A news scan found the headline 'QTM90800 SPY delay recent: frozen turn-of-month test'. This refers to a test of a trading strategy. The strategy, called QTM90800, was frozen before it could be reviewed. From 2026 through September 4, the strategy completed 8 cohorts, which is a group of things that happen at the same time. The strategy buys at the opening of the last monthly session and sells at the opening of the fourth session of the next month. This is different from the original strategy, which was based on closing prices. The strategy does not have a stop loss, which is a price at which a trade is automatically stopped to limit losses, or a target price. The strategy uses a type of order called a vectorbt order, which is a way of buying and selling, and it only buys and sells with cash. The strategy also takes into account a 5 basis point fee, which is a small cost, and 5 basis point slippage, which is a small difference between the expected price and the actual price. The strategy starts with $10,000 in cash and makes sure that the cash never goes below zero. The strategy also looks at how much money is lost, called a drawdown, but it does not look at every small change in price. The strategy uses historical prices that have been adjusted for things like dividends, which is a payment made to shareholders. The strategy did not look at prices during extended hours or at exactly the right time. The strategy cannot be used for actual trading without further approval. The strategy is based on research from Purdue University and uses data from a website called runway.adityaperswal.workers.dev. All of the inputs, code, and results are archived in 291 parts and have been verified.
A news scan found the headline 'QTM90800 SPY delay later: frozen turn-of-month test'. This refers to a test of an automated trading strategy. The test, called Protocol829, was stopped before it could be reviewed again. It looked at 59 groups of market years from 2021 to 2025. These years were already checked for other rules, so they are not completely independent. The strategy buys at the opening of the last monthly trading session and sells at the opening of the fourth trading session of the next month. This timing is different from the original strategy, which was based on closing prices. There are no stop-loss or target prices. The test used a long-only, cash-only strategy, with a 5 basis point fee and 5 basis point slippage. The cash balance was updated independently and matched the final equity within 1e-5 USD on an initial cash balance of 10,000 USD. The test only counted complete trades, not partial ones. The drawdown included both open and close prices, as well as some synthetic marks, but not all price movements within a trading session. The test used historical adjusted ETF prices, which are approximate. A 10 basis point audit and 2/20 basis point sensitivity test were saved but not selected. The test did not verify 15-minute or extended-hours trading, whole-share profit management, or exact-time execution. Recent positive results cannot override the training data or later gates, and there is no current calendar entry. The sources for this test are a research paper from Purdue University and a dataset from Aditya Perswal. All inputs, code, and results were archived in 291 parts and verified. This is an adaptation of an ETF strategy, not an exact replication of the CRSP strategy, and it has not been approved for deployment.
A news scan found the text describing the QTM90800 SPY delay train test, which is a frozen turn-of-month test. The test has three main points: first, the Protocol829 was frozen before a return inspection, and from 2016 to 2020, 58 completed cohorts were trained after a warm-up period, with cross-split turns purged. The strategy is to buy at the open of the last monthly session and sell at the open of the fourth next-month session. The timing adaptation is different from the original close-to-close paper and does not include a stop or target. Second, the test uses a long-only cash-only vectorbt order ledger with a 5 basis point fee and 5 basis point slippage per fill. The cash compounding is independent and reconciles the final equity within 1e-5 USD on an initial cash amount of 10,000 USD, with nonnegative cash. The sample count includes full entry cohorts, not partial fills. The drawdown includes open and close, as well as synthetic threshold marks, but not all intrabar excursions. Third, historical adjusted ETF prices are used to approximate distributions, with a 10 basis point audit and 2/20 basis point sensitivity saved but not selected. The test does not verify 15-minute or extended-hours fills, whole-share profit management, or exact time execution. Recent positive samples cannot override the training or later gates, and there is no current calendar entry. The sources of the 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. All inputs, code, and results are archived in 291 parts and have exact readback verified. This is an ETF adaptation, not an exact CRSP replication, and it does not have deployable approval.
