Stats

The QREV90804 strategy was not optimized. This record combines 9 cells across different time periods: training from 2016 to 2020, holdout from 2021 to 2025, and recent from 2026 through September 4. The costs considered are zero, base, and stress. The figures reported are for the baseline holdout only. The full data is as follows: there are three periods - train, holdout, and recent - each with different costs - zero, base, and stress. For each period and cost, the return, drawdown, number of trades, win percentage, and other metrics are reported. The strategy uses a liquid 12 country ETF with a weekly negative worst return. It also uses a prior close signal and next open, with one position and no overlaps. The stop loss is set at 1 ATR and the target is set at 1.5 ATR. The model is fractional and considers fees and slippage. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars. All metrics are separately recorded for the QREV90804 variant, with 001 to 240 observations and no family winner selection.

This is a record of a trading strategy, which is not optimized, from a frozen strategy926/notes920. The strategy was trained from 2016 to 2020, held out from 2021 to 2025, and recently used from 2026 through September 4. The costs considered are zero, base, and stress costs. The results are reported for the holdout period only. The full results are as follows: there are nine cells across three periods - training, holdout, and recent - with different costs. The figures include return, drawdown, number of trades, win percentage, and other metrics. The strategy uses a liquid 12 country ETF with a weekly negative worst return, prior close signal, and next open, with one position and skipping overlaps. The strategy only considers time exits and is not venue-ready. It uses a fractional model with explicit fees and slippage, and independent cash reconciliation. The holdout period was previously inspected for other strategies, with daily OHLC and adjustments, but not 15-minute cash dividend validation. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars. All metrics were separately recorded for the QREV90804 variant, with 001 to 240 observations, and no family winner selection was used.

The QREV90804 strategy was not optimized. This record combines 9 cells across training from 2016 to 2020, held out from 2021 to 2025, and recent data from 2026 through September 4, with zero, base, and stress costs. The figures only report the baseline holdout. The full data is as follows: there are three periods, train, holdout, and recent, each with different costs, returns, and other metrics. The data includes the return, which is the profit or loss, the drawdown, which is the largest decline from a peak, the number of trades, the win rate, and other metrics. The strategy uses a liquid 12 country ETF with a weekly negative worst return, and it skips overlaps. It also uses a prior close signal and next open, with one position. The stop loss is set at 1 ATR, the target is set at 1.5 ATR, and half plus 1 R then break even, with adverse same bar ordering. The model is fractional, with fees and slippage explicitly vectorized, and independent cash reconciliation. The chronological holdout was previously inspected for other strategies, with daily OHLC and adjustments, but not 15-minute cash dividend validation. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. All metrics were separately recorded for the QREV90804 variant, with 001 to 240 observations, and no family winner selection.

This is a record of a trading strategy, specifically the QREV90804 sweep total lookback 3 hold 5 parent, which has not been optimized. The strategy was tested on data from 2016 to 2020, and its performance was evaluated on data from 2021 to 2025, as well as recent data up to September 4, 2026. The evaluation considered zero, base, and stress costs. The results are reported for the holdout period only. The full results are as follows: there are nine cells across three periods - training, holdout, and recent - with different costs. A news scan found the data line with the following figures: for the training period with zero cost, the return was 48.77545160177237, the maximum drawdown was 39.29767978388606, and the win rate was 55.44041450777202. For the holdout period with zero cost, the return was 44.398438556889985, the maximum drawdown was 29.820176916222042, and the win rate was 49.23076923076923. For the recent period with zero cost, the return was -6.05867915929772, the maximum drawdown was 34.34440185422142, and the win rate was 46.42857142857143. Similar figures are reported for base and stress costs. The strategy used a liquid 12 country ETF with weekly negative worst return, prior close signal, and next open, with one position and skipping overlaps. The time exit was only considered, and the strategy was not venue-ready. The model used was fractional, with explicit vector backtest and independent cash reconciliation. The chronological holdout was previously inspected for other strategies, with daily OHLC and adjustments, but not 15-minute cash dividend validation. The data source was https://runway.adityaperswal.workers.dev/data/stock-bars. All metrics were separately recorded for the QREV90804 variant 001, with 240 observations, and no family winner selection was made. Drawdown, or maximum drawdown, refers to the largest decline in value from a peak to a trough. Win rate refers to the percentage of winning trades.

