Notes

A news scan found the following data: the fund manager of the AA fund reported the results of a costed sweep of the fund's performance, using a strategy called rsi_only, which is a way of making decisions based on the Relative Strength Index, or RSI, a measure of how quickly the price of a stock is changing. The results were as follows: for different combinations of RSI and bp_side, which is the side of the trade, either 20 or 50, the return on investment was between -15.99% and -26.77%, with a maximum drawdown, or DD, of 49.22%. The win rate was between 20% and 25%, and the average win was between 23.98% and 24.72%, while the average loss was between -11.75% and -12.79%. The results were based on data from 2016 to 2022, with a holdout period from 2023 to 2025, and a recent period from 2026 to September 18. The next open trade will use a strategy based on 2 true Average True Range, or ATR, and 6 ATR, with a stop at the first ambiguous bar, and a gap stop at the open. The fund uses a vectorbt long only strategy, with fees of 5 basis points, or bps, and a slip of 15/45 bps on each side. The results were reconciled to an accuracy of 1e-9. The AA fund started on November 1, 2016, and the holdout period is based on historical data, not prospective data. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline 'AA R92006 costed sweep AA/rsi_only/holdout'. The given data is a list of results from a trading simulation, which includes the following information: rsi, or relative strength index, a measure of stock price movement; bp_side, which refers to the side of a trade; return, the profit or loss from the trade; DD, or drawdown, the largest peak to trough decline; win, the percentage of winning trades; N, the total number of trades; closed, the number of closed trades; mean, the average return; halfKelly_risk, a risk management strategy; avgwin, the average winning trade; avgloss, the average losing trade; targets, the number of targets set; and buyhold, the return from buying and holding the stock. The results are as follows: a trading simulation with different parameters, including rsi values of 5, 10, and 15, and bp_side values of 20 and 50, resulted in various returns, with the highest return being 24.476834089047657 and the lowest return being -14.08349817051652. The simulation was observed from September 20, trained on data from 2016 to 2022, and held out from 2023 to 2025, with recent data from 2026 to September 18. The next open trade will use a 2 true ATR and 6 ATR strategy, with 60 sessions, and a stop at the first ambiguous bar or gap stop at open, with window end marks. The simulation used a vectorbt long only strategy, with 5 bp fees and 15/45 bps slip on each side, and was reconciled to 1e-9. The AA starts on November 1, 2016, and the holdout is historical, not pristine prospective. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the fund manager of AA R92006 reported the results of a costed sweep of the AA/rsi_only/train model. The results were as follows: the model was tested with different parameters, including rsi values of 5, 10, and 15, and bp_side values of 20 and 50. The results showed returns ranging from -20.79335319984391 to 67.2914251201573, with drawdowns ranging from 70.53583839132838 to 90.35540146242515. The model was trained on data from 2016 to 2022, and held out from 2023 to 2025, with recent data from 2026 to September 18. The next open is based on 2 true ATR and 6 ATR, with 60 sessions, and a stop at the first ambiguous bar, with a gap stop at open, and window end marks. The model uses vectorbt long only, with 5bp fees and 15/45bps slip on each side, and is reconciled to 1e-9. The AA model starts on November 1, 2016, and is a historical holdout, not a prospective one. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the fund's performance was measured with different settings. The settings included a relative strength index, or RSI, which is a measure of how quickly a stock's price is changing, of 5, 10, and 15, and a buy/sell threshold, or bp_side, of 20 and 50. The results showed returns of -7.78%, -9.42%, -17.17%, -19.13%, -17.17%, and -19.13% with corresponding drawdowns, or DD, of 41.55%, 42.07%, 41.55%, 42.07%, 41.55%, and 42.07%. The win rates were 33.33% and 25%. The average win and average loss were also calculated. The data was observed from September 20 and was trained on data from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data from 2026 to September 18. The next open trade will use a true average true range, or ATR, which is a measure of how volatile a stock is, of 2 and 6, with a 60 session limit and a stop at the first ambiguous bar, or a bar with a conflicting signal. The trade will also use a gap stop at the open and a window end mark. The vectorbt long only strategy, which is a type of trading strategy, was used with fees of 5 basis points, or bps, and a slippage, or the difference between the expected and actual price, of 15 and 45 bps on each side. The results were reconciled to an accuracy of 1e-9. The AA fund started on November 1, 2016, and the holdout period is historical, not prospective, meaning it is based on past data, not future predictions. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the AA fund had different results based on the settings used. The settings included the relative strength index, or rsi, which measures how fast a stock's price is changing, and the bp_side, which is the percentage of the investment that is used to buy or sell a stock. The results were as follows: for an rsi of 5 and a bp_side of 20, the return was -32.34%, and for an rsi of 5 and a bp_side of 50, the return was -33.94%. For an rsi of 10 and a bp_side of 20, the return was -22.91%, and for an rsi of 10 and a bp_side of 50, the return was -26.09%. For an rsi of 15 and a bp_side of 20, the return was 18.00%, and for an rsi of 15 and a bp_side of 50, the return was 11.80%. The data was observed on September 20, and was based on training from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data from 2026 to September 18. The next open trade will use a true average true range, or ATR, which measures how much a stock's price is moving, of 2 and 6, with a stop at the first ambiguous bar, and a gap stop at the open. The trade will also use a window end mark, and will be a long-only trade, meaning the fund will only buy stocks, not sell them short. The fund will also use a 5 basis point fee, and a 15 to 45 basis point slip on each side of the trade. The results were reconciled to 1e-9, which is a very small number. The AA fund started on November 1, 2016, and the holdout period is based on historical data, not prospective data, which means it is based on what actually happened, not what might happen in the future. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the fund manager of AA R92006 reported the results of a costed sweep of AA, which is a type of stock, and pullback, which refers to a short-term decline in price, and train, which is a type of backtest, or simulated trading period. The results were as follows: the fund had a return of 292.90189515384475, a drawdown, or maximum loss, of 28.726765141688272, and a win rate of 58.333333333333336, with 12 trades closed out of 12 total trades, and an average win of 31.94409209168496 and an average loss of -10.613402576348067, with a half Kelly risk, which is a measure of risk, of 0.2224480602842134, and a mean, or average, of 14.211802646671199, with 7 targets, or profit goals, and a buy and hold return of 108.50860420650092. The fund also had returns of 265.6070958039319, 176.61881302232624, 149.79471428264, 176.86219480751214, and 145.5544514266635, with corresponding drawdowns, win rates, and other metrics. The data was observed on September 20, and the training period was from 2016 to 2022, with a holdout period from 2023 to 2025, and a recent period from 2026 to September 18. The next open, or trading session, will use a 2 true ATR, or average true range, and a 6 ATR, with 60 sessions, and a stop at the first ambiguous bar, and a gap stop at the open, with window end marks. The fund uses a vectorbt long only strategy, with 5 bp fees, or costs, and 15/45 bps slip, or additional costs, on each side, and has been reconciled to 1e-9, which is a measure of accuracy. The AA fund started on November 1, 2016, and the holdout period is historical, not prospective, meaning it is based on past data rather than future predictions. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: two sets of trading results for the ticker symbol AA, with the following details. The first set has a relative strength index, or a measure of how quickly a stock's price is changing, of 10, a buy or sell signal threshold of 20, a return of -7.297593355091816 percent, a maximum drawdown, or largest loss, of 22.27260299594217 percent, a win rate of 33.33333333333333 percent, 3 trades, all of which were closed, an average return of -1.8714902962474504 percent, an average win of 13.962485618867927 percent, and an average loss of -9.788478253805138 percent. The second set has a relative strength index of 10, a buy or sell signal threshold of 50, a return of -8.951324566782693 percent, a maximum drawdown of 22.969711075141653 percent, a win rate of 33.33333333333333 percent, 3 trades, all of which were closed, an