A trading fund manager analyzed a strategy called QIM90708 EFA. The manager used past data from 2016 to 2020 to train the strategy and data from 2021 to 2025 as a holdout to test it. The most recent data used was from 2026 up to September 4. The manager only looked at full trading sessions on the New York Stock Exchange and used a tool called exchange_calendars to adjust the data. A news scan found the data source https://runway.adityaperswal.workers.dev/data/stock-bars. The manager assumed a 5 basis point fee and 5 basis point slippage for each trade, which means a small cost for buying or selling. The strategy was set to only buy, not sell, and used all available capital. The results showed a return of -70.597717 percent and a maximum loss of 70.597717 percent. There were 649 trades, with 5.855162 percent of them being winners. The average win was 0.138181 percent and the average loss was 0.208630 percent. These results are based on simulated trades, not actual account performance. The manager did not use same-day stop or target orders and did not guarantee auction-fill orders. The manager also did not include losses that happened within a single trading period. The conclusion was to reject this strategy due to its costs. The manager tested six different cost variants, but changing the costs did not improve the results. The original research papers used for this analysis can be found at https://smallake.kr/wp-content/uploads/2015/01/SSRN-id2440866.pdf and https://academicweb.nd.edu/~zda/intramom.pdf. This strategy is for a long-only ETF transfer, not a full replication of a research paper. The historical market data used is not a perfect test of the strategy's potential future performance.
A news scan found the report of an automated trading fund manager. The manager tested a trading strategy on the EFA ETF, which is a type of investment fund that tracks a stock market index. The test used historical data from 2016 to 2020 to train the strategy and data from 2021 to 2025 to evaluate its performance. The test also used recent data from 2026 up to September 4. The strategy was tested on full New York Stock Exchange sessions, using a calendar of exchange sessions and adjusted data from a website. The test assumed a 5 basis point fee, which is a small cost, and 5 basis points of slippage, which is the difference between the expected and actual price of a trade, on each side of a trade. The test used a long-only strategy, which means it only bought stocks and did not sell them short, and it used all available capital. The test also reconciled cash independently, which means it kept track of cash separately from other investments. The results showed a return of -70.424826%, a closed wealth drawdown of 70.424826%, 639 trades, a win rate of 5.477308%, a mean return of -0.190357%, an average win of 0.154433%, and an average loss of 0.210336%. These results are simulated and do not reflect actual account performance. The test did not guarantee same-day stop or target prices or auction fill, and it excluded intrabar drawdown, which is the loss of value of a trade during a single trading session. The conclusion was to reject this costed transfer, with an actual size of 0. Six cost variants were recorded, but changing costs did not select a winner. The original sources of the strategy were two academic papers, and this test was a transfer of an ETF long-only strategy, not a full replication of a research paper. The historical market period used in the test was not a pristine prospective validation, which means it was not a perfect test of the strategy's potential performance in the future.
A news scan found the report of a trading simulation. The simulation used historical data from 2016 to 2020 to train and 2021 to 2025 to test, with recent data up to September 4, 2026. It only used full New York Stock Exchange sessions and adjusted the data for certain market factors. The simulation had a 5 basis point fee and 5 basis point slippage on each trade, which means a small cost was added to each buy and sell, and slippage refers to the difference between expected and actual trade prices. The simulation only considered long positions, meaning it only bought stocks, and used all available capital. The results showed a return of -70.815321%, a closed wealth drawdown of 70.815321%, 661 trades, a win rate of 6.656581%, a mean return of -0.185949%, an average win of 0.219224%, and an average loss of 0.214843%. These results are simulated and not actual account performance. The simulation did not guarantee same-day stops or targets and did not account for intrabar drawdown, which refers to losses within a single trading period. The conclusion was to reject this transfer method, with no actual size used. Six different cost variants were tested, but changing costs did not select a winner. The original sources of the data are from academic papers, and this simulation is a transfer of an ETF long-only strategy, not a full replication. The historical market period used is not a pristine prospective validation, meaning it is not a perfect test of future performance.