This is a record of a trading strategy, which is not optimized, from Frozen strategy 926 and notes 920. The record covers three periods: training from 2016 to 2020, holdout from 2021 to 2025, and recent from 2026 to September 4. The costs considered are zero, base, and stress. The report only shows figures for the baseline holdout period. The full data is as follows: there are nine cells across the training, holdout, and recent periods. A news scan found the headline is not applicable here, this is a data line. The data line reports the following metrics: return, drawdown, number of trades, win percentage, W, L, and K. For example, in the training period with zero costs, the return was 57.561133899861574, the drawdown was 29.861548652970704, and the win percentage was 56.30630630630631. The strategy uses a liquid 12 country ETF with a weekly negative worst return. It also uses a prior close signal and next open, with one position and skipping overlaps. The stop loss is set at 1 ATR, the target is 1.5 ATR, and half plus 1 R then break even. The model is fractional, with fees and slippage explicitly vectorized and independent cash reconciliation. The holdout period was previously inspected for other strategies, with daily OHLC and adjustments, but not 15-minute cash dividend validation. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars. All metrics were separately recorded for the QREV90804 variant, with 001 to 240 observations, and no family winner selection.

This is a record of a trading strategy, which is not optimized, called Frozen strategy926/notes920. The strategy was tested over three periods: training from 2016 to 2020, holdout from 2021 to 2025, and recent from 2026 to September 4. The costs considered are zero, base, and stress costs. The results are reported for the holdout period only. The full results are: a list of performance metrics for each period and cost type, including return, drawdown, number of trades, win rate, and other metrics. The strategy uses a fractional model, with fees and slippage explicitly considered, and independent cash reconciliation. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars, which provides daily OHLC data and adjustments, but not 15-minute cash dividend validation. The strategy was previously inspected for other strategies and has 240 observations, with no family winner selection. A news scan found the data line with the following metrics: for the train period with zero cost, the return was 157.2376751549046, the drawdown was 21.85065904086422, the number of trades was 222, the win rate was 56.75675675675676, and other metrics were also reported. Similar metrics were reported for the holdout and recent periods, and for the base and stress cost types.

A diagnostic test was run on a trading strategy using the command line interface. The test used a 20-day breakout strategy on the stock symbol GD, with a lookback period of 20 days, 1700 days of data, a stop loss of 5%, and a target profit of 8%. The data came from the website https://runway.adityaperswal.workers.dev/data/stock-bars. The test used 1165 data points and made 83 trades, resulting in a return of -3.23388% and a maximum drawdown of 20.70207%. The win rate was 34.93976%. For comparison, a buy and hold strategy would have given a return of 69.6003%. This test was run to diagnose the strategy's performance and did not take into account any costs or fees. A separate test with costs recorded separately was also run. The command line interface used for this test is not trusted for actual trading or predicting political events.

A preregistered note, number 923, was written before the analysis of stock bars. The analysis used data from 2022 to 2025 for training and from January 2, 2026, to September 4, 2026, as a holdout period, with an adjustment from the IEX, which is a stock exchange, and all data can be found at https://runway.adityaperswal.workers.dev/data/stock-bars. The analysis looked at 1172 bars of data for the stock GD and used a specific strategy to decide when to enter and exit the market. The strategy was to enter the market after the close of a trading day if the next open was higher than the prior 20-day high and the 50-day simple moving average, which is a calculation of the average price of a stock over a certain period. The strategy also used a stop-loss, which is a order to sell a stock when it falls to a certain price, and a target price, which is the price at which the strategy aims to sell the stock. The analysis used a daily gap-stop, which is a stop-loss that is triggered when the stock price gaps up or down, and allowed for same-day entry and exit. The analysis also included a fee of 5 basis points, which is a unit of measurement for interest rates and fees, and 10 basis points of slippage, which is the difference between the expected price of a trade and the actual price, on each side of the trade. The analysis used a stress test, which is a simulation of a worst-case scenario, with 25 basis points of slippage. The analysis was done using a cash-only strategy, which means that the strategy did not use leverage, or borrowed money, and used a hypothetical capital of $10,000, which was reinvested after each trade. The analysis was not a proposal for a fund size. The analysis found that the strategy did not perform well in the training period, with a return of -15.0392% and a maximum drawdown, which is the maximum loss of value, of 23.34594%. The strategy also did not perform well in the holdout period, with a return of -7.4434% and a maximum drawdown of 9.51235%. The analysis also found that the strategy had 7 trades, with 1 win and 6 losses, and that the average win was 2.29118% and the average loss was 1.65053%. The analysis used a bootstrap, which is a statistical method, to simulate the performance of the strategy and found that the mean return was -1.08743% with a 95% confidence interval of -1.99661% to 0.175079%. The analysis also found that the strategy did not have an edge, which means that it did not perform better than a random strategy. The analysis used a Quarter Kelly criterion, which is a method for allocating capital, and found that the optimal allocation was 0, which means that the strategy did not have a positive expected return. The analysis also included an implementation audit, which is a review of the implementation of the strategy, and found that the strategy had been implemented correctly. The analysis also found that the daily closing mark was not the worst-case scenario and that the end window was forced liquidation, which means that the strategy was closed at the end of the period. The analysis also found that all 7 trades in the holdout period were natural closes, which means that they were closed at the end of the period. The analysis was a price-rule test, which means that it tested a specific strategy, and not a backtest of Bombardier political events. The analysis also noted that the exits were not validated and that the sample could not be used to infer the odds of new events.

