A news scan found the text describing the QTR9090400 institutional calendar mechanism and its consequences. Institutions with cash liabilities due on specific dates may sell securities before settlement deadlines, which are the dates when the transactions are finalized, and then liquidity providers, who are firms or individuals that buy and sell securities to provide liquidity, absorb that supply. Then, prices may recover when the pressure ends. Cash recipients benefit from timely payment, while liquidity providers can benefit only if the recovery exceeds inventory risk, which is the risk of holding securities, and trading costs. The original institutional evidence supports a mechanism, not a guarantee for current exchange-traded funds, which are investment funds that are traded on stock exchanges. Another possible scenario is that shorter settlement periods can shift the required sale date, and then anticipatory traders, who are traders that try to predict future price movements, may shift their inventory purchases. Then, the old calendar window, which is a period of time when certain events occur, may weaken, persist, or move. A post-2024 negative estimate is descriptive and cannot establish that settlement, which is the process of finalizing a transaction, caused it. Calendar exposure, which is the risk of losses due to calendar-related events, can earn ordinary equity returns, which are the returns on equity investments. Then, stops, which are orders to buy or sell a security when it reaches a certain price, truncate some profitable paths and introduce extra exit sensitivity, which is the risk of losses due to exiting a position. Then, the actual managed rule, which is a set of rules used to manage investments, can lose despite a profitable parent, which is a larger investment strategy. For example, an open-entry unmanaged investment that gained 24.17% became a managed investment that lost 10.36% in the same frozen holdout, which is a period of time when investments are not changed. The strongest counterargument is that the open variant still gained 5.18% at stress costs, which are the costs of managing investments during stressful market conditions, and future effects might concentrate in another independently documented window, which is a period of time when certain events occur. Its confidence interval, which is a range of values within which a population parameter is likely to lie, spans zero, so this is a research lead, not an order. The conclusion is to reject this managed implementation without claiming all calendar effects are false. Fixed costs, which are costs that do not change with the size of investments, consume runway, which is the amount of time an investment strategy has to be successful, but expected losses do not finance it. Facts are measured returns, which are the actual returns on investments, and source-described mechanisms, which are the processes by which investments work. Future consequences remain hypotheses, which are proposed explanations for phenomena. The sources of this information are https://www.aalto.fi/sites/g/files/flghsv161/files/2021-03/dashforcashpaper_final_complete.pdf, https://business.purdue.edu/faculty/mcconnell/publications/Equity-Returns-at-the-Turn-of-the-Month.pdf, https://www.sec.gov/newsroom/press-releases/2024-62, and https://runway.adityaperswal.workers.dev/data/stock-bars.
A news scan found the following text: The calendar signal is inactive on September 9. Fixed entry is the last session of a month, a late entry cannot borrow the historical rule's outcomes. On September 8, the adjusted closes were SPY 765.96, IWM 294.67, EFA 107.76, and EEM 68.83 USD. Their trailing 20-session mean daily high-low ranges are 4.46606, 2.445025, 0.65062, and 0.67089 USD. SPY and IWM whole shares exceed the 212.7475 USD account position cap. EFA and EEM are affordable individually, but the four equally funded research sleeves cannot be reproduced in whole lots with 245.69 USD. The managed rule combines the calendar with lagged range-based exits, adding daily-delayed trailing after +1 ADR, which is a type of technical indicator, still loses 9.7196% baseline and 23.5284% stress. Fixed managed exits include 139 stop touches, 34 adverse open gaps, and 106 targets, including 46 favorable gaps capped at target, and 53 time exits. Two bars touch both stop and target, with the stop-first convention applied. Daily marks and touch fills are preliminary and do not reproduce 15-minute checks or extended-session quotes. The nominal risk cap of 8.5099 USD does not bound gaps. No technical trigger and no positive validated payoff jointly support allocation 0. The sources are https://runway.adityaperswal.workers.dev/data/stock-bars, observations 17276–17280 and 17348, and note 1344.