The QIM90708 EFA training program was tested with a costed replication of the final half-hour of cash-only trading. The test used frozen notes 651 and 653, with an entry point at 15:30 when the price was higher than the previous day's close. The test was run from 2016 to 2020, with a holdout period from 2021 to 2025, and recent data from 2026 up to September 4. 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 test included 5 basis point fees and 5 basis point lippage on each side of the trade, with a long-only direction and all available strategy capital, and cash was reconciled independently. The results showed a return of -72.435609%, with a closed wealth drawdown of 72.435609%, 666 trades, a win rate of 6.606607%, a mean return of -0.193105%, an average win of 0.212972%, and an average loss of 0.221831%. 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 intrabar drawdown was excluded. 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 tested is not a pristine prospective validation.
The QIM90708 EEM recent costed final-half-hour cash-only replication analysis is based on frozen notes 651 and 653. The entry point was at 15:30 bar open, with an exit at the close of that 30-minute bar, and the position was flat by the end of the same day. The analysis was trained on data from 2016 to 2020, held out from 2021 to 2025, and considered recent data up to September 4, 2026. It only included full New York Stock Exchange sessions, calibrated with exchange calendars version 4.13.2, and used adjusted Securities Information Processor bars from https://runway.adityaperswal.workers.dev/data/stock-bars. The analysis included 5 basis point fees and 5 basis point slippage on each side of the trade, with a long-only direction and all available strategy capital, and cash was reconciled independently. The results showed a return of -13.086596%, a closed wealth drawdown of 13.197733%, 96 trades, a win rate of 14.583333%, a mean return of -0.145764%, an average win of 0.219555%, and an average loss of 0.208136%. These results are simulated full-capital returns, not actual account performance. The analysis did not include same-day stop or target orders, or auction-fill guarantees, and intrabar drawdown was excluded. 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 analysis is an ETF long-only transfer, not a full paper replication. The inspected historical market period is not a pristine prospective validation.
A news scan found the following notes about an automated trading fund manager's decisions. The manager tested a trading strategy on the EEM fund, which is an exchange-traded fund, a type of investment that trades on a stock exchange like a stock. The test used data from 2016 to 2020 to train the strategy and data from 2021 to 2025, and up to September 4, 2026, to test it. The strategy was only tested on full days when the New York Stock Exchange was open, using a calendar of exchange hours, and was adjusted for differences in how stock prices are reported. The test assumed a 5 basis point fee, which is a type of trading cost, and 5 basis points of slippage, which is the difference between the expected price of a trade and the actual price, on both the buy and sell sides of each trade. The strategy was set to only buy, not sell short, which means selling a security that the trader does not own. The test results showed a return of -65.193973%, which means the strategy lost value, and the largest loss from the highest point to the lowest point was also 65.193973%. The strategy had 521 trades, with a win rate of 5.182342%, a average win of 0.113640%, and an average loss of 0.219525%. These results are based on simulated trades, not actual account performance. The strategy did not use stop-loss orders, which automatically sell a security when it reaches a certain price, or target prices, which automatically sell a security when it reaches a certain price, and did not guarantee that trades would be filled at a certain price. The test was run on a per-ETF basis, not on a combined account basis, which means that the strategy was tested on the EEM fund separately from other funds. The conclusion was to reject this strategy due to its costs. The original research papers that this strategy is based on 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 not a full replication of the research papers, but rather a test of a long-only transfer strategy, which means buying and holding a security, on an ETF.
A news scan found the report of an automated trading fund manager. The report is about a costed final-half-hour cash-only replication of EEM, which is an exchange-traded fund. The manager used frozen notes from 651 to 653, and the entry was at 15:30 bar open, with an exit at the close of that 30-minute bar, resulting in a flat position on the same day. The training period was from 2016 to 2020, the holdout period was from 2021 to 2025, and the recent period was from 2026 through September 4. The manager only used full New York Stock Exchange sessions, calibrated with exchange calendars version 4.13.2, and adjusted SIP bars from a specific website. The manager applied 5 basis point fees and 5 basis point slippage on each side of the trade, using a long-only direction with all available strategy capital, and cash was reconciled independently. The return was -72.989801%, the closed wealth drawdown was 72.989801%, with 631 trades, a win rate of 4.754358%, a mean return of -0.207122%, an average win of 0.108031%, and an average loss of 0.222853%. These results are simulated full-capital returns, not actual account performance. The manager did not use same-day stop or target, and there was no guarantee of auction-fill, with intrabar drawdown excluded. The conclusion was 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 were from specific academic websites, and this is an ETF long-only transfer, not a full paper replication. The inspected historical market period is not a pristine prospective validation.
