Notes

A news scan found the headline is not available, but a data line shows Pearson daily close-return correlations through September 17, for a current survivor panel with retrospective adjustments, and pairwise dates, with no causal inference. The correlations are as follows: TEN has a correlation of 0.7081820027, FRO has a correlation of 0.7079429433, STNG has a correlation of 1, LPG has a correlation of 0.5740466733, BWLP has a correlation of 0.5690102237, PSIX has a correlation of -0.0116794475, ALM has a correlation of 0.0460618368, AA has a correlation of -0.0381317951, CENX has a correlation of 0.0014487198, FTK has a correlation of -0.0649281937, MU has a correlation of 0.0467526109, and SPY has a correlation of 0.0764258042. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline 'FRO R91806 252-session correlation row'. The Pearson daily close-return correlations through September 17, for a current survivor panel with retrospective adjustments, and pairwise dates, are as follows: no causal inference is made. The correlations are as follows: TEN has a correlation of 0.8194131928, FRO has a correlation of 1, STNG has a correlation of 0.7079429433, LPG has a correlation of 0.6088741545, BWLP has a correlation of 0.5955808943, PSIX has a correlation of 0.0556715061, ALM has a correlation of 0.1161040572, AA has a correlation of -0.0496410535, CENX has a correlation of -0.0557871736, FTK has a correlation of -0.0583916403, MU has a correlation of 0.0154277653, and SPY has a correlation of 0.1425417285. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline is not available, but a data line shows Pearson daily close-return correlations through September 17 for the stock TEN and other stocks. The correlations are as follows: TEN has a correlation of 1 with itself, 0.8194131928 with FRO, 0.7081820027 with STNG, 0.6001937154 with LPG, 0.5781077787 with BWLP, 0.0320750724 with PSIX, 0.130925374 with ALM, 0.0066666284 with AA, -0.0146631719 with CENX, -0.0454824651 with FTK, 0.0185217866 with MU, and 0.1228311532 with SPY. Pearson correlation is a measure of how much two things are related. https://runway.adityaperswal.workers.dev/data/stock-bars?timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline 'SPY R91806 backtests 3/3'. Methods note3577 is a set of rules for the backtest, which was done on September 2018 using data from completed September 2017 bars. The backtest uses percent units and simulations that are conditional, with a Kelly diagnostic, which is a tool to measure risk. The results are shown in a table with the following columns: split, lookback, filter, cost in basis points per side, number of bars, return as a percentage, closed return as a percentage, drawdown as a percentage, win rate as a percentage, number of trades, mean trade return as a percentage, median trade return as a percentage, open, buy and hold return as a percentage, targets, and gaps. The table has two rows of data: one for forward2026 with a 20-day lookback and a simple moving average filter of 200, and one for forward2026 with a 20-day lookback and a spy200 filter, both with 6 basis points cost per side, 178 bars, 0.530918 percent return, 0.33206418 percent closed return, 8.45082113 percent drawdown, 20 percent win rate, 5 trades, 0.16402143 percent mean trade return, -1.77245247 percent median trade return, 1 open, 11.80992416 percent buy and hold return, 1 target, and 0 gaps. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=SPY&timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline 'SPY R91806 backtests 2/3'. Methods note3577 is a calculation method used for backtesting, which was applied on September 18 to completed bars from September 17. The calculations are in percent units and the simulations are conditional, using a Kelly diagnostic, which is a tool to measure the performance of a trading strategy. The backtest results are as follows: a table with 13 rows and 16 columns, including split, lookback, filter, cost_bps_side, bars, return_pct, closed_return_pct, drawdown_pct, win_rate_pct, n, mean_trade_pct, median_trade_pct, open, buyhold_pct, targets, and gaps. The results show various combinations of these parameters, such as holdout and forward2026, with different values for lookback, filter, and cost_bps_side, and the corresponding results for return_pct, closed_return_pct, and other metrics. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=SPY&timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline 'Methods note3577'. This refers to a set of rules used by the automated trading fund manager. The calculation was done in September 2018 using completed data from September 2017. The results are given in percent units and the simulations are conditional, with a Kelly diagnostic, which is a measure of risk. The results are as follows: the data has 14 columns, including split, lookback, filter, cost, and return, and 12 rows of data, including train and holdout sets, with different parameters such as sma50, sma200, and spy200, which are types of filters, and cost_bps_side, which is a cost in basis points per side of a trade. The data includes results such as return_pct, which is the percentage return, and drawdown_pct, which is the percentage drawdown, or loss. For example, the first row has a return_pct of 96.18495024 and a drawdown_pct of 16.18231928. The data also includes a holdout set, which is a set of data used to test the model, with results such as a return_pct of 26.96537097 and a drawdown_pct of 8.28664777. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=SPY&timeframe=1Day&feed=sip&adjustment=all

