Stats

A news scan found the headline 'N911 LPG fixed 3R long-only breakout: positive holdout, current signal absent'. This refers to a trading strategy for the stock N911 LPG. The strategy was tested using 1428 days of stock data from September 10, 2021, to September 10, 2026. The strategy is based on a simple moving average, or SMA, which is a way to smooth out price changes over time. The strategy buys when the closing price is higher than the highest price in the last 20 days and the 50-day SMA. It sells when the price reaches a target of 3 times the risk, or after 20 days. The strategy also has a stop-loss, which is a price at which the trade is automatically closed to limit losses. The stop-loss is set at 2 times the average daily range, or ADR, of the last 20 days. The strategy was tested using a long-only approach, meaning it only buys and never sells short. The test included fees of 5 basis points, or 0.05%, and a slippage of 20 basis points, or 0.20%, on each trade. The results showed a return of 48.98% during the training period and 47.45% during the holdout period, with a maximum drawdown of 23.34%. The stress test showed a return of 34.76%. The mean confidence interval, or CI, crosses zero, which means the results are not statistically significant. The holdout period was not used to select the parameters of the strategy, but it was used to select the stocks to trade. The strategy does not use a 15-minute trailing stop or cash dividend, and it does not replicate the raw stop. The current price of 54.41 is lower than the prior high of 55.20, so the strategy does not generate a buy signal. The conclusion is to retain the strategy as a watch, but not to reject it merely because the CI includes zero. There is no current order. Alternative holdout periods of 10 and 40 days also showed positive results, but none were selected to replace the 20-day holdout period. The final statistics are shown in figures, and the old command-line interface, or CLI, is different from the current IEX signal exit, which is not a confirmation.

A diagnostic test was run on the LPG stock using a breakout strategy. The test, which used 20 days of historical data and ran for 1500 days, showed a return of 94.53%, with a maximum drawdown of 11.30% and a win rate of 39.02%. For comparison, a buy-and-hold approach would have returned 235.20%. The test was done using a command line interface, or CLI, which is a way for a computer to understand and execute commands. The test used data from the IEX exchange without any adjustments. This test is only for diagnostic purposes and should not be used to make actual investment decisions, as it has not been independently verified and does not take into account real-world costs. The data for the test came from the website https://runway.adityaperswal.workers.dev/data/stock-bars.

A news scan found the headline 'REF91006 15-minute exits with +1R half and breakeven: holdout diagnostic fails'. This refers to a test of a trading strategy. The strategy has three main points: it uses the same daily entry dates, it stops entering trades one day before a 20-day average daily range, and it targets an entry price of 1.5 times the average daily range. The test checks the strategy's performance using 15-minute intervals, including extended hours, and assumes a 5 basis point fee and 10 basis point slip. It sells half of the position when it reaches a 1R profit and moves the stop to the entry point for the remaining position. The test uses data from VLO, MPC, and PSX stocks. The results show a mean return of -0.0309% with a confidence interval of -0.9759% to 0.9150%. The test concludes that the strategy's results are not reliable due to issues with execution, data, and assumptions about slippage and partial quantities. The maximum gap between bars is 88.5 hours, which includes holidays and weekends, and the test did not account for missing market data. The daily touch test mean return of 1.164% is different, and the exits cannot inherit the daily time-rule edge.

A test called REF91006 failed. It had three main points: first, it used daily entry dates and actual 9:30 AM prices to decide when to buy or sell stocks like VLO, MPC, and PSX, with a stop loss and target price based on the average daily range. It checked every 15-minute bar close, including extended hours, and used a hypothetical fill at the close with a 5 basis point fee and 10 basis point slippage, without partial exits. The data came from https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=VLO,MPC,PSX&timeframe=15Min&feed=sip&adjustment=all. Second, it used separate, fully funded accounts with no leverage, and matched trade returns within a small margin. Third, after seeing the results of time exits, it did diagnostics on the same holdout data, not to validate a new strategy. The results showed a mean return of 0.031118497493355032% with a confidence interval of -1.0488466655244033 to 1.1305671955090668%, and the numbers of stops, targets, and time exits were 40, 33, and 14, respectively. The conclusion was to reject the test because the fills were not executable quotes, overnight data was sparse and unvalidated, and slippage was not measured. The maximum elapsed bar gap was 88.5 hours, including holidays and weekends, and it was not proven that there was no missing market data. The daily touch test mean return of 1.164% was different, and exits could not inherit the daily time-rule edge.

