Notes

A controlled experiment using a trading strategy was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The strategy had parameters including 20 high and 10 low, 2 average true range over 14 periods, a fixed target of 3 times the risk with a 10 basis point target, and fees of 25 basis points. The strategy also had a 20-day timeout and checked for the next timestamp open. Additionally, it had an optional 2 times risk basis entry with a 2 average true range trail. The experiment used a 24-hour matching mask to account for daily gaps and a 20-day window. The results showed a return of 7.6357530492738634 percent, a drawdown of 12.87075982047038 percent, and a win rate of 50 percent over 6 samples. The mean return was 1.401989643490039, the average win was 6.087821561976062, and the average loss was 3.283842274995985. There were no zero volume entries or exits. The results were reconciled with Tradewealth and vectorbt, which matched within a very small margin of error, and marked some quotes as not executable. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using a trading strategy was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The strategy had 20 high and 10 low settings, with a 2 average true range over 14 periods, a fixed 3 return target, and 25 basis point credited fees. It also had a 20-day timeout and checked for the next timestamp open. The experiment used a rolling signal, which is a type of trading signal that changes over time, and an hourly execution, meaning trades were made every hour. The results showed a 16.0629 percent return and a 29.3347 percent drawdown, with a win rate of 36.8421 percent. The average win was 12.5306 and the average loss was 5.2894. The experiment used a trail, which is a type of stop-loss order that moves as the price moves, and a slip of 20 basis points. The results were matched to a 24-hour period and used a daily gap and 20-day window. The experiment did not exactly replicate a prior strategy. A news scan found the trade results in JSON format: {symbol: BTC, source: aggregate, signal: rolling, execution: hourly, part: train, trail: true, slip_bp: 20, return: 16.06290417471403, drawdown: 29.33467111136492, win rate: 36.84210526315789, sample: 19, mean: 1.2758262384395724, avg_win: 12.530560655064221, avg_loss: 5.289435504591473, zero_volume_entries: 0, zero_volume_exits: 0}. The trade results were reconciled with vectorbt, a trading software, within a 1e-10 margin of error, and marked any non-executable quotes. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using a trading strategy was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The strategy had 20 high and 10 low parameters, with a 2 ATR (Average True Range, a measure of price volatility) of 14, a fixed target of 3R (a multiple of the initial risk), and fees of 25 basis points (a unit of measurement for interest rates). The strategy also had a 20-day timeout and checked for the next timestamp open. Additionally, it had an optional 2RBE (a risk management technique) and an entry 2ATR trail (a type of stop-loss order). The experiment used a 24-hour matching system to mask daily gaps and a 20-day window. The results showed a return of 20.558174234379432%, a drawdown of 28.481576845685474%, and a win rate of 36.84210526315789%. The sample size was 19, with a mean of 1.478581051238886, an average win of 12.755847513806815, and an average loss of 5.099824385259073. There were no zero-volume entries or exits. The trade wealth was reconciled using vectorbt, a backtesting library, with a precision of 1e-10, and non-executable quotes were marked. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using a trading strategy was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The strategy used a 20-day high and 10-day low, with a 2 average true range over 14 days, a fixed 3 return target, and 25 basis points credited for fees. It also had a 20-day timeout and checked for the next timestamp open. The results showed a 16.06% return, a 29.33% drawdown, and a 36.84% win rate over 19 samples. The average win was 12.53 and the average loss was 5.29. The experiment used a rolling signal and hourly execution, and the results were matched over a 24-hour period, with a 20 basis point slip. This is not an exact replication of a prior strategy. A news scan found the trade details: symbol is BTC, source is aggregate, signal is rolling, execution is hourly, part is train, trail is false, slip in basis points is 20. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using a trading strategy was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The strategy had 20 high and 10 low settings, with a 2 ATR, or average true range, of 14, and a fixed target of 10 basis points, with 25 basis points credited for fees. The strategy also had a 20-day timeout and checked for the next timestamp open, with an optional 2 risk-to-equity, or RBE, entry and 2 ATR trail. The experiment used a 24-hour matching system to mask daily gaps and a 20-day window, but did not exactly replicate the prior strategy. The results showed a return of 20.558174234379432 percent, a drawdown of 28.481576845685474 percent, and a win rate of 36.84210526315789 percent, based on a sample of 19 trades, with a mean of 1.478581051238886, an average win of 12.755847513806815, and an average loss of 5.099824385259073. There were no trades with zero volume entries or exits. The results were reconciled with Tradewealth and vectorbt, with a margin of error of 1e-10, and marked any non-executable quotes. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using a trading strategy was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The strategy used a 20 basis point slip, a 2 ATR (Average True Range, a measure of price volatility) trail of 14 periods, a fixed 10 basis point target, and credited fees of 25 basis points. It also had a 20-day timeout and checked for the next timestamp open. The results showed a return of 10.8053%, a drawdown of 12.2047%, and a win rate of 50%. The average win was 6.8255% and the average loss was 3.0524%. The experiment used a 24-hour matching system to mask daily gaps and a 20-day window. The results were reconciled with Tradewealth and found to be accurate within a very small margin of error. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment to measure the performance of a trading strategy was completed, using data from 2024-25 for training and from January 1 to September 11, 2026, for testing. The strategy used a 20-day high and 10-day low, with a 14-day average true range, a fixed target of 3 times the risk, and fees of 25 basis points. It also had a 20-day timeout and checked for the next timestamp open. The strategy could also use an optional 2 times risk entry with a 2 average true range trail. The experiment matched the strategy to the market 24 hours a day, using daily gap and 20-day window masks, but did not exactly replicate the prior strategy. The results showed a return of 12.143%, a drawdown of 11.867%, and a win rate of 50%. The sample size was 6, with a mean of 2.0905, an average win of 7.0394, and an average loss of 2.8583. There were no zero-volume entries or exits. A news scan found the headline was not applicable, this is raw script output. The trade wealth reconciles with vectorbt within a very small margin of error, and marks quotes that are not executable. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using Bitcoin data was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The experiment used a strategy with a 20-day high and 10-day low, a 14-day average true range, a fixed 10 basis point target, and credited fees of 25 basis points. It also had a 20-day timeout and checked for the next timestamp open. The strategy allowed for an optional 2RBE entry and a 2ATR trail. The experiment matched data for 24 hours, using daily gap and 20-day window masks, but did not exactly replicate the prior strategy. The results showed a return of 10.836452304428201 percent, a drawdown of 12.20466350739664 percent, and a win rate of 50 percent. The sample size was 6, with a mean of 1.8914378194923382, an average win of 6.835279491631119, and an average loss of 3.052403852646442. There were no zero-volume entries or exits. The trade wealth was reconciled using vectorbt within a 1e-10 margin, and non-executable quotes were marked. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment to measure the performance of a trading strategy was completed, using data from 2024-25 for training and from January 1, 2026 to September 11, 2026 for testing. The strategy used a 20-day high and 10-day low, with a 14-day average true range, a fixed target of 3 times the risk, and fees of 25 basis points. The strategy also had a 20-day timeout and checked for new timestamps at the open of each hour. Additionally, it used an optional 2 times risk basis entry and a 2 times average true range trail. The results showed a return of 12.17%, a drawdown of 11.87%, and a win rate of 50%. The average win was 7.05% and the average loss was 2.86%. The experiment used a full 24-hour matching system to account for daily gaps and a 20-day window. The results were verified using Tradewealth and vectorbt, with a margin of error of less than 1e-10. The experiment did not replicate the exact prior strategy and had no zero volume entries or exits. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using a trading strategy was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The strategy used a 20-day high and 10-day low, with a 2 ATR (Average True Range, a measure of price volatility) of 14 days, a fixed net target of 3R (a measure of return), a 10 basis point target, and credited fees of 25 basis points. It also had a 20-day timeout and checked for the next timestamp open. Additionally, it had an optional 2RBE (a type of entry strategy) and an entry 2ATR trail (a type of stop-loss strategy). The experiment matched the full 24-hour period, using daily gap and 20-day window masks, but did not exactly replicate the prior strategy. The results for the BTC symbol, using an aggregate source and a calendar signal with hourly execution, showed a return of 18.304427465635207, a drawdown of 29.14607882770095, and a win rate of 36.84210526315789, based on a sample of 19 trades, with a mean of 1.376876439365853, an average win of 12.585845226133358, and an average loss of 5.161688686248525. There were no zero-volume entries or exits, and the results were reconciled with Tradewealth, using vectorbt, to an accuracy of within 1e-10, and marked any non-executable quotes. