Notes

A simulation for the stock symbol EMN was run with a long regime. The simulation had 20000 paths and a stop percentage of 61.65, a target percentage of 20.93, and a time percentage of 17.42. The mean profit and loss per share was 0.23, with the 5th percentile being -6.38 and the 95th percentile being 12.57. The simulation also showed a 1% loss of -21.25. This simulation used a seed of 92004, with 20,000 paths each, and 4 cells with 80,000 paths. The empirical close return blocks started in either 2017 or 2025, with fixed barriers on September 18 and 20 basis points on each side, including overshoot at close. The simulation did not include intraday high or low, conditional signals, or news models, and the probabilities were not calibrated to trade odds. The stress diagnostic for EMN exceeded the 120 fund cap, but no such position was proposed. https://runway.adityaperswal.workers.dev/data/stock-bars

A simulation of the stock symbol CE was run with the following parameters: 60 sessions, 5-day blocks, and 20,000 paths. The stop percentage was set at 69.85, the target percentage at 24.55, and the time percentage at 5.6. The average profit and loss per share was -0.26, with 5% of outcomes resulting in a loss of -7.79 or more per share and 95% resulting in a gain of 12.78 or less per share. In the worst 1% of cases, the loss was -18.93 per share. This simulation, seeded with the number 92004, used 20,000 paths and was run in 4 cells with a total of 80,000 paths. The simulation used actual closing prices from either 2017 or 2025, with fixed barriers set on September 18 and a 20 basis point buffer on each side, including any overshoot at the close. The simulation did not account for intraday highs and lows, conditional signals, or news models, and the probabilities were not adjusted to reflect real trade odds. A stress test on the shares of EMN exceeded the 120 fund cap, but no such position was proposed. https://runway.adityaperswal.workers.dev/data/stock-bars

A simulation was run for a long position in the symbol CE, using 20,000 paths and a seed of 92004. The simulation had a stop loss of 57.52%, a target gain of 17.2%, and a time percentage of 25.28%. The average profit per share was $0.1505, with the 5th percentile being a loss of $6.7038 and the 95th percentile being a gain of $11.8016. The worst 1% of losses would result in a loss of $21.8457 per share. This simulation started with data from either 2017 or 2025, used fixed barriers from September 18 with a 20 basis point buffer on each side, and included any overshoot at the close. It did not consider intraday highs or lows, conditional signals, or news models, and the probabilities were not adjusted to reflect actual trade odds. A stress test showed that the proposed position would exceed the 120% fund cap, but no such position was suggested. https://runway.adityaperswal.workers.dev/data/stock-bars

A trade analysis of EMN R92004 shows the following results: there are 5 trades, with a win probability of 0.2, an average win percentage of 14.03505982857255, and an average loss percentage of 7.437813415905913. The half Kelly risk fraction is 0, which means the optimal fraction of equity to risk is 0, calculated as half of the probability of winning minus the probability of losing divided by the ratio of average win to average loss. The mean percentage return is -3.1432387670102195, with a 95% confidence interval of -7.870773213216825 to 5.493070312341293. This analysis is based on 20,000 independent and identically distributed bootstrap means, using a small selected conditional sample, and the results are not independently calibrated to predict future odds. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: a trade analysis of EMN R92004 shows the following statistics over a recent 20-day period. The analysis is based on 20,000 independent and identically distributed bootstrap means, using a small selected conditional sample, and the results are not independently calibrated to predict future odds. The data includes the number of trades, which is 5, the percentage of winning trades, which is 0.2 or 20 percent, the average winning trade percentage, which is 14.84 percent, and the average losing trade percentage, which is 6.79 percent. The half Kelly risk fraction, which is a measure of the optimal fraction of equity to risk, is calculated as 0. The mean percentage return is -2.46 percent, with a 95 percent confidence interval of -7.25 percent to 6.30 percent. The half Kelly formula is used to determine the optimal risk fraction, where half Kelly equals the maximum of 0 and 0.5 times the difference between the probability of winning and the probability of losing divided by the ratio of average win to average loss, representing a fraction of equity at risk, not dollars allocated. https://runway.adityaperswal.workers.dev/data/stock-bars

A trade analysis of EMN R92004 shows the following results: in 15 trades, the win rate was 0.13333333333333333, or 13.33%, with an average win of 14.342430364070925% and an average loss of 5.189317280305964%. The half Kelly fraction, which is a measure of the optimal fraction of equity to risk, calculated as half of the difference between the win probability and the loss probability divided by the ratio of average win to average loss, is 0. The average return was -2.585084261055711%, with a 95% confidence interval of -5.485027947247429% to 1.2944488225111732%. This analysis is based on 20,000 bootstrap means, using a small selected sample, and the results are not independently calibrated to predict future odds. The half Kelly formula used is max(0, 0.5 * (p - (1-p) / (avgWin/avgLoss))), which represents the fraction of equity at risk, not the dollars allocated. https://runway.adityaperswal.workers.dev/data/stock-bars

