Stats

A news scan found the note: Frozen note2125. This note explains a trading strategy for the stock VIST. The strategy checks if the stock's close price is higher than its prior 20-day close high and its 50-day Simple Moving Average, which is a calculation of the stock's average price over 50 days. If this condition is met, the strategy will open a position at the next open price. The strategy will exit the position after 20 sessions or when it reaches a target price that is 3 times the Average Daily Range, which is a measure of the stock's daily price movement, with a stop loss at 2 times the Average Daily Range. The strategy was trained on data from 2021 to 2024 and tested on data from 2025 onward, with a flat starting point. The data used can be found at https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=VIST&timeframe=1Day&feed=sip&adjustment=all. The strategy includes fees of 5 basis points and a slippage of 20 basis points on each side, with a stress test of 50 basis points. The strategy uses daily Open, High, Low, and Close prices to stop losses and open gaps, and it only allows long positions, meaning it only buys the stock. The strategy also allows for same-day round trips, meaning it can buy and sell the stock on the same day. The strategy's performance is measured by its return, which is -29.4389% during training and 22.7833% during testing, with a maximum drawdown of 24.7675% and a win rate of 53.85%. The strategy's mean return is 13.5700% under stress, with a 95% bootstrap confidence interval of -3.721 to 8.785, which crosses zero. The current signal for the strategy is true, with a price of 78.95 and a threshold of 77.03. The strategy's sensitivity has been fully recorded, but it is not used for selection. The current universe selection and the history of the stock prevent the strategy from claiming untouched out-of-sample alpha, which refers to the strategy's ability to generate returns that are not explained by the market. The strategy does not use a daily fixed target or 15-minute validation with a 2R trailing stop. If the training data is negative or there is no current entry signal, the strategy will not place an order. The Half Kelly criterion, which is a formula used to determine the optimal bet size, is zero, and there is no need for funding input.

A news scan found the note: the trading rule for QRVO is to buy when the close is higher than the prior 20-day high close and the 50-day simple moving average, and to sell at a target price of 3 times the risk, or after 20 sessions, or at a stop loss of 2 times the average daily range. The system was trained on data from September 10, 2021, to 2026, with a holdout period starting in 2025. The data is from https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=QRVO&timeframe=1Day&feed=sip&adjustment=all. The fees are 5 basis points and the slippage is 20 basis points on each side, with a stress test of 50 basis points. The system uses daily open, high, low, and close prices, and allows for same-day round trips. The training return was -17.4599% over 22 trades, and the test return was 14.5341% over 15 trades, with a maximum drawdown of 29.1677% and a win rate of 40.00%. The stress test return was 4.6761%. The 95% bootstrap confidence interval is [-2.784, 5.670], which crosses zero. The current signal is true, with a price of 112.36 and a threshold of 105.24. The sensitivity analysis is fully recorded, but not used for selection. The current universe selection and the history of LPG prevent claims of untouched out-of-sample alpha. The daily fixed target is not validated by 15-minute or 2R trailing stops. If the training is negative or there is no current entry, no order is placed. The Half Kelly fraction from training is 0, and no funding need is input.

A news scan found the note: Frozen note2125. This note is about a trading strategy for the stock SWKS. The strategy is to buy when the close price is higher than the prior 20-day high close and the 50-day Simple Moving Average, which is a calculation to find the average price of a stock over a certain period. The strategy will sell when it reaches a target price, which is 3 times the risk, or after 20 sessions. The data used to train this strategy is from September 10, 2021, to 2026, and the strategy was tested from 2021 to 2024, with the remaining time used to evaluate its performance. The fees for this strategy are 5 basis points, which is a unit of measurement for interest rates and percentages, and 20 basis points for each trade, with a stress test of 50 basis points. The strategy only allows for buying and selling the same stock on the same day, and it uses the daily high, low, open, and close prices to determine when to stop a trade. The strategy's performance was evaluated using a method called backtesting, which means using historical data to see how the strategy would have performed in the past. The results show that the strategy had a return of -33.0777% during the training period, and 1.8628% during the testing period, with a maximum drawdown of 24.2922%, and a win rate of 41.67%. The strategy's performance was also evaluated using a method called bootstrapping, which means resampling the data to estimate the strategy's performance, and the results show that the mean return is between -4.128 and 5.858. The current signal for this strategy is true, with a price of 84.03 and a threshold of 76.54. The strategy's sensitivity was tested and recorded, but not used for selection. The current universe selection and the history of the stock prevent the strategy from claiming to have found a new source of profit. The strategy does not use a daily fixed target or a 15-minute validation, and it does not require any funding input. A headline from the website https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=SWKS&timeframe=1Day&feed=sip&adjustment=all was found, but its content is not provided here.