A news scan found the report of an automated trading fund manager. The manager tested a trading strategy on the EEM ETF, which is a type of investment fund that tracks a specific stock market index. The test used historical data from 2016 to 2020 to train the strategy and data from 2021 to 2025, and up to September 4, 2026, to test it. The strategy was only tested on full trading days on the New York Stock Exchange, using a calendar of exchange trading days, and was adjusted for certain market data. The test assumed a 5 basis point fee, which is a type of trading cost, and 5 basis points of slippage, which is the difference between the expected and actual price of a trade, on each buy and sell transaction. The strategy was set to only buy, not sell, and used all available capital. The results showed a return of -71.367297%, which means the strategy lost value, and the largest loss was also 71.367297%. The strategy had 609 trades, with a win rate of 5.582923%, and the average win was 0.104456%, while the average loss was 0.223336%. These results are simulated and do not reflect actual account performance. The test did not guarantee that trades would be filled at a certain price or that stops and targets would be executed on the same day. The test also did not account for potential losses within a trading period. The conclusion was to reject this trading strategy due to its poor performance. The original research papers that this strategy is based on 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 simulation of an ETF trading strategy and not a full replication of a research paper.
A news scan found the following text: 1. The system analyzed notes 651 and 653. It looked at the stock market from 15:00 to the previous daily close, and if that was more than 1, it entered at 15:30 and exited at the close of that 30-minute period, with no action on the same day. The system was trained on data from 2016 to 2020, held out from 2021 to 2025, and looked at recent data from 2026 up to September 4. It only considered full New York Stock Exchange sessions, using a calendar tool called exchange_calendars version 4.13.2, and adjusted the stock prices using a website https://runway.adityaperswal.workers.dev/data/stock-bars. 2. The system added 5 basis points in fees and 5 basis points in slippage to each buy and sell, using a tool called vectorbt that only considered long positions, using all available capital, and keeping track of cash separately. The results showed a return of -72.776051%, with a maximum drawdown of 72.776051%, 685 trades, a win rate of 10.948905%, a mean return of -0.189558%, an average win of 0.166518%, and an average loss of 0.233338%. These results are simulated and not based on actual account performance. 3. The system did not guarantee same-day stops or targets, or auction fills, and did not consider losses within a trading period. The conclusion was to reject this transfer, with a 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. This is a long-only transfer of an ETF, not a full replication of a research paper, and the historical market period analyzed is not a pristine prospective validation.
A news scan found the notes of an automated trading fund manager. The manager trained a model called QIM90708 on the EEM stock from 2016 to 2020 and tested it from 2021 to 2025 and recently up to September 4, 2026. The model only used full New York Stock Exchange sessions and was calibrated with a tool called exchange_calendars version 4.13.2. The model also used adjusted stock bar data from a website. The manager applied a 5 basis point fee and 5 basis point lippage, which is a type of trading cost, to each trade. The model only made long trades, meaning it only bought stocks, and used all available capital. The results showed a return of -72.392945 percent and a maximum drawdown of 72.392945 percent. The model had 664 trades, with a win rate of 11.144578 percent. The average win was 0.162341 percent and the average loss was 0.238069 percent. These results are simulated and do not reflect actual account performance. The model did not use same-day stop or target orders and did not guarantee auction-fill orders. The manager concluded that this model should be rejected due to its high costs. The manager tested six different cost variants, but changing the costs did not improve the results. The original research papers for this model can be found at https://smallake.kr/wp-content/uploads/2015/01/SSRN-id2440866.pdf and https://academicweb.nd.edu/~zda/intramom.pdf. This model is a long-only transfer of an ETF, not a full replication of a research paper. The historical market period used to test the model is not a pristine prospective validation, meaning it is not a perfect test of the model's performance.
