A trading strategy called CNXC91106 was tested. The strategy had two main rules: first, it used certain dates from the issuer, entering trades 10 days before and exiting the day before the event, excluding events that happened after the market closed or before it opened. It also excluded announcements made on the same day as the trade entry. Second, it used past data from 2021 to 2024 to train the strategy and data from June 2025 to September 2026 to test it. The strategy used a stop-loss at 1 average daily range below the entry price and a target at 3 average daily ranges above the entry price. If the trade opened with a gap, it would stop the trade. The strategy only considered long trades, with fees of 5 basis points and slippage of 25 basis points on each side. The returns were compounded and reconciled manually. A news scan found the headline was not needed, instead the strategy used synthetic data for bookkeeping. The strategy was tested with different variants, but all of them had negative returns, so it was not adopted. The data used for the strategy came from individual company URLs and a website. The test had some limitations, including only using data from one company, looking back at past events, and assuming certain costs.
A trading fund manager made notes about a trading strategy called CNXC91106. The strategy has two main rules: first, the manager looks at announcements from companies, but only if they happen before a certain date, and second, the manager uses a special adjustment called SIP to look at daily stock prices for two specific stocks, 1451CNXC and 1470SPY, from 2021 to 2026. The manager uses a computer program called vectorbt to make trades, only buying stocks and paying a fee of 5 basis points and a slippage of 45 basis points for each trade. The manager looks at the returns on investment and the number of trades made, and also considers the drawdown, which is the difference between the highest and lowest values of the investment. The manager uses a special measure called mean excess pp to compare the returns to a benchmark, and tests different variations of the strategy. The manager concludes that the strategy is not working because all the variations have negative returns, and even the positive results in the test period cannot make up for the losses. The manager got the data from individual company websites and a website called https://runway.adityaperswal.workers.dev/data/stock-bars. The manager notes that the study has some limitations, including only looking at one company, using old data, and not considering some costs and news events.
A news scan found the text describing the CNXC91106 T-10 time exit train with a 50bp/side condition. The premises of this trading strategy are as follows: first, the strategy uses Freeze2229, which involves entering trades at the open on T-10 and exiting at the close on T-1, excluding event sessions for AMC and BMO, and only considering announcements that predate the entry date. Second, the strategy uses a SIP adjustment with all 1451CNXC and 1470SPY daily bars through 2026-09-10, training from 2021 to 2024, and holding out from June 2025 to 2026. The strategy has a fixed calendar time exit with no stop and is for research control only, not eligible for live policy. Third, the strategy uses vectorbt with long-only orders, fees of 5bp, and slippage of 45bp on each side. The returns and trade counts are reconciled manually, and the initial cash is included in the mark-to-market drawdown. The strategy also uses synthetic two rows per day for bookkeeping, not intraday data, and a fractional capital reinvestment proxy. The mean excess return is the difference against the full T-10/T-1 SPY interval, not exposure-matched alpha. The conclusion is that there will be no adoption of this strategy because all training variants had a negative compounded return, and the positive holdout in T3 cannot rescue the failed train. The sources of the issuer URLs are individually listed in observations 24553-24575, and additional data can be found at https://runway.adityaperswal.workers.dev/data/stock-bars. The limitations of this strategy include the selection of a single company, retrospective calendar recovery, overlap with 2023 Webhelp, 22 events, possible early news, assumed costs, and a 15-minute and +2R policy that is separate.
A trading fund manager made decisions based on certain premises. The first premise is about a trading strategy called Freeze2229, which involves entering trades 10 days before a certain event and exiting on the day before the event, excluding events that happen after the market closes or before it opens. The manager also considered a system called SIP adjustment, which looked at daily stock prices for CNXC and SPY from 2021 to 2026, with a specific time period set aside for testing. The manager used a system called vectorbt to make trades, only going long, with fees of 5 basis points and slippage of 25 basis points on each side. The manager manually checked the returns and trade counts, and included the initial cash in the calculations. The manager also used a system to track the performance of the trades, comparing it to the performance of the SPY stock over a certain time period. The manager tested different variations of the strategy, but none of them had a positive return, so the manager decided not to adopt the strategy. The manager got the data from individual company websites and a website called https://runway.adityaperswal.workers.dev/data/stock-bars. The manager noted some limitations of the study, including that it only looked at one company, used past data, and did not account for all possible costs and news events.