A trade analysis of EMN R92004 shows the following results: the number of trades is 15, the probability of winning is 0.13333333333333333, the average win percentage is 15.14564465072985, and the average loss percentage is 4.523306468345164. The half Kelly risk fraction is 0, which means the recommended fraction of equity to risk is 0. The mean percentage return is -1.9007796524684963, with a 95% confidence interval of -4.822981197569016 to 2.003371063954097. This analysis is based on 20,000 bootstrap means from a small selected conditional sample, and the results are not independently calibrated to predict future odds. The half Kelly formula is used to calculate the optimal fraction of equity to risk, which is max(0, 0.5 * (p - (1-p) / (avgWin/avgLoss))), where p is the probability of winning, avgWin is the average win, and avgLoss is the average loss. https://runway.adityaperswal.workers.dev/data/stock-bars

A trading analysis of EMN R92004 shows the following results: there are 35 trades, with a win probability of 0.3142857142857143, an average win percentage of 10.021291372972179, and an average loss percentage of 5.771079409115892. The half Kelly risk fraction is 0, which is a measure of the optimal fraction of equity to risk, calculated as half of the difference between the win probability and the loss probability divided by the ratio of average win to average loss. The mean percentage return is -0.8077628776024979, with a 95% confidence interval of -3.5475683918097243 to 2.172810174693522. This analysis is based on 20,000 bootstrap means, using a small selected sample, and the results are not independently calibrated to predict future odds. https://runway.adityaperswal.workers.dev/data/stock-bars

A trading analysis of EMN R92004 shows the following results: there were 35 trades, with a win probability of 0.3142857142857143, meaning about 31 percent of trades were winners. The average winning trade percentage was 10.794151218491137 percent, and the average losing trade percentage was 5.109155266047901 percent. The half Kelly risk fraction, which is a measure of the optimal fraction of equity to risk, is 0. The mean percentage return was -0.11097322804991769 percent, with a 95 percent confidence interval of -2.823237055967399 percent to 2.9053580843417706 percent. This analysis is based on 20,000 independent and identically distributed bootstrap means, using a small selected conditional sample, and the results are not independently calibrated to predict future odds. The half Kelly formula used is max(0, 0.5 * (p - (1 - p) / (avgWin / avgLoss))), which calculates the fraction of equity at risk, not the dollars allocated. https://runway.adityaperswal.workers.dev/data/stock-bars

A trade analysis shows the following results: the number of trades is 4, the probability of winning is 0.25, the average win percentage is 23.1537%, and the average loss percentage is 8.9051%. The half Kelly risk fraction, which is a measure of the optimal fraction of equity to risk, is 0. The mean percentage return is -0.8904%, with a 95% confidence interval of -11.3213% to 14.8906%. This data is based on 20,000 bootstrap means, using a small selected conditional sample, and the odds are not independently calibrated for future predictions. The half Kelly formula, which calculates the optimal risk fraction, is max(0, 0.5 * (p - (1-p) / (avgWin/avgLoss))), where p is the probability of winning, avgWin is the average win, and avgLoss is the average loss, and it represents a fraction of equity at risk, not dollars allocated. https://runway.adityaperswal.workers.dev/data/stock-bars

A trade analysis shows the following results: there are 4 trades, with a probability of winning of 0.25. The average winning trade percentage is 24.018780687017184 percent and the average losing trade percentage is 8.265158304774557 percent. The half Kelly risk fraction is 0, which means no equity is at risk. The mean percentage return is -0.1941735568266217 percent, with a 95 percent confidence interval of -10.698381082297276 percent to 15.697712417785498 percent. This data is based on 20,000 bootstrap means from a small selected sample, and the odds are not independently calibrated for future predictions. The half Kelly formula is used to calculate the fraction of equity at risk, which is max(0, 0.5 times the probability of winning minus the probability of losing divided by the average win divided by the average loss). https://runway.adityaperswal.workers.dev/data/stock-bars

A trade analysis shows the following results: the number of trades is 12, the probability of winning is 0.25, the average win percentage is 8.64%, and the average loss percentage is 6.05%. The half Kelly risk fraction is 0, the mean percentage is -2.38%, and the 95% confidence interval for the mean percentage is between -6.09% and 2.42%. This analysis is based on 20,000 independent and identically distributed bootstrap means, using a small selected conditional sample. Note that the results are not independently calibrated for future odds. The half Kelly formula is used to determine the fraction of equity at risk, calculated as max(0, 0.5 * (p - (1-p) / (avgWin/avgLoss))), where p is the probability of winning, avgWin is the average win, and avgLoss is the average loss. https://runway.adityaperswal.workers.dev/data/stock-bars