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using a trading strategy was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The strategy used a 20 high and 10 low setting, with a 2 ATR (Average True Range, a measure of price volatility) setting of 14, a fixed target of 3R (three times the risk), and credited fees of 25 basis points (a unit of measurement for interest rates). It also had a 20-day timeout and checked for the next timestamp open. Additionally, it had an optional setting to add 2R (two times the risk) to the entry point and trail it by 2 ATR. The experiment matched the aggregate calendar signal on an hourly basis, but did not exactly replicate the prior strategy. The results showed a return of 22.886514692330618%, a drawdown of 28.290707816151006%, and a win rate of 36.84210526315789%. The sample size was 19, with a mean of 1.5798335552747362, an average win of 12.811242764919504, and an average loss of 4.9718218170180455. There were no instances of zero volume entries or exits. The results were reconciled with Tradewealth and found to be accurate within a margin of 1e-10, with some quotes marked as not executable. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using a trading strategy was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The strategy used 20 high and 10 low values, with a 2 ATR (Average True Range, a measure of price volatility) of 14, a fixed target of 10 basis points (a unit of measurement for interest rates), and credited fees of 25 basis points. It also had a 20-day timeout and checked for the next timestamp open. The results showed a return of 18.3044%, a drawdown of 29.1461%, and a win rate of 36.8421%. The average win was 12.5858% and the average loss was 5.1617%. The results were matched using a 24-hour period, which masked daily gaps and a 20-day window. The experiment did not exactly replicate a prior strategy. A news scan found the trade results for the symbol BTC, with a source of aggregate, a signal of calendar, and an execution of hourly, with a return of 18.3044% and a drawdown of 29.1461%. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using a trading strategy was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The strategy had 20 high and 10 low settings, with a 2 ATR (Average True Range, a measure of price volatility) of 14, a fixed target of 3R (a risk-reward ratio) with a 10 basis point target, and fees of 25 basis points. The strategy also had a 20-day timeout and checked for the next timestamp open. Additionally, it had an optional 2R (two times risk) buy or entry with a 2 ATR trail. The experiment used a 24-hour matching system to mask daily gaps and a 20-day window, but did not exactly replicate the prior strategy. The results of the experiment were as follows: the symbol was BTC, the source was aggregate, the signal was calendar-based, and the execution was hourly. The strategy had a return of 22.89%, a drawdown of 28.29%, and a win rate of 36.84%. The sample size was 19, with a mean of 1.58, an average win of 12.81, and an average loss of 4.97. There were no zero-volume entries or exits. The results were reconciled with Tradewealth and vectorbt, with a margin of error of 1e-10, and marked any non-executable quotes. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using Bitcoin data was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The experiment used a strategy with 20 high and 10 low parameters, a 2 average true range over 14 days, a fixed 10 basis point target, and 25 basis point credited fees. It also had a 20-day timeout and checked for the next timestamp open. The strategy allowed for an optional 2 risk basis points entry with a 2 average true range trail. The experiment matched data over 24 hours, considering daily gaps and a 20-day window, but did not exactly replicate the prior strategy. The results showed a return of 0.7556932235902591, a drawdown of 13.801790657242508, and a win rate of 40. The sample size was 5, with a mean of 0.29166240277998634, an average win of 6.650451499194132, and an average loss of 3.9475303281627774. There were no zero volume entries or exits. The trade wealth was reconciled using vectorbt within a 1e-10 margin, and non-executable quotes were marked. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using past data from 2024-25 was completed and reused from January 1, 2026, to September 11, 2026, for testing. The experiment used 20 high and 10 low values, with a 2 average true range over 14 periods, a fixed 3 return target, and 25 basis points credited for fees. It also had a 20-day timeout and checked for the next timestamp open. An optional 2 return buffer entry with a 2 average true range trail was used. The experiment matched data over 24 hours, considering daily gaps and a 20-day window, but did not exactly replicate the prior strategy. The results for the symbol BTC, which is a type of cryptocurrency, showed a return of 1.7683071497686775, a drawdown of 13.283045511581715, and a win rate of 40. The sample size was 5, with a mean of 0.49244691366545407, an average win of 6.863966344067074, and an average loss of 3.7552327066022926. There were no entries or exits with zero volume. The trade wealth was reconciled using vectorbt, a backtesting library, within a small margin of error, and marked quotes that were not executable. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using a trading strategy was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The strategy had 20 high and 10 low settings, with a 2 ATR (Average True Range, a measure of price volatility) of 14, a fixed target of 3R (three times the risk), and fees of 25 basis points (a unit of measurement for interest rates). The strategy also had a 20-day timeout and checked for the next timestamp open. Additionally, it had an optional setting to add 2R (two times the risk) to the entry point and trail the stop loss by 2 ATR. The experiment used a 24-hour matching system to mask daily gaps and a 20-day window. The results showed a return of 5.62680428188711, a drawdown of 13.801790657242508, and a win rate of 40. The average win was 9.27872672706187 and the average loss was 3.9475303281627774. There were no zero-volume entries or exits. The trade wealth was reconciled using vectorbt, a backtesting library, with a precision of 1e-10, and non-executable quotes were marked. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using Bitcoin data was completed, training from 2024 to 2025 and testing from January 1, 2026, to September 11, 2026. The experiment used a strategy with a 20 high and 10 low setting, a 2 average true range over 14 periods, a fixed 3 return target, and fees of 25 basis points. It also had a 20-day timeout and checked for the next timestamp open. The strategy allowed for an optional 2 return buffer entry and a 2 average true range trail. The experiment matched data over 24 hours, considering daily gaps and a 20-day window, but did not exactly replicate a prior strategy. The results showed a return of 6.688373802888781, a drawdown of 13.283045511581715, and a win rate of 40. The average win was 9.497503394736995 and the average loss was 3.7552327066022926. A news scan found the trade details in a JSON format: a symbol of Bitcoin, an aggregate source, a daily signal, hourly execution, and a holdout part, with a slip of 10 basis points. The trade wealth reconciles with vectorbt within a small margin of error, and marks quotes that are not executable. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using past data from 2024 to 2025 for training and from 2026 January 1 to September 11 for testing was completed. The experiment used 20 high and 10 low values, with a 14-day average true range, a fixed target of 10 basis points, and fees of 25 basis points. It also had a 20-day timeout and checked for the next timestamp open. The experiment allowed for an optional 2RBE entry with a 2ATR trail. The results showed a full 24-hour match, but did not exactly replicate the prior strategy. The results were: symbol BTC, source aggregate, signal daily, execution hourly, part train, trail true, slip 20 basis points, return -15.198785883777022, drawdown 40.689361015708016, win rate 38.88888888888889, sample 18, mean -0.4530213330605443, average win 9.916863380139858, average loss 7.052038877824438, zero volume entries 0, zero volume exits 0. A tool called Tradewealth checked the results against another tool called vectorbt and found they matched within a very small margin of error, and marked some quotes as not executable. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using past data from 2024 to 2025 for training and data from 2026 for testing was completed. The experiment used a strategy with 20 high and 10 low points, a 14-day average true range, a fixed target of 3 times the risk, fees of 25 basis points, and a 20-day timeout. The strategy also included checks at the next timestamp open and an optional 2 times risk entry with a 2 times average true range trail, which is a way to set a stop-loss price. The experiment used a 24-hour matching system to compare daily gaps and 20-day windows, but did not exactly replicate a prior strategy. The results of the experiment were: symbol BTC, source aggregate, signal daily, execution hourly, part train, trail true, slip 10 basis points, return -12.09%, drawdown 38.70%, win rate 38.89%, sample 18, mean -0.25, average win 10.14, average loss 6.87, zero volume entries 0, zero volume exits 0. The results were checked against another system called vectorbt and were found to be accurate within a very small margin of error, and any quotes that could not be executed were marked as such. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment to understand how a trading strategy works was completed from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The strategy used 20 high and 10 low values, with a 2 average true range over 14 periods, a fixed target of 3 times the risk, and fees of 25 basis points. The strategy also had a 20-day timeout and checked for the next timestamp to open. The results showed a return of -8.435342323805717 and a drawdown of 35.95895516649239, with a win rate of 38.88888888888889. The average win was 11.223237065280035 and the average loss was 7.052038877824438. This experiment used a daily signal and hourly execution for the BTC symbol, with a 20 basis point slip. The results were matched over a 24-hour period, using a daily gap and a 20-day window. The Tradewealth system checked the results against the vectorbt system and found they were the same within a very small margin of error, and marked any quotes that were not executable. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using past data from 2024-25 for training and data from 2026 January 1 to September 11 for testing was completed. The experiment used 20 high and 10 low values, with a 2 average true range over 14 periods, a fixed 3 return target, and fees of 25 basis points. It also had a 20-day timeout and checked for the next timestamp open. An optional 2 return basis point entry with a 2 average true range trail was used. The experiment matched data over 24 hours, including daily gaps and a 20-day window, but did not exactly replicate the prior strategy. The results showed a return of -5.0789543146442355 percent, a drawdown of 33.81023919731595 percent, and a win rate of 38.88888888888889 percent over 18 samples. The average win was 11.445906654338838 percent and the average loss was 6.865956501038532 percent. There were no entries or exits with zero volume. The trade wealth was reconciled with vectorbt, allowing for a difference of within 1e-10, and marked quotes that were not executable. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using a trading strategy was completed from 2024 to September 11, 2026. The strategy had 20 high and 10 low settings, with a 2 ATR (Average True Range, a measure of price volatility) of 14, and a fixed target of 3R (a measure of profit) with 10 basis points (a unit of measurement for interest rates) and 25 basis points credited for fees. The strategy also had a 20-day timeout and checked for the next timestamp open. Additionally, it had an optional 2R (another measure of profit) entry with a 2 ATR trail (a way to adjust the strategy based on price movements). The experiment used a 24-hour matching system to compare daily gaps and 20-day windows, but did not exactly replicate the prior strategy. The results of the experiment were: symbol BTC, aggregate source, daily signal, daily execution, holdout part, trail true, 20 basis points slip, return of 6.3528700788678005, drawdown of 12.748217160474052, win rate of 40, sample of 5, mean of 1.4996760242032914, average win of 9.670485552752394, average loss of 3.9475303281627774, zero volume entries, and zero volume exits. The results were reconciled with Tradewealth and vectorbt, with marks not executable quotes, within a very small margin of error of 1e-10. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the data line: holdout mean percentage is -0.7069703458888735, mean 95 percent confidence interval is between -2.4001668335274973 and 1.1512433681261125, sample size is 74, training probability is 0.1791044776119403, clinical risk difference percentage points is 60.7, and clinical approximate 95 percent confidence interval percentage points is between 50.61704621821972 and 70.78295378178028, this is from an iid bootstrap with 20000 iterations and seed 912, using clinical Wald from rounded rates, not FDA inference. https://runway.adityaperswal.workers.dev/data/stock-bars ; https://clinicaltrials.gov/api/v2/studies/NCT03573401

A controlled experiment using a trading strategy was completed from January 1, 2026, to September 11, 2026. The strategy used a 20-day high and 10-day low, with a 14-day average true range, a fixed 10 basis point target, and 25 basis point credited fees. It also had a 20-day timeout and checked for the next timestamp open. The results showed a 7.42% return and a 12.22% drawdown, with a 40% win rate. The average win was 9.89% and the average loss was 3.75%. The experiment used a daily signal and daily execution, with a 10 basis point slip. The results were matched using a 24-hour window and a 20-day window, but did not exactly replicate a prior strategy. A news scan found the data: a symbol of BTC, an aggregate source, a daily signal, daily execution, and a holdout part, with a trail and a 10 basis point slip. https://runway.adityaperswal.workers.dev/data/crypto-bars

A controlled experiment using a trading strategy was completed from January 1, 2026, to September 11, 2026. The strategy used a 20-day high and 10-day low, with a 14-day average true range, a fixed target of 3 times the risk, and fees of 25 basis points. The experiment also used a 20-day timeout and checked for the next timestamp open. The results showed a return of 6.35%, a drawdown of 12.75%, and a win rate of 40%. The average win was 9.67% and the average loss was 3.95%. The experiment used a daily signal and daily execution, and the results were matched against a 24-hour window. The strategy did not exactly replicate a prior strategy. A news scan found the trade results in JSON format: a symbol of BTC, an aggregate source, a daily signal, daily execution, and a holdout part, with a false trail, a 20 basis point slip, and various other metrics. https://runway.adityaperswal.workers.dev/data/crypto-bars