A backtest was run using the command line interface to test a mean-reversion strategy on the stocks VLO, MPC, and PSX. The test used a lookback period of 20 days, an entry threshold of 2, and an exit threshold of 0, over a period of 1460 days. This test is a distinct rule from a previously registered relative pullback strategy, which is a trading strategy that involves buying a stock when its price pulls back from a high point. The test did not include a holdout validation, which is a way of testing a strategy by setting aside some data to see how it performs, and it did not account for fees or slippage, which are costs associated with buying and selling stocks. The data for the test came from the website https://runway.adityaperswal.workers.dev/data/stock-bars. The results of the test will be preserved, rather than being combined with other data. No action has been authorized based on the results of this test.

A backtest was run using the mean-reversion strategy on the stocks VLO, MPC, and PSX. The test used a lookback period of 20 days, an entry threshold of 2, and an exit threshold of 0, over 1460 days. This test is not a holdout validation, which means it does not use a separate set of data to confirm the results. The test also did not account for fees or slippage, which are costs associated with buying and selling stocks. The data for the test came from the website https://runway.adityaperswal.workers.dev/data/stock-bars. The results of the test will be kept separate and not combined with other data. No actions based on this test have been authorized.

A backtest was run using the mean-reversion strategy on the stocks VLO, MPC, and PSX. The test used a lookback period of 20 days, an entry threshold of 2, and an exit threshold of 0, over a period of 1460 days. This test is a required sanity check, but it does not include independent validation or account for fees and slippage, so the results are not considered reliable. The data came from https://runway.adityaperswal.workers.dev/data/stock-bars. The output will be preserved on its own and not combined with other data. No action has been authorized based on this test.

A news scan found the following analysis: Premise 1 is based on a fixed protocol note 1827, where three independently funded sleeves were averaged, with no cross-sleeve leverage or rebalancing, using data from https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all. Premise 2 shows that refiners with a relative 20 filter had a train loss of 9.6135%, a holdout gain of 11.6746%, and a drawdown of 12.734%, with a stress of -0.5566%, while producers using the same rule had a holdout loss of 20.3984% and a stress of -25.9968%. Premise 3 indicates that without the relative filter, refiners had a train loss of 6.9819%, a holdout gain of 9.4489%, and a stress of -4.8838%. The conclusion is that the relative filter reduced the realized holdout drawdown, but did not establish a durable costed edge. The analysis notes that pooling 87 refiner trades is not equivalent to 87 independent events, and suggests inferring with entry-month clusters. These are normalized full-capital sleeves, not fund-sized trades. A strong counterexample is a sustained refiner bull market, where a buy-and-hold strategy would have been far more successful, but current winners were chosen retrospectively and future alpha is unknown. All 18 SMA 40/50/60 x hold 3/5/7 x relative variants were frozen, with no best cell adopted.

