A news scan found the notes from a trading fund manager. The notes were corrected on 1831 and 1833. The manager used a method called SIP, which is a way to adjust data, and trained it from 2016 to 2019, held out from 2020 to 2025, and used 2026 separately. The manager excluded a type of exit called era-crossing exits. The manager used a mode called control, which means they made decisions based on the penultimate close, or the close before the last one, and the third next month close. They also used a calendar, which is a way to organize time, and looked at the last day open and the third next month close. The manager controlled sessions 10 to 13 and used a swing, which is a type of trading strategy, with a prior ADR, or average daily range, of 20, a stop, or a price to sell, of 1.5k, and a target, or a price to buy, of 1.5k. The manager also used a daily stop, which is a price to sell, and a gap open, which is a big change in price. The fees were 1 basis point, or a small unit of measurement, plus slippage, or the difference between the expected price and the actual price, of 15 basis points per side. The manager used a factor called k, which is a way to measure risk, of 1. The manager had eight independent cash sleeves, which are like separate accounts, with initial equal weights, and no inter-ETF rebalance, which means they did not move money between the accounts. The manager looked at daily close drawdown, which is a measure of loss, and not intraday drawdown, which is a measure of loss during the day. The manager used a custom max error of 1.67e-15, which is a very small number. The columns in the data were symbol, return percentage, drawdown percentage, number of trades, win percentage, average win percentage, average loss percentage, mean percentage, quarter Kelly, which is a way to measure risk, and buy hold percentage. The data included the following ETFs: SPY, IWM, EFA, EEM, EWJ, EWU, EWC, and EWA, with their respective return percentages, drawdown percentages, and other metrics. The data was current and used survivor ETFs, which are ETFs that are still trading, and adjusted prices, which are prices that have been changed to reflect dividends and other factors. The manager did not promote holdout neighbors, which means they did not use certain data to make decisions. The source of the data was https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all.
A news scan found the notes from a trading fund manager. The notes were corrected on 1831, 1833, and 1829. The manager used a method called SIP, which is a way to adjust data, and trained it from 2016 to 2019, held out data from 2020 to 2025, and used 2026 separately. The manager excluded certain types of exits, which are when the fund stops investing in something. The manager had different modes of control, including one that used the price of something at the end of the day, and another that used the price at the end of the month. The manager also used something called a swing, which is a type of investment strategy, with a stop, which is a price at which the fund stops investing, and a target, which is a price at which the fund aims to sell. The manager paid fees of 1 basis point, which is a unit of measurement for interest rates, and 5 basis points for slippage, which is when the price of something changes quickly. The manager used 8 independent cells, which are like separate accounts, with equal weights, which means they were all treated the same. The manager did not rebalance, which means adjust the amounts in each cell, between ETFs, which are types of investments. The manager used a daily close, which is the price at the end of the day, and did not use intraday data, which is data from during the day. The manager used a custom max error, which is a way to measure how accurate something is, of 1.67e-15. The manager looked at columns of data, including symbol, which is a code for a type of investment, return percentage, drawdown percentage, which is a measure of how much something has lost value, and other measures. The data included the following investments: SPY, IWM, EFA, EEM, EWJ, EWU, EWC, and EWA, with their respective return percentages, drawdown percentages, and other measures. The data came from a source at https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all, which is a website that provides financial data.
A news scan found the notes from a trading fund manager. The notes were frozen and then corrected. The manager used a method called SIP to adjust the data from 2016. The manager trained the system using data from 2017 to 2019, held out data from 2020 to 2025, and used 2026 separately. The manager excluded certain types of exits, which are when the system sells a stock. The system uses a calendar, which is a way of organizing time, and it looks at the last day of the month and the next three months. The manager also used something called ADR, or average daily range, which is a measure of how much a stock's price moves in a day, and a stop, which is a price at which the system sells a stock to limit losses. The manager also used a target, which is a price at which the system sells a stock to make a profit. The manager paid fees of 1 basis point, which is a unit of measurement for interest rates, and 15 basis points for slippage, which is when the system buys or sells a stock at a different price than expected. The manager used eight separate accounts, called cash sleeves, with equal amounts of money in each. The manager looked at the daily closing prices, not the prices during the day. The manager used a system called vectorbt and set a maximum error of 1.67e-15. The manager looked at several pieces of data, including the symbol of the stock, the return, which is the profit or loss, the drawdown, which is the amount of money lost, and the win percentage, which is the percentage of trades that made a profit. The manager looked at the following stocks: SPY, IWM, EFA, EEM, EWJ, EWU, EWC, and EWA. The data for these stocks included the return, drawdown, number of trades, win percentage, average win, average loss, mean return, quarter Kelly, which is a measure of how much to bet, and buy hold percentage, which is the percentage of the time that the system would have made a profit if it had just bought and held the stock. The data was as follows: SPY had a return of -10.93%, IWM had a return of -16.13%, EFA had a return of -12.83%, EEM had a return of -13.73%, EWJ had a return of -10.28%, EWU had a return of -20.46%, EWC had a return of -13.97%, and EWA had a return of -16.59%. The manager used adjusted prices, not raw dividend prices, and whole shares, not fractions of shares. The manager did not promote holdout neighbors, which are stocks that are similar to the ones being traded. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all.