A methods note, number 3577, was written. It is about a calculation done on September 18, using data from the previous month, September 17. The calculation is measured in percent units and the results are explicitly named. The simulations are conditional, meaning they depend on certain conditions, and a Kelly diagnostic, a tool used to measure the performance of a trading strategy, was used. The results are shown in a table with the following columns: split, n, min_gap_pct, p01_gap_pct, p001_gap_pct, below10, below20, below30, min_close_pct, and max_close_pct. The table has three rows: train, holdout, and forward2026, with the following data: train has 2011, -10.74205235, -2.05302832, -7.053206, 1, 0, 0, -10.78275736, and 8.67665112; holdout has 502, -3.98836806, -2.15883425, -3.71258617, 0, 0, 0, -5.8550538, and 10.50045049; forward2026 has 178, -1.64897288, -1.43319874, -1.6173419, 0, 0, 0, -2.58074794, and 2.90558056. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=SPY&timeframe=1Day&feed=sip&adjustment=all

A technical analysis of SPY, specifically the R91806 method, was performed on September 18, using data from completed bars on September 17. The calculation used percent units and included simulations that were conditional, with a Kelly diagnostic, which is a measure of risk. The results are presented in a table with the following columns: date, n, close, prior20, sma50, sma200, atr20, atrpct, rv20, volume20, signal, rule_stop, rule_target, and shares_cap. The table contains one row of data for September 17, 2026, with values including a close price of 760.71, a 20-day simple moving average of 771.25, and a signal value of false. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=SPY&timeframe=1Day&feed=sip&adjustment=all

A methods note, number 3577, was written in September 2018, based on calculations from September 2017. The calculations are shown in percent units and the simulations are conditional, using a Kelly diagnostic, which is a tool to measure risk. The results are shown in a table with the following columns: tail replacement probability, equity weight, number of paths, number of trades, mean terminal percent, fifth percentile terminal percent, ninety-fifth percentile drawdown percent, and probability of a 10 percent loss. The table has six rows of data, with the following values: [0, 0.11999953, 20000, 20, 2.28469686, -7.80018633, 9.99462179, 1.715], [0, 0.02999988, 20000, 20, 0.56712926, -1.98385193, 2.58855234, 0], [0.01, 0.11999953, 20000, 20, 1.58753707, -8.66422778, 10.98713776, 3.005], [0.01, 0.02999988, 20000, 20, 0.39457736, -2.20747236, 2.84803269, 0], [0.05, 0.11999953, 20000, 20, -1.41841179, -12.75396854, 14.57534501, 11.255], [0.05, 0.02999988, 20000, 20, -0.35706154, -3.3020212, 3.81912185, 0]. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=MU&timeframe=1Day&feed=sip&adjustment=all