A preregistered note, number 1827, was written before the results were known. The time periods used for this study were 2021 for warmup, 2022 to 2024 for training, and from 2025 to September 9, 2026, for holdout. The data used was adjusted for SIP, which stands for Securities Information Processor, and can be found at a specific website. The first premise of this study was that a signal to buy or sell would be given when the previous close was greater than the 50-day Simple Moving Average, which is a calculation to find the average price of a stock over a certain period, and the 3-day return was less than 0, and the 20-day return was greater than the 20-day return of XLE, which is an energy exchange-traded fund. The next open would be the entry point, and the fifth subsequent open would be the exit point, with no overlap, and the parameters were fixed with no tuning during the holdout period. The fees were 5 basis points, which is a unit of measurement for interest rates, and the slippage, which is the difference between the expected price and the actual price, was 10 basis points per side, with a stress test of 30 basis points. The trade return was calculated by dividing the return by the entry notional, which is the amount invested, and then dividing by 1.0005 to account for the invested cash. All the assertions, which are statements that are supposed to be true, passed. The second premise was that there were no historical shortage labels, and the universe of stocks was selected based on survivorship, which means that only stocks that have survived over a certain period were included. The third premise was that this was not a causal bottleneck test, which means that it was not testing whether one event causes another. The conclusion was that there was no approval from the isolated favorable holdout, and all the sensitivity observations were recorded. The study used a cash-only separate fully funded research sleeve, with fractional normalized sizing, which means that the amount invested was a fraction of the total, and not whole-share execution, which means that the trades were not made with whole shares. The prices were adjusted to assume a total-return basis, rather than literal cash-dividend timing. There were no green partial or 15-minute exits in this test. The results were -25.8821% for the training period, -31.6540% for the test period, and -35.8911% for the stress test. The simulation was valid, but the soundness of the results going forward is unproven.

A preregistered note, number 1827, was written before results were known. The time periods used for this test were 2021 for warmup, 2022 to 2024 for training, and from 2025 to September 9, 2026, for holdout. The data used was adjusted for SIP, which means Securities Information Processor, and can be found at https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all&symbols=CVX. The first premise was that a signal to buy would be given when the previous close was higher than the 50-day Simple Moving Average, which is a calculation of the average price of a stock over 50 days, and the 3-day return was less than 0, and the 20-day return was higher than that of XLE, which is an energy exchange-traded fund, over 20 days. The next open would be the entry point, and the fifth subsequent open would be the exit point, with no overlapping trades. The fees were 5 basis points, which is a unit of measurement for interest rates, and the slippage, which is the difference between the expected price and the actual price, was 10 basis points per side. The stress test was 30 basis points. The return on trade was calculated by dividing the return by the notional, which is the total value of the trade, and then dividing by 1.0005 to account for invested cash. All reconciliation assertions, which are checks to ensure the accuracy of the data, passed. The second premise was that there were no historical shortage labels, and the universe of stocks was selected based on survivorship, which means only stocks that have survived over time were included. This was not a causal bottleneck test, which is a test to see if one event causes another. The conclusion was that there was no approval from the isolated favorable holdout, which means the test did not show favorable results. The full sensitivity was recorded, and there were 91006 rows of data. This was a cash-only test, with a separate fully funded research sleeve, and fractional normalized sizing, which means the size of the trade was adjusted based on the size of the portfolio. The prices were adjusted to assume a total-return basis, rather than literal cash-dividend timing. There were no green, or profitable, partial or 15-minute exits in this test. The results were -14.4896% for the training period, -20.7078% for the test period, and -25.9204% for the stress test. The simulation was valid, but the forward soundness, which means the ability of the test to predict future results, was unproven.

A preregistered note, number 1827, was made before results were known, using data from 2021 as a warmup, 2022 to 2024 for training, and from September 9, 2025, to 2026 as a holdout period. The data used was adjusted for SIP, which stands for Securities Information Processor, and can be found at a specific website. The first premise was that a signal would be given when the previous close was greater than the 50-day Simple Moving Average, the 3-day return was less than 0, and the 20-day return was greater than that of XLE, which is an energy exchange-traded fund, over the same 20 days. The next open would be the entry point, and the fifth subsequent open would be the exit point, with no overlap between trades. The fees were 5 basis points, or 0.05%, and the slippage was 10 basis points, or 0.10%, per side, with a stress test of 30 basis points, or 0.30%. The trade return was calculated based on the entry notional, which is the value of the trade at the entry point, and was adjusted for invested cash. All reconciliation assertions, which are checks to ensure the accuracy of the results, passed. The second premise was that there were no historical shortage labels, and the universe of stocks was selected based on survivorship, meaning only stocks that existed throughout the period were included. This was not a test of causal bottlenecks. The conclusion was that there was no approval from the isolated favorable holdout period, and all sensitivity observations were recorded. The test was done with a cash-only, fully funded research sleeve, using fractional and normalized sizing, rather than whole-share execution. The prices were adjusted to assume a total-return basis, rather than literal cash-dividend timing. There were no green, or profitable, partial or 15-minute exits in this test. The results were 26.0290% for the training period, -8.8336% for the test period, and -16.1788% for the stress test period. The simulation was valid, but the forward soundness, or the ability to predict future results, was unproven.