A trading analysis found the following results: the number of trades is 12, the probability of winning is 0.25, the average win percentage is 9.4077%, and the average loss percentage is 5.3917%. The half Kelly risk fraction, which is a measure of the optimal fraction of equity to risk, is 0. The mean percentage return is -1.6919%. A 95% confidence interval for the mean percentage return is between -5.4125% and 3.1093%. This data is based on 20,000 independent and identically distributed bootstrap means, using a small selected conditional sample. The half Kelly formula is used to calculate the optimal risk fraction, which is the maximum of 0 and 0.5 times the probability of winning minus the probability of losing divided by the ratio of average win to average loss. https://runway.adityaperswal.workers.dev/data/stock-bars

A trading fund manager analyzed the CE R92004 trade dispersion and half Kelly CE_train_55. The results showed 29 trades with a winning percentage of 31.03%. The average win was 9.85% and the average loss was 6.74%. The half Kelly risk fraction was 0. The mean percentage change was -1.59%. A 95% confidence interval for the mean percentage change was between -4.46% and 1.61%. This analysis was based on 20,000 independent and identically distributed bootstrap means from a small, selected conditional sample. The results are not independently calibrated to predict future odds. The half Kelly formula is used to calculate the fraction of equity at risk, which is half of the difference between the probability of winning and the probability of losing divided by the ratio of average win to average loss. https://runway.adityaperswal.workers.dev/data/stock-bars

A trade analysis shows the following results: there are 29 trades, with a winning percentage of 31.03%. The average win is 10.62% and the average loss is 6.08%. The half Kelly fraction, which is a risk management strategy, is 0. This means that no fraction of equity is at risk. The mean percentage return is -0.90%, with a 95% confidence interval of -3.79% to 2.30%. This analysis is based on 20,000 independent and identically distributed bootstrap means, using a small selected sample. The half Kelly formula is used to calculate the fraction of equity at risk, which is the maximum of 0 and half of the difference between the winning probability and the losing probability divided by the ratio of average win to average loss. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data line: {"n":179,"beta":0.9004264152984888,"daily_alpha_pct":-0.00587314299191566,"correlation":0.3671834641052106,"volatility_annual_pct":32.504060023452794}; this is a statistical summary, where beta refers to a measure of risk, and correlation measures how closely something moves with something else, in this case vsSPY, a stock market index. The data is based on a model trained from 2017 to 2022, held apart from 2023 to 2025, and recent data from 2026. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data line: {"n":179,"beta":0.26407268633148945,"daily_alpha_pct":0.077788701262891,"correlation":0.0657465463742872,"volatility_annual_pct":53.238160081965965}; this is a statistical summary of a trading model, where beta is a measure of risk, daily alpha is a measure of return, correlation is a measure of relationship with the SPY stock, and volatility is a measure of price fluctuations, with the data split into training from 2017 to 2022, held apart from 2023 to 2025, and recent data from 2026. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data line: {"n":752,"beta":1.113833738825308,"daily_alpha_pct":-0.09369751646153973,"correlation":0.5441161762727014,"volatility_annual_pct":31.408906230972345}. This is a set of statistics, including a measure of risk called beta, a daily return measure called alpha, a measure of how closely something moves with the SPY stock, called correlation, and a measure of volatility, or how much prices swing, over a year. The data is based on a model, specifically an ordinary least squares, or OLS, model, and includes a number of data points, or n, of 752. The model was trained on data from 2017 to 2022, and then tested on data from 2023 to 2025, with more recent data from 2026 also considered. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: a daily ordinary least squares, or statistical method, analysis of CE R92004, which is a type of investment, shows the following results: it has 752 data points, a beta of 1.462249081085948, which measures volatility, a daily alpha percentage of -0.1927678353747636, which measures return, a correlation of 0.4773252246804038, which measures relationship, and an annual volatility percentage of 47.00359256130575. This analysis compares the investment to SPY, a stock market index. The data is descriptive, not causal, and does not claim any significance or attribution. The data was trained on years 2017 to 2022, held apart for years 2023 to 2025, and is recent as of 2026. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: the daily Ordinary Least Squares, or OLS, for EMN_train has the following results: it has 1510 data points, a beta of 1.1837566914112843, a daily alpha percentage of -0.020711364697883653, a correlation of 0.71076701896477, and an annual volatility percentage of 32.40635428768821. This data compares the intercept and beta to the SPY, and is descriptive, not claiming causation or significance. The data was trained from 2017 to 2022, held apart from 2023 to 2025, and is recent as of 2026. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: a daily ordinary least squares, or OLS, calculation for CE_train, which is a statistical method to find a relationship between variables. The results are as follows: the number of data points is 1510, the beta, which measures how much a stock moves compared to the market, is 1.2435566895446644, the daily alpha percentage, which measures how much a stock outperforms the market, is -0.013515332864204706, the correlation, which measures how closely a stock moves with the market, is 0.7182959731588447, and the annual volatility percentage, which measures how much a stock's price changes, is 33.68659789161049. This is a comparison to the SPY stock, and the data is based on training from 2017 to 2022, held apart from 2023 to 2025, and recent data from 2026. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the headline 'EMN R92004 costed L60 recent 55bp per-side backtest'. The results of a backtest of the symbol EMN, which is a stock ticker, over a 60-day lookback period, show a return of 5.49% and a drawdown of 10.73%. The win rate was 50%. This backtest used a cost of 55 basis points, or 0.55%, per side, meaning per trade. The test used a vectorbt longonly strategy, which is a type of automated trading strategy, with a next-open entry, a 2ATR stop, and a fixed target of 3R, with a 60-session exit. The test was run on data from 2017 to 2022, and then held apart from 2023 to 2025, with the most recent data from 2026. The test portfolio was fully invested, not using fund sizing, which refers to the process of allocating a portion of a fund's assets to a particular investment. The test used daily intrabar stops, which are approximate 15-minute venue stops, and synthetic open and end accounting points, which allow for same-day exits. The stop was triggered first when both conditions were touched. The correct returns were calculated by dividing the profit and loss by the entry value plus entry fees. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the headline 'EMN R92004 costed L60 recent 20bp per-side backtest'. The results of a backtest for the symbol EMN show a return of 6.975171026805382 percent and a drawdown of 10.416401467515913 percent over a 60-day lookback period. The cost per side was 20 basis points, which is a measure of the cost of a trade as a percentage of the trade value. The win rate was 50 percent. This backtest used a strategy called vectorbt longonly, which is a type of automated trading strategy. The strategy used a next-open entry, a 2ATR stop, and a fixed target of 3R, with a 60-session exit. The test was run on data from 2017 to 2022, and then held apart from 2023 to 2025, with the most recent data from 2026. The test portfolio was fully invested, not using a 120 fund sizing, which refers to the amount of money allocated to the fund. The daily intrabar stops were approximate, occurring every 15 minutes, and synthetic open and end accounting points allowed for same-day exits. The stop was triggered first when both conditions were touched. The correct returns were calculated by dividing the profit and loss by the entry value plus entry fees. https://runway.adityaperswal.workers.dev/data/stock-bars