A news scan found the notes from an automated trading fund manager. The notes were corrected on 1831 and 1833. The manager used a method called SIP, which is a way to adjust data, and trained the system from 2016 to 2019, held out data from 2020 to 2025, and used 2026 separately. The manager excluded a type of exit called era-crossing exits. The system used a calendar mode, which means it looked at data from the last day of the month to the third month after that. The manager also used something called ADR, which stands for Average Daily Range, a measure of how much prices move. The fees were 1 basis point, which is a unit of measurement for interest rates, plus 5 basis points for slippage, which is the difference between expected and actual prices. There were eight independent parts, called cash sleeves, with equal weights and no rebalancing between them. The manager used a custom error limit of 1.67e-15. The results included columns for symbol, return percentage, drawdown percentage, and other metrics. The results for the ETFs were as follows: SPY had a return of -4.47%, IWM had a return of -10.05%, EFA had a return of -6.51%, EEM had a return of -7.47%, EWJ had a return of -3.77%, EWU had a return of -14.70%, EWC had a return of -7.74%, and EWA had a return of -10.54%. The data came from a source called runway.adityaperswal.workers.dev, which provided stock bar data with all adjustments.
A news scan found the headline 'QTOM91006 train published 16 1 eight fixed ETF cells'. Frozen notes from 1829 to 1831 were corrected in 1833. The system was trained from 2016 to 2019, held out from 2020 to 2025, and a separate period was used for 2026. The system excludes era-crossing exits. The mode is published, which means it uses the penultimate close to the third next month close. The calendar uses the last day open to the third next month close. The control uses sessions 10 to 13. The swing uses a calendar with a prior ADR 20 stop, a target of 1.5k, half plus 1R, and a buy entry following the day, with a daily stop at the first gap open. Fees are 1 basis point plus slippage of 15 basis points per side. A basis point is one hundredth of a percent. Slippage refers to the difference between expected and actual trade prices. There are eight independent cash sleeves with initial equal weights and no inter-ETF rebalance. Daily close drawdown and no intraday drawdown are used. Vectorbt is a backtesting library, and custom max error is 1.67e-15. The columns show the symbol, return percentage, drawdown percentage, number of trades, win percentage, average win percentage, average loss percentage, mean percentage, quarter Kelly, and buy hold percentage. The data includes the following ETFs: SPY, IWM, EFA, EEM, EWJ, EWU, EWC, and EWA, with their respective return percentages, drawdown percentages, and other metrics. The current survivor ETFs use adjusted prices, not raw dividend, whole-share, and 3 entry cap or overnight 15 minute validated. There is no promote holdout neighbors. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all.
A news scan found the notes from a trading fund manager. The notes were frozen and then corrected. The manager used a method called SIP to adjust some numbers from 2016. They used the years 2017 to 2019 to train, 2020 to 2025 to hold out, and 2026 separately. They excluded some exits that happened when a stock's price crossed a certain point. The manager had a published mode, which means they used the closing price of the second-to-last day and the closing price of the third month. They also used a calendar that went from the last day of the month to the third month. The manager had control over sessions 10 to 13 and used a swing method with a stop and target. The fees were 1 basis point plus 5 basis points for slippage per side. The manager used 8 independent cash sleeves with equal weights and no rebalancing between ETFs. They used daily close drawdown and not intraday drawdown. A tool called Vectorbt was used with a custom max error. The columns in the data included symbol, return percentage, drawdown percentage, and other numbers. The data included the following ETFs: SPY, IWM, EFA, EEM, EWJ, EWU, EWC, and EWA. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all.