This report is based on premises that include evidence for momentum from a 2014 study by AQR, which is a type of investment management firm. The study, found at https://www.aqr.com/-/media/AQR/Documents/Journal-Articles/JPM-Fact-Fiction-and-Momentum-Investing.pdf, is about fact and fiction in momentum investing. The report also references a frozen note from 2024 about nine original sector ETFs, which are a type of investment fund. The note explains that the prior-month-end close price divided by the close price 189 days earlier, minus 1, is used to rank the top 3 sectors. The next session's open price is then used, with three fixed independent cash sleeves and no leverage, which means borrowing money to invest. The report also mentions a drop-rank monthly or 63-session exit, which is a strategy for selling investments, and a 2ATR stop and 6ATR target, where ATR stands for Average True Range, a measure of price volatility. Additionally, a 2R daily high makes the break-even point effective the following day. A gap open is used as an actual proxy, with the same bar stop first. The report also references data from https://runway.adityaperswal.workers.dev/data/stock-bars, which was requested from 2009 but only received from 2016 onward. The warm-up period means the first 252 rule trades from 2017, with no pre-2016 data. The frozen 2019 split was retained and not moved to improve results. The vectorbt long-only cash-sharing strategy is used, with every daily equity and trade count reconciled. A fee of 1 basis point each side, plus a 15 basis point slip, is applied. Corporate action total return is not independently rebuilt, and no taxes, cash yield, or operator costs are included. The results show 190 trades, with a mean return of 0.625286%, and an entry month cluster of 3000 bootstrap CI, which is a measure of confidence interval, of [-0.437693, 1.761003]%. The p-value is 35.2632%, the W-value is 8.1038%, and the L-value is 3.4484%. The plug-in half Kelly risk is 0.038580. The primary 252 training was negative, but the positive 189 neighbor cannot replace the pre-registered rule. The historical holdout may overlap prior research, and the daily break-even proxy is not 15-minute live proof. The report rejects live adoption and retains the positive holdout for prospective research. The artifacts are found in research/test_sector.py, sector_results.json, and percelltrades/returns.

This report is based on two premises. The first premise is that a 2014 study by AQR, which ranked stocks by momentum over a 12-month period, skipping the most recent month, provides evidence for momentum investing, but this specific strategy does not follow that approach. The study can be found at https://www.aqr.com/-/media/AQR/Documents/Journal-Articles/JPM-Fact-Fiction-and-Momentum-Investing.pdf. The second premise, noted in Frozen note 2124, involves nine original sector ETFs, where the momentum is calculated as the difference between the closing price 21 days ago and 189 days ago, and the top three positive sectors are selected. The next session's open is used, with three fixed independent cash sleeves and no leverage. The strategy exits positions monthly or after 63 sessions, using a stop-loss of 6 ATR and a target of 2 ATR. If the daily high is 2R above the entry price, the stop-loss becomes effective the following day. A gap open is used as a proxy for the actual open, with the same bar stop as the first stop. The data used was requested from 2009, but only data from 2016 onwards was received. The warm-up period means that the first 252 trades in 2017 were used to initialize the strategy, with no data used before 2016. The 2019 split was retained and not moved to improve results. The strategy uses vectorbt for long-only cash sharing, with every daily equity and trade count reconciled. The fees are 1 basis point for each side, plus a 15 basis point slip. Corporate actions are included in the total return, but not independently rebuilt, and no taxes, cash yield, or operator costs are included. The strategy made 55 trades, with a mean return of 0.497706%, and an entry month cluster of 3000 bootstrap CI of [-1.106902, 2.078437]%. The plug-in half Kelly risk is 0.042640. The primary 252 training period was negative, but the positive 189 neighbor cannot replace the preregistered rule. The historical holdout may overlap prior research, and the daily BE proxy is not a 15-minute live proof. The strategy is rejected for live adoption, but the positive holdout is retained for prospective research. The research artifacts can be found in research/test_sector.py, sector_results.json, and percelltrades/returns.

