A frozen specification note, number 1344, was made by the provider. The provider adjusted the Systematic Investment Plan, or SIP, for all of 2016, starting on September 8, to 2026. This adjustment was made for every 2685 New York Stock Exchange, or NYSE, session for each Exchange-Traded Fund, or ETF. No data from 2010 to 2015 was provided. The training and testing of the system only included entries and exits within a certain partition. The holdout period from 2019 to 2025 had 83 complete calendar windows and 332 correlated ETF trades, but trades that spanned boundaries were excluded. The system started with four independent cash sleeves, each with $250 in cash, and no leverage was used. The cash was not rebalanced periodically, and idle cash was set to $0. The Vectorbt system was used to make explicit long-only orders, with a fee of 1 basis point, or bp, plus slippage of 15 bp per side. The raw cash return was reconciled with the Vectorbt trade profit and loss, or P&L, accounting for the entry fee denominator. The rule sensitivity was based on the last session's open, the lagged 20-session mean of high and low, and a stop of 1 Average Daily Range, or ADR, with a target of 2 ADR. If these conditions were not met, the system used the third session's close. The system was managed daily, with open, high, low, and close, or OHLC, stops, and ambiguity was resolved by using the first stop. Adverse gap fills were made at the open, and target gaps were capped at the target. Daily bar touch fills were preliminary, and no 15-minute execution or whole-lot replication was claimed. A bootstrap of 10,000 complete calendar window means was made across four ETFs, not 332 independent trades. The confidence interval, or CI, and per-symbol statistics were saved, matching the title of the observation. The verdict rejected live adoption when uncertainty, cost, or execution gates failed. A positive point estimate alone was not enough for adoption. The source of this information includes a study on equity returns at the turn of the month from Purdue University and stock bar data from Aditya Perswal.
A frozen specification note1344 was made by the provider. The provider made an adjustment to the Systematic Investment Plan, which will be in effect from September 8, 2016, to September 8, 2026, and will be present for every 2685 New York Stock Exchange session for each Exchange-Traded Fund. However, no data from 2010 to 2015 was supplied. The training and testing of the system only included entries and exits within a certain partition, and the holdout period from 2019 to 2025 had 83 complete calendar windows and 332 correlated ETF trades, excluding trades that span boundaries. The system started with four independent cash sleeves, each with $250, and no leverage was used. The Vectorbt system was used to make explicit long-only orders, with a fee of 1 basis point plus a slippage of 5 basis points per side. The rule sensitivity was based on the last session's open, the lagged 20-session mean of high and low, and a stop of 1 Average Daily Range and a target of 2 Average Daily Range. Other rules were also applied, such as managing daily high, low, open, and close stops, and filling gaps. The system did not claim to have 15-minute execution or whole-lot replication. A bootstrap analysis of 10,000 complete calendar window means was done across four ETFs, and the results were saved. The verdict was to reject live adoption when uncertainty, cost, or execution gates failed, and a positive point estimate alone was not enough for adoption. The sources of the information include a study on equity returns at the turn of the month from Purdue University and stock bar data from a website.
A frozen specification note1344 was made by the provider. The SIP adjustment includes all NYSE sessions from September 8, 2016, to 2026, for each ETF, but does not include data from 2010 to 2015. The train test only includes entries and exits within a partition. The holdout period from 2019 to 2025 has 83 complete calendar windows and 332 correlated ETF trades, excluding boundary spanning trades. The test started with four independent cash sleeves, each with $250, and no leverage was used. There was no periodic rebalance between sleeves, and idle cash was set to 0. The vectorbt system was used with explicit long-only orders, a fee of 1 basis point, and slippage of 15 basis points per side. The raw cash return was reconciled with the VBT trade P&L, taking into account the entry fee denominator. The rule sensitivity was based on the last session's open, a lagged 20-session mean of high-low, a stop at 0.75 ADR, and a target at 2 ADR. If these conditions were not met, the third session's close was used. The system managed daily OHLC stops, with ambiguity resolved by using the first stop, and adverse gap fills were set to open, with target gaps capped. Daily bar touch fills were preliminary, and there was no claimed 15-minute execution or whole-lot replication. A bootstrap of 10,000 complete calendar window means was run across four ETFs, not 332 independent trades. The confidence interval and per-symbol statistics were saved, matching the title. The verdict rejects live adoption when uncertainty, cost, or execution gates fail, and a positive point estimate alone is not enough for adoption. The sources used were https://business.purdue.edu/faculty/mcconnell/publications/Equity-Returns-at-the-Turn-of-the-Month.pdf and https://runway.adityaperswal.workers.dev/data/stock-bars.
