daily percentage is 0.020486728282477263, annual volatility percentage is 9.293483328543937, Sharpe ratio with zero cash is 0.5555135081942556, and open positions is 0.
The QWIDE91002 monthly report for 12 train 6 basis points per side is as follows. The system uses 50 predetermined cash ETF sleeves, with data from 2016 used for warmup, 2017-2019 for training, 2020-2025 for holdout, and 2026 for separate testing. The month-end return is calculated by subtracting the SHY return, which is a type of bond fund. The system mixes the positive fraction of the return with three components for diagnostics, without selecting any particular component, and uses a passive full sleeve approach. For the next session, the system will open with a monthly target weight within independently compounding sleeves, with 1 basis point fees and 5-15 basis points slippage, and will account for final era close costed liquidation. The system also aggregates partial resizes of vector bt position episodes and accounts for correlated positions that are not independent and identically distributed, or IID, which refers to a statistical concept where events are independent and have the same distribution. Inactive cash is set to zero, and expenses are embedded in prices. This system is a long cash adaptation, not a risk-balanced short futures strategy like AQR, and does not have mandatory ADR exits. The source data comes from 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 monthly, signal is 12, cost side is 0.0006, era is train, return is 12.64417830055451, drawdown is -13.779417138856044, win rate is 61.48648648648649, sample is 148, average win percentage is 9.956674741798178, average loss percentage is 4.926073466009103, quarter Kelly diagnostic is 0.10607973066214499, annual return is 4.062784104918227, mean daily percentage is 0.01686899490862431, volatility annual percentage is 7.360692195381743, Sharpe ratio with zero cash is 0.577525401706172, and open positions is 0.
A news scan found the headline 'QWIDE91002 monthly 3 2026 16bp/side'. The fund manager's notes are about a trading strategy. The strategy uses 50 predetermined cash ETF sleeves, which were set up in 2016 and tested from 2017 to 2019, and then not changed from 2020 to 2025, with 2026 being separate. The strategy looks at the return at the end of each month, subtracting the return of SHY, which is a type of low-risk investment. The strategy combines positive fractions and does diagnostics on its components without selecting any, and uses a passive full sleeve approach. The next session will open with a monthly target weight within independently compounding sleeves, with 1 basis point fees and 5 to 15 slippage, and final era close costed liquidation. The strategy also looks at vector bt position episodes and aggregate partial resizes, and notes that correlated positions are not independent and identically distributed, which is a statistical concept. Inactive cash is set to zero, and expenses are embedded in prices. This strategy is a long cash adaptation, not a risk-balanced short futures strategy like the one used by AQR, and does not require mandatory ADR exits. The source of the data is 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 monthly, signal is 3, cost per side is 0.0016, era is 2026, return is 9.358813838283652, drawdown is -7.351399802803671, win rate is 61.53846153846154, sample is 78, average win percentage is 11.473882329858764, average loss percentage is 2.783318903385474, quarter Kelly diagnostic is 0.13052128350677739, annual return is 13.963397663276588, mean daily percentage is 0.05464328272525098, annual volatility percentage is 11.506014619237055, Sharpe ratio with zero cash is 1.1967747045741475, and open positions is 0.
The system has frozen the 1720, 1721, and 1724 models. It uses 50 predetermined cash ETF sleeves, with data from 2016 used for warmup, 2017-2019 for training, 2020-2025 for holdout, and 2026 separate. The system calculates month-end returns minus the SHY signs, mixes the positive fraction, and performs component diagnostics without selection, using a passive full sleeve approach. For the next session, it sets the open monthly target weight within independently compounding sleeves, with 1 basis point fees and 5/15 slippage, and final era close costed liquidation. The system aggregates vector bt position episodes and partial resizes, and notes that correlated positions are not independently and identically distributed, which means they are not random and unrelated to each other. Inactive cash is set to zero, with expenses embedded in prices. This is a long cash adaptation, not an AQR risk-balanced short futures strategy, and does not require mandatory ADR exits. The source data is from 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 monthly, signal is 3, cost per side is 0.0016, era is holdout, return is 45.87299039167434, drawdown is -10.696500654864716, win rate is 45.233265720081135, sample is 493, average win percentage is 15.224192496731067, average loss percentage is 4.874967612560477, quarter Kelly diagnostic is 0.06924076413388247, annual return is 6.49957294042296, mean daily percentage is 0.0264673889020352, volatility annual percentage is 8.477084264754668, Sharpe ratio with zero cash is 0.7868014278263045, and open positions is 0.