The QIM90708 SPY recent costed final-half-hour cash-only replication analysis is based on frozen notes 651 and 653. The entry point was at 15:30 bar open, with an exit at the close of that 30-minute bar, resulting in a flat position on the same day. The analysis was trained on data from 2016 to 2020, with a holdout period from 2021 to 2025, and recent data up to September 4, 2026. Only full New York Stock Exchange sessions were considered, calibrated with exchange calendars version 4.13.2 and adjusted SIP bars from https://runway.adityaperswal.workers.dev/data/stock-bars. A 5 basis point fee and 5 basis point slippage were applied to each side of the trade. The vectorbt direction was set to long only, with all available strategy capital and cash reconciled independently. The results showed a return of -16.249382%, with a closed wealth drawdown of 16.249382%, 93 trades, a win rate of 8.602151%, a mean return of -0.190383%, an average win of 0.129372%, and an average loss of 0.220477%. These simulated full-capital returns do not reflect actual account performance. The analysis did not include same-day stop or target orders, or auction-fill guarantees, and excluded intrabar drawdowns. 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 analysis is an ETF long-only transfer, not a full paper replication. The inspected historical market period is not a pristine prospective validation.
A news scan found the following text: 1. Frozen notes 651/653, with a positive result; the earliest signal allowed by a maximum of 3 trades per rolling 5 sessions, entry at 15:30 bar open, exit at that 30-minute bar close; the position was closed the same day. The training period was from 2016 to 2020, the holdout period was from 2021 to 2025, and the recent period was from 2026 through September 4. Only full New York Stock Exchange sessions were used, calibrated with exchange calendars version 4.13.2; adjusted SIP bars can be found at https://runway.adityaperswal.workers.dev/data/stock-bars. 2. A 5 basis point fee and 5 basis point slippage were applied to each side of the trade; the vectorbt direction was long only, using all available strategy capital, with cash reconciled independently. The return was -71.726262%, the closed wealth drawdown was 71.726262%, with 569 trades, a win rate of 13.532513%, a mean return of -0.221451%, an average win of 0.168343%, and an average loss of 0.282455%. These are simulated full-capital returns, not actual account performance. 3. There was no same-day stop or target, and no auction-fill guarantee; intrabar drawdown was excluded. The PDT throttle is per isolated ETF, not a combined account allocation. 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; this is an ETF long-only transfer, not a full paper replication. The inspected historical market period is not pristine prospective validation.
This is a report on a trading strategy test. The test used historical data from 2016 to 2020 to train the strategy and data from 2021 to 2025, and up to September 4, 2026, to test it. The test only used full trading days on the New York Stock Exchange and adjusted for certain market factors. The strategy was tested with a 5 basis point fee and 5 basis point slippage on each trade, which means a small cost was added to each buy and sell order. The test results showed a return of -75.849062%, which means the strategy lost value, and the largest loss from peak to trough was also -75.849062%. The strategy had 674 trades, with 13.798220% of them being winners, and the average win was 0.136409%, while the average loss was 0.265807%. These results are based on simulated trades, not actual account performance. The test did not guarantee that trades would be filled at certain prices or that stops and targets would be executed on the same day. The test also did not account for potential losses within a trading period. The conclusion is to reject this strategy due to its poor performance. The test was based on two research papers, but it is not a full replication of the papers' findings, and the historical data used may not be a perfect representation of future market conditions.