A news scan found the headline 'QPAIR91004 2026 swing frozen parameter sweep, all12cells'. This is a report from an automated trading fund manager. The manager used a preregistered lookback of 60 or 120 days, which means they looked at the market data from the past 60 or 120 days to make decisions. They also used an xentry of 1.5, 2, or 2.5, which refers to the price at which they entered a trade. The xcost was 6 or 16 bps, which is a measure of the cost of trading, with bps meaning basis points, or a unit of measurement for interest rates and trading costs. The exit strategy was to sell after 0.5 or 10 sessions, which are periods of trading. The swing parent earlier open or 5 session ADR, which stands for Average Daily Range, was used to determine the best time to enter a trade. The ADR is a measure of the average price range of a security over a certain period. The manager used a half plus 1R, which is a risk management strategy, and a BE, or breakeven, following day strategy. The results were measured using a base 60 or 2 decision cell, which means they used a specific set of criteria to make decisions. The portfolios were all cash-only and were reconciled using a custom method with a very small error rate of 4.55e-13. The daily close DD, which refers to the maximum drawdown, or loss, of the portfolio, was also measured. The results were based on 12 independent sleeves, which are separate parts of the portfolio, and current ETF survivors, which are exchange-traded funds that have survived in the market. The results did not include actual 3 new positions, whole-share, or 15-minute venue validation. The data was obtained from a source at https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. The results are presented in a table with columns for lookback, entryz, bpside, return percentage, DD percentage, N, win percentage, average win percentage, average loss percentage, and mean trade percentage. The table shows the results for different combinations of lookback, xentry, and xcost, with return percentages ranging from -0.54732687668817 to -2.69976468750015, and DD percentages ranging from -0.9448239334113762 to -3.1848498740007836.
A news scan found the headline 'QPAIR91004 2026 partner frozen parameter sweep, all12cells'. The source is a data line from https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. It appears to be a list of trading results with various parameters. The parameters include lookback, which refers to the amount of time used to calculate trading signals, entry, which is the price at which to enter a trade, and bpside, which is a type of trading fee measured in basis points. The results show return percentages, drawdown percentages, and other metrics for different combinations of these parameters. The list includes 12 sets of results with the following values: [[60,2,6,3.4131564952848636,-2.5210388928156524,85,55.294117647058826,2.7062532806392277,2.2792484256888024,0.4774407531043438],[60,2,16,1.9458284757132294,-2.57846801218814,85,52.94117647058824,2.6175583216331755,2.3567943518031274,0.2766864753102092],[60,1.5,6,6.018575168585616,-3.5201054452597247,129,55.03875968992248,2.6915395872429735,2.0073479865564328,0.5788614532866513],[60,1.5,16,3.7618661801841036,-3.712953955723697,129,52.71317829457365,2.6001286105058243,2.099328857306453,0.37790453657908846],[60,2.5,6,0.7120918786366781,-1.8582079570809262,43,55.81395348837209,1.8825944267432826,1.9242956125660584,0.20048022332752732],[60,2.5,16,-0.011390753006634835,-1.9562562535828332,43,51.162790697674424,1.8426251865026122,1.929797315073492,0.0002793136398636214],[120,1.5,6,2.9026855756213443,-4.567855756216687,124,49.193548387096776,2.629597506595963,1.947157319159152,0.30431078060747724],[120,1.5,16,0.8077353288156619,-4.732183913137355,124,45.16129032258064,2.64901687549503,1.9920741956895571,0.10390241710348201],[120,2,6,2.8827204039914234,-2.5134078512216496,67,46.26865671641791,3.4000299635638083,1.90512634439062,0.549498216006205],[120,2,16,1.744104386984624,-2.635554803993767,67,44.776119402985074,3.303395475428498,2.0471801746986076,0.3485999671493503],[120,2.5,6,0.53024381436102,-2.206907447828388,36,61.111111111111114,2.4130203278479314,3.3257235096204005,0.18128661327691348],[120,2.5,16,-0.06733158788386762,-2.2493833084077375,36,55.55555555555556,2.4432307376448184,3.09650930395529,-0.01887594751078556]].
A news scan found the headline 'QPAIR91004 2026 long frozen parameter sweep, all12cells'. The details are about a trading strategy. The strategy has a preregistered lookback of 60 or 120, which means the system looks back at 60 or 120 previous sessions to make decisions. It also has an xentry of 1.5, 2, or 2.5, which refers to the entry point, and a bpside of 6 or 16, which refers to the cost in basis points, a measure of the cost of a trade. The exit strategy is based on.5 or 10 sessions, and a swing parent earlier open or 5 session ADR, which is a measure of the average daily range of a stock. The system does not select the best cell, instead, it uses a base of 60 and 2 as the decision cell. The portfolios are all cash-only and use a vectorbt custom reconcile of 4.55e-13. The daily close is used to calculate the drawdown, which is a measure of the decrease in value of a portfolio. There are 12 independent sleeves, which are groups of stocks, and the current ETF survivors are used, but not actual new positions. The system also uses whole-share and 15-minute venue validation. The results are shown in a table with columns for lookback, entryz, bpside, return percentage, drawdown percentage, number of trades, win percentage, average win percentage, average loss percentage, and mean trade percentage. The table shows the results for different combinations of lookback, entryz, and bpside. The data comes from the source https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all.