A trading rule was tested on the PATH stock. The rule was to buy after a big drop in price, called a negative overnight gap, and hold for 10 days. The test used prices from 2022 to 2025 to train the rule and 2026 to see how it worked. The training period had a return of -18.7216% and the biggest loss was 27.5520%. In the holdout period, the return was -15.1665% and the biggest loss was 22.9383%. The rule did not work well in the holdout period. A news scan found the source of the data, which included a headline about stock bars. The test also used a measure called RSI, or Relative Strength Index, which is a way to measure the speed of price changes. The RSI strategy was to buy when the RSI was low and sell when it was not high. The test was done with a $1000 investment and a fee of 5 basis points plus 10 basis points of slippage. The results were not good, with all holdout variants losing money. The daily marked drawdown, which is the biggest loss from peak to trough, missed the worst intraday extremes. The all-in returns were a normalized test and not a real fund size. The raw vectorbt max drawdown was negative, but the figures reported the positive loss magnitude. A separate test using the CLI node had a return of -7.33254% and a biggest loss of 22.2915%. The source of the data was https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=PATH&feed=sip&adjustment=all and the strategies and engine used were in /app/agent/dist/backtest/strategies.js and /app/agent/dist/backtest/engine.js.

A news scan found the notes from an automated trading fund manager. The notes mentioned a delay in the QREV90804, which had a managed stress level recently. The original protocol analysis was done on 926. The manager used a signal that was based on intraday data, looking back 5 days and forecasting 5 days ahead, with a managed cost of stress over a recent period. The return percentage was 11.80706782012544, and the drawdown percentage was 15.654258918747011, over 29 trades, with a win percentage of 55.172413793103445. The average win percentage was 2.2491980684160264, and the average loss percentage was 1.8295700987638936. The mean percentage was 0.42078475209399335, and the quarter Kelly was 0.046770531017564676. The reconciliation in US dollars was 3.637978807091713e-12. The manager skipped 3 overlapping trades and made 2 day trades, with a lag of 2. The manager looked at the country ETF with the lowest negative signal among the prior 5 sessions, with a dollar volume of at least 5 million. The manager entered a trade on the first weekly session open, with one lot, and skipped overlapping entries. The manager closed the trade on the fifth session close. The signal was given two sessions before entry, with one full skipped session. The manager used a stop loss of 1 ATR, with a target of 1.5 ATR, and then broke even. The manager also used a daily bar stop, an opening gap stop, and a target cap. The manager used a fill of zero or a base fee of 5 basis points plus a 5 basis point slip, with a stress level of 5 plus 20. The cash ledger was reconciled to vectorbt events. The returns were based on a fully deployed model strategy sleeve, not account allocation. The manager used a fractional diagnostic, with whole shares, PDT, 15-minute bars, and cash dividends unvalidated. The training data was from 2016 to 2020, with a holdout period from 2021 to 2025, and recent data from 2026 through September 4. The manager noted that a recent positive result cannot rescue a failed training or cost stress. The source of the data was https://runway.adityaperswal.workers.dev/data/stock-bars. The manager did not make a proposal based on this individual cell.