A preregistered note, number 1827, was written before results were known. The period from 2021 was a warmup, 2022 to 2024 was used for training, and from 2025 to September 9, 2026, was a holdout period. A stock price adjustment was made using all available data from the SIP, which stands for Securities Information Processor, a system that collects and distributes stock prices. The data can be found at https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all&symbols=PSX. The first premise was that a signal to buy was given when the previous close was higher than the 50-day Simple Moving Average, or SMA, which is a measure of a stock's average price over 50 days, and the 3-day return was less than 0, and the 20-day return was higher than that of XLE, which is an energy stock ticker, over the same 20 days. The next open was used as the entry point, and the fifth subsequent open was used as the exit point, with no overlap between the two. The fees were 5 basis points, or 0.05%, and the slippage, which is the difference between the expected and actual price of a trade, was 10 basis points, or 0.1%, per side. A stress test of 30 basis points, or 0.3%, was also applied. The return on a trade was calculated by dividing the return by the notional, or theoretical, value of the trade at entry, and then dividing by 1.0005 to account for invested cash. All assertions, or checks, passed. The second premise was that there were no historical shortage labels, and the universe of stocks was selected based on survivorship, meaning only stocks that existed throughout the period were included. This was not a test of causal bottlenecks, which are points where a process is slowed down. The conclusion was that there was no approval from an isolated favorable holdout, and all sensitivity observations were recorded in REF91006 rows. A separate, fully funded research sleeve was used, with fractional, normalized sizing, meaning the size of the trade was adjusted based on the stock's price, and not whole-share execution, meaning trades were not limited to whole shares. Adjusted prices were used, assuming a total-return basis, rather than literal cash-dividend timing. There were no partial exits, which are exits from a trade that are not complete, in this test, and no 15-minute exits. The train period had a return of -9.4516%, the test period had a return of -2.3151%, and the stress period had a return of -13.0141%. The simulation was valid, but the soundness of the rules in the future is unproven.

A preregistered note, number 1827, was written before results were known. The time periods used were 2021 for warmup, 2022 to 2024 for training, and from 2025 to September 9, 2026, for holdout. The data used was adjusted for SIP, which stands for Securities Information Processor, and can be found at https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all&symbols=MPC. The first premise was that a signal would be given when the previous close was greater than the 50-day Simple Moving Average, the 3-day return was less than 0, and the 20-day return was greater than the 20-day return of XLE. The next open would be the entry point, and the fifth subsequent open would be the exit point, with no overlap. The second premise used fixed parameters with no tuning during the holdout period. Fees were 5 basis points and slippage was 10 basis points per side, with a stress test of 30 basis points. Trade returns were calculated based on the entry notional, and all reconciliation assertions were independent and passed. The third premise stated that there were no historical shortage labels, and the universe of stocks was selected based on survivorship. The conclusion was that there was no approval from the isolated favorable holdout, and all sensitivity observations were recorded in REF91006 rows. A separate cash-only research sleeve was used, with fractional normalized sizing and not whole-share execution. Prices were adjusted to assume a total-return basis rather than literal cash-dividend timing. There were no partial exits in this test. The training period resulted in a return of -17.6185%, the test period resulted in a return of 20.1209%, and the stress test resulted in a return of 6.9647%. The simulation was valid, but forward soundness was unproven.