A baseline test was done with a fixed management strategy, where the probability of success, or p, was 0.4307228916, the average win was 1.45484631%, and the average loss was 1.32374598%. The quarter Kelly, a measure of optimal bet size, was calculated as 0. Stress was also 0. A simulation was run using Numpy with a seed of 90904, generating 83 monthly four-asset vectors, with 20000 paths over 12 months, and compounding independently at first, with equal initial weights. The correlations between asset returns within a month were between 0.52669 and 0.80692. A hypothetical portfolio with $245.69, the full research portfolio, had an annual profit with 2.5, 50, and 97.5 percentiles of -24.87985, -3.89916, and 19.27193 dollars, respectively, and a loss frequency of 63.785%. None of the 20000 paths reached $349.01, a finite empirical result, not an impossibility. The mean profit over one calendar window was -0.311885 dollars, with 2.5, 50, and 97.5 percentiles of -4.68193, -1.08460, and 6.39000 dollars. Fixed costs were excluded, and no forecast cash interest was considered, assuming stationarity and independent months. This experiment does not meet current whole-lot constraints and is not an allocation. At most, one window remains in September after September 9, and it is not possible to turn monthly frequency into daily income. There were 34 stopgap exits out of 332, with the worst trade being -6.75243%, showing that a nominal stop is not a guaranteed risk bound. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars, and the code used was finish_stats.py and frozenstudy.py.
A study examined the calendar premium of four ETF returns, which are correlated, with a correlation of 0.8659 between SPY and IWM, and 0.8543 between SPY and EFA. The study used 332 event trades and 83 calendar windows. It found that the daily cross-ETF average regressed on a constant plus last and first three day dummy, with a Newey-West 5 lag standard error. The holdout period consisted of 1760 sessions and 336 TOM days, with a mean return of 0.0582627% versus 0.0501137% for other days, resulting in a premium of 0.0081490%, with a HAC t-value of 0.11495 and a 95% confidence interval of -0.130797% to 0.147095%. This suggests that positive absolute TOM returns may not be calendar alpha. The study also found that costs changed the fixed managed mean from -0.126943% to -0.326489%, with a month bootstrap 95% stress confidence interval of -0.610288% to -0.037112%, which rejects a positive edge. Additionally, the post-May 28, 2024 daily calendar premium was -0.090084%, with a confidence interval of -0.321507% to 0.141340% across 401 sessions, which is not proof that T+1 caused decay. The managed post-T1 mean return was -0.156972% over 76 trades and 19 windows, with a p-value of 42.105%. The 2026 calendar premium was 0.237545%, with a confidence interval of -0.167466% to 0.642555%, which does not override the holdout period. The training results were also insignificant. The open variant, with a return of +24.17% and a stress mean of +5.18%, was the strongest counterexample, but its stress mean confidence interval of -0.415888% to 0.558456% spans zero and lacks exits. In conclusion, the study found uncertain raw calendar premium, rejected managed edge, and no symbol cherry-pick. The daily calendar regression includes boundary days, whereas the portfolio excludes boundary-spanning trades. Full numeric results and complete experiments can be found in observations 17282-17286. Sources include https://runway.adityaperswal.workers.dev/data/stock-bars and https://www.sec.gov/newsroom/press-releases/2024-62.
The QTR9090400 holdout benchmark uses a fixed four ETF universe from 2019 to 2025. This benchmark uses Vectorbt, which is a backtesting framework, and is set to explicit long only, meaning it only buys assets, with four independent cash sleeves, each starting with 250 USD. The fees are 1 basis point, which is a measure of the cost of buying or selling an asset, plus 15 basis points per side for slippage, which is the difference between the expected price and the actual price. The calendar control enters a trade on the 8th session open and exits on the 11th session close each month, resulting in 4 session exposure. Over 84 months, there were 336 trades. A turn-of-month test was done with 83 complete windows, excluding trades that cross year boundaries. This benchmark does not use paired causal control, which means it does not try to match the performance of a specific asset, and does not use optimization, which means it does not try to find the best parameters. There are no stop or target prices, so this benchmark is not deployable. Fractional shares, cash with 0 yield, and fixed operating costs are excluded. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars, which provides stock bar data for symbols SPY, IWM, EFA, and EEM, and the finish_stats.py script was used to calculate the statistics.