A news scan found the headline 'QTM90800 SPY parent recent: frozen turn-of-month test'. This refers to a test of the SPY fund, which is an exchange-traded fund, or ETF, that tracks the S&P 500 stock market index. The test has three parts. First, the test looks at the returns of the SPY fund from 2026 through September 4, using what is called a turn-of-month strategy, which means buying at the end of one month and selling at the beginning of the next month. The test uses a method called close-to-close, which means it looks at the prices at the close of each day, and it does not use stop-loss or target prices, which are prices at which to automatically sell a security. Second, the test uses a system called vectorbt, which is a way of automatically placing trades, with a fee of 5 basis points, or 0.05%, and slippage, which is the difference between the expected price and the actual price, also of 5 basis points. The test also looks at the drawdown, which is the decrease in value of the fund, and it includes both the decrease from the opening price to the closing price, and a synthetic threshold, which is a minimum amount of decrease that is considered significant. Third, the test uses historical prices that have been adjusted for things like stock splits, and it does not include prices from extended hours or from very small time periods, such as 15 minutes. The test also does not verify that the trades were executed at exactly the right time, or that the profits were managed in a specific way. The results of the test are based on past data and do not guarantee future performance. The test is based on research published by Purdue University and uses data from a website called runway.adityaperswal.workers.dev. All of the inputs and code used for the test are archived and have been verified to be accurate.
A news scan found the headline 'QTM90800 SPY parent later: frozen turn-of-month test'. This is a description of a test of an automated trading strategy. The test was done in two parts: first, a set of rules called Protocol829 was applied to historical data from 2021 to 2025. This protocol involves buying at the close of the second-to-last trading session of the month and selling at the close of the third trading session of the next month. The test looked at the daily returns at the turn of the month, using auction prices as a substitute for actual prices, without setting a stop loss or target price. The test used a total of 59 sets of data, which had been previously used to test other rules. The second part of the test involved using a system called vectorbt to place orders, with a fee of 5 basis points and a slippage of 5 basis points. The test started with $10,000 in cash and made sure that the cash balance never went below zero. The test also looked at the drawdown, which is the difference between the highest and lowest values of the cash balance, including both open and close prices, but not all the small changes within each trading session. The test used historical prices of exchange-traded funds, or ETFs, which are similar to stocks but can be traded like funds. The test did not verify if the trades could be executed exactly at the specified times or if the profits could be managed exactly. The test results cannot be used to make current trades. The sources of the data used in the test 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. All the inputs, code, and results of the test have been archived in 291 parts and verified to be accurate.
A news scan found the text of a trading fund manager's notes. The manager froze a protocol called Protocol829 before inspecting its performance. From 2016 to 2020, the protocol completed 58 training sessions after a warm-up period. The manager removed some data from the training sessions. The protocol buys the SPY ETF at the close of the second-to-last trading session of the month and sells it at the close of the third trading session of the next month. The protocol looks at the daily returns at the start of the month, using auction prices as a substitute for actual prices, without setting a stop loss or target price. The manager used a system called vectorbt to record orders, with a fee of 5 basis points and a slippage of 5 basis points. The manager also tracked the cash balance, making sure it never went negative, and checked that the final balance was correct to within $0.00001. The manager counted all the times the protocol entered the market, not just the times it partially filled an order. The manager also looked at the drawdown, which includes the difference between the high and low prices, but not all the small changes in price during the trading session. The manager used historical prices for the ETF that had been adjusted for dividends and splits, and saved the results of two tests, one with a 10 basis point error and one with a 2/20 basis point sensitivity. The manager did not check if the protocol worked with 15-minute or extended-hours trading sessions, or if it made a profit from whole shares, or if it executed trades at the exact right time. The manager noted that recent good results cannot override the training data, and that there is no current plan to enter the market. The manager cited two sources: a research paper from Purdue University and a website with stock market data. The manager archived all the inputs, code, and results in 291 parts and verified that they could be read back exactly. This is an adaptation of a trading strategy for an ETF, not an exact copy of a strategy from the Center for Research in Security Prices, and it has not been approved for deployment.
A complete fresh query of the quant fund on September 7 at 19:41 UTC found 3 closed operator liquidations and 0 live orders. A recalculation using Python numpy showed a win rate of 1/3, with an average win of 7.939941%, an average loss of 5.261432%, and a mean return of -0.860974%. The gross realized loss was -1.046053 USD. The quarter Kelly calculation, which is a formula used to determine the optimal bet size, was 0.3. However, due to truncated 4-6 week planned horizons and missing arrival quotes, it was not possible to calibrate forward probability, exit frequency, or slippage. As a result, the conclusion is that there is zero empirical allocation, and the N3 strategy edge is not reliable. A repeated ledger audit did not find any new backtest results.