A news scan found the headline 'QPAIR91004 holdout swing frozen parameter sweep, all12cells'. The source is a data line from https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. It appears to be a set of trading parameters and results. The parameters include lookback periods of 60 or 120, entry points of 1.5, 2, or 2.5, and costs of 6 or 16 basis points. The exit strategy is based on 0.5 or 10 sessions, and the swing parent is determined by the earlier open or 5-session average daily range. The results are presented in a table with columns for lookback, entry, cost, return percentage, drawdown percentage, number of trades, win percentage, average win percentage, average loss percentage, and mean trade percentage. The table contains 12 rows of data, each representing a different combination of parameters. For example, the first row shows a lookback of 60, entry of 2, cost of 6, return of -7.482735811444297 percent, drawdown of -8.062771031087145 percent, 693 trades, win percentage of 47.33044733044733 percent, average win of 1.1622766582272532 percent, average loss of 1.298209026864466 percent, and mean trade of -0.13365014560893357 percent.
A news scan found the headline 'QPAIR91004 holdout partner frozen parameter sweep, all12cells'. This is a report from an automated trading fund manager. The manager tested different trading strategies, also known as a parameter sweep, using historical data from the past 60 and 120 days, which is called the lookback period. The manager used different entry points, or xentry, of 1.5, 2, and 2.5, and different costs, or bpside, of 6 and 16 basis points, which is a measure of the cost of a trade. The manager also tested different exit strategies, including exiting after 0.5 or 10 sessions, or using a swing parent earlier open or 5 session average daily range, which is a measure of the average daily price movement. The results are shown in a table with columns for lookback period, entry point, cost, return percentage, drawdown percentage, number of trades, win percentage, average win percentage, average loss percentage, and mean trade percentage. The table shows the results for 12 different combinations of these parameters. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all.
A news scan found the headline 'QPAIR91004 holdout long frozen parameter sweep, all12cells'. This is a report from an automated trading fund manager. The report includes a table with results from different trading strategies. The strategies are defined by several parameters: lookback, which is the amount of time used to calculate the strategy, entryz, which is the price at which to enter a trade, and bpside, which is a type of trading fee, measured in basis points, or 0.01% increments. The report also includes the return percentage, drawdown percentage, number of trades, win percentage, average win percentage, average loss percentage, and mean trade percentage for each strategy. The table shows the results for 12 different combinations of these parameters. The data was sourced from https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. The results are as follows: lookback of 60 or 120 days, entryz of 1.5, 2, or 2.5, and bpside of 6 or 16. The return percentages range from -14.86% to 9.73%, and the drawdown percentages range from -14.84% to -24.06%. The number of trades ranges from 281 to 1250. The win percentages range from 48.24% to 54.56%. The average win percentages range from 2.04% to 2.78%, and the average loss percentages range from 2.12% to 3.42%. The mean trade percentages range from -0.26% to 0.13%.
A news scan found the headline 'QPAIR91004 train swing frozen parameter sweep, all12cells'. The source is a data line from https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. It appears to be a set of trading parameters and results. The parameters include lookback periods of 60 or 120, entry points of 1.5, 2, or 2.5, and costs of 6 or 16 basis points, which is a measure of the cost of a trade as a fraction of the trade value. The results include return percentages, drawdown percentages, and win percentages for different combinations of these parameters. The data is presented in a table with columns for lookback, entry, cost, return percentage, drawdown percentage, number of trades, win percentage, average win percentage, average loss percentage, and mean trade percentage. The table contains 12 rows of data, each representing a different combination of parameters. For example, one row shows a lookback of 60, an entry of 2, a cost of 6 basis points, a return of -3.9049%, a drawdown of -4.7856%, 327 trades, a win percentage of 47.0948%, an average win of 0.7343%, an average loss of 0.9407%, and a mean trade percentage of -0.1518%.