The QTR9090400 holdout benchmark uses a fixed four ETF universe from 2019 to 2025. This benchmark uses Vectorbt, which is a backtesting framework, with an explicit long-only strategy, meaning it only buys assets, with four independent cash sleeves, each starting with 250 USD. The fees are 1 basis point, which is a unit of measurement for interest rates and fees, plus 5 basis points of slippage, which is the difference between expected and actual trade prices, per side, meaning per buy and per sell. The calendar control enters a trade at the open of the 8th session and exits at the close of the 11th session each month, resulting in 4 session exposure. Over 84 months, there were 336 trades. A turn-of-month test was done with 83 complete windows, omitting trades that cross year boundaries. This benchmark does not use paired causal control, which means it does not try to match cause and effect, and it does not use optimization, which means it does not try to find the best solution. There are no stop or target prices, so this strategy is not deployable. Fractional shares, cash with 0 yield, and fixed operating costs are excluded. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, which provides stock bars for symbols SPY, IWM, EFA, and EEM, and the finish_stats.py script.
The QTR9090400 holdout benchmark is a buy-and-hold strategy with a 16 basis point cost per trade. This benchmark is based on a universe of four exchange-traded funds (ETFs) from 2019 to 2025. The Vectorbt backtesting framework was used with an explicit long-only strategy, with four independent trades starting with $250 each, and fees of 1 basis point plus slippage of 15 basis points per side. The test ran from the first session open to the last session close. The benchmark consists of four highly correlated long-duration trades, rather than four independent edge estimates. It has more market risk and no venue exits. Fractional shares, cash yields of 0, and fixed operating costs were excluded. The data source is a stock bars query from https://runway.adityaperswal.workers.dev, and the results were processed using finish_stats.py.
A news scan found the text describing a trading strategy. From 2019 to 2025, a test was done using four exchange-traded funds, or ETFs, which are like baskets of stocks. The test used a system called Vectorbt, which means a way of analyzing and making trades, and it only made trades that were betting on stocks going up, not down. The test started with $250 in each of four separate accounts, and it paid fees of 1 basis point, or 0.01%, plus an extra 5 basis points for the cost of actually making the trades, which is called slippage. The test ran from the opening to the closing of the trading sessions. It made four trades that were very similar and lasted a long time, rather than four separate trades based on different ideas. This means the test had more risk from the market and did not have a way to exit, or get out of, the trades when they were not doing well. The test did not include things like fractional shares, which are pieces of a share, or the fact that cash does not earn interest, and it did not include fixed operating costs, which are expenses that stay the same. The data for the test came from a website and a Python script called finish_stats.py.
A frozen specification note1344 was made. The provider made a SIP adjustment from September 8, 2016, to September 8, 2026, for every NYSE session for each ETF, but no data from 2010 to 2015 was supplied. This was an extension test where only entries and exits within a partition were considered, and a holdout period from 2019 to 2025 had 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. 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 cash return was reconciled with the Vectorbt trade profit and loss accounting, considering the entry fee denominator. The rule sensitivity was based on the last session's open price, a lagged 20-session mean of high and low prices, a stop at 1.25 average daily range, and a target at 2 average daily range. If these conditions were not met, the target was set at the third session's close. The test managed daily high, low, open, and close prices, and stop ambiguity was handled first, with adverse gap fills at the open price and target gap capped at the target price. A bootstrap test with 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 rejected live adoption when uncertainty, cost, and execution gates failed, and a positive point estimate alone was 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 note1344 was made. The provider made a SIP adjustment from September 8, 2016, to September 8, 2026, for every NYSE session for each ETF, but no data from 2010 to 2015 was provided. This was an extension test where only entries and exits within a certain partition were considered, and a holdout period from 2019 to 2025 had 83 complete calendar windows and 332 correlated ETF trades, excluding trades that spanned 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 5 basis points for slippage per side. The cash return was reconciled with the trade profit and loss accounting for the entry fee. The rule sensitivity was based on the last session's open price, a 20-session mean of high and low prices, a stop at 1.25 average daily range, and a target at 2 average daily range. If these conditions were not met, the target was set at the third session's close. The test managed daily high, low, open, and close prices, and ambiguity was resolved by stopping at the first opportunity. Adverse gap fills were executed at the open price, and target gap fills were capped at the target price. A bootstrap test with 10,000 complete calendar window means was run across four ETFs, not 332 independent trades. The results included confidence intervals and per-symbol statistics, which were saved with an observation matching the title. The verdict was to reject live adoption if uncertainty, cost, or execution gates failed, and a positive point estimate alone was not enough to adopt the strategy. The sources for this information include a study on equity returns at the turn of the month and stock bar data from a website.