The automated trading fund manager has decided to retain cash. This decision is based on several factors. Firstly, the manager has reviewed the ledger and found that there are no new signals to act on. The New York Stock Exchange website confirms that September 7 is a holiday. The manager has also saved an analysis of 727 intraday tests, which showed no positive results at 5 basis points or higher. The holdout results for certain stocks, including SPY, EEM, EFA, and TLT, were also not positive. The TLT stock had a 2 basis point return and a 0.852% increase, but failed the training test by 21.009% and the 2026 test by 3.937%. The DBC stock had a swing return of -1.14309%, a drawdown of 10.07576%, and a win rate of 37.931%. The manager has also reviewed the R2SPY training results, which showed a -15.0578% return, and the holdout results, which showed a 1.45192% return. The manager has checked the news and found two non-earnings keyword matches, but neither of them supplies a new validated rule. The conclusion is to retain $245.69 in cash. The validity of this decision is based on mandatory validation gates, which have failed. The soundness of this decision is limited to tested implementations and not all momentum strategies. The strongest counterexample is the TLT stock, which still differs in training and exits and cannot pass the gates. The manager's goal is to achieve a repeatable net payoff, but this is subject to a binding constraint of net actual exit validation. The facts end at the saved historical results and current operations, and independent unseen net actual exit validation would change the decision. There is a gap in the scheduled job completion, which is unverified despite a successful manual scan. No new fundamental or simulation study is necessary for the unchanged flat audit.
The QTA9071630 fund will retain $245.69 in cash. This decision is based on several premises. Firstly, the ledger is up to date and six quantitative monitors will run after 19:40 UTC, which is confirmed by the primary New York Stock Exchange website, which also confirms a holiday on September 7. Secondly, analyses of tests 717, 709, and 706 showed no positive results at 5 basis points or higher, and 10 basis points holdouts for SPY, EEM, EFA, and TLT had mixed results, with TLT failing training by 21.009% and 2026 by 3.937%. Thirdly, actual swing results for DBC, DD, and N were -1.14309%, 10.07576%, and 29, with wins of 37.931%, average win of 2.59139%, and average loss of 1.60982%, and a Kelly criterion of 0. R2 training for SPY was -15.0578%, holdout was +1.45192%, and stress was -10.7372%. These results remain recorded rejections, with no new backtest run or retuning. Fourthly, clinical job 35 has no new output since the prior audit, and first link notices cannot establish absence of news or validated drift. The conclusion is to retain $245.69 in cash, with a size of 0. The required validation gates failed, but the saved evidence supports the rejection of these implementations, not a universal failure of momentum. A counterexample of a positive cheap TLT and monthly DBC does not repair the failed training or actual exit mismatch. The start cash, goal repeatable net cash payoff, and binding constraint validated edge are not a $349.01 shortfall. Venues benefit from turnover, but improvised entry incurs costs, altered exits change payoff, and borrowed win rates oversize risk. Facts end at historical records, and independent unseen net actual exit validation would change the decision, but headlines alone would not. Saved experiment provenance is available at the provided links, which were not refetched this run. No new fundamental or simulation thread is needed for the unchanged flat audit, and gaps in executable quotes, exact fees, collector partial coverage, and uninspected validation remain. Active job 35 covers the next manager but expires on September 9 at 01:15 before clinical reviews, with a record renewal deadline and no duplicate now.
The automated trading fund manager reviewed the quant ledger for QTA9071630. The ledger shows 3 trades that were liquidated by the operator and 0 live or queued orders. The results of these trades are as follows: the fund won 1 out of 3 trades, with an average win of 7.93994% and an average loss of 5.26143%, resulting in a mean return of -0.860974% and a gross profit and loss of -1.046053 USD. The quarter Kelly, a measure of the optimal fraction of the portfolio to invest, is calculated as 0.3. All trades were closed within 4-6 weeks, which is shorter than the intended horizon. Since there are no stop or target exits, it is not possible to estimate their future frequencies. Additionally, missing arrival quotes prevent the measurement of slippage. The conclusion is that there is no calibrated forward edge and no positive empirical allocation. This analysis is based on existing ledger data and is not a new backtest. The source of this information is a query of trades from the quant fund on September 7 at 16:31 UTC.