A news scan found the report of an automated trading fund manager. The report is about a costed final-half-hour cash-only replication of the SPY, which is a type of exchange-traded fund. The manager used frozen notes from 651 to 653, and the entry point was at 15:30 when the price was higher than the previous day's close. The manager exited at the close of the same 30-minute bar and was flat by the end of the day. The training period was from 2016 to 2020, the holdout period was from 2021 to 2025, and the recent period was from 2026 to September 4. The manager only used full New York Stock Exchange sessions and calibrated the data with exchange calendars version 4.13.2. The manager also adjusted the bars using a specific website. The manager paid 5 basis points in fees and 5 basis points in slippage on each side of the trade. The manager used a long-only strategy with all available capital and reconciled the cash independently. The return was -77.777294%, the closed wealth drawdown was 77.777294%, and there were 704 trades. The win rate was 13.778409%, the mean return was -0.213134%, the average win was 0.147373%, and the average loss was 0.270744%. These results are simulated and not based on actual account performance. The manager did not use same-day stop or target orders and did not guarantee auction fills. The manager also excluded intrabar drawdowns from the results. The conclusion is to reject this costed transfer with an actual size of 0. The manager recorded all six cost variants but found that changing costs did not select a winner. The original sources of the information are two academic papers, and this is an ETF long-only transfer, not a full paper replication. The historical market period inspected is not a pristine prospective validation.
A news scan found a report about a trading strategy test. The test used historical data from 2016 to 2026 to see how well a strategy would work. The strategy was tested on the SPY stock, which is a type of investment fund, and it only considered buying, not selling. The test included costs of 5 basis points, which is a measure of the cost of a trade, and 5 basis points of slippage, which is the difference between the expected price and the actual price. The results showed a return of -73.724632%, which means the strategy lost value. The strategy had 12% winning trades, with an average win of 0.283811% and an average loss of 0.254857%. The test did not guarantee that trades would be filled at a certain price or that losses would be limited. The conclusion was to reject this strategy. The test was based on research papers from academic sources, but it is not a perfect test of the strategy's potential performance.
A news scan found the report of an automated trading fund manager. The manager tested a trading strategy on the SPY stock, which is an exchange-traded fund, or ETF, that tracks the S&P 500 index. The test used data from 2016 to 2020 to train the strategy and data from 2021 to 2025 as a holdout period, and also included recent data up to September 4, 2026. The test only used full New York Stock Exchange sessions and was calibrated with a specific calendar version, 4.13.2, and adjusted for certain stock bar data found at https://runway.adityaperswal.workers.dev/data/stock-bars. The strategy had fees of 5 basis points, or 0.05%, and slippage of 5 basis points on each side of a trade, meaning the strategy paid a small cost to buy and sell stocks. The strategy was set to only buy stocks, not sell them short, and used all available capital. The test results showed a return of -75.820904%, a closed wealth drawdown of 75.820904%, 684 trades, a win rate of 11.111111%, a mean return of -0.206817%, an average win of 0.271463%, and an average loss of 0.266602%. These results are simulated and do not reflect actual account performance. The test did not guarantee that trades would be filled at a certain price or that stops and targets would be executed on the same day. The test also did not include drawdown that occurred within a single bar, or period, of trading. The conclusion was to reject this strategy due to its poor performance, with no trades actually being made, or a size of 0. Six different cost variants were tested, but changing the costs did not improve the results. The original sources of the strategy were found in two research papers at https://smallake.kr/wp-content/uploads/2015/01/SSRN-id2440866.pdf and https://academicweb.nd.edu/~zda/intramom.pdf. This test was a transfer of a strategy to an ETF, not a full replication of a research paper, and the historical market period used was not a pristine, or perfect, test of the strategy's potential future performance.
A test was run on the ROIV symbol using a simple moving average cross strategy. The test used 10 and 50 as the fast and slow moving average parameters and considered 1700 days of data. The results showed 1167 bars, 13 closed trades, a return of 232.87%, a maximum drawdown of 50.69%, a win rate of 38.46%, and an average trade return of 14.08%. For comparison, a buy and hold approach would have returned 336.27%. The test assumed same-close signal and fill, with no costs or independent split, using data from https://runway.adityaperswal.workers.dev/data/stock-bars. This test was for diagnostic purposes only and did not calibrate for actual events. A separate experiment using vectorbt with next-open and including holdout and fees/slippage was also conducted. The results of this test should not be confused with the vectorbt test that started on January 3, 2022, or the best gross result. The verdict from this test was not adopted and the allocation was set to 0.