A news scan found the following trading fund notes. The fund manager made three premises. First, the manager considered Freeze2229, which involves the issuer's advance dates, entering at T-10 open and exiting at T-1 close, excluding event sessions for AMC and BMO. Announcements must be made before the entry date, and same-day unknown release times are excluded. Second, the manager made a SIP adjustment using all 1451CNXC and 1470SPY daily bars through 2026-09-10, training from 2021 to 2024, and holding out from June 2025 to 2026. The manager used a fixed calendar time exit with no stop, for research control only, and not for live policy. A stop is a price level that, when reached, automatically closes a trade. Third, the manager used vectorbt, a backtesting framework, with long-only orders, 5 basis points fees, and 25 basis points slippage on each side. Basis points are units of measurement for interest rates and fees. Slippage refers to the difference between expected and actual trade execution prices. The manager reconciled compounded returns and trade counts manually and included initial cash in mark-to-market drawdown. Mark-to-market is a method of valuing assets at current market prices. The manager used synthetic two rows per day for bookkeeping, not intraday data, and fractional capital reinvestment proxy. The mean excess return is the difference against the full T-10/T-1 SPY interval, not exposure-matched alpha. Alpha refers to the excess return of an investment relative to the market. The manager froze Sweep3/5/10 and fixed primary T5, reporting all variants without picking a test winner. The conclusion was no adoption because all training variants had negative compounded returns, and T3 positive holdout could not rescue the failed train. The sources are issuer URLs individually in observations 24553-24575 and https://runway.adityaperswal.workers.dev/data/stock-bars. The limitations include a selected company, retrospective calendar recovery, 2023 Webhelp overlap, 22 events, possible early news, assumed costs, and 15-minute and +2R policy separate.
A news scan found the following trading notes. The trading strategy is based on two premises. First, the strategy involves entering a trade five days before a specific event and exiting the trade one day before the event, excluding events that happen after the market closes or before it opens. The strategy also excludes announcements that are made on the same day as the trade entry, if the release time is unknown. Second, the strategy uses historical data from 2021 to 2024 to train a model, and then tests the model on data from June 2025 to September 10, 2026. The strategy involves setting a stop loss at 1 average daily range below the entry price and a target at 3 average daily ranges above the entry price. If the market opens with a large gap, the stop loss is triggered. The strategy only considers long trades, and it includes fees of 5 basis points and slippage of 45 basis points on each side of the trade. The returns are compounded and reconciled manually. The strategy also includes a bookkeeping adjustment to account for fractional capital reinvestment. The results show that all training variants had negative compounded returns, and even the positive holdout results were not enough to rescue the failed training. The sources of the data are listed individually, and the data can be found at https://runway.adityaperswal.workers.dev/data/stock-bars. The strategy has several limitations, including the selection of a specific company, the use of retrospective calendar recovery, and the assumption of certain costs. A headline about the trade results mentioned a 50 basis point per side stop and a 3 average daily range target holdout.
A news scan found the following trading notes. The premises of the trade are as follows: the trade is based on an automated system called Freeze2229, which uses issuer advance dates to enter a trade five days before an event and exit the day before the event, excluding events that happen at the start or end of the trading day. The system also excludes announcements that are made on the same day as the trade entry, if the exact release time is unknown. The system was trained on historical data from 2021 to 2024, using daily price bars for the ticker symbols 1451CNXC and 1470SPY up to September 10, 2026. The system uses a stop-loss at 1 average daily range below the entry price and a target at 3 average daily ranges above the entry price. If the trade opens with a gap, the stop-loss is triggered. The system only considers long trades, with fees of 5 basis points and slippage of 45 basis points on each side. The returns and trade counts are reconciled manually, and the initial cash is included in the mark-to-market drawdown. The system uses a mean excess return metric, which is the difference between the return of the trade and the return of the SPY ticker over the same period. The results of the trade are negative, with all training variants showing a negative compounded return. The system was tested on a holdout period from June 2025 to June 2026, but the results were not positive enough to rescue the failed training period. The sources of the data are listed in observations 24553 to 24575, and are also available at https://runway.adityaperswal.workers.dev/data/stock-bars. The limitations of the system include the selection of a single company, retrospective calendar recovery, overlap with web help in 2023, 22 events, possible early news, assumed costs, and a 15-minute and 2R policy that is separate from the main system.