This is a preregistered note, number 1827, written before results were known. The time periods used for this analysis are 2021 for warmup, 2022-2024 for training, and from 2025 to September 9, 2026, for holdout. The data used is from the SIP feed with all adjustments, for the stock symbol VLO, which can be found at https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all&symbols=VLO. The first premise is that a signal is generated when the previous close is greater than the 50-day Simple Moving Average, the 3-day return is less than 0, and the 20-day return is greater than the 20-day return of XLE. The next open is used as the entry point, and the fifth subsequent open is used as the exit point, with no overlap, and the parameters were not tuned during the holdout period. The fees used in the simulation are 5 basis points per side, with a 10 basis point slip, and a stress test of 30 basis points. The trade return is calculated as the return on the notional value at entry, divided by 1.0005 to account for invested cash. All reconciliation assertions have passed. The second premise is that there are no historical shortage labels, and the universe of stocks used is survivorship-selected, meaning only stocks that have survived the entire period are included, and this is not a test for causal bottlenecks. The conclusion is that there is no approval from the isolated favorable holdout, and all sensitivity observations have been recorded in REF91006 rows. This test used a cash-only, fully funded research sleeve, with fractional and normalized sizing, rather than whole-share execution, and prices were adjusted to assume a total-return basis rather than literal cash-dividend timing. There were no partial or 15-minute exits in this test. The results were -1.7706% for the training period, 17.2180% for the test period, and 4.3797% for the stress test. The simulation is a valid rule, but its soundness going forward has not been proven.

A re-examination of the original records from 1896 to 1939 was conducted, which was not a new run or a new independent sample. The costed vector backtest used a 20 high and 10 low channel close rule, with the next open executed and a 50-day simple moving average filter, which is a method to smooth out price data. The fees were 5 basis points and the slip was 10 basis points on each side. The results from 2022 to 2024 showed a 54.0393% return, and from 2025 to September 9, there was a 144.1551% return, with a maximum drawdown of 22.9576%, 7 closed trades, and a win rate of 42.8571%. The average win was 42.9894% and the average loss was 5.8732%, with a mean return of 15.0679%. The bootstrap 95% confidence interval was between -4.1565% and 44.1486%. A stress test with a 30 basis point slip showed a return of 136.9402%. The data source was https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=SSL&timeframe=1Day&feed=sip&adjustment=all. A prior command line interface breakout with a 20/3% stop and 4.5% target over 1460 days showed an 11.0736% return, a 20.672% drawdown, and a 37.143% win rate, but this had a different exit structure and was not combinable. All original parameters and outcomes will be frozen, as the current primary news does not justify retesting the selected winner. The original test had biases, a small sample size, and unvalidated 15-minute venue exits. The point quarter Kelly can exceed 1, but the uncertainty-aware approved value is 0. No new strategy will be trusted or traded.

A test was run using a computer program called node to analyze the performance of a trading strategy. The program was given the following parameters: it was told to look at the stocks FTK, SSL, ATI, and IREN, use a strategy called breakout, look back 20 days, and test for 1460 days. It was also given a stop loss of 3 percent and a target profit of 4.5 percent. The test used 1002 bars of data from the website https://runway.adityaperswal.workers.dev/data/stock-bars. The results were as follows: for FTK, the return was -13.879 percent, the drawdown was 24.292 percent, the win rate was 36.667 percent, and there were 60 trades; for SSL, the return was 11.074 percent, the drawdown was 20.672 percent, the win rate was 37.143 percent, and there were 70 trades; for ATI, the return was 36.180 percent, the drawdown was 15.591 percent, the win rate was 40.385 percent, and there were 104 trades; and for IREN, the return was -34.563 percent, the drawdown was 45.320 percent, the win rate was 34.737 percent, and there were 95 trades. Note that a drawdown is the amount of money lost from the peak, a win rate is the percentage of trades that made money, and a trade is when the program buys or sells a stock. The test did not take into account any fees or slippage, which is when the price of a stock changes quickly, and it did not validate the daily stop and target sequencing, which is when the program decides to stop or sell a stock, or corporate actions, which are actions taken by a company that can affect its stock price. The conclusion is that these results are only for diagnostic purposes and do not validate the strategy. In a separate test, a program called vectorbt was used and it had different results, with held-out data from 2025 and later, and different channel exits, which is when the program decides to sell a stock based on its price movements, and all mean confidence intervals, which is a way to measure the accuracy of the results, crossed zero. The results from the two tests should not be combined to create a new strategy.