A news scan found the headline 'QPAIR91004 train partner frozen parameter sweep, all12cells'. This refers to a set of experiments for an automated trading system. The system was tested with different parameters, including lookback periods of 60 or 120, entry points of 1.5, 2, or 2.5, and costs of 6 or 16 basis points. A basis point is a unit of measurement for interest rates and other financial percentages, equal to one hundredth of a percent. The system would exit after 0.5 or 10 sessions. A session refers to a period of trading activity. The system also considered the average daily range, or ADR, which is a measure of the average daily price movement of a security. The results of the experiments are shown in a table with columns for lookback period, entry point, cost, return percentage, drawdown percentage, number of trades, win percentage, average win percentage, average loss percentage, and mean trade percentage. Drawdown refers to the peak-to-trough decline in the value of a portfolio. The table shows the results of 12 different experiments, including the return percentage, which ranged from -7.359 to 6.066, and the drawdown percentage, which ranged from -4.768 to -13.915. The data came from a source at https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all, which is a URL for a data feed.
A news scan found the headline 'QPAIR91004 train long frozen parameter sweep, all12cells'. This is a report from an automated trading fund manager. The manager used a preregistered lookback of 60 or 120 days, with an entry point of 1.5, 2, or 2.5, and a cost of 6 or 16 basis points, which is a measure of the cost of a trade as a fraction of the trade value. The exit strategy was based on 0.5 or 10 sessions, with a swing parent earlier open or 5 session average daily range of 1 or 1.5 half plus 1 risk to reward ratio, which is a measure of the potential profit or loss of a trade, following the next day. The manager did not select the best cell, instead using a base of 60 days and 2 as the decision cell. The manager used all cash-only portfolios with a vectorbt custom reconcile of 4.55e-13, which is a very small number, and a daily close drawdown, which is a measure of the decline in value of a portfolio from its peak. The manager also used 12 independent sleeves, which are separate parts of the portfolio, and current ETF survivors, which are exchange-traded funds that have survived a certain period of time, but not actual 3 new positions, whole shares, or 15 minute venue validation. The results are shown in a table with columns for lookback, entry, basis points, return percentage, drawdown percentage, number of trades, win percentage, average win percentage, average loss percentage, and mean trade percentage. The table shows the results of 12 different scenarios, with lookbacks of 60 or 120 days, entries of 1.5, 2, or 2.5, and costs of 6 or 16 basis points. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all.
A news scan found the headline 'QPAIR91004 FINAL swing 2026 16bp holding-count correction'. This is a correction to a previous holding duration, which was in place from 2018 to 2023. The return, drawdown, win rate, payoffs, sample, and orders remain unchanged. The opening gap or spread exits are now counted as completed sessions, and intraday or close exit counts are increased by 1. An event index, which is the actual exit index, is used to explicitly separate the exit index from its parent index. The prior file retained the parent index while the exit date was already correct. A 12 ETF pair cash-only adaptation was fixed, which is not an exact Gatev replication. Earlier notes, including 1770, 1773, and 1776, were preregistered and corrected. The prior close log ratio is used to determine buys and exits. The swing strategy adds a prior 20 ADR stop, target 1.5, and half plus 1 risk to breakeven following day. Fees are 1 basis point plus 5 or 15 basis points per side. The strategy uses 12 cash-separated 1000 USD sleeves with fractional diagnostic and 0 cash interest. Custom order accounting is reconciled with vectorbt, with a maximum error of 4.55e-13. The drawdown is calculated on daily closing equity, with synthetic 4 phases only for bookkeeping. The training period is from 2017 to 2019, and the holdout period is from 2020 to 2025, with 2026 through September 9 separate. The warm-up period is 2016. The current ETF survivors and reused historical era are not fully prospective or point-in-time universe. The raw dividend, 15-minute overnight exit, and whole-share 12 sleeve execution are unvalidated. The actual allocation is 0. A data source is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. The strategy parameters are: era is 2026, mode is swing, lookback is 60, threshold is 2, cost basis point per side is 16, sample is 85, win rate is 44.70588235294118, average win percentage is 0.944269809591242, average loss percentage is 1.3829640925000688, mean trade percentage is -0.3425536421533652, return percentage is -2.3871083914865365, drawdown percentage is -2.917901489156405, annual percentage is -3.477892493775503, quarter Kelly is 0, and reconciliation error is 2.2737367544323206e-13, mean holding is 1.8823529411764706.