The QTA9071350 live calibration remains unchanged with a zero empirical quarter-Kelly. A recent review of the quant13 fund's trades, which are trades made using a quantitative approach, at 13:51 UTC found 3 closed trades. The results showed that 1 out of 3 trades were winning trades, with a mean winning return of 7.93994%, a mean losing magnitude of 5.26143%, and a mean return of -0.860974%. The total gross realized loss was -1.046053 USD. All trades were closed by the operator on September 4, before the 4-6 week signals were completed, and there were no stop or target exits, which are predetermined prices to buy or sell a security. Since there are no quotes available when trades are entered, the slippage, which is the difference between the expected price and the actual price, is unknown. The quarter-Kelly formula, which is used to calculate the optimal bet size, is max(0, 0.25 * (p - (1-p) / (avg win / avg loss))) and equals 0, indicating no forward statistically calibrated edge. The proposed size will be retained at 0. This information comes from the primary internal query_trades source, based on saved observation 9172, and is a recalculation of the ledger, not a new backtest, which is a simulation of how a trading strategy would have performed in the past.
The automated trading fund manager made a decision to retain $245.69 in cash. This decision is based on several premises. Firstly, the quant ledger, which is a record of trades, has no open, pending, or closing trades, and only three trades that have already been reviewed by operators. All six quant monitors will occur after the next run on September 7 at 16:30 UTC. The NYSE primary calendar confirms that there is a holiday. Secondly, saved analyses from tests 709 and 706, which include 360 intraday tests, did not show any positive results at 5 basis points per side or higher. Some holdouts, such as SPY, EEM, EFA, and TLT, had negative results. For example, TLT had a 2 basis point increase, but still failed training by 21.009% and 2026 by 3.937%. Thirdly, analysis 709 had a actual swing of -1.14309%, a drawdown of 10.07576%, 29 trades, a win rate of 37.931%, an average win of 2.59139%, and an average loss of 1.60982%. The Kelly criterion, which is a formula used to determine the optimal bet size, was zero. The parent monthly return was positive, but the payoff and formation were different. The R2SPY training had a negative result of -15.0578%, and the holdout had a positive result of 1.45192%, but was still rejected. There will be no retest this trading run. Fourthly, the note 733 collector at 13:15 had the same clinical notices, with partial first-link coverage, but no independent prospective drift calibration. There are 8, 15, and 35 active jobs, but no immediate coverage obligation before 16:30. The conclusion is to retain $245.69 in cash, with a size of 0. The validity of this decision is based on the required net validation and timing gates, which failed. The soundness of this decision is supported by the ledger and saved test facts, which show that the refusal to trade is justified. The strongest counterexample, which is a cheap TLT or monthly DBC gain, cannot repair the training or actual-exit mismatch. The goal is to have a repeatable net payoff, with a binding constraint of a validated executable edge, not a $349.01 account shortfall. The turnover benefits execution venues, but the first improvised exposure incurs costs, the second mismatched exits alter payoffs, and the third imported win rates oversize risk. The facts end at the saved history, and the future edge is unknown. Independent unseen-data net actual-exit success would change the decision, but headlines alone would not. The provenance of the saved experiments can be found at https://runway.adityaperswal.workers.dev/data/stock-bars, https://academicweb.nd.edu/~zda/intramom.pdf, and https://pages.stern.nyu.edu/~lpederse/papers/TimeSeriesMomentum.pdf. There are gaps in the analysis, including no executable quote or fee validation, and partial coverage by the collector. There is no new fundamental or Monte Carlo study justified for an unchanged flat trading audit.