This report is based on premises that include evidence for momentum from a 2014 AQR study, which is a research paper on fact and fiction in momentum investing. The study can be found at https://www.aqr.com/-/media/AQR/Documents/Journal-Articles/JPM-Fact-Fiction-and-Momentum-Investing.pdf. The report also references a frozen note from 2024, which details a strategy using nine original sector ETFs, where the prior-month-end close is compared to the close 189 days prior, and the top three positive sectors are selected. The next session's open is used, with three fixed independent cash sleeves and no leverage. The strategy includes a monthly or 63-session exit, with a stop loss set at 6 ATR, which stands for Average True Range, a measure of volatility. The strategy also includes a target at 6 ATR and a daily high that makes the break-even point effective the following day. A gap open is used as an actual proxy, with the same bar stop as the first stop. The report uses data from 2016 onward, with a warm-up period that means the first 252 trades in 2017 are used, and there is no pre-2016 data. The frozen 2019 split is retained and not moved to improve results. The vectorbt, which is a backtesting library, is used for long-only cash sharing, with every daily equity and trade count reconciled. The fee is 1 basis point, or 0.01%, each side, plus a 5 basis point slip, which is a small cost. The corporate action total return is not independently rebuilt, and there are no taxes, cash yields, or operator costs. The results show 188 trades, with a mean return of 0.890330%, and an entry month cluster of 3000 bootstrap confidence intervals of [-0.188323, 2.061320]%. The p-value is 36.1702%, the W-value is 8.3338%, and the L-value is 3.3276%. The plug-in half Kelly risk is 0.053417, which is a measure of risk. The primary 252 training is negative, and the positive 189 neighbor cannot replace the pre-registered rule. The historical holdout may overlap prior research, and the daily break-even proxy is not a 15-minute live proof. The report rejects live adoption and retains the positive holdout for prospective research. The artifacts of the research can be found in the files research/test_sector.py, sector_results.json, and percelltrades/returns.

This report is based on two premises. The first premise is that a 2014 study by AQR, which ranked momentum based on a 12-month period with a 1-month skip, is evidence for momentum, but this adapter does not use that method. The study can be found at https://www.aqr.com/-/media/AQR/Documents/Journal-Articles/JPM-Fact-Fiction-and-Momentum-Investing.pdf. The second premise, from a frozen note numbered 2124, involves nine original sector ETFs and a specific trading strategy. The strategy involves calculating the momentum of each sector based on the prior month's end close and the close 189 days prior, then selecting the top three positive sectors. The next session's open is used to determine the trade, with three fixed independent cash sleeves and no leverage. A stop-loss is set at 6 ATR, which stands for Average True Range, a measure of volatility. The strategy also includes a target at 6 ATR and a daily high that makes the break-even point effective the following day. A gap open is used as an actual proxy, with the same bar stop first. The data used for this strategy was requested from 2009, but only data from 2016 onward was received. The warm-up period means that the first 252 trades in 2017 were used to establish the baseline, with no data used from before 2016. The frozen 2019 split was retained and not moved to improve results. The vectorbt long-only cash-sharing strategy was used, with every daily equity and trade count reconciled. A fee of 1 basis point, or 0.01%, was charged on each side, plus a 5 basis point slip. Corporate actions and total return were not independently rebuilt, and no taxes, cash yield, or operator costs were considered. The results show 54 trades, with a mean return of 0.689527%. The entry month cluster had a 95% confidence interval of -0.960180% to 2.353536%, with a p-value of 37.0370% and a W-value of 5.9756%. The plug-in half Kelly risk was 0.057695. The primary 252 training period was negative, and the positive 189 neighbor cannot replace the pre-registered rule. The historical holdout may overlap prior research, and the daily break-even proxy was not live-proofed at 15 minutes. As a result, live adoption was rejected, but the positive holdout was retained for prospective research. The artifacts from this research can be found in the files research/test_sector.py, sector_results.json, and percelltrades/returns.