The automated trading fund manager's notes show a delay in the QREV90804 strategy. The original protocol analysis was done on 926. The strategy's performance is as follows: it had a return percentage of -72.38141854276972, a drawdown percentage of 73.72960985843812, and a win percentage of 45.023696682464454. The strategy was based on a signal that occurred two sessions before entry, with a stop loss set at one ATR, which is a measure of volatility, and a target set at 1.5 ATR. The strategy also included a daily bar stop and an opening gap stop. The returns are based on a fully deployed model strategy sleeve, not account allocation. The training data used was from 2016-2020, the holdout data was from 2021-2025, and the recent data was from 2026 through September 4. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. The data is used to analyze the performance of the strategy, but no proposal is based on this individual cell.

A news scan found the notes from a trading fund manager. The notes are about a trading strategy called QREV90804. The strategy had a return percentage of -75.81119474064985 and a drawdown percentage of 77.97399678573255. This means the strategy lost a lot of value. The strategy was tested using data from 2016 to 2020 and then from 2021 to 2025. The strategy was also tested with recent data up to September 4, 2026. The notes mention a country ETF, which is a type of investment fund that tracks a country's stock market. The strategy used a signal, which is a trigger to buy or sell, based on the ETF's price. The signal was generated two sessions before the strategy entered the market. The strategy used a stop-loss, which is a rule to sell when a loss reaches a certain size, set at one times the average true range, or ATR, which is a measure of how much a stock's price moves. The strategy also used a target price, which is a price at which to sell, set at 1.5 times the ATR. The notes mention a fee, which is a cost of 5 basis points, or 0.05%, plus a 5 basis point slip, which is a cost of buying or selling. The strategy was tested with a stress test, which is a simulation of difficult market conditions, with a cost of 5 plus 20. The results are based on a fully deployed model, which means the strategy was tested with all available data, not just a portion of it. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars.

A news scan found the headline 'QREV90804 delay intraday managed base recent'. The trading fund manager's notes are as follows: the fund's performance was analyzed using a protocol called 'protocol analysis' on September 26, with the results showing a return percentage of 21.97% and a drawdown percentage of 13.61% over 29 trades, with a win percentage of 58.62%. The notes also mention a'signal', which refers to a trigger to buy or sell, and a 'lookback' period of 5 days, which is the time frame used to analyze the data. The 'horizon' is also 5 days, which is the time frame used to predict future prices. The fund is'managed', meaning it is actively controlled, and the 'cost' is 'base', referring to the basic cost of trading. The 'period' is'recent', meaning the analysis is based on recent data. The fund's'return percentage' is 21.97%, and the 'drawdown percentage' is 13.61%. The 'win percentage' is 58.62%, and the 'average win percentage' is 2.42%. The 'average loss percentage' is 1.68%, and the'mean percentage' is 0.72%. The 'quarter Kelly' is 0.0746, which is a measure of the optimal bet size. The'reconciliation' in US dollars is a very small number, 3.64e-12, which means the accounts are balanced. The'skipped overlap' is 3, which refers to the number of overlapping trades that were skipped. The 'day trades' is 2, which refers to the number of trades made in a single day. The 'lag' is 2, which refers to the delay between the signal and the trade. The notes also mention a 'country ETF', which is an exchange-traded fund that tracks a country's stock market, and a'signal' that is based on the ETF's price. The signal is triggered when the ETF's price is at its lowest negative level in the prior 5 sessions, and the dollar volume is greater than or equal to 5 million. The trade is entered on the first weekly session open, with one lot, and overlapping entries are skipped. The signal is triggered two sessions before the entry, with one full skipped session. The stop loss is set at 1 ATR, which is a measure of volatility, and the target is set at 1.5 ATR. The stop loss is also set at the daily bar, and the opening gap stop is set at the open. The target is capped, and the same bar partial and breakeven are conservative. The fill is zero or base 5 basis points fee plus 5 basis points slip, with a stress of 5 plus 20. The cash ledger is reconciled to vectorbt events, which is a backtesting platform. The returns are based on a fully deployed model strategy sleeve, not account allocation, and are fractional and diagnostic. The model was trained on data from 2016 to 2020, and the holdout period is from 2021 to 2025. The recent period is from 2026 through September 4. The notes also mention that the recent positive results cannot rescue the failed training and cost stress. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.