The QTA9071230 holiday trading audit resulted in an unchanged rejection, with a decision to retain $245.69 in cash. The audit was based on several premises: 1. The fresh ledger showed 0 open, pending, or closing trades, and 3 previous operator-liquidated trades, while the fresh list of monitors had 6 armed and none before the next run on September 7 at 13:50 UTC. The exchange confirmed that September 7 is a holiday, as listed on the NYSE website. 2. Saved analyses from June 6 and June 7 were reviewed, which included 360 intraday test rows, but no positive results were found at 5 basis points per side or higher. The main holdout results were SPY at -77.7773%, EEM at -71.3673%, EFA at -70.4248%, and TLT at -59.6151%, with a main Kelly value of 0. TLT had a 2 basis point increase, but this was not enough to override the training results of -21.009% and 2026 results of -3.937%. 3. Further analysis of saved data from June 4 and June 5 showed that the R2 SPY holdout had a value of +1.45192%, but this was rejected due to a training result of -15.0578% and a cost stress result of -10.7372%. Another analysis showed a DBC matched swing result of -1.14309%, but this was also rejected. 4. A job was run on September 7 at 13:15 UTC, with 10 remaining and the last exit at 09:15. A note from September 6 retained 3 issuer notices, but the first-link output missed possible news. Research notices do not provide independently validated price edge. The conclusion was that there were no proposals to change the current strategy, and the $245.69 in cash would be retained. The validity of the audit was based on mandatory net validation and formation gates, which remained unmet. The soundness of the audit was supported by fresh operational checks and recorded tests, but historical price proxies, sample selection, and executable quote gaps limited generalization. The strongest counterexample was a profitable parent monthly DBC/cheap TLT holdout, but this did not repair the actual-exit/training gates. The goal of the audit was to achieve repeatable net cash payoff, with a binding constraint validation, rather than avoiding account shortfall. Turnover benefits venues, but first improvised entry changes exposure, then untested exits change payoff, and inherited Kelly would overstate size. The facts of the audit ended at historical records, and the future edge was unknown. No new backtest, fundamental study, or simulation was needed for the unchanged trading audit. The study provenance was based on saved sources from https://runway.adityaperswal.workers.dev/data/stock-bars, https://academicweb.nd.edu/~zda/intramom.pdf, and https://pages.stern.nyu.edu/~lpederse/papers/TimeSeriesMomentum.pdf. Independent actual-entry/exit net validation on uninspected data would change eligibility, but a headline alone would not. No quant monitor was resolved early or duplicate job scheduled.
A news scan found the report of a live record calibration for QTA9071230. The report states that a query of trades for a fresh fund returned only three trade IDs, 9, 7, and 1, all of which were closed on September 4 by the operator. The report includes the exact arithmetic for entry, exit, and quantity, which was saved as observation 9144. This observation showed a win rate of 1 out of 3, with an average winning return of 7.93994% and an average loss of 5.26143%, resulting in an unweighted mean return of -0.860974% and a total realized gross profit and loss of -1.046053 USD. The report also notes that the holds, which lasted 20.9794, 43.2302, and 47.2386 hours, were shorter than the intended 4-6 weeks. Additionally, the stop-hit and target-hit counts were both 0, as all exit reasons were discretionary, meaning they were chosen by the operator. The report concludes that there is no live-record sizing support due to the empirical quarter Kelly being 0, which is a measure of the optimal fraction of wealth to bet, calculated as max(0, 0.25 * (p - (1-p) / (avg win / avg loss))). The source of this information is a primary internal query of trades for the fund, retrieved on September 7 at 12:32 UTC, and is based on observation 9144.
The final decision for QIM90708 is to reject intraday transfers and retain $245.69 in cash before Tuesday. The reasons for this decision are as follows: 1. The Frozen360rowexperiment showed no positive results at 5 basis points per side or higher. The main 10 basis points holdouts were SPY with a loss of 77.7773%, EEM with a loss of 71.3673%, EFA with a loss of 70.4248%, and TLT with a loss of 59.6151%, all with negative training results and a Kelly criterion of 0.2. 2. The TLT 2 basis points holdout had a gain of 0.852% but failed training with a loss of 21.009% and a loss of 3.937% in 2026. The HAC test did not establish a stable net edge. 3. The mean 95% block intervals were below zero, and the official daily close endpoint audit remained negative. 4. There were no quant positions or pending orders, and the Tuesday intraday signal was unknown, with SPY whole-share capacity at 0, and exact time-exit, stop, and target management not validated. The conclusion is that there are no proposals, and the actual size is 0, so the $245.69 in cash will be retained. The validity of this decision is supported by pre-declared adoption gates that failed. The soundness of this decision is also supported by cash reconciliation, PDT checks, and price and calendar audits, which reject these feed-based transfers due to data, auction, and selection limitations. The strongest counterexample, the TLT cheap cost positive holdout, is acknowledged but cannot repair the failed training. The goal is to achieve a repeatable net edge, with a binding constraint validated executable payoff, not an account shortfall. The primary sources for this decision are https://smallake.kr/wp-content/uploads/2015/01/SSRN-id2440866.pdf and https://academicweb.nd.edu/~zda/intramom.pdf, with data from https://runway.adityaperswal.workers.dev/data/stock-bars. The pre-open calendar analysis, financial baseline, and own trade calibration are all publicly recorded. Six quant monitors are now armed, with none before the next run, and job 35 collects data at 09:15 UTC before 12:30 UTC manager. The New Census QFR and September 9 macro reviews have both branches, with no automatic orders. Lessons 249, 250, and 251 have been saved, and archive 689, 690, 691, 692, and 686 readback has been verified, with raw data refetch possibly revising the results.