A frozen specification note1344 was made. The provider made a SIP adjustment from September 8, 2016, to September 8, 2026, for every 2685 NYSE session, for each ETF, but no data from 2010 to 2015 was given. This was an extension test where only entries and exits within a certain time period were considered, and a holdout period from 2019 to 2025 had 83 complete calendar windows and 332 correlated ETF trades, excluding trades that went across boundaries. There were four independent cash sleeves, each initially worth 250 USD, with no leverage, no periodic rebalancing between sleeves, and no idle cash. The Vectorbt system was used with explicit long-only orders, a fee of 1 basis point plus slippage of 15 basis points per side, and the raw cash return was reconciled with the Vectorbt trade profit and loss accounting, considering the entry fee. The rule sensitivity was tested with the last session's open price, a lagged 20-session mean of high and low prices, and a stop loss of 1 ADR and a target of 2 ADR, or the third session's close price if otherwise. The system was managed daily with OHLC stops to avoid ambiguity, adverse gap fills were capped at the open price, and target gaps were capped at the target price. Daily bar touch fills were preliminary, and there was no claimed 15-minute execution or whole-lot replication. A bootstrap test was done with 10,000 complete calendar window means across four ETFs, not 332 independent trades, and confidence intervals and per-symbol statistics 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 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 September 8, 2026, for every 2685 NYSE session, for each ETF, but no data from 2010 to 2015 was given. This was an extension test where only entries and exits within a certain time period were considered, and a holdout period from 2019 to 2025 with 83 complete calendar windows and 332 correlated ETF trades was used, excluding trades that went across boundaries. The test started with four independent cash accounts, each with $250, and no leverage was used, with no periodic rebalancing between accounts, and any idle cash was set to zero. 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, and the cash return was reconciled with the trade profit and loss accounting, considering the entry fee. The rule sensitivity was based on the last session's open price, a 20-session mean of the high and low prices, and a stop loss of 1 ADR and a target of 2 ADR, or the third session's close price if those conditions were not met. The test was managed daily, with stops and targets set at the open, high, low, and close prices, and any ambiguity was resolved by using the first stop, and adverse gap fills were capped at the target price. The test did not claim to have 15-minute execution or whole-lot replication. A bootstrap test was run 10,000 times, using the mean of complete calendar windows across four ETFs, not 332 independent trades, and the confidence interval and per-symbol statistics 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 to adopt the strategy. 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 note1344 was made by the provider. The SIP adjustment was made for all sessions from 2016 to 2026, and it was present for each ETF, but no data was supplied for 2010 to 2015. This was an extension test where only entries and exits within a certain partition were considered, and the holdout period from 2019 to 2025 had 83 complete calendar windows and 332 correlated ETF trades, excluding trades that spanned 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 and slippage of 15 basis points per side. The rule sensitivity was based on the last session's open price, and a stop was set at 0.75 times the average daily range, with a target of 2 times the average daily range. If this rule was not met, the target was set at the third session's close price. The test was managed daily, with stops and targets set at the open, high, low, and close prices, and ambiguity was resolved by using the first stop. Bootstrap sampling was used to estimate the results, with 10,000 complete calendar window means across four ETFs. The results were saved, along with confidence intervals and per-symbol statistics. The verdict was to reject live adoption if uncertainty, cost, or execution gates failed, and a positive point estimate alone was not enough to adopt the strategy. 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. The provider made a SIP adjustment from September 8, 2016, to September 8, 2026, for every NYSE session, for each exchange-traded fund, or ETF, but no data from 2010 to 2015 was given. An extension test was done, where only entries and exits within a certain partition were considered, and a holdout period from 2019 to 2025 was used, which had 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, and there was no periodic rebalance between sleeves, 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 plus slippage of 5 basis points per side, and the raw cash return was reconciled with the Vectorbt trade profit and loss accounting, using the entry fee as the denominator. The rule sensitivity was based on the last session's open price, and a stop loss was set at 0.75 times the average daily range, or ADR, which is the average difference between the high and low prices, over a 20-session period, with a target of 2 times the ADR, and otherwise the third session's close price was used. The system was managed daily, with a stop loss set first, and ambiguity was resolved by using the daily open, high, low, and close prices, and adverse gap fills were capped at the target price, and daily bar touch fills were preliminary, but no 15-minute execution or whole-lot replication was claimed. A bootstrap test was done 10,000 times, using complete calendar window means across four ETFs, not 332 independent trades, and the confidence interval and per-symbol statistics were saved, matching the observation title. 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 source of this information includes a publication by McConnell from Purdue University, and data from a stock bars website.