A backtest of the symbol EMN with a 60-day lookback period was conducted on the holdout window with a cost of 55 basis points per side. The results showed a return of -13.46%, a drawdown of 16.12%, and a win rate of 28.57% over 7 trades. The manual closed return was -13.46%. This was a long-only strategy using vectorbt, with entry at the next open, a 2ATR stop, and a fixed target of 3R, with a 60-session exit. The test was run from 2017 to 2022 for training, 2023 to 2025 was held apart, and 2026 was recent. The test portfolio was fully invested, not sized to a 120 fund. Daily intrabar stops were approximated to a 15-minute venue, and synthetic accounting points allowed for same-day exits, with stops triggered first when both were touched. Returns were calculated by dividing the profit and loss by the entry value plus entry fees. https://runway.adityaperswal.workers.dev/data/stock-bars

A backtest of the symbol EMN, which is a type of stock symbol, was done with a 60-day lookback period, meaning the system looked at 60 days of data to make decisions. The test used a holdout window, which is a part of the data set aside to test the system. The cost was 20 basis points, or 0.2%, per trade, on both the buy and sell sides. The return was -9.1146% and the drawdown, which is the largest decrease in value, was 14.9387%. The win rate, or percentage of winning trades, was 28.5714%. There were 7 trades in total. The manual closed return, which is the return when trades are closed manually, was -9.1146%. The test used a long-only strategy, meaning it only bought stocks and did not sell short. The system entered trades at the next open, with a stop loss of 2 average true ranges, or a measure of volatility, and a fixed target of 3 times the reward to risk ratio. Trades were exited after 60 sessions. The test was run from 2017 to 2022 for training, 2023 to 2025 was held apart, and 2026 was recent. The test portfolio was fully invested, not using fund sizing, which is a way to adjust the amount of money invested. Daily intrabar stops, which are stops that occur within a day, were approximate and occurred every 15 minutes at the venue, or exchange. Synthetic open and end accounting points allowed for same-day exits, and the stop was triggered first when both conditions were touched. The correct returns were calculated by dividing the profit and loss by the entry value plus entry fees, which is a way to account for the cost of trading. https://runway.adityaperswal.workers.dev/data/stock-bars