A news scan found the headline 'IREN frozen20/10 breakout: independent period does not establish deployable edge'. This refers to a trading strategy for the stock IREN. The strategy was tested on daily stock prices from January 2022 to September 9, 2026. The test was done before the run, which was preregistered on January 23. The strategy used a vectorbt, which is a type of trading tool, to decide when to buy and sell. It bought when the stock's closing price was higher than its prior 20-day high and its 50-day moving average, and sold when the closing price was lower than its prior 10-day low. The test included fees of 5 basis points and slippage of 10 basis points on each trade, with a total stress of 30 basis points. The test was divided into two periods: 2022-2024 for training and 2025 for holdout. The results were 61.7789% for the training period, 102.4264% for the holdout period, and a drawdown of 72.1911%. The strategy had 8 closed trades, with a 25% win rate and a mean return of 23.4239%. A bootstrap test with 10,000 samples had a 95% confidence interval of -17.5992% to 77.0301%. Another test with 96 total cells across 4 symbols, 3 lookbacks, 2 exits, 2 periods, and 2 costs was also done. The primary rule was frozen, with no winner selection. The conclusion was that no capital should be invested because the confidence interval crosses zero, meaning the strategy may not be profitable. The strategy also has limitations, such as not using a 15-minute stop or target, and not simulating partial profits. The current winner universe selection, regime shift, corporate-action basis, and overlapping exposure limit soundness are also concerns. The strongest argument against this conclusion is the positive return, but the unvalidated executable expectancy remains a binding issue.

A news scan found the headline 'ATI frozen20/10 breakout: independent period does not establish deployable edge'. This refers to a trading strategy for the stock ATI. The strategy was tested using daily stock prices from January 2022 to September 9, 2026. The test was done before the run on September 17, 2023. The strategy involved buying when the stock's closing price was higher than its highest price in the last 20 days and its 50-day moving average, and selling when the closing price was lower than its lowest price in the last 10 days. The test included fees of 5 basis points and slippage of 10 basis points for each trade, with a total stress of 30 basis points. The test was split into two periods: 2022-2024 for training and 2025 for testing. The results showed a loss of 19.58% during training and a gain of 114.40% during testing, with a maximum loss of 25.11%. The strategy had 6 closed trades, with a win rate of 50%. The average return was 16.68%, with a 95% confidence interval of -1.69% to 43.08%. The test also included 96 different combinations of trading rules, but did not select a winning rule. The conclusion was that no capital should be invested because the confidence interval crossed zero, meaning the strategy's returns were not statistically significant. The strategy's returns were only calculated when the portfolio included an open trade. The test did not use a 15-minute stop or target, or a partial simulation of a 1R trade. The test also did not consider the soundness of the trading strategy based on factors such as regime shift, corporate actions, and overlapping exposure limits. The strongest argument against this conclusion was the positive return, but the strategy's expected return was not validated.

A news scan found the headline 'SSL frozen20/10 breakout: independent period does not establish deployable edge'. This refers to a trading strategy for the stock SSL. The strategy was tested on daily stock prices from January 2022 to September 9, 2026. The test used a specific set of rules, including a long-only approach, where the stock is bought when its closing price is higher than its prior 20-day high and its 50-day moving average, and sold when its closing price is lower than its prior 10-day low. The test also accounted for fees of 5 basis points and slippage of 10 basis points on each trade, with a total stress of 30 basis points. The results showed a loss of 54.0393% during the training period and a gain of 144.1551% during the holdout period, with a drawdown of 22.9576%. The strategy had 7 closed trades, with a win rate of 42.857% and a mean return of 15.0679%. A bootstrap analysis with 10,000 iterations showed a 95% confidence interval of -4.1565% to 44.1486%. The test was run across 96 different scenarios, including 4 symbols, 3 lookbacks, 2 exits, 2 periods, and 2 costs. The primary rule was kept the same, with no selection of winning trades. The conclusion was that no capital should be allocated to this strategy, as the confidence interval crosses zero and the returns are only calculated when the portfolio includes an open trade. The strategy does not use a 15-minute stop or target, and the current selection of trades, regime shift, corporate action basis, and overlapping exposure limit are sound. The strongest argument against this conclusion is the positive return, but the unvalidated executable expectancy remains a binding constraint.

