Notes

A trading fund manager analyzed FEAM, a symbol representing a stock, and found the following information: it has 20,000 possible paths, with 20 trades per path, and an allocation of 0.12. The terminal percentage values at the 5th, 50th, and 95th percentiles are -35.551515536775554, -34.27709178581574, and -33.01403715821915, respectively. The terminal loss percentage is 100, and the maximum drawdown percentage at the 95th percentile is 35.551515536775554. The gap stress fraction is 0.5117755886214443, and the size ceiling is 58.619443105541954. A quarter probe of 14.654860776385489 was also calculated, with an actual size of 0. This data is from a training trade empirical distribution, which means it is based on past trades and not on current live odds. A scenario with a 2 times worst negative opening gap stress plus a stop and a 50% cushion was not assigned a probability. The BTDR history is limited to the operating company. The ceilings were calculated before considering Kelly, current entry, and whole-share constraints, and the actual size is 0. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A trading analysis of BTDR shows the following results: the symbol is BTDR, with 20,000 paths and 20 trades per path. The allocation is 0.12. The terminal percentage values are -6.67127077928493 for the 5th percentile, 26.65385844252143 for the 50th percentile, and 73.15047050056343 for the 95th percentile. The terminal loss percentage is 10.345. The maximum drawdown percentage for the 95th percentile is 17.82049199841763. The gap stress fraction is 0.5268518985983547. The size ceiling is 56.941998462589744. The quarter probe is 14.235499615647436. The actual size is 0. This data is from a training trade empirical distribution, which means it is based on past trade data and not on current live odds. A scenario with a 2 times worst negative opening gap stress plus a stop and a 50% cushion is not assigned a probability. The BTDR history is limited to the operating company. The ceilings are before Kelly, which refers to a formula for bet sizing, and current entry and whole-share constraints. The actual size is 0. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following data line for OCC R91902: it has 20000 conditional paths and a separate gap stress. The data includes 20 trades per path, an allocation of 0.12, and terminal percentage values of -17.20623648966911, -7.538724725724805, and 5.7196771334997685 for p5, p50, and p95 respectively. The terminal loss percentage is 83.735, and the p95 maximum drawdown percentage is 18.09468157388593. The gap stress fraction is 0.617411918804197, and the size ceiling is 48.589926896947475. A quarter probe of 12.147481724236869 was noted, with an actual size of 0. This data is from a training trade empirical distribution, which means it is not based on live odds, and uses a scenario with a 2 times worst negative opening gap stress plus a stop and a 50 percent cushion, but this scenario does not have an assigned probability. The BTDR history is limited to the operating company, and ceilings are considered before Kelly, current entry, and whole-share constraints, with an actual size of 0. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A trading analysis for the symbol GLW shows the following results: it considered 20,000 paths, with 20 trades per path, and an allocation of 0.12. The terminal percentage values were -5.668621742622865, 0.5420426018418079, and 8.103012585405457 for the 5th, 50th, and 95th percentiles, respectively. The terminal loss percentage was 44.95, and the maximum drawdown percentage at the 95th percentile was 6.926446145148253. The gap stress fraction was 0.3769214911825876, and the size ceiling was 79.59217158426091. A quarter probe of 19.898042896065228 was also calculated, with an actual size of 0. This data is from a training trade empirical distribution, which means it is not based on live odds. A scenario with a 2 times worst negative opening gap stress plus a stop, and a 50% cushion, was not assigned a probability. The BTDR history is limited to the operating company. The ceilings were determined before considering Kelly, current entry, and whole-share constraints, and the actual size is 0. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following trade statistics for the symbol MU: the period is holdout, the number of trades is 18, the mean percentage is 2.416842037618298, and the mean confidence interval is between -4.346967701541617 and 9.467591961255954. The average win percentage is 17.940737245034864 and the average loss percentage is -10.002274128314955. The half Kelly risk bank is 0.06735626314038914. This is based on a numpy seed of 91902 and 20000 IID resamples. The confidence interval estimates the mean, not future trade bounds. Chronological regime or clustering can invalidate these estimates. The half Kelly average payoff is an approximation, not a notional permission. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following trade statistics for the symbol MU: the period is train, the number of trades is 52, the mean percentage is 0.7880639366326176, the mean confidence interval is between -2.268432794598495 and 4.111712073594872, the average win percentage is 17.02694800887532, the average loss percentage is -7.099394041313839, and the half Kelly risk bank is 0.023141667438634245. This is based on a numpy seed of 91902 and 20000 independent and identically distributed resamples. The confidence interval estimates the mean, not the future trade bounds. The half Kelly average payoff is an approximation, not a notional permission. Note that chronological regime or clustering can invalidate the results. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following trade statistics for FCEL: the symbol is FCEL, the period is holdout, and the number of trades is 14. The average percentage change is -5.838426244031591, with a 95% confidence interval of -16.60373687953101 to 6.512750435163009. The average win percentage is 35.52084476750601 and the average loss percentage is -17.118227428996395. The half Kelly risk bank is 0. This is based on a numpy seed of 91902 and 20000 IID resamples. The confidence interval estimates the mean, not future trade bounds, and chronological regime or clustering can invalidate the results. The half Kelly average payoff is an approximation, not a notional permission. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A trade statistics report for the symbol FCEL shows the following results for the training period: the mean percentage change is 2.244260590879341, with a 95% confidence interval of -5.5899994795508015 to 10.73279954401375. The average win percentage is 43.65210258603539 and the average loss percentage is -15.322702679792918. The half Kelly risk fraction, a measure of optimal bet size, is 0.025706214110260264. This report is based on 47 data points and 20000 independent and identically distributed resamples, with a numpy seed of 91902. The confidence interval estimates the mean, not the bounds of future trades. Additionally, chronological regime or clustering can invalidate these estimates. The half Kelly fraction is an average payoff approximation, not a notional permission. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following trade statistics for FEAM: the symbol is FEAM, the period is holdout, and there are 9 trades. The average percentage change is -2.2498267093586954, with a 95% confidence interval of -21.236784501130998 to 22.705511844113623. The average win percentage is 60.04159246982594 and the average loss percentage is -20.047375046268595. The half Kelly risk bank is 0. This is based on 20000 IID resamples with a numpy seed of 91902. The confidence interval estimates the mean, not future trade bounds. Chronological regime or clustering can invalidate these estimates. The half Kelly average payoff is an approximation, not a notional permission. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following trade statistics for FEAM: the symbol is FEAM, the period is train, and the number of trades is 7. The mean percentage change is -17.30549672205359, with a 95% confidence interval of -18.907778249682373 to -15.781188943407745. The average win percentage is 0, and the average loss percentage is -17.30549672205359. The half Kelly risk bank is 0. This data is based on 20000 IID resamples, using a numpy seed of 91902. The confidence interval estimates the mean, not the bounds of future trades. Chronological regime or clustering can invalidate these estimates. The half Kelly average payoff is an approximation, not a notional permission. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following trade statistics for BTDR: the symbol is BTDR, the period is holdout, and there are 14 data points. The average percentage change is -0.40434205206053164, with a 95% confidence interval of -14.031106948876515 to 15.178161241236918. The average win percentage is 43.31722160771177 and the average loss percentage is -17.892967515969456. The half Kelly risk, which is a measure of bet size, is 0. This data is based on 20,000 independent and identically distributed resamples, with a numpy seed of 91902. The confidence interval estimates the mean, not the bounds of future trades. Chronological regime or clustering can invalidate these estimates. The half Kelly average payoff is an approximation, not a notional permission. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A data scan found the following trade statistics for BTDR: the symbol is BTDR, the period is train, and the number of trades is 5. The average percentage change is 10.708362240385808. The average win percentage is 52.85996883428338 and the average loss percentage is -17.392708822212573. A statistical method called Half Kelly estimates the average payoff risk at 0.10128990308296104. This data is based on 20000 resamples, with a mean confidence interval of -17.759574441388644 to 41.56172441496322. Note that this estimates the mean, not the bounds of future trades, and chronological regime or clustering can affect the results. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following trade statistics for OCC: the symbol is OCC, the period is holdout, and the number of trades is 14. The mean percentage change is 5.339115579085075, with a 95% confidence interval of -9.82350697979137 to 21.831921836780754. The average win percentage is 44.384995079688686 and the average loss percentage is -16.353039699028045. The half Kelly risk bank is 0.06014550153153385. This data is based on 20000 IID resamples with a numpy seed of 91902. The confidence interval estimates the mean, not future trade bounds. Chronological regime or clustering can invalidate these estimates. The half Kelly average payoff is an approximation, not a notional permission. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following trade statistics for OCC: the symbol is OCC, the period is train, and the number of trades is 46. The mean percentage change is -2.996345515577651, with a 95% confidence interval of -6.775329160946324 to 1.1850289994991061. The average win percentage is 19.99288093748876 and the average loss percentage is -10.221530972255664. The half Kelly risk bank is 0. This data is based on 20,000 independent and identically distributed resamples, with a numpy seed of 91902. The confidence interval estimates the mean, not future trade bounds, and chronological regime or clustering can invalidate the results. The half Kelly average payoff is an approximation, not a notional permission. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following trade statistics for the symbol GLW: the period is holdout, the number of trades is 16, the mean percentage is 4.556873998416445, the mean confidence interval is between 0.09015016796399877 and 9.33522711903153, the average win percentage is 11.999359864272217, and the average loss percentage is -5.012036400540977. The half Kelly risk bank is 0.18987987900856357. This is based on a numpy seed of 91902 and 20000 independent and identically distributed resamples. The confidence interval estimates the mean, not the future trade bounds. Chronological regime or clustering can invalidate these estimates. The half Kelly average payoff is an approximation, not a notional permission. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following trade statistics for GLW: the symbol is GLW, the period is train, the number of trades is 39, the mean percentage change is 0.321682063692746, the mean confidence interval at 95 percent is between -2.0036746476864984 and 2.869515758639974, the average win percentage is 10.219912817224792, the average loss percentage is -4.627433313073277, and the half Kelly risk bank is 0.01573800429836239. This is based on 20000 independent and identically distributed resamples with a numpy seed of 91902. The confidence interval estimates the mean, not the bounds of future trades. The half Kelly fraction is an average payoff approximation, not a notional permission, and chronological regime or clustering can invalidate the results. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following data lines for the MU R91902 six-cell costed parameter sweep and stress: the data is divided into sections including train, holdout, and 2026, which refer to different time periods, with train being the training period, holdout being the holdout period, and 2026 being the year 2026. The columns represent the following: period, which is the time frame, L, which is a parameter, ATRstop, which is a type of stop-loss order based on average true range, return%, which is the percentage return, DD%, which is the maximum drawdown percentage, win%, which is the percentage of winning trades, N, which is the number of trades, mean%, which is the mean return, and targets. The data includes the following entries: train with 15, 2, 59.54808, 55.43691, 35.84906, 53, 1.61104, 15, holdout with 15, 2, 34.85749, 64.49051, 42.10526, 19, 2.6644, 6, 2026 with 15, 2, 35.54875, 39.70405, 50, 8, 5.68191, 3, and so on. The data also includes stress tests, which are simulations of extreme market conditions, with double the usual stress. The fees are 5 basis points per side, and slippage is based on GLW/MU10, OCC/FEAM50, and BTDR/FCEL25. There is no best cell selection, meaning that no single combination of parameters is chosen as the best. The train period is from 2016 to 2023, the holdout period is from 2024 to 2025, and the 2026 period is a known period. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following data: this is a list of results from a test of a trading strategy for the stock FCEL. The test used different parameters, including the length of the trading period, the type of stop-loss order, which is an order to sell a stock when it falls to a certain price, and the amount of risk taken. The results are divided into three groups: train, holdout, and 2026. The train group used data from 2016 to 2023, the holdout group used data from 2024 to 2025, and the 2026 group used data from 2026. The results include the return on investment, the maximum drawdown, which is the largest decline in value, the percentage of winning trades, the number of trades, the average return per trade, and the number of targets hit. The test also included fees of 5 basis points per trade and slippage, which is the difference between the expected price of a trade and the actual price. The test used a long-only strategy, which means it only bought stocks and did not sell short. The results are as follows: [[ https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following data line: this is a list of results from a costed parameter sweep and stress test for the FEAM R91902 six-cell model. The list includes the following columns: period, L, ATR stop, return percentage, drawdown percentage, win percentage, number of trades, mean percentage, and targets. The periods tested were train, holdout, and 2026. The train period used data from 2016 to 2023, the holdout period used data from 2024 to 2025, and the 2026 period was a known period. The fees were 5 basis points per side, and slippage was based on the GLW and MU10, OCC and FEAM50, and BTDR and FCEL25 models. The stress test doubled the fees. There was no best cell selection. The results were as follows: [[ https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A data scan found the following output: it is a list of results from a six-cell costed parameter sweep and stress test for BTDR. The list includes 18 sets of data, each with the following columns: period, L, ATR stop, return percentage, drawdown percentage, win percentage, number of trades, mean percentage, and targets. ATR stop refers to a type of stop-loss order that uses average true range. The periods tested include train, holdout, and 2026. The train period used data from 2016 to 2023, the holdout period used data from 2024 to 2025, and the 2026 period used known data. The test assumed fees of 5 basis points per side, slippage based on GLW, MU, OCC, FEAM, and BTDR, and FCEL. The stress test doubled the parameters. There was no best cell selection made. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the headline 'OCC R91902 six-cell costed parameter sweep and stress'. The data is presented in a table format with columns representing period, L, ATR stop, return percentage, drawdown percentage, win percentage, number of trades, mean percentage, and targets. ATR stop refers to a trading strategy that uses the average true range to set stop-loss levels. The periods include train, holdout, and 2026, with train using data from 2016 to 2023, holdout using data from 2024 to 2025, and 2026 being a known period. The fees are 5 basis points per side, and slippage is based on GLW and MU10, with OCC and FEAM50, and BTDR and FCEL25. The stress test doubles the fees. There is no best cell selection. The data includes the following values: train with 15, 2, -72.74729, 82.65606, 27.08333, 48, -1.66879, 9, holdout with 15, 2, 42.93596, 48.80173, 35.71429, 14, 6.92045, 5, and 2026 with 15, 2, -31.7389, 59.03663, 22.22222, 9, 0.15457, 2, among others. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the following data: this is a list of results from a six-cell costed parameter sweep and stress test for the GLW R91902 automated trading fund manager. The list includes the following information for each cell: period, which is the time frame of the test, L, which is a parameter, ATRstop, which is a type of stop-loss order based on average true range, return percentage, drawdown percentage, win percentage, number of trades, mean percentage return, and number of targets. The periods tested were train, holdout, and 2026. The train period used data from 2016 to 2023, the holdout period used data from 2024 to 2025, and the 2026 period used known data for that year. The fees for the trades were 5 basis points per side, and slippage was based on the performance of the GLW, MU, OCC, FEAM, BTDR, and FCEL stocks. The stress test doubled the parameters. There was no best cell selection made. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the data line for FIL-USD. The symbol is FIL-USD, from the source https://query1.finance.yahoo.com/v8/finance/chart/FIL-USD. The data is as of 1789783784, in USD currency. The last bar epoch is 1789603200, based on Yahoo adjusted close, excluding September 19 UTC. The number of data points is 364, with a close of 0.8400030136108398. The return over 21 days is 19.31216568383578 percent, and over 63 days is 9.273232705908407 percent. The simple moving average over 200 days is 0.8416724014282226. The price is not above the 200-day simple moving average, which is false. The prior 20-day value is 0.952547013759613, and there is no breakout, which is false. This is from Purposivepanel, using native currency, with adjusted closes as a diagnostic, assuming no foreign exchange or venue eligibility. The crypto data excludes unfinished September 19 UTC, and this screen is not for trading rule validation. https://query1.finance.yahoo.com/v8/finance/chart/FIL-USD

A news scan found the headline is not available, but a data line shows information about the LINK-USD symbol. The data is from the website https://query1.finance.yahoo.com/v8/finance/chart/LINK-USD, which is a finance website that provides stock and cryptocurrency information. The data is current as of a certain time, represented by the number 1789783802, which is a way to measure time in seconds. The currency being used is the United States dollar, or USD for short, which is a type of money. The last time the data was updated was at a time represented by the number 1789603200, which is also measured in seconds. The basis for the data is the adjusted close prices from Yahoo, which means the prices have been changed to account for things like stock splits, and it excludes prices from September 19, UTC, which is a time zone. The number of data points is 364, which is the number of days the data covers. The last closing price was 11.390055656433105 dollars. The return on investment over the past 21 days was -4.64708326796619 percent, which is a loss, and the return over the past 63 days was 36.70332626161983 percent, which is a gain. The simple moving average, or SMA, over the past 200 days was 9.172092561721803 dollars, which is a way to calculate the average price over a long period of time. The price is currently above the 200-day SMA, which is a good sign for investors. The price 20 days ago was 13.223810195922852 dollars. There was no breakout, which means the price did not suddenly increase or decrease. This data is from a system called Purposivepanel, which uses the native currency, or the currency that the investment is normally traded in, and it uses adjusted closes, which are prices that have been changed to account for things like stock splits, as a diagnostic tool. The system assumes there are no issues with foreign exchange or venue eligibility, which are things that can affect the price of an investment. The system also excludes any unfinished data from September 19, UTC, and it is not used to validate trading rules, which are rules that determine when to buy or sell an investment. https://query1.finance.yahoo.com/v8/finance/chart/LINK-USD

A news scan found the headline is not available, but a data line shows the SOL-USD overseas and crypto completed daily screen. The symbol is SOL-USD, which is a type of cryptocurrency, and the source of the data is https://query1.finance.yahoo.com/v8/finance/chart/SOL-USD. The data is as of a specific time, 1789783815, and the currency is USD, which stands for United States Dollar. The last bar epoch, a term that refers to a specific point in time, is 1789603200. The basis of the data is the Yahoo adjusted close, which means it is based on the closing prices adjusted by Yahoo, and it excludes September 19 UTC, which is a specific date and time zone. The number of data points, referred to as n, is 364. The close price is 101.6033935546875, and the return over 21 days, referred to as ret21, is -6.963623319957057, which is a percentage. The return over 63 days, referred to as ret63, is 34.98170696108514, which is also a percentage. The simple moving average over 200 days, referred to as sma200, is 83.41287990570068. The price is above the 200-day moving average, which is indicated by above200 being true. The prior 20-day price is 106.4476318359375, and there is no breakout, which means the price has not suddenly increased, as indicated by breakout being false. This data is from a purposive panel, which is a type of data analysis, and it is based on the native currency, which is the original currency of the data. The adjusted closes are used for diagnostic purposes, and it is assumed that there is no foreign exchange or venue eligibility, which refers to the ability to trade in a specific market. The crypto data excludes any unfinished data from September 19 UTC, and the screen is not used for trading rule validation, which means it is not used to check if trades are allowed. https://query1.finance.yahoo.com/v8/finance/chart/SOL-USD