The QREV90804 delay is related to intraday managed base holdout. Frozen notes are from 920 to 924, and the original protocol analysis is from 926. A signal was generated with the following parameters: signal is intraday, lookback is 5, horizon is 5, managed is true, cost is base, period is holdout, return percentage is -47.98719724238867, drawdown percentage is 55.69676095921634, n is 211, win percentage is 48.81516587677725, average win percentage is 1.6298930478631921, average loss percentage is 2.1145691682909344, and mean percentage is -0.286703726282048. The quarter Kelly is 0, and the reconciliation in USD is 3.637978807091713e-12. There were 14 skipped overlaps, 26 day trades, and a lag of 2. The country ETF had the lowest negative prior 5 session signal among the prior 20 day median dollar volume, which was greater than or equal to 5 million. The first weekly session open was one lot, with overlapping entries skipped, and the fifth session close was used. The signal was two sessions before entry, with one full skipped session. The prior ATR 14 stop was 1 ATR, and the target was 1.5 ATR, with half plus 1 R, then breakeven. Daily bar stop was first, and opening gap stop was at open, with target capped, and same bar partial and breakeven was conservative. Per fill was zero or base 5 bp fee plus 5 bp slip, with stress 5 plus 20. The cash ledger was reconciled to vectorbt events. Returns were on fully deployed model strategy sleeve, not account allocation, with fractional diagnostic, whole-share, PDT, 15 minute, and cash dividend unvalidated. Training was from 2016 to 2020, holdout was from 2021 to 2025, and recent was 2026 through September 4. Periods were previously inspected for other strategies. Recent positive cannot rescue failed training or cost stress. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.

A news scan found the notes from an automated trading fund manager. The notes mentioned a delay in the QREV90804 intraday managed base train. The original protocol analysis was done on notes 920 through 924, and 926. The analysis showed the following results: the signal was intraday, the lookback was 5, the horizon was 5, it was managed, the cost was base, the period was train, the return percentage was -54.03450266833326, the drawdown percentage was 58.853320097046435, the number of trades was 214, the win percentage was 50, the average win percentage was 1.4738097609417955, the average loss percentage was 2.1521154204816773, and the mean percentage was -0.3391528297699408. The quarter Kelly was 0, and the reconciliation in USD was 5.4569682106375694e-12. The skipped overlap was 8, the day trades were 29, and the lag was 2. The country ETF had the lowest negative prior 5 session signal among the prior 20 day median dollar volume, which was greater than or equal to 5 million. The first weekly session open was one lot, with overlapping entry skipped, and the fifth session close. The signal was two sessions before entry, with one full skipped session. The prior ATR 14 stop was 1 ATR, the target was 1.5 ATR, half plus 1 R, then break even. The daily bar stop was first, the opening gap stop was at open, the target was capped, and the same bar partial and break even were conservative. The fill was zero or base 5 bp fee plus 5 bp slip, stress 5 plus 20. The cash ledger was reconciled to vectorbt events. The returns were on a fully deployed model strategy sleeve, not account allocation, and were fractional diagnostic, whole share, PDT, 15 minute, and cash dividend unvalidated. The training was from 2016 to 2020, the holdout was from 2021 to 2025, and the recent period was from 2026 through September 4. The periods were previously inspected for other strategies. The recent positive cannot rescue the failed training and cost stress. The source of the data was https://runway.adityaperswal.workers.dev/data/stock-bars. There was no proposal based on this individual cell.