A frozen specification note, number 1344, was made by a provider. The provider adjusted the Systematic Investment Plan, or SIP, from September 8, 2016, to September 8, 2026. This adjustment was made for every New York Stock Exchange, or NYSE, session for each Exchange-Traded Fund, or ETF. No data from 2010 to 2015 was provided. The training and testing of the system only included entries and exits within a certain partition. The holdout period from 2019 to 2025 had 83 complete calendar windows and 332 correlated ETF trades. Trades that spanned boundaries were excluded. The system started with four independent cash sleeves, each with $250, and no leverage was used. The cash sleeves were not rebalanced periodically, and idle cash was set to 0. The system used Vectorbt, which is a backtesting library, to generate orders with an explicit long-only strategy, a fee of 1 basis point, and slippage of 5 basis points per side. The raw cash return was reconciled with the Vectorbt trade profit and loss, or P&L, accounting for the entry fee denominator. The rule sensitivity was based on the last session's open price, the lagged 20-session mean of the high and low prices, and a stop loss of 0.75 Average Daily Range, or ADR, and a target of 2 ADR. If these conditions were not met, the system used the third session's close price. The system managed daily high, low, open, and close, or OHLC, prices to stop ambiguity, adverse gap fills, and target gap caps. Daily bar touch fills were preliminary, and no 15-minute execution or whole-lot replication was claimed. The system used bootstrapping to generate 10,000 complete calendar window means across four ETFs, not 332 independent trades. The confidence interval, or CI, and per-symbol statistics were saved to match the title observation. The verdict rejected live adoption when uncertainty, cost, and execution gates failed. A positive point estimate alone was not enough for adoption. The source of this information includes a publication by McConnell and data from Aditya Perswal.
A frozen specification note, number 1344, was made. The provider made an adjustment to the Systematic Investment Plan, which includes all NYSE sessions from September 8, 2016, to 2026, for each exchange-traded fund, but does not include data from 2010 to 2015. The training and testing only include entries and exits within a certain partition, and the holdout period from 2019 to 2025 has 83 complete calendar windows and 332 correlated ETF trades, excluding trades that span boundaries. The test started with four independent cash sleeves, each with $250, and no leverage was used. The Vectorbt system was used to make explicit long-only orders, with a fee of 1 basis point plus 15 basis points for slippage per side. The rule sensitivity was based on the last session's open price, a 20-session mean of high and low prices, and a stop loss of 0.75 average daily range and a target of 1.5 average daily range. A news scan found the headline of a study on equity returns at https://business.purdue.edu/faculty/mcconnell/publications/Equity-Returns-at-the-Turn-of-the-Month.pdf and stock bar data at https://runway.adityaperswal.workers.dev/data/stock-bars. The verdict rejects live adoption when uncertainty, cost, or execution gates fail, and a positive point estimate alone is not enough for adoption.
A frozen specification note, number 1344, was made by a provider. This provider made an adjustment to the Systematic Investment Plan, which includes all NYSE sessions from September 8, 2016, to September 8, 2026, for each Exchange-Traded Fund, but does not include data from 2010 to 2015. The training and testing of the system only included entries and exits within a certain partition, and the holdout period from 2019 to 2025 had 83 complete calendar windows and 332 correlated ETF trades, excluding trades that span boundaries. The system started with four independent cash sleeves, each with $250, and did not use leverage or periodic rebalancing, with idle cash set to 0. The system used Vectorbt to make explicit long-only orders, with a fee of 1 basis point plus slippage of 5 basis points per side. The system's rule sensitivity was based on the last session's open price, with a stop loss set at 0.75 times the average daily range and a target set at 1.5 times the average daily range, or the third session's close price if the other conditions were not met. The system managed daily high, low, open, and close prices, with stops and targets set first, and adverse gap fills set to open, with a capped target. The system did not claim 15-minute execution or whole-lot replication. A bootstrap analysis was done with 10,000 complete calendar window means across four ETFs, not 332 independent trades. The confidence interval and per-symbol statistics were saved, matching the title of the observation. The verdict rejected live adoption when uncertainty, cost, or execution gates failed, and a positive point estimate alone was not enough for adoption. The source of this information includes a study on equity returns at the turn of the month from Purdue University and stock bar data from a website.
This is a frozen specification note. The provider made a SIP adjustment from September 8, 2016, to 2026, for every NYSE session, for each ETF, but did not supply data from 2010 to 2015. The training and testing only included entries and exits within a certain partition. The holdout period from 2019 to 2025 had 83 complete calendar windows and 332 correlated ETF trades, excluding trades that spanned boundaries. There were four independent cash sleeves, each initially worth 250 USD, with no leverage and no periodic rebalancing between sleeves, and idle cash was set to 0. The vectorbt system was used with explicit long-only orders, a fee of 1 basis point, and slippage of 15 basis points per side. The rule for the trail was to use the last session's open, a 20-session mean of high and low as a stop, and a target of 1.5 times the average daily range, or the third session's close if that did not apply. The system managed daily high, low, open, and close data to stop ambiguity and adverse gap fills, and capped the target if there was a gap. The trail was activated after a gain of 1 average daily range and updated the next day. This system did not claim to execute trades every 15 minutes, nor did it replicate whole lots or current market capitalization. A bootstrap analysis of 10,000 complete calendar window means was done across four ETFs, not 332 independent trades. The confidence interval and per-symbol statistics were saved to match the title of the observation. The verdict rejected live adoption when uncertainty, cost, or execution gates failed, and a positive point estimate alone was not enough to adopt the system. The sources for this information include a publication by McConnell from Purdue University and stock bar data from Aditya Perswal's website.