A news scan found the headline 'FTK frozen20/10 breakout: independent period does not establish deployable edge'. This refers to a trading strategy for the stock FTK. The strategy was tested using daily stock prices from January 2022 to September 9, 2026. The test was done before the run started, on a preregistered date of 1723. The strategy involved buying when the stock's closing price was higher than its prior 20-day high and 50-day moving average, and selling when the closing price was lower than its prior 10-day low. The test included fees of 5 basis points and slippage of 10 basis points for each trade, with a total stress of 30 basis points. The results showed a loss of 46.4835% during the training period from 2022 to 2024, and a loss of 63.6175% during the holdout period in 2025. The strategy had a drawdown of 67.1654%, with 10 closed trades, a win rate of 30.000%, and a mean return of -7.6294%. A bootstrap analysis with 10,000 samples showed a 95% confidence interval of -19.2006% to 5.4067%. The test was done across 96 total cells, including 4 symbols, 3 lookbacks, 2 exits, 2 periods, and 2 costs. The primary rule was frozen, with no selection of winning trades. The conclusion was that no capital should be invested, as the confidence interval crossed zero. The strategy's returns were only considered when the portfolio included a marked open lot. The daily channel exits were not based on a 15-minute stop or target, or a partial simulation of a 1R trade. The soundness of the strategy depended on the selection of the winner universe, regime shift, corporate-action basis, and overlapping exposure limit. The strongest counterargument was the positive return, but the unvalidated executable expectancy remained a binding constraint.

A news scan found the headline 'AVAV costed channel breakout: positive small holdout does not repair negative training'. This refers to a study on the stock AVAV. The study used 1002 adjusted bars from September 12, 2022, to September 9, 2026. It applied a long-only strategy, entering when the close was higher than the previous 20-day high and exiting when the close was lower than the previous 10-day low. The study was divided into training and holdout periods, with fees of 5 basis points per side and slippage of 10 and 30 basis points. A 3x2 sweep was performed, but no winning combination was found. The training period from 2024 showed a return of -24.4721% and a drawdown of 41.4508%. The holdout period from 2025 showed a return of 50.033% and a drawdown of 52.0352%. However, the conclusion was to not enter a trade due to the small sample size, unstable training and holdout periods, and lack of validation. The positive holdout result was not enough to justify entering a trade.

A computer program tested a trading strategy on the stock AVAV, which is a ticker symbol for a company. The test used a breakout strategy, meaning it looked for when the stock price breaks out of a certain range, and it looked back at 20 days of data over 1460 days. The test stopped trading when it lost 3 percent of its value and aimed to make a 4.5 percent profit. The test used data from a website and found that the strategy had a 72.9481 percent return, a 13.3253 percent drawdown, and a 47.2973 percent win rate, with an average trade return of 0.79278 percent. The test also compared the strategy to a benchmark, called buy and hold, which had a 40.94047 percent return. However, the test was just exploratory and did not verify some assumptions about costs, so it does not authorize actual trading. Another test using a different method and costs was done separately and should not be compared directly to this test. The result of the test was attractive, but it needs to be tested further in a real-world setting before it can be used for actual trading, and no parameters from the test are recommended for use.