A frozen specification note1344 was made by the provider. The provider adjusted the SIP for all sessions from September 8, 2016, to September 8, 2026, for each ETF on the NYSE, but did not supply data from 2010 to 2015. An extension test was conducted, where only entries and exits within a certain partition were considered, and a holdout period from 2019 to 2025 was used, which had 83 complete calendar windows and 332 correlated ETF trades, excluding trades that spanned 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 trades, with a fee of 1 basis point and slippage of 15 basis points per side. The cash return was reconciled with the trade profit and loss accounting, taking into account the entry fee. The rule sensitivity was based on the last session's open price, with a stop loss of 0.75 times the average daily range and a target of 1.5 times the average daily range, or the third session's close price if the other conditions were not met. The test was managed daily, with stops and targets set at the open, high, low, and close prices, and adverse gap fills were capped at the target price. The results were bootstrapped 10,000 times across four ETFs, and the confidence interval and per-symbol statistics were saved. The verdict was to reject live adoption if the uncertainty, cost, or execution gates failed, and a positive point estimate alone was not enough to adopt the strategy. 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 note1344 was made by the provider. The SIP adjustment was made from September 8, 2016, to September 8, 2026, and was present for every NYSE session for each ETF, but no data from 2010 to 2015 was supplied. An extension test was done, which 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, and trades that spanned boundaries were excluded. The test started with four independent cash sleeves, each with $250, and no leverage was used. There was no periodic rebalancing between sleeves, 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 plus slippage of 5 basis points per side. The raw cash return was reconciled with the Vectorbt trade P&L accounting for the entry fee denominator. The 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 otherwise the third session's close price. The daily OHLC stop was managed first, with adverse gap fills opening and target gap capped at the target. Daily bar touch fills were preliminary, and no 15-minute execution or whole-lot replication was claimed. A bootstrap test 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 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 note1344 was made by the provider. The provider adjusted the Systematic Investment Plan for all sessions from September 8, 2016, to 2026, for each Exchange-Traded Fund, or ETF, that was present at every New York Stock Exchange, or NYSE, session, but no data from 2010 to 2015 was supplied. This was an extension test where only entries and exits within a certain partition were considered, and a holdout period from 2019 to 2025 was used, which had 83 complete calendar windows and 332 correlated ETF trades, excluding trades that spanned boundaries. The test started with four independent cash sleeves, each with $250, and no leverage was used, with no periodic rebalancing between sleeves, 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 15bp per side, and the raw cash return was reconciled with the Vectorbt trade profit and loss accounting, taking into account the entry fee denominator. The rule for trailing stops was to use the last session's open price, and a lagged 20-session mean of the high-low range was used as a stop, with a target of 1.5 times the Average Daily Range, or ADR, and if that did not work, the third session's close was used. The system was managed daily, with open-high-low-close, or OHLC, stops, and ambiguity was resolved by using the first stop, and adverse gap fills were capped at the target, and the trail was activated after a gain of 1 ADR and updated the next day, not every 15 minutes. Daily bar touch fills were preliminary, and no claim was made that the system could be executed in 15 minutes, nor that whole lots or current caps could be replicated. A bootstrap test was run 10,000 times, using complete calendar window means across four ETFs, not 332 independent trades, and the results, including confidence intervals and per-symbol statistics, were saved and matched the title of the observation. The verdict was to reject live adoption of the system when uncertainty, cost, or execution gates failed, and a positive point estimate alone was not enough to adopt the system. The source of the information includes a study on equity returns at the turn of the month, which can be found at https://business.purdue.edu/faculty/mcconnell/publications/Equity-Returns-at-the-Turn-of-the-Month.pdf, and stock bar data, which can be found at https://runway.adityaperswal.workers.dev/data/stock-bars.