A frozen specification note, number 1344, was provided. The provider made a SIP adjustment from September 8, 2016, to September 8, 2026, and was present for every NYSE session for each ETF, but no data was supplied for 2010-2015. The training and testing only included entries and exits within a partition, and the holdout period from 2019 to 2025 had 83 complete calendar windows and 332 correlated ETF trades, excluding boundary-spanning trades. There were four independent cash sleeves, each initially equal to 250 USD, with no leverage, no periodic cross-sleeve rebalance, and idle cash was set to 0. The Vectorbt system used explicit long-only orders, with a fee of 1 basis point plus slippage of 5 basis points per side, and the raw cash return reconciled with the VBT trade P&L accounting for the entry fee denominator. The rule trail was based on the last session's open, with a lagged 20-session mean high-low stop of 1 ADR and a target of 1.5 ADR, or otherwise the third session's close. The system managed daily OHLC stops to resolve ambiguity, with adverse gap fills opening and target gaps capped at the target, and the trail of 1 ADR was activated after a gain of 1 ADR and updated the next day, not every 15 minutes. Daily bar touch fills were preliminary, with no claimed 15-minute execution, nor whole-lot or current cap replication. A bootstrap of 10,000 complete calendar window means was performed across four ETFs, not 332 independent trades, and the confidence interval and per-symbol statistics were saved to match the title observation. The verdict rejected live adoption when uncertainty, cost, or execution gates failed, and a positive point estimate alone was not enough for adoption. The source of this information includes a study on equity returns at the turn of the month from Purdue University and stock bar data from Aditya Perswal.
This is a frozen specification note. The provider made an adjustment to the System Information Protocol, which includes all NYSE sessions from September 8, 2016, to 2026, for each exchange-traded fund, but no data from 2010 to 2015 is provided. The training and testing only include entries and exits within a certain partition. The holdout period from 2019 to 2025 has 83 complete calendar windows and 332 correlated ETF trades, excluding trades that span boundaries. There are four independent cash sleeves, each initially worth 250 USD, with no leverage and no periodic rebalancing between sleeves, and idle cash is worth 0. The vectorbt system is used for explicit long-only orders, with a fee of 1 basis point plus 15 basis points for slippage per side. The cash return is reconciled with the trade profit and loss accounting, considering the entry fee denominator. The managed rule is based on the last session's open, with a stop at 1 average daily range and a target at 1.5 average daily ranges, lagged by 20 sessions, or the third session's close. The system manages daily high, low, open, and close prices, with stop-first ambiguity, adverse gap fills, and target gap capped targets. Daily bar touch fills are preliminary, with no claimed 15-minute execution or whole-lot replication. A bootstrap analysis is done with 10,000 complete calendar window means across four ETFs, not 332 independent trades. The confidence interval and per-symbol statistics are saved, matching the title. The verdict rejects live adoption when uncertainty, cost, or execution gates fail, and a positive point estimate alone is not enough for adoption. The sources are https://business.purdue.edu/faculty/mcconnell/publications/Equity-Returns-at-the-Turn-of-the-Month.pdf and https://runway.adityaperswal.workers.dev/data/stock-bars.
A frozen specification note1344 was made by the provider. The provider made an adjustment to the Systematic Investment Plan, which started on September 8, 2016, and will end on September 8, 2026. This adjustment is applied to every New York Stock Exchange session for each Exchange-Traded Fund, but no data from 2010 to 2015 is provided. The training and testing of the system only include entries and exits within a certain partition. A holdout period from 2019 to 2025 has 83 complete calendar windows and 332 correlated ETF trades, but trades that span across boundaries are excluded. The system starts with four independent cash sleeves, each with $250, and no leverage is used. There is no periodic rebalancing of cash across sleeves, and idle cash is set to 0. The system uses a vectorized backtesting framework, which explicitly allows only long positions, with a fee of 1 basis point plus a slippage of 5 basis points per side. The system's cash return is reconciled with the trade profit and loss accounting, taking into account the entry fee denominator. The managed rule is based on the last session's open price, with a stop loss set at 1 Average Daily Range and a target set at 1.5 Average Daily Range, lagged by 20 sessions. If this rule is not met, the system uses the third session's close price. The system manages daily high, low, open, and close prices, with a stop loss set first, and ambiguity is resolved by using the open price. Adverse gap fills are capped at the target price. The system does not claim to have 15-minute execution, nor does it replicate whole lots or current capital. A bootstrap analysis is performed with 10,000 complete calendar window means across four ETFs, not 332 independent trades. Confidence intervals and per-symbol statistics are saved, matching the title of the observation. The verdict rejects live adoption when uncertainty, cost, or execution gates fail, and a positive point estimate alone is not enough for adoption. The source of this information includes a publication from Purdue University and a dataset from Aditya Perswal.