A news scan found the headline 'QPAIR91004 FINAL swing 2026 6bp holding-count correction'. This supersedes the matching 2018–2023 holding duration only. The return, drawdown, win rate, payoffs, sample, and orders remain unchanged. The opening gap or spread exits now count as completed sessions. Intraday or close exit counts are now one more than the actual exit index. The actual exit index is called event e, and the parent index is explicit and separate. The prior file retained the parent index while the exit date was already correct. The adaptation for 12 ETF pairs is cash-only and not an exact Gatev replication. Prior notes 1770 and 1773 were preregistered, and an earlier spread exit note 1776 was corrected. The prior 60 close log ratio z is greater than or equal to 2, which means buying the losing leg at the next open, and exiting when the signed z is less than or equal to 0.5 at the next open or 10 sessions. The parent partner control has identical entry and exit dates. The swing adds a prior 20 ADR stop 1, target 1.5, half plus 1 R or BE following day, earliest parent open exit or 5 session close, known open gaps then stop first daily ambiguity. Fees are 1 basis point plus 5 or 15 basis points per side. There are 12 cash-separated 1000 USD sleeves, with fractional diagnostic and 0 cash interest. Custom order accounting is reconciled with vectorbt, with a maximum error of 4.55e-13. Drawdown is calculated on daily closing equity, with synthetic 4 phases only for bookkeeping. The training period is 2017–19, the holdout period is 2020–25, and 2026 through September 9 is separate, with 2016 as a warm-up. The current ETF survivors or reused historical era are not fully prospective or point-in-time universe. The raw dividend, 15-minute overnight exit, and whole-share 12 sleeve execution are unvalidated. The actual allocation is 0. The source is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. The data includes the era 2026, mode swing, lookback 60, threshold 2, cost per basis point per side 6, sample 85, win rate 49.411764705882355, average win percentage 1.046315050016964, average loss percentage 1.3047338220121734, mean trade percentage -0.14303908524483494, return percentage -0.9904116127343765, drawdown percentage -1.9254991703749558, annual percentage -1.4477200319909067, quarter Kelly 0, and reconciliation error 2.2737367544323206e-13, with a mean holding of 1.8823529411764706.
A news scan found the text of a final swing holdout report. This report supersedes the matching 2018-2023 holding duration only. The return, drawdown, win rate, payoffs, sample, and orders remain unchanged. The opening gap or spread exits now count as completed sessions. Intraday or close exit counts are now one more than the actual exit index. The actual exit index is called event e, and the parent index is explicit and separate. The prior file retained the parent index while the exit date was already correct. The report fixed the 12 ETF pair cash-only adaptation, which is not an exact Gatev replication. The preregistered notes are 1770 and 1773, and the report corrected an earlier spread exit note 1776. The prior 60 close log ratio z is greater than or equal to 2, which means buying the losing leg at the next open, and exiting when the signed z is less than or equal to 0.5 at the next open or 10 sessions. The parent partner control has identical entry and exit dates. The swing adds a prior 20 ADR stop 1, target 1.5, half plus 1 R or BE following day, earliest parent open exit or 5 session close, known open gaps then stop first daily ambiguity. The fees are 1 basis point plus 5 or 15 basis points slip per side. There are 12 cash-separated 1000 USD sleeves, fractional diagnostic, and 0 cash interest. The custom order accounting is reconciled vector bt max 4.55e-13, and the drawdown is on daily closing equity, synthetic 4 phases only bookkeeping. The train period is 2017-2019, holdout is 2020-2025, and 2026 through September 9 is separate, with 2016 as a warm-up. The current ETF survivors or reused historical era are not fully prospective or point-in-time universe, and the raw dividend, 15-minute overnight exit, whole-share 12 sleeve execution is unvalidated. The actual allocation is 0. The source is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. The report includes the following data: era is holdout, mode is swing, lookback is 60, threshold is 2, cost basis point per side is 16, sample is 693, win rate is 43.722943722943725 percent, average win percent is 1.0497530757657871, average loss percent is 1.4076187714913904, mean trade percent is -0.3331834616516719, return percent is -17.443805966494452, drawdown percent is -17.631252757542924, annual percent is -3.1525611975993906, quarter Kelly is 0, and reconciliation error is 2.2737367544323206e-13, mean holding is 2.168831168831169.