A trading strategy called CNXC91106 was tested. The strategy had two main rules: first, it would start trading five days before a certain event and stop trading one day before the event, excluding events that happen at the start or end of the trading day. Second, it would use past data from 2021 to 2024 to train the strategy and then test it from June 2025 to September 10, 2026. The strategy would buy a stock and set a stop-loss at the price minus one average daily range and a target at the price plus three average daily ranges. If the stock opened at a bad price, the strategy would stop the trade immediately. The strategy was tested with fees of 5 basis points and slippage of 25 basis points on each trade. The results showed that the strategy did not work well, with all versions of the strategy having negative returns during the training period. Even the version that worked well during the test period could not make up for the losses during training. The data used for the test came from the internet and a website called runway.adityaperswal.workers.dev. There were some limitations to the test, including only using data from one company and not accounting for all possible costs and news events.
A trading strategy called CNXC91106 was tested. The strategy had two main rules: first, it looked at the dates when companies announced their financial results, and it started trading five days before these announcements and stopped one day before. It avoided trading on the days of the announcements if they happened before or after the market closed. Second, it used past data from 2021 to 2024 to train the strategy and data from 2025 to June 2026 to test it. The strategy was tested on a specific stock, CNXC, and compared to the performance of the SPY stock index. The goal was to make money by buying the stock, with a stop-loss at 1 average daily range below the entry price and a target at 3 average daily ranges above the entry price. A stop-loss is a price at which to automatically sell a stock to limit losses, and a target is a price at which to automatically sell a stock to secure profits. The average daily range is the difference between the highest and lowest prices of a stock in a day. The strategy also accounted for fees and slippage, which is the difference between the expected price of a trade and the actual price. The results showed that the strategy did not work well, with all versions of the strategy resulting in negative returns. This means that the strategy lost money. The data used for the test came from individual company websites and a website called https://runway.adityaperswal.workers.dev/data/stock-bars. The test had some limitations, including only looking at one company, using past data, and not accounting for all possible costs and news events.
This is a report about a trading strategy called CNXC91106. The strategy is based on two main ideas: first, to buy and sell stocks based on certain dates, and second, to adjust the strategy using historical data from two stocks, 1451CNXC and 1470SPY, from 2021 to 2026. The strategy was tested using a computer program called vectorbt, which simulated buying and selling with certain fees and slippage, meaning the difference between expected and actual prices. The results showed that the strategy did not work well, with negative returns in all training variants, and even a positive result in one test period could not make up for the overall failure. The data used for this strategy came from individual company websites and a website called https://runway.adityaperswal.workers.dev/data/stock-bars. There are some limitations to this strategy, including that it only looked at one company, used past data, and did not account for all possible costs and news events.
A news scan found the following text: Premises for the CNXC91106 T-5 time exit train with 50 basis points per side are as follows. The first premise is called Freeze2229, which involves the issuer's advance dates, entering at T-5 open and exiting at T-1 close, excluding event sessions for after-market close and before-market open announcements. Announcements must be made before the entry date, and same-day unknown release times are excluded. The second premise involves a SIP adjustment using all 1451CNXC and 1470SPY daily bars through 2026-09-10, training from 2021 to 2024, and a chronological holdout from June 2025 to 2026. The exit is based on a fixed calendar time with no stop, and is for research control only, not eligible for live policy. The third premise uses vectorbt with long-only orders, fees of 5 basis points, and slippage of 45 basis points on each side. Compounded returns and trade counts are reconciled manually, and initial cash is included in the mark-to-market drawdown. Synthetic two rows per day are for bookkeeping and are not intraday data. Fractional capital reinvestment is used as a proxy, and adjusted prices are not raw executable stops. Mean excess return is the difference against the full T-5/T-1 SPY interval, not exposure-matched alpha. The conclusion is that there will be no adoption because all training variants had negative compounded returns, and a positive holdout in T3 cannot rescue a failed train. Sources include issuer URLs individually in observations 24553-24575 and https://runway.adityaperswal.workers.dev/data/stock-bars. Limitations include a selected company, retrospective calendar recovery, 2023 Web help overlap, 22 events, possible early news, costs assumed, and 15-minute and +2R policy separate.