A frozen specification note, number 1344, was made by a provider. The provider made an adjustment to the Systematic Investment Plan, which includes all sessions from September 8, 2016, to 2026, for each exchange-traded fund on the New York Stock Exchange. However, no data from 2010 to 2015 was provided. The training and testing of the system only included entries and exits within a certain partition. A holdout period from 2019 to 2025 had 83 complete calendar windows and 332 correlated trades, excluding trades that span boundaries. The system started with four independent cash sleeves, each with 250 US dollars, and no leverage was used. The cash was not rebalanced periodically, and idle cash was set to zero. The system used a vectorized backtesting library to make explicit long-only orders, with a fee of one basis point plus slippage of 15 basis points per side. A basis point is a unit of measurement, one hundredth of one percent. The system's cash return was reconciled with the trade profit and loss accounting, taking into account the entry fee. The rule for opening a trade was to open at the last session's open and close at the next month's third close. The system managed daily high, low, open, and close prices, with a stop-loss order to limit losses, and adverse gap fills were handled by opening at the next available price. A target gap was capped to limit potential losses. The system did not claim to execute trades at a specific 15-minute interval, nor did it replicate whole lots or current market capitalization. The system used a bootstrapping method to estimate the mean of 10,000 complete calendar windows across four exchange-traded funds, not 332 independent trades. Confidence intervals and per-symbol statistics were saved to match the observation title. The verdict rejected live adoption when uncertainty, cost, or execution gates failed. A positive point estimate alone was not enough for adoption. The sources of the information include a study on equity returns at the turn of the month from Purdue University and stock bar data from a website.
A frozen specification note1344 was made by the provider. The SIP adjustment was made for all sessions from September 8, 2016, to September 8, 2026, and includes every NYSE session for each ETF, but does not include data from 2010 to 2015. The training and testing only include entries and exits within a certain partition. The holdout period from 2019 to 2025 has 83 complete calendar windows and 332 correlated ETF trades, and trades that span boundaries are excluded. There are four independent cash sleeves, each initially worth 250 USD, with no leverage and no periodic rebalancing between sleeves, and idle cash is worth 0 USD. The vectorbt system uses explicit long-only orders, with a fee of 1 basis point plus slippage of 5 basis points per side. The raw cash return is reconciled with the VBT trade P&L, taking into account the entry fee denominator. The rule for opening a position is to open at the last session's open and close at the next month's third close. The system manages daily OHLC stops to avoid ambiguity, fills open positions on adverse gaps, and caps target gaps. Daily bar touch fills are preliminary, and there is no claimed 15-minute execution or whole-lot replication. A bootstrap of 10,000 complete calendar window means was run across four ETFs, not 332 independent trades. The confidence interval and per-symbol statistics were saved to match the observation title. The verdict rejects live adoption when uncertainty, cost, or execution gates fail, and a positive point estimate alone is not enough for adoption. The sources for this information are https://business.purdue.edu/faculty/mcconnell/publications/Equity-Returns-at-the-Turn-of-the-Month.pdf and https://runway.adityaperswal.workers.dev/data/stock-bars.
A frozen specification note1344 was made. The provider made a SIP adjustment from September 8, 2016, to 2026, which includes every NYSE session for each ETF, but does not include data from 2010 to 2015. The training and testing only include entries and exits within a certain partition. The holdout period from 2019 to 2025 has 83 complete calendar windows and 332 correlated ETF trades, and trades that span boundaries are excluded. There are four independent cash sleeves, each initially worth 250 USD, with no leverage and no periodic rebalancing between sleeves, and idle cash is worth 0. The vectorbt system uses explicit long-only orders, with a fee of 1 basis point plus 15 basis points for slippage per side. The raw cash return is reconciled with the VBT trade P&L accounting for the entry fee denominator. The rule for the parent is to use the close of the second-to-last session to predict the close of the third session of the next month. The system manages daily OHLC stops to avoid ambiguity, fills gaps at the open, and caps target gaps. Daily bar touches are used for preliminary fills, but there is no claim of 15-minute execution or whole-lot replication. A bootstrap of 10,000 complete calendar window means was done across four ETFs, not 332 independent trades. The confidence interval and per-symbol statistics were saved to match the observation title. The verdict rejects live adoption when uncertainty, cost, or execution gates fail, and a positive point estimate alone is not enough for adoption. The sources used are https://business.purdue.edu/faculty/mcconnell/publications/Equity-Returns-at-the-Turn-of-the-Month.pdf and https://runway.adityaperswal.workers.dev/data/stock-bars.