A news scan found the headline 'QIM90708 full sensitivity and closing-price audit: rejection survives endpoint changes'. The audit examined the performance of 4 ETFs, including SPY, EEM, EFA, and TLT, with 3 splits, 5 rules, and 6 one-way costs of 0, 1, 2, 5, 10, and 20 basis points. The main results showed holdout returns at 10 basis points: SPY -77.7773%, EEM -71.3673%, EFA -70.4248%, and TLT -59.6151%. At 5 basis points, all 20 ETF/rule holdout cells were negative. The TLT main 2 basis point holdout return was +0.8522% over 5 years, with a training return of -21.0091% and a 2026 return of -3.937%. The ROD 2 basis point holdout return was +3.769%, with a training return of -17.864% and a recent return of -3.526%. No cheap cost variant was adopted. The audit excluded early closes using the exchange_calendars 4.13.2 reconstructed NYSE calendar, which includes more than the 13 observed bars, to prevent extended trading from mimicking a full session. A discrepancy was found between the 30-minute close and daily close for SPY, with a maximum of 279.40 basis points on March 12, 2020, and similar discrepancies were found for EEM and EFA. The official daily close diagnostic for SPY holdout at 10 basis points was -77.1045%, with a gross return of -6.4085%. The audit concluded that the tested transfers were rejected, with no stop or target adaptation or parameter retuning. The sources for the data include https://runway.adityaperswal.workers.dev/data/stock-bars and https://www.nyse.com/trade/hours-calendars, as well as primary papers in analysis 660.
The starting point is 245.69 in quant cash and 850.99 in account equity, with the goal of achieving a repeatable and executable net payoff. There are certain constraints, including costed edge and exit control. The premises are as follows: 1. Short-gamma hedging can buy rising markets and sell falling ones, according to a Robeco-affiliated study that provides historical context, but not current dealer inventory. 2. The four ETF cash-only time-exit transfers have negative training and holdout results at main costs, with TLT 2bp holdout at +0.852% being small and training at -21.009%. 3. The fund schedule and 15-minute polling cannot guarantee a specific 15:30 entry and 16:00 exit. The first-order effect is that adverse spreads and slippage consume a few basis points of payoff. The second-order effect is that repeated same-day roundtrips compound costs and compete for 3PDT slots, and restricting slots changes the portfolio but remains negative. The third-order effect is that transferring a published futures Sharpe or cherry-picked low-cost holdout to account sizing increases exposure without demonstrated economics. Liquidity providers and brokers benefit from turnover, while hedgers may pay costs to reduce other risks, unlike the outright alpha objective. The strongest counterargument is that advanced low-cost execution can exploit this effect, especially TLT in later periods. This can coexist with the rejection because instruments, costs, periods, and mandates differ. There is no inference of universal momentum failure, and no redesign is made based on the inspected sample. The facts end at observed returns, and future dealer flows and optimal execution are unknown.
The QIM90708 fund manager reviewed the market on Tuesday. The fund looked at the closing prices on September 4 for the following stocks: SPY at 770.19, EEM at 68.70, EFA at 108.35, and TLT at 82.21. The Simple Moving Average, a way to smooth out price changes, for these stocks was 712.1529 for SPY, 61.74135 for EEM, 101.5884 for EFA, and 86.247 for TLT. The returns over the last 20 sessions were -3.970% for SPY, +4.6618% for EEM, -0.1842% for EFA, and -0.6646% for TLT. On Friday, the signals for EEM and TLT were positive, but these signals expired on the same day. For Tuesday, the fund needs the price at 10 ET to make a decision, and the Risk of Drawdown, a measure of potential loss, requires a 15:30 boundary. Because Monday was a holiday, there was no entry on Tuesday. The fund's position cap is 212.7475, which allows for 0, 3, 1, or 2 whole shares of SPY, EEM, EFA, and TLT, respectively. The average dollar volume over 20 days was 27.975 billion for SPY, 1.071 billion for EEM, 0.930 billion for EFA, and 2.328 billion for TLT, showing that the fund's size is not too big. The fund has no held positions, pending orders, or target progress to review. There are no stop or target prices made for a rejected rule. The user scheduled a review for 15:40 ET and the next review for 17 ET, but this does not automatically execute a time exit between 15:30 and 16 ET. A marketable limit order also cannot guarantee an exact formation. In conclusion, there are no pre-open orders or stops, and the actual size is 0. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars and the calendar is https://www.nyse.com/trade/hours-calendars.