A news scan found the headline 'QREV90804 delay intraday parent stress recent'. The trading fund manager's notes are as follows: the fund's performance was analyzed using the original protocol from 926. The analysis showed the following results: the signal was intraday, the lookback period was 5 days, the horizon was 5 days, the fund was not managed, the cost was stress, the period was recent, the return percentage was 19.824254694571096, the drawdown percentage was 13.053110923837696, the number of trades was 26, the win percentage was 57.692307692307686, the average win percentage was 2.7974367058143366, the average loss percentage was 2.0487054393374917, the mean percentage was 0.7471457982501014, the quarter Kelly was 0.06677057220787114, the reconciliation in USD was 3.637978807091713e-12, the skipped overlap was 6, the day trades were 0, and the lag was 2. The fund's strategy was to buy a country ETF with the lowest negative prior 5 session signal among the prior 20 day median dollar volume greater than or equal to 5 million. The entry was on the first weekly session open, with one lot, skipping overlapping entries, and the fifth session close. The signal was two sessions before entry, with one full skipped session. The parent fund has a time exit only, not a venue-ready stop or target strategy. The fill was zero or a base 5 basis point fee plus 5 basis points lip, with stress 5 plus 20. The cash ledger was reconciled to vectorbt events. The returns were on a fully deployed model strategy sleeve, not account allocation, with a fractional diagnostic, whole-share, PDT, 15 minute, and cash dividend unvalidated. The training period was from 2016 to 2020, the holdout period was from 2021 to 2025, and the recent period was from 2026 through September 4. The periods were previously inspected for other strategies. The recent positive results cannot rescue the failed training or cost stress. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.

A news scan found the headline 'QREV90804 delay intraday parent stress holdout'. The automated trading fund manager's notes are as follows: the fund's performance was analyzed from September 20 to September 24, and the original protocol analysis was done on September 26. The analysis showed that the signal was intraday, meaning it was based on prices within a single trading day, with a lookback period of 5 days and a horizon of 5 days. The cost was stress, and the period was holdout, meaning it was a period of testing. The return percentage was -40.33%, and the drawdown percentage was 56.98%. The number of trades was 191, with a win percentage of 47.12%. The average win percentage was 2.66%, and the average loss percentage was 2.76%. The mean percentage was -0.20%. The quarter Kelly criterion, a measure of risk, was 0. The reconciliation in US dollars was 5.46e-12. There were 37 skipped overlaps, and 0 day trades. The lag was 2. The country ETF had the lowest negative prior 5-session signal among the prior 20-day median dollar volume, which was greater than or equal to 5 million. The first weekly session open was one lot, with a skip overlapping entry, and the fifth session close. The signal was two sessions before entry, with one full skipped session. The parent had a time exit only, not a venue-ready stop or target strategy. The fill was zero or a base 5 basis point fee plus 5 basis points lip, with stress 5 plus 20. The cash ledger was reconciled to vectorbt events. The returns were on a fully deployed model strategy sleeve, not account allocation. The training period was 2016-2020, the holdout period was 2021-2025, and the recent period was 2026 through September 4. The source of the data was https://runway.adityaperswal.workers.dev/data/stock-bars. There was no proposal based on this individual cell.

A news scan found the headline 'QREV90804 delay intraday parent stress train'. The original protocol analysis was done on date 926. The results of the analysis are as follows: the signal was intraday, with a lookback period of 5 days and a horizon of 5 days, and the strategy was not managed, with a cost of stress, during the training period. The return percentage was -55.327371019122126, the drawdown percentage was 64.61808586632517, and the win percentage was 46.596858638743456. The average win percentage was 2.0579540905413096, and the average loss percentage was 2.4964007033982627. The mean percentage was -0.37421443815940436. A country ETF had the lowest negative signal among the prior 20-day median dollar volume, which was greater than or equal to 5 million. The strategy was to enter on the first weekly session open, with one lot, and skip overlapping entries, and to exit on the fifth session close. The signal was given two sessions before entry, with one full skipped session. The parent strategy has a time exit only, and not a venue-ready stop or target strategy. The fees were either zero or a base fee of 5 basis points plus a 5 basis point slip, with a stress of 5 plus 20. The cash ledger was reconciled to vectorbt events. The returns were based on a fully deployed model strategy sleeve, and not on account allocation. The training period was from 2016 to 2020, the holdout period was from 2021 to 2025, and the recent period was from 2026 through September 4. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.