average return of -2.4585042748784147 percent, an average win of 13.280751306385575 percent, and an average loss of -10.32813206551041 percent. These results were observed on September 20, and were based on training data from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data from 2026 to September 18. The next open trade will use a true average trading range, or a measure of how much a stock's price is moving, of 2 and 6, over 60 trading sessions, with a stop at the first ambiguous bar, or a trading session with conflicting signals, and a gap stop at the open, with window end marks. The vector backtest, or a test of the trading strategy using historical data, was long only, meaning it only bought stocks, with fees of 5 basis points, or 0.05 percent, and a slippage, or difference between the expected and actual price, of 15 and 45 basis points. The results were reconciled to an accuracy of 1e-9, and the AA strategy started on November 1, 2016, with a separation of data. The holdout data is historical, not prospective, meaning it is based on past data, not future predictions. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: two sets of results for a trading strategy, one with a parameter set to 20 and the other to 50. The first set has a return of -0.8103274947137038, a maximum drawdown of 49.11608329145595, and a win rate of 31.25%. The second set has a return of -9.889836107520376, a maximum drawdown of 52.934222955378885, and a win rate of 31.25%. The data was observed on September 20, and was trained on data from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data from 2026 to September 18. The strategy uses a next open, 2 true average true range, and 6 average true range, with a stop at the first ambiguous bar, and a gap stop at open. The strategy also uses a window end mark, and is a long-only strategy with 5 basis point fees and 15/45 basis point slippage on each side. The results were reconciled to 1e-9. The strategy started on November 1, 2016, and the holdout period is historical, not prospective. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: two sets of trading results for a strategy, with the first set having a return of 96.08567853997877 percent, a maximum drawdown of 61.01011328207102 percent, and a win rate of 37.142857142857146 percent, and the second set having a return of 58.943636443363744 percent, a maximum drawdown of 63.71873125456779 percent, and a win rate of 37.142857142857146 percent. The data was observed on September 20, and was based on training data from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data from 2026 to September 18. The strategy used a next open, 2 true average true range, and 6 average true range, with 60 sessions, and a stop at the first ambiguous bar, and a gap stop at the open, with window end marks. The strategy was a long only strategy, with 5 basis point fees, and 15 and 45 basis point slippage on each side, and was reconciled to 1e-9. The strategy started on November 1, 2016, and the holdout period was based on historical data, not prospective data. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the automated trading fund manager for KALU stock reported the results of different trading strategies. The strategies used a measure called Relative Strength Index, or RSI, which is a way to measure how much a stock's price has changed, and a measure called bp_side, which refers to the percentage of the stock's price used to set buy and sell points. The results were as follows: for RSI of 5 and bp_side of 20, the return was 22.59548700399472 percent, the maximum loss, or drawdown, was 22.25872689938395 percent, and the win rate was 50 percent; for RSI of 5 and bp_side of 50, the return was 19.68819403541903 percent, the drawdown was 22.258726899383984 percent, and the win rate was 50 percent; for RSI of 10 and bp_side of 20, the return was 4.9990908775631855 percent, the drawdown was 26.50668369583118 percent, and the win rate was 25 percent; for RSI of 10 and bp_side of 50, the return was 2.5090879739062646 percent, the drawdown was 26.94632762945193 percent, and the win rate was 25 percent; for RSI of 15 and bp_side of 20, the return was 16.276263082120774 percent, the drawdown was 26.506683695831036 percent, and the win rate was 40 percent; for RSI of 15 and bp_side of 50, the return was 12.83974715970985 percent, the drawdown was 26.946327629451794 percent, and the win rate was 40 percent. The data was observed from September 20 and the training period was from 2016 to 2022, with a holdout period from 2023 to 2025 and recent data from 2026 to September 18. The next open trade will use a strategy with 2 true Average True Range, or ATR, and 6 ATR, with 60 sessions, and a stop at the first ambiguous bar, with a gap stop at the open, and window end marks. The vectorbt long only strategy was used, with 5 basis points fees and 15/45 basis points slippage on each side, and the results were reconciled to 1e-9. The AA, or Autoregressive Integrated Moving Average, model starts on November 1, 2016, and the holdout is historical, not prospective. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline 'KALU R92006 costed sweep KALU/rsi_only/holdout'. The results of a backtest of a trading strategy on the stock KALU are as follows: the strategy was tested with different parameters, including rsi values of 5, 10, and 15, and bp_side values of 20 and 50. The results include return, drawdown, win rate, number of trades, and other metrics. For example, with an rsi of 5 and a bp_side of 20, the return was 28.119744729731394, the drawdown was 36.32994037310422, and the win rate was 35.294117647058826. The strategy was trained on data from 2016 to 2022, and tested on holdout data from 2023 to 2025, with recent data from 2026 to September 18. The next open trade will use a 2 true ATR and 6 ATR, with a 60 session limit, and a stop at the first ambiguous bar or gap stop at open. The strategy uses vectorbt long only, with 5 bp fees and 15/45 bps slip on each side, and was reconciled to 1e-9. The AA starts on November 1, 2016, and the holdout is historical, not prospective. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the KALU R92006 costed sweep KALU/rsi_only/train had the following results: a list of trade results with different Relative Strength Index, or RSI, values and buy/sell percentages, or bp_side, including return, drawdown, or DD, win percentage, number of trades, or N, and other metrics. The results were observed from September 20, and were trained on data from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data from 2026 to September 18. The next open trade will use a true Average True Range, or ATR, of 2 and 6, with 60 sessions, and a stop at the first ambiguous bar, with a gap stop at open, and window end marks. The trade will use a vectorbt long only strategy, with 5 basis point fees and 15/45 basis point slippage on each side, and was reconciled to 1e-9. The AA, or Autocorrelation Analysis, starts on November 1, 2016, as a separation point. The holdout is historical, not pristine prospective. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the results of a trading strategy for KALU stock, which is a type of investment, are as follows: the strategy had different settings, including a thing called rsi, which is short for relative strength index, a way to measure stock performance, and bp_side, which refers to the side of a trade, either buying or selling. The results were: a 5 rsi and 20 bp_side had a return of 22.59548700399472 percent, a 5 rsi and 50 bp_side had a return of 19.68819403541903 percent, a 10 rsi and 20 bp_side had a return of 4.9990908775631855 percent, a 10 rsi and 50 bp_side had a return of 2.5090879739062646 percent, a 15 rsi and 20 bp_side had a return of 16.276263082120774 percent, and a 15 rsi and 50 bp_side had a return of 12.83974715970985 percent. The data was observed from September 20, and the training period was from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data from 2026 to September 18. The next open trade will use a true average true range, which is a way to measure stock volatility, and a 60 session stop, which is a way to limit losses. The strategy also uses a thing called vectorbt, which is a way to backtest trades, and long only, which means only buying stocks, with fees of 5 basis points, which is a way to measure a small percentage, and a 15 to 45 basis point slip, which is a way to measure a small loss. The results were reconciled to 1e-9, which is a very small number, and the AA, which is a type of investment strategy, starts on November 1, 2016. The holdout is historical, not prospective, meaning it looks at past data, not future predictions. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the results of a trading strategy for the stock KALU, which is a ticker symbol, a code used to identify a stock on an exchange. The strategy was tested with different parameters, including a relative strength index, or RSI, which measures the speed and change of price movements, of 5, 10, and 15, and a buy/sell signal threshold, or bp_side, of 20 and 50. The results showed returns ranging from -21.94% to 5.43%, with a maximum drawdown, or DD, which is the maximum loss from a peak to a trough, of 49.35%. The strategy had a win rate, which is the percentage of trades that were profitable, of 16.67% to 37.5%, and an average win, which is the average profit of winning trades, of 17.23% to 25.54%. The strategy also had an average loss, which is the average loss of losing trades, of -7.11% to -8.89%. The data was observed from September 20, and the strategy was trained on data from 2016 to 2022, with a holdout period, which is a period of time used to test the strategy, from 2023 to 2025, and a recent period from 2026 to September 18. The next open trade will use a true average true range, or ATR, which is a measure of volatility, of 2 and 6, with a stop loss, which is an order to sell a stock when it falls to a certain price, at the first ambiguous bar, and a gap stop at the open. The strategy uses a vectorized backtesting library, or vectorbt, which is a library used to test trading strategies, and has a fee of 5 basis points, or bps, which is a unit of measurement for interest rates and fees, plus a slippage, which is the difference between the expected price of a trade and the actual price, of 15/45 bps on each side. The results were reconciled to an accuracy of 1e-9, which is a very small number. The strategy started on November 1, 2016, and the holdout period is historical, not prospective, meaning it is based on past data, not future predictions. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the results of a trading strategy for KALU stock, which is a type of investment, from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data up to September 18, 2026. The strategy used a relative strength index, or RSI, which measures stock performance, and a buy/sell side, or bp_side, which determines when to buy or sell. The results were as follows: for an RSI of 5 and bp_side of 20, the return was 76.38%, with a maximum drawdown, or DD, of 24.66%, and a win rate of 50%. For an RSI of 5 and bp_side of 50, the return was 60.24%, with a DD of 25.34%, and a win rate of 43.75%. For an RSI of 10 and bp_side of 20, the return was 24.44%, with a DD of 26.11%, and a win rate of 36.36%. For an RSI of 10 and bp_side of 50, the return was 9.05%, with a DD of 27.64%, and a win rate of 36.36%. For an RSI of 15 and bp_side of 20, the return was 34.46%, with a DD of 26.11%, and a win rate of 33.33%. For an RSI of 15 and bp_side of 50, the return was 16.43%, with a DD of 30.05%, and a win rate of 33.33%. The strategy used a vectorbt long-only approach, which means it only bought stocks, with fees of 5 basis points, or bps, and a slippage of 15/45 bps on each side. The results were reconciled to an accuracy of 1e-9. The strategy started on November 1, 2016, and the holdout period was historical, not prospective, meaning it was based on past data, not future predictions. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the trading results for KALU are given in two scenarios. The first scenario has a return of 7.4788918271295195 percent, a maximum drawdown of 28.59801040858352 percent, and a win rate of 40 percent out of 5 trades. The second scenario has a return of 4.302380015547123 percent, a maximum drawdown of 29.23838826418703 percent, and a win rate of 40 percent out of 5 trades. These results were observed on September 20, and were trained on data from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data up to September 18, 2026. The next open trade will use a strategy based on 2 true average trading ranges and 6 average trading ranges, over 60 sessions, with a stop at the first ambiguous bar and a gap stop at the open, and marks at the end of the window. The strategy uses a vectorbt long-only approach, with fees of 5 basis points and a slip of 15 to 45 basis points on each side, and has been reconciled to an accuracy of 1e-9. The AA, or autonomous agent, starts on November 1, 2016, and separates the data into training and holdout sets, with the holdout set being historical data rather than pristine prospective data. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: two sets of results for the stock ticker KALU, with the following details. The first set has an RSI of 10, a bp_side of 20, a return of 38.488947181928616, a drawdown of 36.562076228492266, a win rate of 29.411764705882355, 17 trades, 16 closed trades, a mean of 2.8622020228313114, a half Kelly risk of 0.058883529417924185, an average win of 24.303927185791746, an average loss of -6.071850128402204, 5 targets, and a buy and hold return of 69.67016491754123. The second set has an RSI of 10, a bp_side of 50, a return of 25.059487511507122, a drawdown of 38.43696822576508, a win rate of 29.411764705882355, 17 trades, 16 closed trades, a mean of 2.2468706513221015, a half Kelly risk of 0.047683345455076354, an