The system is using a set of rules called Frozen1720/1721/1724. It has 50 pre-set groups of cash ETFs, which were tested from 2016 to 2019 and will be used from 2020 to 2025. The system looks at the returns from the 1st, 3rd, and 12th of each month, and compares them to the SHY sign, which is a type of investment. It mixes the positive parts of the investments and checks the components, but does not select any. The system uses a passive approach with all the groups. For the next session, it will set a target weight for each group, considering fees of 1 basis point and potential losses of 5 to 15 basis points. The system also looks at the size of the investments and adjusts them accordingly. It does not use a type of investment called AQR risk balanced short futures, and it does not have mandatory exits. The system gets data from 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 monthly, signal is 3, cost per side is 0.16%, era is train, return is 14.31%, drawdown is -11.21%, win rate is 55.06%, sample size is 247, average win percentage is 8.95%, average loss percentage is -4.49%, quarter Kelly diagnostic is 0.0813, annual return is 4.57%, mean daily percentage is 0.0186%, annual volatility percentage is 6.74%, Sharpe ratio with zero cash is 0.697, and there are 0 open positions.
A news scan found the headline 'QWIDE91002 monthly 3 2026 6bp/side'. This refers to a monthly report for QWIDE91002, with 3 as the signal and 6 basis points per side, for the year 2026. The report mentions Frozen1720/1721/1724, which are likely frozen cash positions. The report also mentions fifty predetermined cash ETF sleeves, with a warm-up period in 2016, a training period from 2017 to 2019, a holdout period from 2020 to 2025, and a separate period in 2026. The month-end return is calculated minus the SHY signs, which refers to the iShares 1-3 Year Credit Bond ETF, a type of bond fund. The report also mentions a mix of positive fractions, component diagnostics, and no selection, with a passive full sleeve approach. The next session will open with a monthly target weight within independently compounding sleeves, with 1 basis point fees and 5/15 slippage, and a final era close costed liquidation. The report also mentions vector bt position episodes, which refers to a type of trading strategy, and aggregate partial resizes, which refers to adjusting the size of trades. Correlated positions are not independent and identically distributed, which refers to a statistical concept. Inactive cash is zero, and expenses are embedded in prices. This is a long cash adaptation, not an AQR risk-balanced short futures strategy, which refers to a type of investment approach. There are no mandatory ADR exits, hence unapproved. The report cites two sources: 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 also provided, including a family of monthly, signal of 3, cost side of 0.0006, era of 2026, return of 9.695504014789558, drawdown of -7.337137905363456, win rate of 61.53846153846154, sample of 78, average win percentage of 11.697073453035019, average loss percentage of 2.5886707470497834, quarter Kelly diagnostic of 0.13256641667478453, annual return of 14.47637736288696, mean daily percentage of 0.05642596927191758, vol annual percentage of 11.493910788412876, Sharpe zero cash of 1.2371197687438023, and open positions of 0.
The QWIDE91002 monthly report for the 3 holdout period with 6 basis points per side is as follows. The system uses a method called backtesting, which tests the performance of a strategy using historical data, and has frozen the parameters for 1720, 1721, and 1724. The system was trained on data from 2017 to 2019 and is being tested on data from 2020 to 2025, with 2026 being a separate test period. The system uses 50 predetermined cash ETF sleeves, which are groups of investments, and started with a warm-up period in 2016. The system calculates the return on investment at the end of each month, subtracting the return of a benchmark called SHY, which is a type of low-risk investment. The system also calculates the mix of positive fractions, which refers to the proportion of successful investments, and performs diagnostics on the components, which are the individual parts of the system. The system does not select specific investments, but instead uses a passive full sleeve approach, which means it invests in all available options. The system will adjust its target weight, which is the desired level of investment, at the start of the next session, taking into account a 1 basis point fee and 5 to 15 basis points of slippage, which is the difference between the expected and actual price of an investment. The system will also liquidate, or sell, its holdings at the end of the period, taking into account the costs of doing so. The system uses a vector, which is a mathematical concept, to represent its positions, and aggregates partial resizes, which refers to the process of adjusting the size of its investments. The system assumes that its positions are correlated, meaning they tend to move together, and are not independent and identically distributed, which is a statistical concept. The system also assumes that inactive cash, which is cash that is not being used, has zero value, and that expenses are embedded in the prices of the investments. This system is a long cash adaptation, which means it is designed to perform well in a market with low interest rates, and is not a risk-balanced short futures strategy, which is a different type of investment approach. The system does not require mandatory ADR exits, which refers to the process of selling certain types of investments, and is not approved. The data for this report comes from two sources: 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 for the system are as follows: family is monthly, signal is 3, cost per side is 0.0006, era is holdout, return is 48.64499307763008, drawdown is -10.364238382573133, win rate is 47.05882352941176, sample size is 493, average win percentage is 14.857720578411277, average loss percentage is 4.848150145599255, quarter Kelly diagnostic is 0.07445961781272206, annual return is 6.834461686275861, mean daily percentage is 0.02771569990188647, volatility annual percentage is 8.476160592243211, Sharpe ratio zero cash is 0.8240000055764617, and open positions is 0.