A methods note, number 3577, was written in September 2018, using data from completed bars in September 2017. The calculations are in percent units and the simulations are conditional, with a Kelly diagnostic, which is a measure of risk. The results are as follows: the columns in the data are split, lookback, filter, cost in basis points per side, number of bars, return percent, closed return percent, drawdown percent, win rate percent, number of trades, mean trade percent, median trade percent, open, buy and hold percent, targets, and gaps. The rows of data show three scenarios for forward 2026, with a lookback of 20, and different filters: none, sma200, which is a simple moving average over 200 periods, and spy200, which is likely a filter based on the S&P 500 index over 200 periods. The cost per side is 6 basis points, and the results are: 57.99755862 percent return, 54.79304613 percent closed return, 36.91631322 percent drawdown, 50 percent win rate, 6 trades, 9.5941149 percent mean trade, 9.15069743 percent median trade, 1 open, 231.40086791 percent buy and hold, 3 targets, and 1 gap. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=MU&timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline 'MU R91806 backtests 2/3'. Methods note3577 is a calculation method used in this context, which refers to a specific way of analyzing data. The Sep18 calculation was done on completed Sep17 bars, which means the data from September 2017 was used for calculations in September 2018. Percent units are explicitly named, which means that percentages are clearly stated. Simulations are conditional, meaning they depend on certain conditions, and a Kelly diagnostic is used, which is a tool to measure the performance of a system. The results are presented in a table format with the following columns: split, lookback, filter, cost_bps_side, bars, return_pct, closed_return_pct, drawdown_pct, win_rate_pct, n, mean_trade_pct, median_trade_pct, open, buyhold_pct, targets, gaps. The rows represent different scenarios with varying parameters, including holdout and forward2026, which refer to different testing methods, and sma50, sma200, and spy200, which are types of filters used in the analysis. The results show various percentages and numbers, including return percentages, drawdown percentages, and win rates, for each scenario. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=MU&timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline 'MU R91806 backtests 1/3'. Methods note3577 is a calculation method used for this backtest, which was done in September 2018 on completed September 2017 bars. The calculations are in percent units and the simulations are conditional, using a Kelly diagnostic, which is a tool to measure the performance of a trading strategy. The results are shown in a table with the following columns: split, lookback, filter, cost_bps_side, bars, return_pct, closed_return_pct, drawdown_pct, win_rate_pct, n, mean_trade_pct, median_trade_pct, open, buyhold_pct, targets, gaps. The rows of the table show the results of different simulations, including the split, which refers to the division of data into training and testing sets, the lookback, which is the number of previous bars used to calculate the filter, the filter, which is a rule used to determine when to buy or sell, the cost_bps_side, which is the cost of trading in basis points, the bars, which is the number of bars used in the simulation, the return_pct, which is the return on investment as a percentage, the closed_return_pct, which is the return on investment as a percentage after closing positions, the drawdown_pct, which is the maximum loss as a percentage, the win_rate_pct, which is the percentage of winning trades, the n, which is the number of trades, the mean_trade_pct, which is the average return on investment per trade as a percentage, the median_trade_pct, which is the middle value of the returns on investment per trade as a percentage, the open, which is the opening price, the buyhold_pct, which is the return on investment as a percentage if the stock was bought and held, the targets, which are the price targets for the trades, and the gaps, which are the price gaps between the trades. The results are as follows: train with 10 lookback and sma50 filter had a return of 196.05535654 percent, train with 10 lookback and sma50 filter and 16 cost_bps_side had a return of 166.01357366 percent, train with 20 lookback and sma50 filter had a return of 14.81978875 percent, train with 20 lookback and sma50 filter and 16 cost_bps_side had a return of 3.58212054 percent, train with 40 lookback and sma50 filter had a return of 14.21165098 percent, train with 40 lookback and sma50 filter and 16 cost_bps_side had a return of 4.48611776 percent, train with 20 lookback and no filter had a return of -20.97950544 percent, train with 20 lookback and sma200 filter had a return of -28.86846646 percent, train with 20 lookback and spy200 filter had a return of 4.68747129 percent, holdout with 10 lookback and sma50 filter had a return of 51.24061444 percent, holdout with 10 lookback and sma50 filter and 16 cost_bps_side had a return of 46.03889696 percent, holdout with 20 lookback and sma50 filter had a return of 32.44523908 percent. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=MU&timeframe=1Day&feed=sip&adjustment=all

A methods note, number 3577, explains that a calculation was done in September 2018 using data from completed September 2017 bars. The calculation uses percent units and simulations that are conditional, with a Kelly diagnostic, which is a measure of risk. The results are shown in a table with the following columns: split, regime, above, number of times, mean percent, and win percent. The table has the following rows: for the train set, own200 regime with values above true had 37 times, a mean percent of 0.03465003, and a win percent of 29.72972973, and with values above false had 14 times, a mean percent of 3.39346771, and a win percent of 42.85714286, for the train set, spy200 regime with values above true had 40 times, a mean percent of 1.53822191, and a win percent of 35, and with values above false had 11 times, a mean percent of -1.15802521, and a win percent of 27.27272727, for the holdout set, own200 regime with values above true had 14 times, a mean percent of 3.55736058, and a win percent of 42.85714286, and with values above false had 3 times, a mean percent of -1.68758041, and a win percent of 33.33333333, for the holdout set, spy200 regime with values above true had 16 times, a mean percent of 1.16030744, and a win percent of 37.5, and with values above false had 1 time, a mean percent of 26.17538792, and a win percent of 100, for the forward2026 set, own200 and spy200 regimes with values above true both had 6 times, a mean percent of 9.5941149, and a win percent of 50. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=MU&timeframe=1Day&feed=sip&adjustment=all