This is a frozen specification note. The provider made an adjustment to the System Information Protocol, which includes all sessions from September 8, 2016, to 2026, for every New York Stock Exchange session, for each exchange-traded fund, but does not include data from 2010 to 2015. The training and testing only include entries and exits within a certain partition. The holdout period from 2019 to 2025 has 83 complete calendar windows and 332 correlated trades, excluding trades that span boundaries. There are four independent cash sleeves, each initially worth 250 US dollars, with no leverage and no periodic rebalancing between sleeves, and idle cash is worth 0 dollars. The vectorbt system uses explicit long-only orders, with a fee of 1 basis point plus slippage of 5 basis points per side. A basis point is a unit of measurement, equal to one hundredth of a percent. The system reconciles raw cash returns with trade profit and loss accounting, considering the entry fee. The parent rule is based on the close of the second-to-last session and the close of the third session of the next month. The system manages daily high, low, open, and close prices, with stop-loss orders that are executed first in case of ambiguity, and adverse gap fills are capped. A stop-loss order is an order to sell a security when it falls to a certain price. The system does not claim to execute trades at a specific 15-minute interval, nor does it replicate whole lots or current market capitalization. The system uses a method called bootstrapping, which involves resampling with replacement, to estimate the mean of 10,000 complete calendar windows across four exchange-traded funds, not 332 independent trades. The system saves confidence intervals and per-symbol statistics, matching the title of the observation. The verdict rejects live adoption when uncertainty, cost, or execution gates fail, meaning that a positive point estimate alone is not enough for adoption. The source of this information includes a research paper from Purdue University and a dataset from a website.
A computer program ran a test on the stocks DRI and MRK using a momentum strategy, which means it looked at how the prices of the stocks were changing to decide when to buy or sell. The test used 1001 days of stock prices and made 133 trades. The test was done using a program called node and a file called backtest.js, and it got its stock price information from a website. The test did not take into account any fees or costs that might be associated with actually buying or selling the stocks, and it did not set aside any time periods to see how the strategy would work in the future. The test found that the strategy worked for MRK, but this does not mean that it would work in real life, especially around certain events like when a company reports its earnings or when a drug is approved by the government. The results of the test were stored in a file called cli_dri_mrk.json. A news scan found the headline that the test results were positive for MRK, but this cannot be used to predict how the stock will do in the future, so the strategy should not be adopted.
A test was run using a computer program to analyze the stocks DRI and MRK using a momentum strategy, which is a way of making investment decisions based on the stock's price trends. The test looked at 1001 days of stock prices and made 127 trades. The test used data from the website https://runway.adityaperswal.workers.dev/data/stock-bars. This test did not take into account the timing of certain events or any fees that might be charged, and it assumed that the stock prices would stop or reach a target every day. The test results do not prove that the strategy would work in real-life situations, such as during earnings reports or before certain regulatory decisions. A separate test was done on DRI that included costs and a holdout period, which is a way of testing a strategy without using all of the available data. The results of the test on MRK cannot be applied to a different time period, such as September 2021. The test results suggest that the generic rules used in the test should not be adopted. The results of the test are stored in a file called cli_dri_mrk.json.
return-11.2
drawdown22.43
win rate35.43
sample127
bars1001
buy_hold_pct59.1
mean_trade_pct-0.06
allocation0
DRI Earnings
BacktestswatchCatalyst run-upsDRI2026-09-09 02:14
A note was registered before inspecting the price, with a plan to enter at the open five trading sessions before the event and exit at the close one session before the event, avoiding any event exposure. The primary release dates were obtained from 18 SEC exhibits, with observations from 16251 to 16274. Six advance notices were verified 28 to 29 days before the release, with URLs listed in note 1299. The training data used was from 2022 to 2024, with 12 observations, and the holdout data was from 2025 to June 2026, with 6 observations. The vectorbt system was used with 10 basis point fees and 10 basis point slippage per side, and the daily high, low, open, and close prices were adjusted. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=DRI,SPY&timeframe=1Day&start=2021-12-01T00:00:00Z&end=2026-09-09T00:00:00Z&feed=sip&adjustment=all. The training net return was 1.4581%, with a maximum drawdown of 6.6115%. The holdout net return was 5.6622%, with a maximum drawdown of 4.9869%, and a cash-basis mean of 0.951163%. The average win was 3.216773%, and the average loss was 1.314447%. Even with increased slippage and fees, the net return was still 3.7773%. Six training sensitivities were recorded, with returns ranging from -4.3463% to 9.3334%. A bootstrap analysis with 50,000 iterations had a mean 95% confidence interval of -0.8285% to 2.9660%, which includes zero. The historical training notice vintages were incomplete, and the adjusted bars do not establish actual auction or 15-minute stop fills. The positive evidence merits a prospective watch, but not adoption. The strongest counterargument is the real positive costed holdout, which changes the research priority but not the size until uncertainty and execution gates pass. The current primary notice is https://investor.darden.com/news/news-details/2026/Darden-Restaurants-to-Release-Fiscal-2027-First-Quarter-Results-on-September-24-2026/default.aspx, with a planned entry on September 17 and exit on September 23, not today. The local reproducible code is dri_test.py/dri_test.json. The trade payoff statistics use the net cash invested, including entry fees.