A news scan found the text describing an update to a trading system. This update supersedes the holding duration from 2018 to 2023, but other metrics like return, drawdown, win rate, payoffs, sample, and orders remain unchanged. The system now counts completed sessions for opening gap or spread exits, and intraday or close exit counts are one more than the actual exit index. An actual exit index is called event e, and a separate index is called parent e. The prior file retained the parent index while the exit date was already correct. The system was adapted for 12 ETF pairs with cash only, not exactly replicating Gatev. Earlier notes were preregistered, with corrections made to note 1776 about spread exits. The system buys the losing leg at the next open if the log ratio z is greater than or equal to 2, and exits when z is less than or equal to 0.5 at the next open or after 10 sessions. The system has a swing component that adds a prior 20 ADR stop, with a target of 1.5 and a half plus 1 risk to breakeven the following day. Fees are 1 basis point plus 5 or 15 basis points per side. The system uses 12 cash-separated 1000 USD sleeves with fractional diagnostics and no cash interest. Custom order accounting was reconciled with a vectorbt maximum error of 4.55e-13. The system was trained from 2017 to 2019, with a holdout period from 2020 to 2025, and a separate period from 2026 to September 9. The system uses current ETF survivors and reused historical era, not a fully prospective or point-in-time universe. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. The system's performance metrics include a win rate of 47.33%, an average win percentage of 1.16%, an average loss percentage of 1.30%, and a mean trade percentage of -0.13%. The return percentage is -7.48%, the drawdown percentage is -8.06%, and the annual percentage is -1.29%.
A news scan found the headline 'QPAIR91004 FINAL swing train 16bp holding-count correction'. This is a final update to the QPAIR91004 swing train, which is a type of automated trading strategy. The update supersedes, or replaces, the matching 2018-2023 holding duration only. The return, drawdown, win rate, payoffs, sample, and orders remain unchanged. The opening gap or spread exits now count as completed sessions, and intraday or close exit counts are increased by 1. An event index, which is a way to track exits, is now actual, and the parent index, which is a separate way to track exits, is explicit. The prior file retained the parent index while the exit date was already correct. The update also fixed a 12 ETF pair cash-only adaptation, which is not an exact replication of the Gatev method. Prior notes 1770 and 1773 were preregistered, and an earlier spread exit note 1776 was corrected. The strategy buys the losing leg at the next open if the prior 60 close log ratio is greater than or equal to 2, and exits when the signed log ratio is less than or equal to 0.5 at the next open or after 10 sessions. The parent partner control has identical entry and exit dates. The swing strategy adds a prior 20 ADR stop, which is a way to limit losses, at 1, target 1.5, half plus 1 risk to reward, or break even, following day, earliest parent open exit, or 5 session close. Fees are 1 basis point plus 5 or 15 basis points per side, which is a way to measure trading costs. The strategy uses 12 cash-separated 1000 USD sleeves, which is a way to manage risk, with fractional diagnostic, and 0 cash interest. Custom order accounting is reconciled with vectorbt, which is a way to track trades, with a maximum error of 4.55e-13. Drawdown is calculated on daily closing equity, with synthetic 4 phases only for bookkeeping. The train period is 2017-2019, the holdout period is 2020-2025, and 2026 through September 9 is separate, with 2016 as a warmup. The current ETF survivors or reused historical era are not fully prospective or point-in-time universe, which means the strategy is not based on real-time data. Raw dividend, 15 minute overnight exit, and whole-share 12 sleeve execution are unvalidated. The actual allocation is 0. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. The strategy has a sample size of 327, a win rate of 36.09%, an average win percentage of 0.72%, an average loss percentage of 0.96%, a mean trade percentage of -0.35%, a return percentage of -8.99%, a drawdown percentage of -9.24%, and an annual percentage of -3.10%.
A news scan found the text describing an update to a trading system. This update supersedes the holding duration from 2018 to 2023, but other metrics like return, drawdown, win rate, payoffs, sample, and orders remain unchanged. The system now counts completed sessions for opening gap or spread exits, and intraday or close exit counts are increased by one. An event index, which is the actual exit index, is explicitly separated from its parent index. A prior file retained the parent index while the exit date was already correct. The update fixed a 12 ETF pair cash-only adaptation, which is not an exact Gatev replication. Earlier notes, including 1770, 1773, and 1776, were preregistered and corrected. The system buys the losing leg at the next open if the prior 60 close log ratio is greater than or equal to 2, and exits when the signed ratio is less than or equal to 0.5 at the next open or after 10 sessions. The swing system adds a prior 20 ADR stop at 1, with a target of 1.5, and half of the risk or break-even point following the next day, or at the earliest parent open exit or 5 session close. Fees are 1 basis point plus 5 or 15 basis points per side. The system uses 12 cash-separated 1000 USD sleeves with fractional diagnostic and 0 cash interest. Custom order accounting is reconciled with a vectorbt maximum error of 4.55e-13, and drawdown is calculated on daily closing equity. The system is trained from 2017 to 2019, with a holdout period from 2020 to 2025, and a separate period from 2026 to September 9. The current ETF survivors or reused historical era are not fully prospective or point-in-time universe. The system's actual allocation is 0. Source is a data feed from https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all, with the following metrics: era is train, mode is swing, lookback is 60, threshold is 2, cost per basis point per side is 6, sample is 327, win rate is 47.09480122324159 percent, average win percentage is 0.7343180414451267, average loss percentage is 0.9406512971323767, mean trade percentage is -0.1518278165790571, return percentage is -3.9049073757491115, drawdown percentage is -4.78559410583509, annual percentage is -1.3224310717029675, quarter Kelly is 0, and reconciliation error is 2.2737367544323206e-13.