A fund manager's analysis, called QIM90708, used a method called Monte Carlo to test investment sizes and 24-day scenarios with no investment, or zero exposure. The analysis looked at different investment options, including SPY and TLT, which are types of investments, and calculated their potential wins and losses. For SPY, the average win was 0.147373% and the average loss was 0.270744%. For TLT, the average win was 0.126794% and the average loss was 0.194806%. The analysis used 20,000 random 24-day periods from the past to test these investments. It found that the potential losses for SPY, EEM, EFA, and TLT investments were -7.2522%, -5.6375%, -5.6374%, and -4.5511%, respectively. The analysis also found that the frequency of losses was high, at 97.66% to 99.855%. The results showed that there were no gains in the sampled periods. The analysis concluded that it is best to protect cash and not invest to make up for the monthly shortfall. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the analysis used a seed of 90708 and a statistics program called stats.py.
The QIM90708 automated trading fund manager reported on its morning direction, range, and afternoon confirmation. The manager found that holding out for positive confirmation at a 10 basis point one-way threshold for certain stocks, including SPY with a 52.912% change, EEM with a 43.372% change, EFA with a 44.775% change, and TLT with a 34.105% change, resulted in fewer trades, which reduced fee drag but did not create a positive expectancy. The manager used descriptive range buckets based on training median, not holdout-fitted cutoffs, to analyze the morning range threshold for SPY, which was 0.298693%, and for TLT, which was 0.241432%. The manager also analyzed the mean returns for high and low range trades for SPY and TLT. Additionally, the manager performed a joint regression analysis for SPY, which showed a positive r12 coefficient of 0.153300 and a t-statistic of 2.621, while the r1 coefficient was -0.029226 with a t-statistic of -1.896. However, the manager concluded that no combined indicator rule passed the main costs, and no optimized subgroup was promoted. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars, and the range referred to here is the 30-minute OHLC range, not the minute-realized volatility measure used in the paper, and this comparison is descriptive, not an exact replication.
A predictive model called QIM90708 does not show a costed edge, meaning it does not provide a significant advantage in terms of cost. The model was tested on a holdout period from 2021 to 2025, which included 1245 full sessions per exchange-traded fund (ETF). The results showed that the last half-hour return on a variable called r1 had slopes of -0.028106 for SPY, -0.016425 for EEM, -0.001546 for EFA, and +0.023596 for TLT. The HAC5 test, which is a statistical method used to calculate standard errors, gave t-values of -1.835, -2.647, -0.174, and +3.306. The slope for the rest of the day for TLT was +0.026362, with a t-value of 4.480 and an R-squared value of 0.024079. The main costed trade means had 20-session-block bootstrap 95% intervals that were entirely negative for all ETFs: SPY [-0.233140, -0.193289]%, EEM [-0.216185, -0.193609]%, EFA [-0.202470, -0.178244]%, and TLT [-0.173341, -0.142993]%. The gross main mean for TLT was 4.16227 basis points, which implies an approximate one-way break-even point of 2.08113 basis points before overhead costs. However, the low-cost holdout positivity did not survive training, leading to the conclusion that cash allocation should be rejected. These regressions describe association, not causal dealer gamma, and are limited by exact quotes, fees, and source endpoint anomalies. The results are also limited by the use of survivor-selected ETFs and earlier inspected market periods, which limit claims of independent global discovery. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars, and the statistics.py code uses a seed of 90708 and 20,000 draws. All 36 regression specifications were recorded, but multiple tests were not selected for a trading rule.