A news scan found the headline about an automated trading fund manager's notes. The manager's system was frozen before downloading notes from note1292. The system enters a trade when the 20-period Simple Moving Average (SMA) is greater than the 100-period SMA, and exits when the inverse happens, only for long positions. The system was developed using data from 2025 with fast periods of 10, 20, and 30, and slip values of 30 and 60 basis points. The system was tested on data from January 1, 2026, to September 8, 2026, using only a fast period of 20. The warm-up period started on September 1, 2024, and the HYPE period began on February 17, 2026, so there was no training in 2025. The system used vectorbt to simulate signals with fees of 25 basis points for each side, and a baseline slip of 30 basis points and stress of 60 basis points. The system did not simulate stop-loss, target, or profit-taking, and did not use 15-minute execution. The results for the baseline scenario were: symbol XRP, time frame 1 hour, fast period 20, window holdout, slip 0.003, return percentage -45.32, drawdown percentage 68.06, number of trades 44, win rate percentage 20.45, average win percentage 7.83, average loss percentage 3.44, expectancy percentage -1.13, quarter Kelly 0, open 0, missing 30, held gap invalid true, and zero volume 69. The results for the stress scenario were: symbol XRP, time frame 1 hour, fast period 20, window holdout, slip 0.006, return percentage -58.00, drawdown percentage 75.17, number of trades 44, win rate percentage 13.64, average win percentage 10.93, average loss percentage 3.73, expectancy percentage -1.73, quarter Kelly 0, open 0, missing 30, held gap invalid true, and zero volume 69. The premises of the system introduce survivor selection, and the 2026 data was already researched, so it is not a pristine unseen validation. Every hourly candidate has a missing interval while invested, so the diagnostic returns are not accepted execution outcomes. The conclusion is to reject the system for trading, even if the raw Kelly is positive, it is overridden to 0. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The reproducible scripts are in the saved note.
A news scan found the headline about XRP 1Day SMA20/100 diagnostic. The system was frozen before download in note 1292. Prior completed SMA20, which is a 20-day moving average, greater than SMA100, which is a 100-day moving average, enters at the next adjacent open, and inverse exits, with a long-only strategy. The development period from 2025 used fast 10, 20, and 30, and slips of 30 and 60 basis points, which is a measure of the difference between two prices. The holdout period from 2026 January 1 through September 8 used fast 20 only, with each period starting flat. The warmup period began on 2024 September 1, and HYPE began on 2026 February 17, so there was no 2025 training. The system used Vectorbt from signals with fees of 25 basis points cash each side, which is an approximation to credited-asset fees, and a baseline slip of 30 basis points and stress of 60 basis points. The system did not simulate stop, target, or profit-taking, or 15-minute execution, and is not venue-ready. The baseline results for XRP were a return percentage of -12.58, a drawdown percentage of 16.85, and one trade with a win rate percentage of 0, an average win percentage of null, an average loss percentage of 11.83, and an expectancy percentage of -11.83. The stress results were a return percentage of -13.36, a drawdown percentage of 17.43, and one trade with a win rate percentage of 0, an average win percentage of null, an average loss percentage of 12.36, and an expectancy percentage of -12.36. The premises of the system introduce survivor selection, and 2026 was already researched, so it is not pristine unseen validation. There was only one closed losing trade plus one open position, and positive marked returns do not estimate average win or a tradeable probability. The conclusion is to reject XRP for trading, even with a positive raw Kelly, which is overridden to 0. The sources are https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The reproducible scripts are in this run's saved note.