This report is based on premises that include evidence for momentum from a 2014 study by AQR, which can be found at https://www.aqr.com/-/media/AQR/Documents/Journal-Articles/JPM-Fact-Fiction-and-Momentum-Investing.pdf. The report also references a frozen note, number 2124, which describes a strategy using nine original sector ETFs. The strategy involves ranking these ETFs based on their performance over the past 252 days, excluding the most recent month, and then selecting the top three. The next session's open is used to determine the entry point, with three fixed independent cash sleeves and no leverage. The strategy also includes a stop-loss and target, with a daily high of 2R making the stop-loss effective the following day. A gap open is used as a proxy, with the same bar stop being the first stop. The data used for this report was requested from 2009, but only data from 2016 onward was received. The warm-up period means that the first 252 rule trades were in 2017, with no pre-2016 data used. The frozen 2019 split was retained and not moved to improve results. The vectorbt long-only cash-sharing strategy was used, with every daily equity and trade count reconciled. The fees were 1 basis point on each side, plus a 15 basis point slip. The corporate action total return was not independently rebuilt, and no taxes, cash yield, or operator costs were included. The results show 190 trades, with a mean return of 1.011710%, and an entry month cluster of 3000 bootstrap CI of [-0.048485, 2.130268]%. The p-value was 38.4211%, the W-value was 8.2380%, and the L-value was 3.4970%. The plug-in half Kelly risk was 0.061405. The primary 252-day training period showed negative results, but a positive 189-neighbor cannot replace the pre-registered rule. The historical holdout may overlap prior research, and the daily BE proxy is not a 15-minute live proof. As a result, live adoption is rejected, but the positive holdout is retained for prospective research. The artifacts from this research can be found in the files research/test_sector.py, sector_results.json, and percelltrades/returns.

This report is based on two premises. First, a 2014 study by AQR found evidence for momentum, which is a trading strategy that involves buying assets that have performed well in the past. The study is available at https://www.aqr.com/-/media/AQR/Documents/Journal-Articles/JPM-Fact-Fiction-and-Momentum-Investing.pdf. Second, a frozen note from 2021, note 2124, describes a trading strategy that uses nine original sector ETFs and a specific set of rules to buy and sell assets. The rules include using the prior-month-end close price and the close price 252 days ago to determine which assets to buy, and using a stop-loss order to limit losses. The strategy also uses a target price, which is six times the average true range, a measure of volatility. If the daily high price is two times the average true range above the entry price, the stop-loss order is moved to the break-even point the next day. The strategy uses a gap open as a proxy for the actual open price, and the same bar stop is used as the first stop. The data used for this strategy was obtained from https://runway.adityaperswal.workers.dev/data/stock-bars, but only data from 2016 onwards was available, although data from 2009 was requested. The first 252 trades in 2017 were used as a warm-up period, and no data from before 2016 was used. The strategy was split in 2019, but the split was not moved to improve the results. The vectorbt library was used to backtest the strategy, which is a long-only strategy that shares cash every day and reconciles the equity and trade count daily. The fee for each trade is 1 basis point, plus a 15 basis point slip. The total return does not include corporate actions, taxes, cash yield, or operator costs. The strategy made 48 trades, with a mean return of -0.511591%. The entry month cluster had a confidence interval of [-2.046171, 0.966631]%, and the p-value was 33.3333%. The W-score was 4.4882%, and the L-score was 3.0115%. The plug-in half Kelly risk was 0.000000. The primary 252-day training period had a negative return, and the positive 189-neighbor cannot replace the preregistered rule. The historical holdout period may overlap with prior research, and the daily break-even proxy is not a 15-minute live proof. Therefore, the strategy is not recommended for live adoption, but the positive holdout is retained for prospective research. The artifacts of this research are available in the files research/test_sector.py, sector_results.json, and percelltrades/returns.

This report is based on premises that include evidence for momentum from a 2014 AQR study, which is a research paper by AQR, a company that studies investment strategies. The study can be found at https://www.aqr.com/-/media/AQR/Documents/Journal-Articles/JPM-Fact-Fiction-and-Momentum-Investing.pdf. The report also references a frozen note, number 2124, which describes a trading strategy using nine original sector ETFs, or exchange-traded funds, which are a type of investment fund. The strategy involves ranking the ETFs based on their performance over the prior 252 days, excluding the last 21 days, and then selecting the top three. The next session's open price is used, and three fixed independent cash sleeves, or portions of the investment, are used, with no leverage, or borrowing. The strategy also includes a stop-loss, which is a rule to sell a security when it falls to a certain price, and a target price, with a daily high that makes the stop-loss effective the following day. A gap open, which is when a security's price opens higher than its previous close, is used as a proxy, or substitute, for the actual price. The report also references a data request to a website, https://runway.adityaperswal.workers.dev/data/stock-bars, which was supposed to provide data from 2009, but only provided data from 2016 onward. The report states that the first 252 days of trades in 2017 were used as a warm-up period, and that there was no data before 2016. The report also states that the data from 2019 was retained, and not moved to improve the results. The report uses a vectorbt, or a type of backtesting software, to test the strategy, and reconciles the daily equity and trade count. The report also states that there is a fee of 1 basis point, or 0.01%, each side, plus a 5 basis point slip, which is a small reduction in the price of a security. The report provides statistics on the strategy's performance, including 189 trades, with a mean return of 1.268803%, and a confidence interval of [0.218449, 2.374473]%. The report also states that the primary 252-day training period was negative, but the positive 189-neighbor, or nearby, period cannot replace the pre-registered rule. The report concludes that the historical holdout, or test period, may overlap with prior research, and that the daily break-even, or BE, proxy is not a live proof. The report rejects live adoption, but retains the positive holdout for prospective research. The report references artifacts, or files, including research/test_sector.py, sector_results.json, and percelltrades/returns.