A news scan found the headline 'QREV90804 delay intraday parent base recent'. The automated trading fund manager's notes are as follows: the fund's performance was analyzed using the original protocol from 920 to 924, and the results from 926 were used. The analysis showed a signal to buy or sell during the day, looking back 5 days and forward 5 days, with a return percentage of 29.54%, a drawdown percentage of 10.32%, and a win percentage of 61.54%. The average win percentage was 2.93% and the average loss percentage was 1.95%. The fund's strategy is based on a country ETF with a low negative signal in the prior 5 sessions, and the first weekly session open is used as an entry point. The parent fund has a time-based exit strategy but does not have a stop or target strategy based on the trading venue. The fund's costs include a 5 basis point fee and a 5 basis point slip, with a stress test of 5 and 20. The cash ledger is reconciled to vectorbt events, which is a backtesting framework, and the returns are based on a fully deployed model strategy, not account allocation. The training data used was from 2016 to 2020, the holdout data was from 2021 to 2025, and the recent data was from 2026 to September 4. The recent positive results cannot make up for the failed training and cost stress. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.

A news scan found the notes from a trading fund manager. The notes mentioned a delay in the QREV90804 system. The system's performance was analyzed from 920 to 924, and the original protocol was analyzed on 926. The analysis showed the following results: the system had a 5.824774831534096 percent return, a 45.257728879512406 percent drawdown, and a 50.26178010471204 percent win rate. The system also had an average win of 2.7956042643107883 percent and an average loss of 2.6305774157315547 percent. The mean return was 0.09671808837349746 percent. The system used a country ETF with a low negative prior 5-session signal among the prior 20-day median dollar volume, which was greater than or equal to 5 million. The system entered a trade on the first weekly session open, with one lot, and skipped overlapping entries. The system had a signal two sessions before entry, with one full skipped session. The parent system has a time exit only, and not a venue-ready stop or target strategy. The system used a fee of 5 basis points, a slip of 5 basis points, and a stress test of 5 and 20. The cash ledger was reconciled to vectorbt events. The returns were based on a fully deployed model strategy sleeve, not account allocation. The system was trained from 2016 to 2020, and the holdout period was from 2021 to 2025. The recent period was from 2026 through September 4. The system's recent positive results cannot rescue the failed training or cost stress. The data source was https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.

A news scan found the notes from an automated trading fund manager. The notes mentioned a delay in the QREV90804, which had frozen notes from 920 to 924 and original protocol analysis from 926. The manager provided data on the performance of the fund, including a return percentage of -20.769447384957964 and a drawdown percentage of 42.91665420056017 over 191 periods. The data also showed a win percentage of 51.832460732984295 and an average win percentage of 2.142545142650252. The manager used a country ETF with the lowest negative prior 5-session signal among the prior 20-day median dollar volume, which was greater than or equal to 5 million. The manager entered a trade on the first weekly session open, with one lot, skipping overlapping entries, and closed on the fifth session. The signal to enter the trade was given two sessions before entry, with one full skipped session. The parent fund has a time exit only, with no venue-ready stop or target strategy. The manager used a fee of 5 basis points plus a 5-basis-point slip, with a stress test of 5 plus 20. The cash ledger was reconciled to vectorbt events. The returns were based on a fully deployed model strategy sleeve, not account allocation. The training data was from 2016 to 2020, with a holdout period from 2021 to 2025, and recent data from 2026 through September 4. The manager noted that recent positive results cannot rescue failed training or cost stress. The source of the data was https://runway.adityaperswal.workers.dev/data/stock-bars. The manager did not make a proposal based on this individual cell.

A news scan found the headline 'QREV90804 delay total managed stress recent'. The automated trading fund manager's notes are as follows: the fund's performance was analyzed from September 20 to September 24, and the original protocol analysis was done on September 26. The analysis showed a signal with a total lookback period of 5 days and a horizon of 5 days, with managed cost being stress over a recent period. The return percentage was 1.3604070565877535, the drawdown percentage was 11.262384237747414, and the win percentage was 55.172413793103445. The average win percentage was 1.6895017579455593 and the average loss percentage was 1.9166946729614924. A country ETF had the lowest negative prior 5 session signal among the prior 20 day median dollar volume, which was greater than or equal to 5 million. The first weekly session open was used to enter a trade, with one lot and skipping overlapping entries, and the fifth session close was used to exit. The signal was given two sessions before entry, with one full skipped session. The stop loss was set at 1 ATR, with a target of 1.5 ATR, and half of the position was closed at 1R, with the rest being moved to breakeven. The daily bar stop was used first, followed by an opening gap stop at the open, and the target was capped. The same bar partial and breakeven were used conservatively. The fill was zero or a base 5 bp fee plus 5 bp slip, with stress 5 plus 20. The cash ledger was reconciled to vectorbt events. The returns were based on a fully deployed model strategy sleeve, not account allocation, and were fractional and diagnostic, with whole-share, PDT, 15-minute, and cash dividend unvalidated. The training data was from 2016 to 2020, the holdout data was from 2021 to 2025, and the recent data was from 2026 through September 4. The recent positive results cannot rescue the failed training and cost stress. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.