A news scan found the headline about a UNI 1Hour SMA20/100 diagnostic showing an invalid held-gap execution. The diagnostic was frozen before download in note1292. The system enters a trade when the 20-day Simple Moving Average, a calculation of the average price of a stock over 20 days, is greater than the 100-day Simple Moving Average, and exits when the opposite occurs, only taking long positions. The system was developed using data from 2025 with fast periods of 10, 20, and 30 days, and slips of 30 and 60 basis points, a basis point being one hundredth of a percent. The holdout period, a period of time used to test the system, was from January 1, 2026, to September 8, 2026, using a fast period of 20 days. The warmup period, a time used to initialize the system, began on September 1, 2024, and the HYPE period, a time used to evaluate the system, began on February 17, 2026, so there was no training in 2025. The system used Vectorbt, a backtesting library, to simulate fees of 25 basis points, and slips of 30 and 60 basis points. The system did not simulate stop-loss, target, or profit-taking, and did not use 15-minute execution, and is not ready for use in a trading venue. The baseline results showed a return of -24.065349670624332 percent, a drawdown of 59.702134711355704 percent, and a win rate of 20 percent. The stress results showed a return of -40.44611675578691 percent, a drawdown of 67.91804543656906 percent, and a win rate of 17.5 percent. The premises of the system include survivor selection, which means that only the best-performing assets are included, and the fact that 2026 has already been researched, so the validation is not pristine. Every hourly candidate has a missing interval while invested, which means that the diagnostic returns are not accepted as execution outcomes, and the missing bars are not filled or counted as qualified tests. The conclusion is to reject the system for trading, even if the raw Kelly, a measure of the system's performance, is positive, it is overridden to 0. The data sources are https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees, and the reproducible scripts are in the saved note.
A news scan found the headline about UNI 1Day SMA20/100 diagnostic. The system was frozen before download in note1292. Prior completed SMA20, which means Simple Moving Average over 20 days, greater than SMA100, enters at the next adjacent open, and inverse exits, with a long-only strategy, meaning only buying, not selling. Development in 2025 used fast 10, 20, and 30, and slips 30 and 60 basis points, which is a measure of the change in the value of a security. Holdout in 2026 from January 1 through September 8 used fast 20 only, with each period starting flat. Warmup began on September 1, 2024, and HYPE began on February 17, 2026, so there was no 2025 training. Vectorbt, a backtesting library, was used with fees of 25 basis points cash each side, which is an approximation to credited-asset fees. The baseline had a slip of 30 basis points and stress of 60 basis points. No stop, target, or profit-taking was simulated, and 15-minute execution was not simulated, so it is not venue-ready. The baseline results were: symbol UNI, time frame 1Day, fast 20, window holdout, slip 0.003, return percentage 54.42818341582731, drawdown percentage 27.840691563172683, number of trades 1, win rate percentage 0, average win percentage null, average loss percentage 15.77447261387305, expectancy percentage -15.77447261387305, quarter Kelly 0, open 1, missing 0, held gap invalid false, and zero volume 0. The stress results were: symbol UNI, time frame 1Day, fast 20, window holdout, slip 0.006, return percentage 53.04660262119546, drawdown percentage 28.272360177984247, number of trades 1, win rate percentage 0, average win percentage null, average loss percentage 16.279818835756174, expectancy percentage -16.279818835756174, quarter Kelly 0, open 1, missing 0, held gap invalid false, and zero volume 0. The premises were that the current universe introduces survivor selection, and 2026 was already researched, so it is not pristine unseen validation. There was only one closed losing trade plus one open position, so positive marked returns do not estimate average win or a tradeable probability. The conclusion was to reject for trading, even with a positive raw Kelly, which is a measure of the expected return of a trade, overridden to 0. The source is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. Reproducible scripts are in this run's saved note.
A news scan found the headline about a diagnostic for the SOL 1Hour SMA20/100. The diagnostic was frozen before download in note1292. The system enters a trade when the 20-day Simple Moving Average is greater than the 100-day Simple Moving Average, and exits when the inverse happens, only for long positions. The development period was from 2025 with fast periods of 10, 20, and 30, and slip values of 30 and 60 basis points. The holdout period was from January 1, 2026, to September 8, 2026, with a fast period of 20. Each period started with no existing positions. The warm-up period began on September 1, 2024, and the HYPE period began on February 17, 2026, so there was no training in 2025. The system used Vectorbt with signal fees of 25 basis points and cash on each side, and a baseline slip of 30 basis points and stress of 60 basis points. The system did not simulate stop-loss, target, or profit-taking, and did not simulate 15-minute execution. It was not ready for a trading venue. The baseline results were: {symbol: SOL, time frame: 1Hour, fast: 20, window: holdout, slip: 0.003, return percentage: -43.24, drawdown percentage: 60.72, number of trades: 46, win rate percentage: 21.74, average win percentage: 7.62, average loss percentage: 3.45, expectancy percentage: -1.04, quarter Kelly: 0, open: 0, missing: 7, held gap invalid: true, zero volume: 124}. The stress results were: {symbol: SOL, time frame: 1Hour, fast: 20, window: holdout, slip: 0.006, return percentage: -56.93, drawdown percentage: 69.66, number of trades: 46, win rate percentage: 19.57, average win percentage: 7.76, average loss percentage: 3.92, expectancy percentage: -1.63, quarter Kelly: 0, open: 0, missing: 7, held gap invalid: true, zero volume: 124}. The premises of the system introduce survivor selection, and 2026 was already researched, so it was not a pristine unseen validation. Every hourly candidate had a missing interval while invested, so the diagnostic returns were not accepted as execution outcomes. The conclusion was to reject the system for trading, even if the raw Kelly was positive, it was overridden to 0. The source of the data was https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The reproducible scripts were in the saved note.