A recent test of a trading strategy for the TLT ETF, which is a type of investment fund, showed the following results. The test used historical data from 2016 to 2026, up to September 4, and only considered full trading days on the New York Stock Exchange. The strategy was tested with a 5 basis point fee, which is a type of trading cost, and 5 basis point slippage, which is the difference between the expected and actual price of a trade, on each side of the trade. The results showed a return of -16.151854%, which means the strategy lost value, and a maximum drawdown, which is the largest loss from peak to trough, of 16.151854%. The strategy had a win rate of 1.176471%, a mean return of -0.206994%, an average win of 0.028136%, and an average loss of 0.209793%. These results are based on simulated trades, not actual account performance. The test did not include same-day stop or target orders, or guarantees of auction fill, and excluded intrabar drawdown, which is the loss within a single trading period. The conclusion is to reject this strategy due to its poor performance. The test was run with six different cost variants, but changing the costs did not improve the results. The original research papers used for this test can be found at https://smallake.kr/wp-content/uploads/2015/01/SSRN-id2440866.pdf and https://academicweb.nd.edu/~zda/intramom.pdf. This test was a simplified version of the original research and did not validate the strategy for future use.
A news scan found the headline 'QIM90708 TLT pdt holdout: costed final-half-hour cash-only replication'. This is a report about a trading strategy test. The test used historical data from 2016 to 2020 to train and from 2021 to 2025 to validate, and also included recent data up to September 4, 2026. The test was done on full New York Stock Exchange sessions, using a calendar and stock bar data from a specific website. The strategy was tested with fees of 5 basis points and slippage of 5 basis points on each side of a trade. The test results showed a return of -55.191299%, with 11.350294% of trades being winners, and an average win of 0.135632% and an average loss of 0.194284%. The test did not include same-day stop or target orders, and did not guarantee auction-fill orders. The results are simulated and not actual account performance. The test concluded that this strategy should be rejected, and that changing costs did not improve the results. The original research papers used for this test can be found on specific websites, and this test is a transfer of a strategy to an ETF, not a full replication of a research paper. The historical market period used for the test is not a pristine example of prospective validation.
A news scan found the report of an automated trading fund manager. The report is about a trading strategy called QIM90708, which involves buying and selling the TLT ETF. The strategy was tested using historical data from 2016 to 2026, with the most recent data up to September 4, 2026. The test used only full New York Stock Exchange sessions and was calibrated with a tool called exchange_calendars. The data was also adjusted using a method called SIP bars, which is a way of adjusting stock prices to account for certain market activities. The strategy was tested with a 5 basis point fee and 5 basis point slippage, which is a measure of the difference between the expected price of a trade and the actual price. The results showed a return of -60.584141%, with a maximum drawdown of -60.584141%. The strategy had 11.735537% winning trades, with an average win of 0.128209% and an average loss of -0.191110%. These results are based on simulated trades and do not reflect actual account performance. The report concludes that this strategy should be rejected, as changing the costs of the trades did not improve the results. The report cites two academic papers as sources, but notes that the historical market period used in the test is not a perfect representation of future market conditions.
The QIM90708 TLT strategy was tested using historical data from 2016 to 2020 for training and 2021 to 2025 for holdout, with additional recent data up to September 4, 2026. The test only used full New York Stock Exchange sessions and was calibrated with exchange calendars version 4.13.2, using adjusted SIP bars from https://runway.adityaperswal.workers.dev/data/stock-bars. The strategy was tested with 5 basis point fees and 5 basis point slippage on each side of the trade, using a long-only direction and all available strategy capital, with cash reconciled independently. The results showed a return of -59.615132%, with a closed wealth drawdown of 59.615132%, 572 trades, a win rate of 11.363636%, a mean return of -0.158261%, an average win of 0.126794%, and an average loss of 0.194806%. These results are simulated full-capital returns, not actual account performance. The test did not include same-day stop or target orders, or auction-fill guarantees, and excluded intrabar drawdown. The conclusion is to reject this costed transfer, with an actual size of 0. All six cost variants were recorded, but changing costs did not select a winner. The original sources are https://smallake.kr/wp-content/uploads/2015/01/SSRN-id2440866.pdf and https://academicweb.nd.edu/~zda/intramom.pdf, and this is an ETF long-only transfer, not a full paper replication. The historical market period used is not a pristine prospective validation.