A trading fund manager made notes about a trading strategy called CNXC91106. The strategy has three main points: first, it uses certain dates to decide when to buy and sell, excluding days when important events happen before the market opens or closes, and only considering announcements made before the trading day starts. Second, the strategy uses historical data from 2021 to 2024 to train, and from June 2025 to September 10, 2026, to test, with a fixed exit time and no stop-loss, and it only considers buying, not selling, with fees of 5 basis points and slippage of 25 basis points on each side. Third, the strategy uses a method called vectorbt to make trades, and it calculates returns and trade counts manually, including the initial cash in the calculations, and it uses a proxy for reinvesting capital. The strategy compares its performance to the performance of the SPY stock, and it reports the results of different variants without choosing a winner. The conclusion is that the strategy did not work well, with all variants having negative returns during the training period, and even the best variant during the testing period could not make up for the losses. The sources of the data are listed, including a website, and the limitations of the strategy are noted, including the use of data from only one company, and the possible effects of early news and costs.
A news scan found the following text: Premises for the CNXC91106 T-5 time exit train, with a 30 basis points per side fee, are as follows. The first premise is based on Freeze2229, which involves the issuer's advance dates, entering at T-5 open and exiting at T-1 close, excluding event sessions for after-market close and before-market open announcements. Announcements must be made before the entry date, and same-day unknown release times are excluded. The second premise involves a SIP adjustment using all 1451CNXC and 1470SPY daily bars through 2026-09-10, with training from 2021 to 2024 and a chronological holdout from 2025 to June 2026. The exit is based on a fixed calendar time, with no stop, and is for research control only, not eligible for live policy. The third premise uses vectorbt from orders with a long-only direction, fees of 5 basis points, and slippage of 25 basis points on each side. Compounded returns and trade counts are reconciled manually, and initial cash is included in the mark-to-market drawdown. Synthetic two rows per day are for bookkeeping and are not intraday data. A fractional capital reinvestment proxy is used, with adjusted prices and not raw executable stops. Mean excess pp is the difference against the full T-5/T-1 SPY interval, and is not exposure-matched alpha. The conclusion is that there will be no adoption, as all training variants had a negative compounded return, and the T3 positive holdout cannot rescue the failed train. Sources include issuer URLs individually in observations 24553-24575 and https://runway.adityaperswal.workers.dev/data/stock-bars. Limitations include a selected company, retrospective calendar recovery, 2023 web help overlap, 22 events, possible early news, assumed costs, and a 15-minute and +2R policy that is separate.
A trading strategy called CNXC91106 was tested. The strategy is based on three premises. First, the strategy uses certain dates called issuer advance dates to decide when to buy and sell. It buys on the third day before an event and sells on the day before the event, unless the event happens after the market closes or before it opens. The strategy also excludes events that are announced on the same day. Second, the strategy uses historical data from 2021 to 2024 to train itself and data from June 2025 to September 2026 to test itself. It uses a stop-loss of 1 average daily range (ADR) below the entry price and a target of 3 ADRs above the entry price. If the price gaps down at the open, the strategy stops the trade. The strategy only buys and does not sell short. It also takes into account fees of 5 basis points and slippage of 45 basis points on each trade. Third, the strategy uses a measure called mean excess return to compare its performance to the performance of the SPY index over the same period. The strategy was tested with different variations, but all of them had negative returns during the training period. Even the variation that performed well during the test period could not make up for the losses during the training period. The data used for the strategy came from individual company websites and a website called https://runway.adityaperswal.workers.dev/data/stock-bars. The strategy has several limitations, including that it only tested one company, it looked back at past data, and it did not take into account all possible costs and risks.