A news scan found the headline 'QPAIR91004 hedged diagnostic 2026 16bp; unavailable venue'. This refers to a diagnostic test of a trading strategy called QPAIR91004. The test used a hypothetical trading schedule with a 0.5 unit long position loser and a -0.5 unit short position winner per unit of capital. The test assumed fees of 1 basis point plus a 5 to 15 basis point slip for both long and short positions, and an annual short borrow rate of 3% with no interest rebate. The test also used a custom cash and profit and loss diagnostic, but did not account for venue availability or short order limitations. The results showed a net negative return for all six era and cost cells, with a return of -2.46% and a drawdown of -2.46%. The test was based on 85 samples, with a win rate of 7.06% and an average win of 0.36% and an average loss of -0.41%. The mean trade return was -0.35%. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all.
A news scan found the headline 'QPAIR91004 hedged diagnostic 2026 6bp; unavailable venue'. This is a diagnostic report for a trading strategy called QPAIR91004. The strategy uses a schedule to enter and exit trades, with a hypothetical adjustment of +0.5 for long losers and -0.5 for short winners per unit of capital. The report includes gross and daily close marks, as well as actual open entry and exit data. Both legs of the trade have fees of 1 basis point plus 5 to 15 basis points for slippage, and short borrowing is assumed to be 3% annual interest with no interest rebate on actual calendar days. The report is a custom cash and profit and loss diagnostic, but it is not offered by the venue and does not include short orders. The report also lacks data on borrow availability and margin history, which prevents trades from being made even if they are positive. The results show a net negative return for all six era and cost cells. This adaptation of an exchange-traded fund does not disprove the published stock distance pairs. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all. The data includes the following metrics: era is 2026, mode is hedged diagnostic, cost per side is 6 basis points, return is -1.0646%, drawdown is -1.1187%, sample size is 85, win rate is 14.12%, average win is 0.3272%, average loss is 0.2298%, mean trade is -0.1512%, borrow annual interest is 3%, and gross exposure is 1.
A news scan found the headline 'QPAIR91004 hedged diagnostic holdout 16bp; unavailable venue'. This is a report about a trading strategy called QPAIR91004. It uses a schedule to enter and exit trades, with a hypothetical extra 0.5 units of capital for long trades that lose and 0.5 units less for short trades that win. The strategy has fees of 1 basis point plus 5 to 15 basis points for slipping, and assumes short borrowing costs 3% per year. A basis point is one hundredth of a percent. The report also mentions a custom diagnostic tool to track profit and loss, but this tool is not offered by the trading venue and does not allow short orders. The report concludes that the strategy has a net negative result in all six areas examined, with a return of -18.526144243475727% and a drawdown of -18.526144243475727%. A drawdown is a decrease in value. The report is based on data from https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all.
A news scan found the headline 'QPAIR91004 hedged diagnostic holdout 6bp; unavailable venue'. This refers to a trading strategy test. The test used a schedule to enter and exit trades over ten sessions, comparing results with and without a hypothetical adjustment. The adjustment added 0.5 to losing long trades and subtracted 0.5 from winning short trades per unit of capital. The test included fees of 1 basis point plus a 5 to 15 basis point slip for both long and short trades, and assumed a 3% annual short borrow cost over actual calendar days with no interest rebate. A custom diagnostic was used to evaluate cash and profit and loss, but the test was limited because it did not account for venue availability or short order feasibility, and lacked data on borrow availability and historical margin requirements. As a result, the test could not be completed even if the results were positive. The results showed a net negative outcome across all six cost cells, and this adaptation of an exchange-traded fund strategy did not disprove published stock distance pairs data. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all, which provided the following statistics: the test was in holdout era mode with a hedged diagnostic approach, had a cost of 6 basis points per side, a return of -8.56982548022306%, a drawdown of -8.56982548022306%, 693 samples, a win rate of 15.151515151515152%, an average win of 0.1638875388825972%, an average loss of 0.21198345841403582%, a mean trade of -0.15503330730848536%, a borrow annual percentage of 3%, and a gross exposure of 1. The actual size was 0.