A diagnostic test was run on the HUBB stock using a command line interface, which is a way to interact with a computer program using text commands. The test used a node, a type of computer program, to run a backtest, which is a simulation of a trading strategy, on the HUBB and WCC stocks. The strategy used was a breakout strategy, which means it looks for stocks that are breaking out of a certain price range, and it looked back at 20 days of data and ran the test for 730 days. The test also used a stop loss, which is a rule to sell a stock when it falls by a certain percentage, in this case 3%, and a target profit, which is a rule to sell a stock when it rises by a certain percentage, in this case 4.5%. The results of the test were: the stock HUBB had 501 data points, a return of -10.145%, a buy and hold return of 22.815%, a maximum drawdown of 19.799%, a win rate of 34.210%, and an average trade return of -0.259%. The data for the test came from the website https://runway.adityaperswal.workers.dev/data/stock-bars. The test showed that the results from the command line interface were different from the results from another source, IEX, and that the costs of buying and selling the stock were not taken into account. This test was not meant to validate the costs of holding the stock for a certain period of time, and the results of the test were recorded separately. The qualification for the stock remains rejected.

A diagnostic test was run on the stock symbol WCC using a command line interface, which is a way to interact with a computer program using text commands. The test used a node, a type of computer program, to run a backtest, which is a simulation of a trading strategy, on the symbols WCC and HUBB. The strategy used was a breakout strategy, which means buying a stock when its price breaks out of a certain range, and it looked back at 20 days of data over a period of 730 days. The test also used a stop loss, which is a rule to sell a stock when it loses a certain percentage of its value, in this case 3%, and a target profit, which is a rule to sell a stock when it gains a certain percentage of its value, in this case 4.5%. The results of the test were: for the symbol WCC, there were 501 bars of data, which is a unit of time, and the return on investment was -17.52%, while the return on investment from buying and holding the stock was 135.55%. The maximum drawdown, which is the largest loss of value, was 21.15%, the win rate, which is the percentage of successful trades, was 31.82%, and the average trade return was -0.42%. The data used for the test came from the website https://runway.adityaperswal.workers.dev/data/stock-bars. The test showed that the results from the command line interface were different from the results from another source, IEX, and that the costs of the trades were not explicitly modeled. This means that the test did not take into account the costs of buying and selling the stocks. The test was recorded separately and the qualification, which is a measure of how well the strategy performed, was rejected.

A news scan found the headline about HUBB 2026 ablation_no_sma: frozen 20/5 electrical breakout. The trading strategy, called Preregister1385, used data from 2026 to September 8. It worked as follows: if the stock closed higher than its 50-day Simple Moving Average, which is the average of the last 50 days of trading, then the strategy would hold the stock for 5 sessions and then sell. The strategy did not use the 50-day Simple Moving Average for this test, which is called an ablation. There were costs of 0.1% fee plus 0.1% slippage, which is the difference between the expected price and the actual price, on each side of the trade. The data was adjusted daily using the Securities Information Processor, or SIP. The results were verified using manual compounding from vectorbt. The data came from https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=WCC,HUBB,SPY&timeframe=1Day&feed=sip&adjustment=all. The results were as follows: return of 7.3594412063739405%, drawdown of 6.444767464595802%, sample size of 9, win rate of 55.55555555555556%, average win of 1.9044055710644336%, average loss of 0.5660111983929988%, and mean of 0.8064425624166859%. The manual return was 7.3594412063738845%. The baseline trade dates and returns were: January 5-12, 2026, January 14-22, 2026, January 30-February 6, 2026, February 10-18, 2026, February 20-27, 2026, April 9-16, 2026, April 21-28, 2026, June 17-25, 2026, and August 5-12, 2026, with returns of -0.0009072605700398695, 0.008819856212863186, 0.00006152074017973241, 0.030373035942439675, -0.016980343310967982, -0.003362906146165745, -0.001389937908546357, 0.04130353571598655, and 0.04078685622110889. The 95% bootstrap mean confidence interval was -0.15619409475090745% to 2.4420381181021766%. There were 9 selected surviving stocks, with no event causal identification and no 15-minute routing. The training rule was frozen and deeply negative, with no approval despite a positive point estimate.