A news scan found the headline about a trading strategy for CNXC91106. The strategy has three main premises. First, it looks at the issuer's advance dates and enters a trade three days before and exits one day before, excluding event sessions for AMC and BMO. Announcements must be made before the entry date. Second, it uses a specific adjustment for 1451CNXC and 1470SPY daily bars through 2026-09-10, training from 2021 to 2024, and holding out from June 2025 to 2026. It also freezes prior 20 ADR, stops at E-ADR, targets E+3ADR, and has an adverse open on gap stop. Third, it uses vectorbt with long-only direction, fees of 5bp, and slippage of 45bp each side. The strategy was tested and all training variants had negative compounded returns. The sources of the data are issuer URLs and a website. The strategy has limitations, including a selected company, retrospective calendar recovery, and possible early news.
A news scan found the following trade notes. Premises for the trade are as follows: the trade is based on certain rules, including entering a trade three days before a specific event and exiting the day after the event, excluding events that happen at the start or end of the trading day. Announcements related to the trade must be made before the trade starts, and same-day announcements with unknown release times are excluded. The trade uses historical data from 2021 to 2024 to train a model, and data from June 2025 to September 2026 to test it. The model uses a stop-loss at 1 average daily range below the entry point and a target at 3 average daily ranges above the entry point, where average daily range refers to the average amount a stock price moves in a day. The trade is only for buying stocks, not selling, and includes fees of 5 basis points and slippage of 25 basis points on each side, where basis points refer to a unit of measurement for interest rates and slippage refers to the difference between expected and actual trade prices. The trade also includes a manual reconciliation of returns and trade counts, and initial cash is included in the calculation of drawdown, which refers to the decrease in value of a stock or portfolio. The trade uses synthetic data, which is not real-time data, and adjusted prices, which are not the actual prices at which trades can be executed. The mean excess return is calculated as the difference between the return of the trade and the return of the SPY index over the same period, and is not an exposure-matched alpha, which refers to a measure of return that takes into account the risk of the trade. The trade uses a fixed set of parameters and reports all variants without choosing a winner. The conclusion is that the trade will not be adopted because all training variants had negative returns, and the positive return in the test period is not enough to make up for the failed training period. The sources of the data are listed in observations 24553-24575 and are available at https://runway.adityaperswal.workers.dev/data/stock-bars. The limitations of the trade include the selection of a single company, the use of historical data, overlap with web help in 2023, and the assumption of certain costs and policies.
A news scan found the following trading plan. The plan is based on two premises. First, the plan uses certain dates: it enters a trade three days before a specific event, and exits the day after the event, unless the event happens at the start or end of the trading day. It also excludes any announcements made on the same day as the trade entry. Second, the plan uses historical stock data from 2021 to 2024 to test its strategy, and it uses data up to September 10, 2026, to adjust its calculations. The plan also freezes certain data from before 2020 and uses a stop-loss and target price based on the stock's average daily range. The plan only considers long trades, and it includes fees and slippage of 5 and 25 basis points per trade. The plan also manually reconciles its returns and trade counts, and it includes the initial cash in its calculations. The plan uses a method called vectorbt and reports its results without choosing a winner. The plan concludes that it should not be adopted because all of its variants had negative returns. The plan's data comes from individual company websites and a website called https://runway.adityaperswal.workers.dev/data/stock-bars. The plan has several limitations, including only using data from one company, possible early news releases, and assumed costs.
A trading strategy called CNXC91106 has been tested. The strategy is based on three premises. First, it looks at the dates when companies announce important information, and it decides to buy or sell based on those dates. It buys on the third day before the announcement and sells on the day after the announcement, unless the announcement is made after the market closes or before it opens. Second, the strategy uses historical data from 2021 to 2024 to train itself, and it tests itself on data from 2025 to 2026. It does not use a stop-loss, which is a rule to sell a stock when it falls to a certain price. Third, the strategy only buys stocks, not sells, and it takes into account the costs of buying and selling. The strategy was tested on a stock called CNXC and a stock index called SPY. The results showed that the strategy did not work well, and it is not recommended for use. The data used for the test came from the internet, and the test had some limitations, such as only looking at one company and not taking into account all the costs of buying and selling.