A methods note, number 3577, was made. It used a September 2018 calculation on completed September 2017 bars. The percent units are explicitly named. Simulations are conditional, using a Kelly diagnostic, which is a way to measure risk. The trade statistics are as follows: the columns are split, n, mean percent, mean confidence interval 95 percent, win percent, average win percent, average loss percent, half Kelly stock fraction, half Kelly dollars, minimum trade percent, and maximum trade percent. The rows are divided into train, holdout, and forward 2026. For train, the values are 51, 0.95667842, [-2.22276035, 4.36924824], 33.33333333, 17.33147956, 7.23072216, 0.36, 101.99, -11.02537784, and 27.5896377. For holdout, the values are 17, 2.63178276, [-4.53502445, 10.13577977], 41.17647059, 20.44880425, 9.84013228, 0.5, 101.99, -18.03046755, and 26.65037946. For forward 2026, the values are 6, 9.5941149, [-5.58388995, 25.46180527], 50, 30.4548317, 11.2666019, 0.5, 101.99, -14.02093522, and 35.72163904. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=MU&timeframe=1Day&feed=sip&adjustment=all

This is a methods note, number 3577, from September 18, regarding calculations on completed data from September 17. The calculations are in percent units and the simulations are conditional, using a Kelly diagnostic, which is a tool to measure risk. The results are presented in a table with the following columns: split, n, minimum gap percent, 1 percent gap percent, 0.1 percent gap percent, below 10, below 20, below 30, minimum close percent, and maximum close percent. The table has three rows: train, holdout, and forward2026, with the following values: train has 2011, -13.12022901, -4.15369576, -9.86261066, 2, 0, 0, -19.82347328, 13.33542516, holdout has 502, -13.31140563, -5.34860128, -10.68294983, 1, 0, 0, -16.18457967, 18.81597063, and forward2026 has 178, -10.84553208, -7.37915122, -10.33506093, 1, 0, 0, -13.25199578, 19.29203068. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=MU&timeframe=1Day&feed=sip&adjustment=all

A methods note, number 3577, was written. It is about a calculation done in September 2018 using data from September 2017. The calculation is shown in percent units and includes simulations that are conditional, with a Kelly diagnostic, which is a way to measure how well a trading strategy is working. The data is organized into columns and rows, with columns including the date, the number of days, the closing price, and other technical indicators such as simple moving averages, or sma, and average true range, or atr. The rows show the specific data for a given date, in this case September 17, 2026, with a closing price of 977.5 and other values, including a signal that is false, a stop rule of 889.63, and a target rule of 1241.11, with 0 shares capped. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=MU&timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: Methods note3577 used a September 2018 calculation on completed September 2017 bars. The results are in percent units and the simulations are conditional, with a Kelly diagnostic. The data includes the following columns: split, lookback, filter, cost in basis points per side, number of bars, return percent, closed return percent, drawdown percent, win rate percent, number of trades, mean trade percent, median trade percent, open, buy and hold percent, targets, and gaps. The rows of data are as follows: for forward2026 with a 20 period lookback and no filter, the cost was 6 basis points per side, 178 bars were used, the return was -29.24660765 percent, the closed return was -29.24660765 percent, the drawdown was 32.36556249 percent, the win rate was 16.66666667 percent, there were 6 trades, the mean trade was -4.44704726 percent, the median trade was -11.75175051 percent, the open was 0, the buy and hold return was 75.25773196 percent, there was 1 target, and 0 gaps. The same results were found for forward2026 with a 20 period lookback and a simple moving average 200 filter, and for forward2026 with a 20 period lookback and a spy200 filter. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FTK&timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline 'FTK R91806 backtests 2/3'. Methods note3577 is a calculation method used for backtesting, which was applied in September 2018 to completed data from September 2017. The calculations are in percent units and the simulations are conditional, using a Kelly diagnostic, which is a tool to determine the optimal bet size. The results are presented in a table with the following columns: split, lookback, filter, cost_bps_side, bars, return_pct, closed_return_pct, drawdown_pct, win_rate_pct, n, mean_trade_pct, median_trade_pct, open, buyhold_pct, targets, gaps. The table contains 12 rows of data, each representing a different backtest scenario, with various parameters such as holdout, sma50, sma200, and spy200, which are types of filters used in the backtesting process. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FTK&timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline 'FTK R91806 backtests 1/3'. Methods note3577 is a calculation method used for backtesting. The Sep18 calculation was done on completed Sep17 bars, which refers to September 2018 calculations based on data from September 2017. The results are given in percent units. Simulations are conditional, meaning they depend on certain conditions, and a Kelly diagnostic is used, which is a tool to measure the performance of a trading strategy. The results are presented in a table with the following columns: split, lookback, filter, cost_bps_side, bars, return_pct, closed_return_pct, drawdown_pct, win_rate_pct, n, mean_trade_pct, median_trade_pct, open, buyhold_pct, targets, gaps. The rows of the table show the results of different simulations, including the type of simulation, such as 'train' or 'holdout', the lookback period, the filter used, and the cost in basis points per side. The table shows the results for 12 different simulations, with return percentages ranging from -90.93776344 to -20.33895654, and drawdown percentages ranging from 94.69388136 to 45.83549864. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FTK&timeframe=1Day&feed=sip&adjustment=all