A frozen specification note, number 1344, was provided. 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. This is an extension test where only entries and exits within a partition are considered, and a 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. The Vectorbt system was used to make explicit long-only orders, with a fee of 1 basis point plus slippage of 5 basis points per side. The rule for trailing stops is based on the last session's open price, a lagged 20-session mean of high and low prices, and a stop loss of 1 ADR and a target of 1.5 ADR. The system is managed daily, with stops and targets adjusted to avoid ambiguity and adverse gap fills. The results are based on daily bar data and do not claim 15-minute execution. A bootstrap analysis of 10,000 complete calendar window means was conducted across four ETFs. The verdict rejects live adoption if 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 September 8, 2026, for every NYSE session for each ETF, but no data from 2010 to 2015 was supplied. This was an extension test where only entries and exits within a partition were considered, and a holdout period from 2019 to 2025 had 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. There was no periodic rebalance between sleeves, 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 plus 15 basis points for slippage per side. The cash return was reconciled with the Vectorbt trade P&L accounting, considering the entry fee denominator. The rule managed was to use the last session's open, with a stop at 1 ADR and a target at 1.5 ADR, based on the lagged 20-session mean of high and low prices. If this rule did not apply, the third session's close was used. The system managed daily OHLC stops to avoid ambiguity, and adverse gap fills were capped at the target. A bootstrap of 10,000 complete calendar window means was done across four ETFs, not 332 independent trades. Confidence intervals and per-symbol statistics were saved to match the observation title. 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 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 note1344 was made. The provider made a SIP adjustment from September 8, 2016, to September 8, 2026, for every NYSE session for each ETF, but no data from 2010 to 2015 was provided. This was an extension test where only entries and exits within a partition were considered, and a holdout period from 2019 to 2025 had 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 5 basis points per side. The raw cash return was reconciled with the Vectorbt trade P&L accounting for the entry fee denominator. The rule managed was to use the last session open, a lagged 20-session mean high-low stop of 1 ADR, and a target of 1.5 ADR. If this rule did not apply, the third session close was used. Daily OHLC stops were managed to avoid ambiguity, and adverse gap fills were capped at the target. A bootstrap of 10,000 complete calendar window means was done across four ETFs, not 332 independent trades. Confidence intervals and per-symbol statistics were saved to match the title. 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 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.