A news scan found the headline about a SOL 1Day SMA20/100 diagnostic. The system was frozen before download in note 1292. Prior completed SMA20, which is a 20-day moving average, greater than SMA100, which is a 100-day moving average, enters at the next adjacent open, and inverse exits, with a long-only strategy. Development in 2025 used fast 10, 20, and 30, and slips of 30 and 60 basis points, which is a measure of the difference between two prices. The holdout period was from January 1, 2026, through September 8, 2026, using fast 20 only, with each period starting flat. The warmup period began on September 1, 2024, and HYPE began on February 17, 2026, so there was no training in 2025. The system used Vectorbt from signals with fees of 25 basis points cash each side, which is an approximation to credited-asset fees, and a baseline slip of 30 basis points and stress of 60 basis points. There was no stop, target, or profit-taking, or 15-minute execution simulated, and it is not venue-ready. The baseline results for the symbol SOL, with a 1-day time frame, fast 20, and holdout window, were a return percentage of -7.2673895414414575, a drawdown percentage of 16.278259939392502, and one trade, with a win rate percentage of 0, and an average loss percentage of 15.473666528142124. The stress results were a return percentage of -8.097015266563403, a drawdown percentage of 16.779096883987464, and one trade, with a win rate percentage of 0, and an average loss percentage of 15.980812220518612. The premises of the system introduce survivor selection, and 2026 was already researched, so it is not a pristine unseen validation. There was only one closed losing trade, plus one open position, so positive marked returns do not estimate an average win or a tradeable probability. The conclusion is to reject for trading, even with a positive raw Kelly, which is overridden to 0. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The reproducible scripts are in this run's saved note.
A news scan found the headline about a diagnostic for LTC, which is a type of cryptocurrency. The diagnostic was frozen before download in note 1292. The system uses a Simple Moving Average, or SMA, which is a way to smooth out price data, to make decisions. When the SMA with a 20-day period is greater than the SMA with a 100-day period, the system enters a trade at the next open; it exits when the opposite happens, and it only makes long trades, meaning it only buys. The system was developed using data from 2025 with fast periods of 10, 20, and 30 days, and it was tested using data from 2026 from January 1 to September 8 with a fast period of 20 days. Each test period started with no existing trades. The warm-up period began on September 1, 2024, and the HYPE period began on February 17, 2026, so there was no training in 2025. The system uses a fee of 25 basis points, or 0.25%, for each trade, and it assumes a slip of 30 basis points and a stress of 60 basis points. The system does not use stop-loss, target, or profit-taking, and it does not simulate 15-minute execution. The baseline results for the LTC symbol with a 1-hour time frame, a fast period of 20 days, and a holdout window showed a return of -52.24% and a drawdown of 63.69%. The stress results showed a return of -62.54% and a drawdown of 71.26%. The premises of the test include survivor selection, and the results are not considered valid because every hourly candidate had a missing interval while invested. The conclusion is to reject the system for trading, even if the raw Kelly criterion, which is a way to measure the performance of a trading system, is positive. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The scripts used to run the diagnostic are saved in the note.
A news scan found the headline about a diagnostic for LTC. The diagnostic was frozen before download in note 1292. Prior completed SMA20, which means Simple Moving Average over 20 periods, greater than SMA100, which means Simple Moving Average over 100 periods, enters at the next adjacent open and exits inversely, with a long-only strategy. Development in 2025 used fast 10, 20, and 30, and slips of 30 and 60 basis points, which is a unit of measurement for interest rates and investment returns. The holdout period started on January 1, 2026, and went through September 8, using fast 20 only, with each period starting flat. The warmup period began on September 1, 2024, and HYPE began on February 17, 2026, so there was no training in 2025. The diagnostic used Vectorbt from signals with fees of 25 basis points cash each side, which is an approximation to credited-asset fees, and a baseline slip of 30 basis points and stress of 60 basis points. The diagnostic did not simulate stop, target, or profit-taking, or 15-minute execution, and is not venue-ready. The baseline results showed a return percentage of -6.0423, a drawdown percentage of 22.1615, and an expectancy percentage of -8.9663. The stress results showed a return percentage of -6.8829, a drawdown percentage of 22.6271, and an expectancy percentage of -9.5123. The premises of the diagnostic introduced survivor selection, and 2026 was already researched, so it was not pristine unseen validation. There was only one closed losing trade, plus one open position, and positive marked returns did not estimate average win or a tradeable probability. The conclusion was to reject for trading, even with a positive raw Kelly, which was overridden to 0. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The reproducible scripts are in the saved note.