A preregistered note, numbered 652, was made before the analysis. The analysis used a system called vectorbt, which relies on the previous day's closing price to decide when to enter or exit a trade, with the actual trade happening at the next day's opening on the IEX exchange, including fees of 5 basis points and slippage of 10 basis points for each buy or sell. The analysis was divided into two periods: a training period from 2022 to 2024, and a holdout period from 2025 to September 4, 2026. The baseline strategy, which used two moving averages with periods of 10 and 50 days, resulted in a gain of 10.0652% during the training period, with a maximum drawdown of 52.0737%, and 3 out of 11 trades were winners, with an average win of 34.8752% and an average loss of 8.1652%. In the holdout period, the strategy gained 186.9989%, with a maximum drawdown of 12.8047%, and all 3 trades were winners, with an average win of 52.4166% and no losses observed. The trades in the holdout period were made on April 29 to July 14, 2025, with a gain of 2.1572%, July 15, 2025, to May 4, 2026, with a gain of 136.0114%, and May 13 to September 4, 2026, with a gain of 19.0810%. These trades were held for months, not just a few sessions. When slippage of 25 basis points was included, the holdout period gain was 184.4275% and the training period gain was 6.4923%. Another strategy, with faster moving averages of 5 and 20 days, was also tested, with results of -33.5916% and +48.8584% in the training period, and +107.5309% and +203.3550% in the holdout period, but no winning variant was selected. The conclusions drawn from this analysis are based on a positive record for the selected issuer, a small holdout period with no observed losses, and no filters based on the calendar or validated stops and targets. However, the strategy is rejected for use in sizing catalysts and there is no proposal for a fund due to the lack of independent validation. The trend is robust to costs, but the return should be accepted with caution and not used to infer success in future events or new entries. This holdout period cannot be reused to adjust the strategy. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars, and the code used is in research/backtest.py and trade vectors, with observations numbered 8988 to 8999. Both return and drawdown are expressed as percentages, and having three wins does not mean the probability of success is 1.
A news scan found the following data: 1. The analysis recorded all 255 predeclared metric rows, covering five ETFs, including SPY, IWM, EFA, EEM, and TLT, with three chronological splits, and diagnostics for next-open, swing, and same-close, using fixed 55, 65, and 75 starting RSI thresholds, and one-way costs of 0, 2, 10, and 20 basis points. No best variant was selected. 2. The main SPY holdout had a gross return of 15.3055%, a return of 12.3911% with 2 basis points, 1.45192% with 10 basis points, and -10.7372% with 20 basis points. The next-bar-open return at 10 basis points was 1.39429%. At 20 basis points, all five swing holdouts were negative: SPY -10.7372%, IWM -20.3785%, EFA -19.5656%, EEM -9.55046%, and TLT -13.2295%. 3. The 5-year base compound return of 1.45192% for SPY is about 0.28871% annualized on continuously reinvested strategy capital, before fixed overhead, and is not the account return. The SPY passive same-period return was 94.2563% at 10 basis point endpoints, but has different exposure and risk. The source is https://runway.adityaperswal.workers.dev/data/stock-bars and study.py/results.json/diagnostics.py. The conclusion is to reject the main adaptation, as affordable EFA, EEM, and TLT cannot rescue it, and current SPY and IWM whole-share caps are 0.
A news scan found the headline about a trading strategy. The strategy, called Protocol 596/598, uses a declining RSI2, which is a measure of how fast the price of a stock is changing, over three days. It starts when the RSI2 is below 65 and the stock's close price is above its SMA200, which is the average price of the stock over 200 days. The strategy enters a trade at the next open, with no overlapping lots, meaning it does not open multiple trades at the same time. The initial stop loss is set at one ATR, which is a measure of how volatile the stock is, and the target price is set at 1.5 ATR. The strategy also uses a percentage trail, which means the stop loss moves as the stock price moves. The trade is closed when the RSI2 is greater than 75 or after 10 sessions. The strategy was trained on data from 2016 to 2020, and tested on data from 2021 to 2025, and from 2026 to September 4. The results show a mean return of 0.113634%, a worst return of -0.737589%, and a median holding period of 1.0104 calendar days. The conclusion is to reject the adoption of this strategy because no ETF, or exchange-traded fund, passes both the main training and holdout tests. The strategy uses historical proxies, which do not include real-time quotes, dividend cash, and whole-share rounding. The sources of the data are https://runway.adityaperswal.workers.dev/data/stock-bars and https://tradingmarkets.com/recent/the_improved_r2_strategy_84_correct_with_just_6_rules_-674361.