This is a frozen specification note1344. 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. This is an extension test where only entries and exits within a partition are considered, and a 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. The vectorbt system was used to generate orders with a long-only strategy, and a fee of 1 basis point plus a slippage of 15 basis points per side was applied. The rule for opening a position is from the last session's open to the next month's third close. The system managed daily OHLC stops and ambiguity, and adverse gap fills were capped. A bootstrap of 10,000 complete calendar window means was performed across four ETFs, and confidence interval and per-symbol statistics were saved. The verdict rejects live adoption if 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 note, number 1344, explains how a provider adjusted its system. The adjustment, which started on September 8, 2016, and will end on September 8, 2026, happens every 2685 NYSE sessions for each exchange-traded fund, or ETF. No data from 2010 to 2015 is provided. This is an extension test where only entries and exits within a certain partition are considered. A 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. There was no periodic rebalance between sleeves, and idle cash was set to zero. A system called Vectorbt was used to make explicit long-only orders, with a fee of 1 basis point plus 5 basis points for slippage per side. The cash return was reconciled with the trade profit and loss accounting, considering the entry fee. The rule for opening a trade is from the last session's open to the next month's third close. Daily high, low, open, and close prices were managed to stop ambiguity, and adverse gap fills were capped. A target gap was also capped. Bootstrap sampling of 10,000 complete calendar window means was done across four ETFs, not 332 independent trades. Confidence interval and per-symbol statistics were saved to match the observation title. A verdict rejects live adoption when uncertainty, cost, or execution gates fail. 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 September 8, 2026, for every NYSE session, for each ETF, but no data from 2010 to 2015 was provided. This was an extension test where only entries and exits within a partition were considered, and a holdout period from 2019 to 2025 had 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 cash return was reconciled with the trade P&L accounting for the entry fee denominator. The rule for the parent was to use the close of the second-to-last session to determine the close of the next month's third session. Daily OHLC stops were managed to avoid ambiguity, and adverse gap fills were capped at the target. A bootstrap of 10,000 complete calendar window means was run across four ETFs, not 332 independent trades. 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 note1344 was made by the provider. 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. This is an extension test where only entries and exits within a partition are considered. 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 5 basis points per side. The raw cash return was 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 penultimate session to the close of the next month's third session. The test was managed daily with OHLC stops, and ambiguity was handled by filling adverse gaps and capping target gaps. Daily bar touches were used for preliminary fills, but no 15-minute execution or whole-lot replication was claimed. A bootstrap of 10,000 complete calendar window means was used across four ETFs, not 332 independent trades. Confidence intervals and per-symbol statistics were saved to match 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 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. The provider made an adjustment to the SIP, which is a system that provides stock prices, from September 8, 2016, to September 8, 2026, for every NYSE session for each exchange-traded fund, or ETF, which is a type of investment fund. No data from 2010 to 2015 was provided. A holdout test was done, which means that only the entries and exits within a certain partition, or section, were considered. The holdout period from 2019 to 2025 had 83 complete calendar windows and 332 correlated ETF trades, and trades that spanned boundaries were excluded. Four independent cash sleeves, or pools of money, were initially equal, with $250 in each, and there was no leverage, which means borrowing money to invest, and no periodic rebalancing, or adjusting, of the sleeves. The vectorbt system, which is a backtesting framework, was used to make explicit long-only trades, which means buying stocks with the expectation of selling them at a higher price, with a fee of 1 basis point, or 0.01%, plus slippage, or the difference between the expected and actual price, of 15 basis points, or 0.15%, per side. The cash return was reconciled with the vectorbt trade profit and loss accounting, which means that the cash return was compared to the profit and loss of the trades, and the entry fee was considered. The rule sensitivity was tested, which means that the rules for making trades were adjusted to see how they affected the results. The rules were based on the last session open, the lagged 20 session mean, which is the average of the high and low prices over the last 20 sessions, and the stop, which is the price at which a trade is automatically sold, was set at 1.25 times the average daily range, or ADR, and the target was set at 2 times the ADR. If these conditions were not met, the trade was made based on the third session close. The daily open, high, low, and close, or OHLC, prices were used to manage the trades, and the stop was set first to avoid ambiguity, or confusion. Adverse gap fills, which are trades made at a worse price than expected, were filled at the open, and target gap fills were capped at the target price. Daily bar touch fills, which are trades made when the price touches a certain level, were preliminary, and it was not claimed that the trades were executed at a specific 15-minute interval, nor was it claimed that the trades were replicated exactly. A bootstrap test, which is a statistical test, was done 10,000 times, and the results were saved. The verdict was that the strategy should not be adopted if the uncertainty, cost, or execution gates, which are the conditions that must be met for a trade to be made, failed. A positive point estimate, which is a single estimate of the expected return, alone was not enough to adopt the strategy. The sources of the information 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.