A methods note, number 3577, was written in September 2018, using data from September 2017. The calculations are in percent units and the simulations are conditional, using a Kelly diagnostic, which is a tool to measure risk. The results are shown in a table with the following columns: split, regime, above, number of times, mean percent, and win percent. The rows in the table show the results for different regimes, including own200 and spy200, and different time periods, including train, holdout, and forward2026. The table shows the number of times, mean percent, and win percent for each regime and time period, with results such as -10.07103807 percent and 5.88235294 percent win rate for the train own200 regime when the value is above a certain point, and 0.64462035 percent and 26.31578947 percent win rate when the value is not above that point. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FTK&timeframe=1Day&feed=sip&adjustment=all

A methods note, number 3577, was made. It used a calculation from September 2018 on completed data from September 2017 bars. The percent units are explicitly named, and the simulations are conditional, with a Kelly diagnostic. The trade statistics are as follows: the columns are split, number of trades, mean percent, mean confidence interval 95 percent, win percent, average win percent, average loss percent, half Kelly stock fraction, half Kelly dollars, minimum trade percent, and maximum trade percent. The rows show the results for the train, holdout, and forward 2026 sets. For the train set, there were 36 trades, with a mean percent of -4.41555168, a mean confidence interval 95 percent of -9.99677025 to 2.25404988, a win percent of 16.66666667, an average win percent of 35.72056973, an average loss percent of 12.44277597, a half Kelly stock fraction of 0, a half Kelly dollars of 0, a minimum trade percent of -26.01476151, and a maximum trade percent of 63.56802362. For the holdout set, there were 19 trades, with a mean percent of -0.57513221, a mean confidence interval 95 percent of -7.43690406 to 7.59424185, a win percent of 26.31578947, an average win percent of 28.11839973, an average loss percent of 10.82282219, a half Kelly stock fraction of 0, a half Kelly dollars of 0, a minimum trade percent of -13.97988777, and a maximum trade percent of 35.09912094. For the forward 2026 set, there were 6 trades, with a mean percent of -4.44704726, a mean confidence interval 95 percent of -12.29545919 to 10.11828516, a win percent of 16.66666667, an average win percent of 31.73505331, an average loss percent of 11.68346737, a half Kelly stock fraction of 0, a half Kelly dollars of 0, a minimum trade percent of -12.59844923, and a maximum trade percent of 31.73505331. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FTK&timeframe=1Day&feed=sip&adjustment=all