The automated trading fund manager's notes show a delay in the QREV90804 system. The notes are based on an analysis from September 26, which was frozen on September 20 out of 24 total notes. The analysis shows a signal with the following parameters: total signal, 5-day lookback, 5-day horizon, managed, stress cost, holdout period, -75.92% return percentage, 76.85% drawdown percentage, 217 data points, 43.32% win percentage, 1.55% average win percentage, 2.29% average loss percentage, and -0.63% mean percentage. The system also shows a quarter Kelly value of 0, a reconciliation value of $3.64e-12, 9 skipped overlaps, 20 day trades, and a lag of 2. The system is based on a country ETF with the lowest negative prior 5-session signal among those with a prior 20-day median dollar volume of $5 million or more. The system enters a trade on the first weekly session open, with one lot, skipping overlapping entries, and closes on the fifth session. The signal is given two sessions before entry, with a stop loss of 1 ATR and a target of 1.5 ATR. The system also uses a daily bar stop, opening gap stop, and target cap. The cash ledger is reconciled to vectorbt events. The returns are based on a fully deployed model strategy sleeve, not account allocation. The system was trained on data from 2016 to 2020, with a holdout period from 2021 to 2025, and recent data from 2026 through September 4. A news scan found the source of the data to be https://runway.adityaperswal.workers.dev/data/stock-bars. The notes do not propose any changes based on this individual cell.

A news scan found the notes from a trading fund manager. The notes mentioned a delay in the QREV90804 system, which had a total managed stress of -65.21398190313406 percent return and 68.00693525199648 percent drawdown. The system used a signal with a 5-day lookback and horizon period, and the cost was measured by stress during the training period. The notes also mentioned a country ETF with the lowest negative prior 5-session signal among the prior 20-day median dollar volume, which was greater than or equal to 5 million. The system entered a trade on the first weekly session open, with one lot, and skipped overlapping entries, with a target set at the fifth session close. The signal was given two sessions before entry, with one full skipped session. The stop loss was set at 1 ATR, with a target of 1.5 ATR, and the system would move to breakeven after half of the target was reached. The system also used daily bar stops, opening gap stops, and target capping, with partial closes and breakeven points. The notes mentioned a cash ledger reconciled to vectorbt events, with returns based on a fully deployed model strategy sleeve, not account allocation. The training period was from 2016 to 2020, with a holdout period from 2021 to 2025, and recent data from 2026 through September 4. The notes stated that recent positive results cannot rescue a failed training or cost stress. The source of the data was https://runway.adityaperswal.workers.dev/data/stock-bars. The notes concluded that there was no proposal based on this individual cell.

A news scan found the headline 'Q4 Update'. The automated trading fund manager has made notes about the performance of a trading strategy. The notes start with some numbers: 920/924 and 926, which seem to refer to a protocol analysis. The manager then shares some data in a format that looks like a computer code. This data includes a signal to manage the total portfolio, looking back at 5 periods and forward to 5 periods, with a return percentage of 10.57% and a drawdown percentage of 9.21%. The data also mentions a win percentage of 58.62% and an average win percentage of 1.88%. The manager explains that the strategy is based on a country ETF with a low negative signal in the prior 5 sessions, and the first weekly session open is used to enter a trade. The manager also mentions a stop-loss strategy based on the average true range, or ATR, which is a measure of how much a stock's price moves. The ATR is used to set a stop-loss at 1 ATR and a target at 1.5 ATR. The manager also talks about a cash ledger that is reconciled to some events, and mentions that the returns are based on a fully deployed model strategy, not the actual account allocation. The strategy was trained on data from 2016 to 2020, and the manager notes that the recent positive performance cannot make up for failed training or cost stress. The source of the data is a website.