average win of 23.560329396759034, an average loss of -6.6337371592766186, 5 targets, and a buy and hold return of 69.67016491754123. The data was observed on September 20, trained from 2016 to 2022, held out from 2023 to 2025, and recently updated from 2026 to September 18. The next open will use 2 true average true ranges and 6 average true ranges, with 60 sessions, and a stop at the first ambiguous bar or a gap stop at open, with window end marks. The strategy used is a long only strategy with 5 basis point fees and 15/45 basis point slippage on each side, reconciled to 1e-9. The AA, or risk parity, starts on November 1, 2016, as a separation. The holdout is historical, not pristine prospective. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: two sets of results for the stock ticker KALU, with the following details. The first set had an RSI, or Relative Strength Index, of 10, and a bp_side of 20, which refers to the side of a trade, with a return of -50.09353039973693 percent, a drawdown, or largest loss, of 59.24919990202133 percent, a win rate of 23.25581395348837 percent, and 43 closed trades out of 43 total trades. The second set had an RSI of 10 and a bp_side of 50, with a return of -61.44259652803644 percent, a drawdown of 67.75144641134894 percent, a win rate of 23.25581395348837 percent, and also 43 closed trades out of 43 total trades. These results were observed on September 20, and were based on training data from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data from 2026 to September 18. The next open trade will use a 2 true Average True Range, or measure of price volatility, and a 6 Average True Range, with a 60 session limit, and a stop at the first ambiguous bar, or unclear price movement, and a gap stop at the open, with a window end mark. The vectorbt long only strategy, which only buys stocks, was used, with 5 basis point fees, and 15 and 45 basis point slippage, or difference between expected and actual trade prices, on each side. The results were reconciled to an accuracy of 1e-9. The AA, or automated trading system, started on November 1, 2016, and the holdout period was based on historical data, not pristine prospective data, which refers to data that has not been used before. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the results of a costed sweep of CSTM, which is a stock ticker, using a strategy called rsi_only, which refers to a trading strategy based on the Relative Strength Index, or RSI, a measure of stock price movement. The results are as follows: a list of six sets of data, each representing a different combination of RSI and bp_side, which refers to the side of a trade, either buying or selling, with a specific number of basis points, or bp. The results include return, which is the profit or loss, DD, which is the maximum drawdown, or loss, win, which is the percentage of winning trades, N, which is the total number of trades, closed, which is the number of closed trades, mean, which is the average return, halfKelly_risk, which is a measure of risk, avgwin, which is the average winning trade, avgloss, which is the average losing trade, targets, which is the number of targets, and buyhold, which is the return of a buy and hold strategy. The specific results are: for RSI 5 and bp_side 20, return was 15.578749965592612, DD was 15.959444235824217, win was 50, N was 2, closed was 2, mean was 9.086026276527626, halfKelly_risk was 0.1647440504835857, avgwin was 27.57618939760411, avgloss was -9.40413684454886, targets was 1, and buyhold was 34.191176470588246, and similarly for the other combinations. The data was observed on September 20, and was trained on data from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data from 2026 to September 18. The next open trade will use a strategy with 2 true ATR, or Average True Range, which is a measure of price movement, and 6 ATR, with 60 sessions, and a stop at the first ambiguous bar, and a gap stop at open, with window end marks. The strategy uses vectorbt, which is a trading library, and long only, which means only buying, with 5 bp fees, and 15 and 45 bp slippage, or the difference between the expected and actual price, on each side. The results were reconciled to 1e-9, which is a measure of precision. The AA, or Autocorrelation Analysis, starts on November 1, 2016, and is used for separation. The holdout is historical, not pristine prospective, meaning it is based on past data, not future predictions. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the results of a costed sweep of CSTM, which is a stock ticker, using a strategy called rsi_only, with a holdout period, are as follows: the strategy was tested with different parameters, including rsi, which stands for Relative Strength Index, a measure of stock price movement, and bp_side, which refers to the side of a trade. The results were: a return of -30.185389673395036 percent with an rsi of 5 and a bp_side of 20, a return of -35.810317705649744 percent with an rsi of 5 and a bp_side of 50, a return of 25.996646276052378 percent with an rsi of 10 and a bp_side of 20, a return of 10.415884267099774 percent with an rsi of 10 and a bp_side of 50, a return of 83.84561144829658 percent with an rsi of 15 and a bp_side of 20, and a return of 60.147456134563114 percent with an rsi of 15 and a bp_side of 50. The data also includes other metrics, such as win rate, average win, and average loss. The strategy was observed from September 20, and was trained on data from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data from 2026 to September 18. The next open trade will use a 2 true ATR, which stands for Average True Range, a measure of stock price volatility, and a 6 ATR, with a 60 session limit, and a stop at the first ambiguous bar, with a gap stop at the open, and a window end mark. The strategy uses a vectorbt long only approach, with 5 basis point fees, and 15 and 45 basis point slippage on each side, and was reconciled to 1e-9. The AA, which stands for Autocorrelation Analysis, starts on November 1, 2016, and the holdout is historical, not prospective. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the results of a costed sweep of CSTM, which is a stock ticker symbol, using a strategy based on the Relative Strength Index, or RSI, which is a measure of stock price movement. The results are as follows: a list of six sets of data, each with the following information: the RSI value, which is a number that measures the speed and change of stock price movements, the bp_side value, which is the percentage of the stock's price movement that is used to determine buy and sell signals, the return on investment, the maximum drawdown, or DD, which is the maximum loss of value, the win rate, the number of trades, the number of closed trades, the mean return, the half Kelly risk, which is a measure of the optimal amount of money to bet on a trade, the average win and loss, the number of targets, and the buy and hold return. The results are for the stock CSTM, and the data was observed on September 20, and the training period was from 2016 to 2022, with a holdout period from 2023 to 2025, and a recent period from 2026 to September 18. The strategy used a next open, 2 true Average True Range, or ATR, which is a measure of stock price volatility, and a 6 ATR stop, with 60 sessions, and a stop at the first ambiguous bar, and a gap stop at the open, with a window end mark. The strategy also used vectorbt long only, which is a type of trading strategy, with 5 basis point fees, and 15 and 45 basis point slippage on each side, and was reconciled to 1e-9, which is a very small number. The AA, or Autonomous Agent, started on November 1, 2016, and the separation was based on historical data, not prospective data. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the results of a trading strategy for CSTM are as follows: the strategy was tested with different parameters, including rsi, which is a measure of how quickly the stock price is changing, and bp_side, which refers to the side of the trade. The results show return, which is the profit made, DD, which is the maximum loss, win, which is the percentage of winning trades, N, which is the total number of trades, closed, which is the number of trades that were closed, mean, which is the average profit, halfKelly_risk, which is a measure of risk, avgwin, which is the average profit of winning trades, avgloss, which is the average loss of losing trades, targets, which is the number of targets, and buyhold, which is the return if the stock was bought and held. The results are: a return of 15.578749965592612 with an rsi of 5 and bp_side of 20, a return of 14.200080087365881 with an rsi of 5 and bp_side of 50, a return of -2.064094574652381 with an rsi of 10 and bp_side of 20, a return of -4.386597434850933 with an rsi of 10 and bp_side of 50, a return of -3.853342622405114 with an rsi of 15 and bp_side of 20, and a return of -6.1334143263238055 with an rsi of 15 and bp_side of 50. The data was observed on September 20, and the strategy was trained on data from 2016 to 2022 and held out from 2023 to 2025, with recent data from 2026 to September 18. The next open trade will use 2 true ATR, which is a measure of volatility, and 6 ATR, with a stop at the first ambiguous bar, and a gap stop at the open. The strategy uses vectorbt long only, with 5 bp fees, which is a measure of the cost of the trade, and 15/45 bps lip each side, which is a measure of the slippage, or the difference between the expected and actual price. The results were reconciled to 1e-9, which is a measure of the accuracy. The strategy starts on November 1, 2016, and the holdout is historical, not prospective, meaning it is based on past data, not future predictions. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the results of a trading strategy test for CSTM, which is a stock ticker symbol, are as follows: the test was run with different parameters, including rsi, which stands for relative strength index, a measure of stock price movement, and bp_side, which refers to the side of a trade, either buying or selling. The results are: a list of outcomes with different rsi and bp_side values, including return, which is the profit or loss, DD, which stands for drawdown, the largest loss, win, the number of winning trades, N, the total number of trades, closed, the number of closed trades, mean, the average return, halfKelly_risk, a measure of risk, avgwin, the average winning trade, avgloss, the average losing trade, targets, the number of targets, and buyhold, the return if the stock was bought and held. The test was run on historical data from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data from 2026 to September 18. The next open trade will use a 2 true ATR, which stands for average true range, a measure of stock price volatility, and a 6 ATR stop, a stop-loss order to limit losses. The test used a vectorbt long only strategy, which means only buying stocks, with 5 basis point fees, and 15 and 45 basis point slippage, which is the difference between the expected and actual price of a trade. The results were reconciled to an accuracy of 1e-9, which is a very small number. The test started on November 1, 2016, and the holdout period is historical, not prospective, meaning it is based on past data, not future predictions. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: the results of a trading strategy test on CSTM stock are as follows: the strategy was tested with different parameters, including rsi, which is a measure of how overbought or oversold a stock is, and bp_side, which refers to the side of a trade. The results are: a return of 197.54% with an rsi of 5 and bp_side of 20, a return of 163.89% with an rsi of 5 and bp_side of 50, a return of 165.74% with an rsi of 10 and bp_side of 20, a return of 128.72% with an rsi of 10 and bp_side of 50, a return of 135.71% with an rsi of 15 and bp_side of 20, and a return of 96.88% with an rsi of 15 and bp_side of 50. The strategy was trained on data from 2016 to 2022 and tested on data from 2023 to 2025, with a recent test on data up to September 18, 2026. The strategy uses a next open, 2 true average true range, and 6 average true range, with a stop at the first ambiguous bar and a gap stop at open. The strategy also uses a vectorbt long only approach, with 5 basis point fees and 15/45 basis point slippage on each side. The results were reconciled to 1e-9. The strategy starts on November 1, 2016, and the holdout is historical, not prospective. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: two sets of results for CSTM, with the following details. The first set has an RSI of 10, a bp_side of 20, a return of 7.874531869916485, a drawdown of 22.347687680984397, a win rate of 33.33333333333333, 6 closed trades out of 6 total trades, a mean of 2.4119627145284706, a half Kelly risk of 0.050351476854645236, an average win of 23.95126086858712, an average loss of -8.357686362500855, 2 targets, and a buy and hold return of 34.191176470588246. The second set has an RSI of 10, a bp_side of 50, a return of 4.06008355679603, a drawdown of 24.189174893245145, a win rate of 33.33333333333333, 6 closed trades out of 6 total trades, a mean of 1.7993247169276305, a half Kelly risk of 0.03876222174443833, an average win of 23.20977276264872, an average loss of -8.905899305932913, 2 targets, and a buy and hold return of 34.191176470588246. The data was observed on September 20, and was trained on data from 2016 to 2022, with a holdout period from 2023 to 2025, and recent data from 2026 to September 18. The next open, 2 true ATR, 6 ATR, 60 sessions, stop at the first ambiguous bar, and gap stop at open, with window end marks. The strategy used was vectorbt long only, with 5 bp fees and 15/45 bps lip each side, and was reconciled to 1e-9. The AA starts on November 1, 2016, separation. The holdout is historical, not pristine prospective. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all