A methods note, number 3577, was written. It is about a calculation done in September 2018 using data from September 2017. The calculation is shown in percent units and the results are explicitly named. The simulations are conditional and a Kelly diagnostic was used. The results are shown in a table with the following columns: split, n, min_gap_pct, p01_gap_pct, p001_gap_pct, below10, below20, below30, min_close_pct, and max_close_pct. The table has three rows: train, holdout, and forward2026, with the following values: train has 2011, -24.05063291, -7.17318328, -19.20868925, 7, 2, 0, -34.93939394, and 95.74468085, holdout has 502, -7.27272727, -3.88074866, -6.44235256, 0, 0, 0, -12.42532855, and 42.15686275, and forward2026 has 178, -13.53383459, -4.12465588, -12.55560565, 1, 0, 0, -20.01116383, and 27.86246012. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FTK&timeframe=1Day&feed=sip&adjustment=all

A methods note, number 3577, was written for the FTK R91806 technical analysis on January 1. The analysis used a September 2018 calculation based on completed September 2017 data. The results are given in percent units and the simulations are conditional, using a Kelly diagnostic, which is a tool to measure the performance of a trading strategy. The data includes the following information: date, number of days, closing price, prior 20-day average, 50-day simple moving average, 200-day simple moving average, 20-day average true range, average true range as a percentage, 20-day realized volatility, 20-day average volume, signal to buy or sell, stop loss rule, target price rule, and shares capital. The data is as follows: on September 17, 2026, the closing price was 30.6, the prior 20-day average was 28.13, the 50-day simple moving average was 27.2462, the 200-day simple moving average was 20.4251, the 20-day average true range was 1.560535, the average true range as a percentage was 5.09978758, the 20-day realized volatility was 0.69965088, the 20-day average volume was 487763.05, the signal was to buy, the stop loss rule was 27.47893, the target price rule was 39.96321, and the shares capital was 3. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FTK&timeframe=1Day&feed=sip&adjustment=all

A methods note, number 3577, was written in September 2018, based on calculations from September 2017 data. The calculations are shown in percent units and the simulations are conditional, using a Kelly diagnostic, which is a tool to measure risk. The results are shown in a table with the following columns: tail replacement probability, equity weight, number of paths, number of trades, mean terminal percent, fifth percentile terminal percent, ninety-fifth percentile drawdown percent, and probability of a 10 percent loss. The rows of the table show the following values: [0, 0.11999953, 20000, 20, 9.53228833, -9.18643148, 13.73119367, 4.025], [0, 0.02999988, 20000, 20, 2.30630253, -2.30739031, 3.59637644, 0], [0.01, 0.11999953, 20000, 20, 8.60974408, -10.01674517, 14.55839185, 5.025], [0.01, 0.02999988, 20000, 20, 2.08876692, -2.52979786, 3.82502003, 0], [0.05, 0.11999953, 20000, 20, 5.15053992, -13.01855242, 17.11179449, 9.62], [0.05, 0.02999988, 20000, 20, 1.2639107, -3.33714929, 4.53665136, 0]. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=CENX&timeframe=1Day&feed=sip&adjustment=all

A news scan found the simulation results for CENX R91806. The methods note3577 explains that the simulation was run on September 18, using completed bars from September 17. The results are in percent units and the simulations are conditional, using a Kelly diagnostic, which is a measure of risk. The simulation results are as follows: the columns are period, block, levels, paths, horizon, stop, target, stop first percent, target first percent, timeout percent, mean percent, median percent, p05 percent, p01 percent, mean sessions, and sizing. The rows show the results for different scenarios: pre2024 with a block of 5, pre2024 with a block of 10, last252 with a block of 5, and last252 with a block of 10. Each scenario has the following results: levels are 2ATR6ATR, paths are 20000, horizon is 60, stop is 36.39879, target is 53.80363, stop first percent is between 67.48 and 60.875, target first percent is between 30.295 and 35.38, timeout percent is between 2.225 and 5.155, mean percent is between 2.24486318 and 5.04103053, median percent is between -10.9631903 and -12.02052732, p05 percent is between -11.64909551 and -14.95260274, p01 percent is between -14.71134553 and -15.88225283, mean sessions is between 15.98515 and 20.6658. The sizing results are also provided, with dollars ranging from 25.4975 to 101.99, p01 account loss percent ranging from 0.44133863 to 1.90586287, and prob account loss gt3pct being 0. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=CENX&timeframe=1Day&feed=sip&adjustment=all