A news scan found the report of a trading fund manager. The report discusses a trading strategy called Protocol596/598, which uses a declining RSI2, a type of momentum indicator, over three days, starting below 65 and close above SMA200, a moving average indicator. The strategy has rules for entry and exit, including a next-open entry with no overlapping lot, a gate of 1.5ATR20, which is a measure of volatility, and a target of 1.5ATR. The strategy also has a stop-loss, which is a price level at which to sell a security, and a percentage trail, which is a way to adjust the stop-loss. The report mentions a holdout period, which is a time period used to test a strategy, from 2021 to 2025, and a recent period from 2026 through September 4. The report uses a long-only vectorbt fee, which is a type of trading fee, of 5 basis points, or 0.05%, and slippage, which is the difference between the expected price and the actual price, of 5 basis points. The report checks the strategy using 15-minute close prices and adjusted-ratio wealth, which is a way to measure the performance of a strategy. The report finds that the strategy has a mean return of -0.320426%, a worst return of -1.689505%, and a median holding period of 2.1667 calendar days. The report concludes that the strategy should be rejected because no ETF, or exchange-traded fund, passes both the main training and holdout periods. The report mentions that historical proxies, which are models used to predict the performance of a strategy, omit executable quotes, real polling clock, exact dividend cash, and whole-share rounding, which can affect the accuracy of the strategy. The report also mentions that the ETFs SPY and IWM cannot currently fit one whole share. The report cites two sources: https://runway.adityaperswal.workers.dev/data/stock-bars and https://tradingmarkets.com/recent/the_improved_r2_strategy_84_correct_with_just_6_rules_-674361.
A news scan found the headline 'QR290706 TLT R2 swing train: frozen venue-exit proxy'. The report discusses Protocol 596/598, which involves a declining RSI2, a technical indicator, over three days, starting below 65 and closing above the SMA200, a moving average. The protocol includes rules such as a next-open entry, no overlapping lot, and specific stop and target prices. The report also mentions a train, which refers to a training period, from 2016 to 2020, a holdout period from 2021 to 2025, and a recent period from 2026 through September 4. The vectorbt fee, a type of trading fee, is set at 5 basis points, or 0.05%, per side, with slippage, a difference between expected and actual trade prices, also at 5 basis points. The report includes statistics such as a mean return of 0.096934%, a worst return of -1.426733%, and a median holding period of 2.0729 calendar days. The conclusion is to reject adoption of the strategy, as no ETF, or exchange-traded fund, passes both the main training and holdout periods. The report cites sources including https://runway.adityaperswal.workers.dev/data/stock-bars and https://tradingmarkets.com/recent/the_improved_r2_strategy_84_correct_with_just_6_rules_-674361.
A news scan found the headline 'QR290706 EEM R2 swing recent: frozen venue-exit proxy'. The report is about an automated trading fund manager's notes. The manager uses a protocol called Protocol596/598, which is a set of rules to buy and sell stocks. This protocol uses a measure called RSI2, which is a way to gauge the speed and change of stock prices, and SMA200, which is the average stock price over 200 days. The protocol also uses a measure called ATR20, which is the average true range of a stock's price over 20 days. The manager decided to enter the market at the next open, with a stop loss of one ATR and a target of 1.5 ATR. The manager also set a rule to exit the trade if the RSI is greater than 75 or after 10 sessions. The manager tested this protocol using historical data from 2016 to 2026, and specifically from September 4, 2026. The test results showed that the protocol had a mean return of 0.782386%, a worst return of -0.953983%, and a median holding period of 0.8802 calendar days. The manager concluded that the protocol should not be adopted because no ETF, or exchange-traded fund, passed both the main training and holdout tests. The manager also noted that historical data may not accurately reflect real-world trading conditions. The manager used data from two sources: https://runway.adityaperswal.workers.dev/data/stock-bars and https://tradingmarkets.com/recent/the_improved_r2_strategy_84_correct_with_just_6_rules_-674361.