A trading strategy called CNXC91106 has a rule to exit a trade 3 days before a certain event, with a 50 basis point, or 0.5%, limit on each side. The strategy is based on three premises. First, it looks at the dates when companies announce important information, and it enters trades on the opening of the third day before the announcement and exits on the closing of the day before. It avoids trading on days when companies like AMC and BMO make announcements. The strategy only considers announcements that are made before the trade entry date, and it excludes announcements made on the same day if the release time is unknown. Second, the strategy uses data from 1451CNXC and 1470SPY from 2021 to 2026, up to September 10, 2026, to train and test its rules. It uses a fixed calendar time to exit trades, without stopping, and it is only for research, not for actual trading. The strategy also considers fees and slippage, which is the difference between the expected price and the actual price, of 5 basis points and 45 basis points on each side of the trade. Third, the strategy uses a method called vectorbt to make trades, only going long, meaning it only buys, and it reconciles its returns and trade counts manually. The strategy also includes the initial cash in its calculations and uses a proxy for reinvesting capital. The mean excess return is calculated against the full interval of the SPY, not against a matched alpha. The strategy tested different variants, but none of them had a positive compounded return, so it was not adopted. The sources of the data are listed, including individual company URLs and a website. The strategy has limitations, including only looking at one company, using past data, and assuming certain costs.
A trading fund manager made notes about a trading strategy called CNXC91106. The strategy has three main premises. First, the manager looks at the issuer's advance dates and enters trades on the third day before an event, and exits trades on the day after the event, unless the event happens before or after the market opens. The manager excludes announcements made on the same day as the trade. Second, the manager uses historical data from 2021 to 2024 to train the strategy, and tests it on data from June 2025 to September 10, 2026. The manager uses a fixed calendar time to exit trades, with no stop-loss, and only for research purposes. Third, the manager uses a tool called vectorbt to make trades, only going long, with fees of 5 basis points and slippage of 25 basis points on each side. The manager manually checks the returns and trade counts, and includes the initial cash in the mark-to-market drawdown. The manager also uses a proxy for reinvesting capital and adjusts prices. The mean excess return is the difference between the strategy's return and the return of the SPY index over the same period. The manager tested different variants of the strategy, but none of them had a positive compounded return, so the manager decided not to adopt the strategy. The manager used data from individual company websites and a website called https://runway.adityaperswal.workers.dev/data/stock-bars. The manager notes that the strategy has limitations, including only being tested on one company, using historical data, and assuming certain costs.
A trading strategy called CNXC91106 has a rule to exit a trade 3 days before a certain event, with a 30 basis points per side condition. The strategy is based on three premises. First, it considers the issuer's advance dates and enters a trade on the third day before the event and exits on the day before the event, excluding events that happen at the start or end of the trading day. The strategy also excludes announcements made on the same day as the entry date if the release time is unknown. Second, the strategy uses a specific set of data, including 1451CNXC and 1470SPY daily bars up to September 10, 2026, and trains the model on data from 2021 to 2024, with a holdout period from June 2025 to 2026. The strategy has a fixed calendar time exit and no stop, and is only used for research, not for live trading. Third, the strategy uses a long-only direction, with fees of 5 basis points and slippage of 25 basis points on each side, and reconciles returns and trade counts manually. The strategy also includes initial cash in its mark-to-market drawdown and uses synthetic data for bookkeeping. The mean excess return is calculated against the full T-3/T-1 SPY interval, not against exposure-matched alpha. The strategy was tested with different variants, but all of them had negative compounded returns, and even the positive holdout period could not rescue the failed training period. The sources of the data are listed in observations 24553-24575 and are available at https://runway.adityaperswal.workers.dev/data/stock-bars. The strategy has several limitations, including the selection of a single company, retrospective calendar recovery, overlap with 2023 web help, 22 events, possible early news, assumed costs, and a 15-minute and +2R policy that is separate.