The QWIDE91002 monthly report for train 6 basis points per side is as follows: the system is using frozen models from 1720, 1721, and 1724. It has 50 predetermined cash ETF sleeves, which were warmed up in 2016, trained from 2017 to 2019, and held out from 2020 to 2025, with a separate period in 2026. The system calculates the return minus the SHY signs at the end of each month. It mixes the positive fraction of the return with three components, performs diagnostics, and does not select any particular component. The system uses a passive full sleeve approach. For the next session, the system will open with a monthly target weight within independently compounding sleeves, with 1 basis point fees and 5 to 15 basis points of slippage, and will cost the final era close and liquidation. The system also aggregates partial resizes of vector bt position episodes and notes that correlated positions do not have independent and identically distributed edges. Inactive cash is set to zero, and expenses are embedded in prices. This is a long cash adaptation, not an AQR risk-balanced short futures strategy, and does not have mandatory ADR exits, hence it is unapproved. The source data can be found at 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 monthly, signal is 3, cost side is 0.0006, era is train, return is 15.425279913670842, drawdown is -11.010769148343936, win rate is 57.08502024291497, sample is 247, average win percentage is 8.848571177592667, average loss percentage is 4.509627254008149, quarter Kelly diagnostic is 0.08803407245709802, annual return is 4.915171280484776, mean daily percentage is 0.01992949691124022, volatility annual percentage is 6.736328987187456, Sharpe zero cash is 0.7455445289541022, and open positions is 0.
A news scan found the headline 'QWIDE91002 monthly 1 2026 16bp/side'. This refers to a monthly report for the QWIDE91002 fund, which is a type of automated trading fund, for the month of January 2026, with a 16 basis points per side, which means a 0.16% fee for buying or selling. The fund uses a strategy called 'Frozen1720/1721/1724', which involves 50 predetermined cash ETF sleeves, or groups of investments, that were set up in 2016 and tested from 2017 to 2019, and then held from 2020 to 2025, with 2026 being a separate period. The fund's performance is measured by its return minus the return of the SHY, which is a type of low-risk investment, at the end of each month, on the 1st, 3rd, and 12th days. The fund's components are diagnosed, but no selection is made, and the fund is passively managed, meaning it is not actively trying to beat the market. The fund's target weight is set at the start of each month, and it is rebalanced, or adjusted, to maintain its target weight, with a 1 basis point fee, which is 0.01%, and a 5 to 15 slippage, which refers to the difference between the expected and actual price of a trade. The fund also uses a vector, which is a mathematical concept, to manage its positions, and it aggregates, or combines, its positions to minimize risk. The fund has no inactive cash, and its expenses are embedded in its prices. This fund is a long cash adaptation, which means it is designed to perform well when the market is going up, and it is not a risk-balanced short futures fund, which would be designed to perform well when the market is going down. The fund does not have mandatory ADR, or American Depositary Receipt, exits, which means it does not have to sell its investments at a certain time. The source of this information is 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 for the fund are: family: monthly, signal: 1, cost side: 0.0016, era: 2026, return: 4.462375800089524, drawdown: -7.594363348139376, win rate: 46.96969696969697, sample: 132, avg win pct: 6.3672792021447595, avg loss pct: 2.6192418394489425, quarter Kelly diagnostic: 0.06288792320298117, annual return: 6.586060873688537, mean daily pct: 0.02778053393079898, vol annual pct: 11.008935288039073, Sharpe zero cash: 0.6359102281369043, and open positions: 0.
The QWIDE91002 monthly report for the holdout period shows a 16 basis points per side cost. The system uses 50 predetermined cash ETF sleeves, with data from 2016 used for warmup, 2017-2019 for training, 2020-2025 for holdout, and 2026 for separate evaluation. The month-end return is calculated minus the SHY sign, with a mix of positive fraction and component diagnostics, but no selection. The system uses a passive full sleeve approach. For the next session, the open monthly target weight is set within independently compounding sleeves, with 1 basis point fees and 5/15 slippage, and final era close costed liquidation. The system also considers vector bt position episodes aggregate partial resizes, and notes that correlated positions are not independently and identically distributed, which means they are not random and unrelated. Inactive cash is set to zero, with expenses embedded in prices. This is a long cash adaptation, not a risk-balanced short futures strategy like AQR, and does not require mandatory ADR exits. The source data is from 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 monthly, signal is 1, cost per side is 0.0016, era is holdout, return is 31.563513578995185, drawdown is -23.163194329116322, win rate is 44.713656387665196, sample is 908, average win percentage is 9.323533406376454, average loss percentage is 4.361832258759633, quarter Kelly diagnostic is 0.047122561896515786, annual return is 4.681397174618174, mean daily percentage is 0.019747360940023353, annual volatility percentage is 8.84778262407613, Sharpe ratio with zero cash is 0.5624386547816556, and open positions is 0.