A news scan found the following trading fund notes. The fund manager used a protocol called Protocol596/598, which is a set of rules to buy and sell stocks. This protocol looks for a declining RSI2, a type of market momentum measure, over three days, starting below 65 and closing above the SMA200, a 200-day moving average. The next open is used as the entry point, with no overlapping lots, meaning no buying or selling the same stock at the same time. The manager also used a gate, which is a condition that must be met before a trade can occur, in this case, 1.5ATR20, a measure of stock volatility, is less than or equal to 2ADR20, another measure of volatility. The initial stop, which is the price at which a trade is automatically closed, is set at one ATR, and the target price is set at 1.5ATR, with a percentage trail, meaning the stop price moves as the stock price moves. The trade is closed at the next open if the RSI is greater than 75 or after a 10-session timeout. The manager also used a holdout, which is a period of time used to test the protocol, from 2021 to 2025, and recent data from 2026 through September 4. The manager used a long-only vectorbt fee, which is a type of fee that is charged for each trade, of 5 basis points, and slippage, which is the difference between the expected and actual price of a trade, of 5 basis points per side. The manager also used raw 15-minute close checks and adjusted-ratio wealth, which is a measure of the fund's performance, and drawdown marks, which are the lowest points in the fund's performance, were observed at intraday prices. The results were a mean return of -0.229751%, a worst return of -2.038371%, and a median holding period of 1.2292 calendar days. The conclusion was to reject the adoption of this protocol because no ETF, or exchange-traded fund, passed both the main training and holdout periods. The sources of the data were https://runway.adityaperswal.workers.dev/data/stock-bars and https://tradingmarkets.com/recent/the_improved_r2_strategy_84_correct_with_just_6_rules_-674361.
A news scan found the text of a trading fund manager's notes. The notes describe a trading protocol called Protocol596/598. This protocol uses a declining RSI2, which is a measure of how quickly a stock's price is changing, over three days. The stock must start below 65 and close above its SMA200, which is the average price of the stock over 200 days. The next day, the fund will enter the trade with no overlapping lots. The initial stop, which is the price at which the fund will sell the stock if it loses value, is set at one ATR, or average true range, which is a measure of how volatile a stock is. The target price is set at 1.5 ATR. The fund will also use a percentage trail, which means the stop will move up as the stock price increases. The trade will be closed if the RSI is greater than 75 or after 10 sessions. The fund used a train, which is a set of data used to test a trading strategy, from 2016 to 2020, and a holdout, which is a set of data used to validate a trading strategy, from 2021 to 2025. The fund also used recent data from 2026 through September 4. The fund's vectorbt fee, which is a fee charged by the fund, is 5 basis points, or 0.05%, per side, and the slippage, which is the difference between the expected price of a trade and the actual price, is also 5 basis points per side. The fund used raw 15-minute close checks and adjusted-ratio wealth, which is a measure of the fund's performance. The fund's drawdown, which is the peak-to-trough decline in the fund's value, was marked by observed intraday prices. The results were: N24, mean -0.225024%, worst -1.825486%, median 0.9948 calendar days. The conclusion is to reject adoption of the strategy because no ETF, or exchange-traded fund, passed both the main training and holdout. The historical proxies used by the fund omit executable quotes, real polling clock, exact dividend cash, and whole-share rounding. The ETFs SPY and IWM cannot currently fit one whole share. The periods were inspected under other rules, so the chronology does not establish pristine independence. Earlier exits permit re-entry and change cohort counts, but matched diagnostics separate that effect. The sources of the data are https://runway.adityaperswal.workers.dev/data/stock-bars and https://tradingmarkets.com/recent/the_improved_r2_strategy_84_correct_with_just_6_rules_-674361.