A diagnostic test for BFRI911 was run using a momentum strategy with specific parameters, including a 20-day lookback period, 1460 days of data, a 5% stop loss, and a 15% target profit. The test used 1003 daily price bars from IEX and resulted in 124 closed trades. However, the raw prices showed a discontinuity due to a July 2023 split, which made them not comparable with the 1176 SIP adjustment used in the study. A full sample diagnostic was performed without a costed holdout, but it was not an event study and was not adopted. Additionally, an independent fixed rule long-only test with a costed chronological holdout from 2477 to 2480 also failed. The data source was https://runway.adityaperswal.workers.dev/data/stock-bars?feed=iex and local cli.json.
A news scan found the following analysis of BFRI911: Premises include two main points. First, the analysis uses a rule where if the closing price is higher than the closing price 20 sessions before, the next open is used as an entry point, and the position is exited at the next open if the signal is flat. The analysis also uses a 5% stop loss and a 15% target, with the stop loss taking priority if both are hit, and an adverse open can trigger a gap stop, with a final forced close. Second, the analysis adjusts for SIP, or Securities Information Processor, which is a system that provides real-time market data, for all 1176 bars from January 2022 to September 10, 2026, with training from 2022 to 2024, and held out from 2025 to September 10, 2026. The analysis uses a long-only strategy with a 5 basis point fee and stated slippage on each side, which refers to the difference between the expected price and the actual price of a trade. Two synthetic bookkeeping rows per day allow for entry day stops, but these are not based on intraday data. The analysis concludes that momentum alone is not sufficient for a run-up, based on a technical diagnostic that is not a matched FDA event backtest, meaning it does not test for a specific event or condition. The analysis also notes that selection, current company regime, corporate actions, and slippage assumptions may limit the transfer of these results. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=BFRI&timeframe=1Day&feed=sip&adjustment=all.
A news scan found the following analysis of BFRI911: Premises include two main points. First, a frozen momentum strategy was tested, where a position is entered when the lagged close is greater than the 20-session prior close, and exited when the next open is flat, with a 5% stop loss and 15% target, and the stop loss is prioritized if both are hit. Second, the strategy was backtested on data from January 2022 to September 10, 2026, with the training period from 2022 to 2024 and the holdout period from 2025 to September 10, 2026. The backtest used a 5 basis point fee and stated slippage on each side, with no tuning, and utilized vectorbt with a long-only strategy. Two synthetic bookkeeping rows per day were used to permit entry day stops, but these are not intraday data. The conclusion is to reject momentum alone for the run-up, as this is a technical diagnostic and not a matched FDA event backtest, with no established positive edge conditioned on the calendar. The selection, current company regime, corporate actions, and slippage assumptions limit the transferability of the results. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=BFRI&timeframe=1Day&feed=sip&adjustment=all.
A trading strategy called BFRI911 with a fixed momentum of 20 was trained and tested. The rules were: if the closing price was higher than 20 sessions before, the next open would be an entry signal, and the position would be closed at the next open if the signal was flat. The stop loss was 5% and the target was 15%. If both were hit, the stop loss would be executed first. If the opening price was adverse due to a gap, the stop loss would be triggered. The position would be closed at the final close. The strategy was tested on data from January 2022 to September 10, 2026, with the training period being 2022-2024 and the held-out period being 2025-September 10, 2026. No tuning was done, and a 5 basis point fee was applied on each side, with stated slippage. Two synthetic bookkeeping rows were added per day to allow for entry day stops, but these are not intraday data. The results were manually compounded and validated against vectorbt, a trading backtester, with a fractional capital proxy, but without 15-minute or 2R management validation. The initial implementation did not include entry day exits, but this was corrected before journaling the results, and the initial numbers were discarded. The conclusion is to reject momentum alone for a run-up. This is a technical diagnostic, not a matched FDA event backtest, and no calendar-conditioned positive edge was established. The selection, current company regime, corporate actions, and slippage assumptions limit the transferability of the results. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=BFRI&timeframe=1Day&feed=sip&adjustment=all.