This report is based on premises that include evidence for momentum from a 2014 AQR study, which is a type of investment research, and a frozen note from 2124. The study found that momentum, or the tendency of stocks to continue rising if they have been rising, is a real effect. The frozen note described a trading strategy that used nine original sector ETFs, which are a type of investment fund, and ranked them based on their performance over the past 252 days, with a 12-month skip of one month. The top three performing sectors were selected, and the next session's open was used to determine the trade. The strategy used three fixed independent cash sleeves, which means that the investment was divided into three parts, and no leverage, which means that no borrowed money was used. The strategy also included a stop-loss, which is a rule to sell a stock if it falls by a certain amount, and a target, which is a price at which to sell a stock. If the daily high was two times the risk, the stop-loss was moved to the break-even point, which is the price at which the trade becomes profitable. The data used for this strategy was obtained from a website, but it only went back to 2016, although it was requested to go back to 2009. The strategy was tested using a method called vectorbt, which is a type of backtesting, and the results were reconciled, which means that they were checked for accuracy. The strategy had a fee of one basis point, which is a unit of measurement for interest rates, on each side of the trade, plus a five basis point slip, which is a fee for buying or selling a stock. The strategy made 47 trades, with a mean return of -0.085267%, and the results were analyzed using a method called bootstrapping, which is a way of estimating the accuracy of a statistic. The results showed that the strategy was not effective, and it was decided not to adopt it for live trading. The artifacts of this research, including the code and results, are available in files called research/test_sector.py, sector_results.json, and percelltrades/returns.

A trading plan was created based on historical prices before September 2024. The issuer, Tamboran, has eight upcoming earnings dates: 2024-09-20, 2024-11-12, 2025-02-12, 2025-05-14, 2025-09-25, 2025-11-13, 2026-02-11, and 2026-05-13, as found on their website. The plan involves entering a trade at the open price of the fifth prior trading session and exiting at the close of the prior session. A stop-loss is set at one times the prior 20-day mean daily range below the entry price, and a target is set at three times the range above. The plan also includes a gap stop and a target limit. The plan was trained on data from 2024 to 2025 and tested on data from 2026. Fees are 5 basis points plus 45 basis points for slippage on each side. The plan uses a vectorbt long-only strategy with two marks per day and explicit entry and exit prices. A preliminary bug was corrected before publication. The plan's premises are that historical runups are positive, but the selection and sample mean are uncertain. A bootstrap confidence interval was calculated to be between 1.8919149420659975% and 2.5688714251883793% with 20,000 resamples. The plan is for watching or paper trading only and is not eligible for live trading due to lack of independent evidence and uncalibrated risk. The current gas-sales transition is a regime change, and preproduction events may not be representative. A proposed paper entry on September 18 requires actual prints on September 18 and an exit before September 25.

A trading fund manager made notes about a train of events for the ticker symbol TBN from T-5 to T-1 with a 1ADR/3ADR setup and a 50 basis point movement. The manager looked at historical prices before eight earnings dates: 2024-09-20, 2024-11-12, 2025-02-12, 2025-05-14, 2025-09-25, 2025-11-13, 2026-02-11, and 2026-05-13, which were found on the website https://ir.tamboran.com/news-events/ir-calendar/past. The manager used the original release details from 13, 14, 20, 36, 38, and 45. The manager decided to enter the trade at the open price of the fifth prior trading session and exit at the close price of the prior session. The manager set a stop loss at one times the prior 20-day mean daily range below the entry price and a target at three times above the entry price. If there was a gap, the stop loss would be at the minimum of the open price or the stop loss price, and the stop loss would be triggered on the first bar that hit both conditions. The manager also set a target limit. The manager used all-adjusted SIP data through September 10 and trained the model from 2024 to 2025, holding out 2026 for chronological testing. The fees were 5 basis points plus 45 basis points for slippage on each side. The manager used a vectorbt long-only strategy with two marks per day and explicit entry and exit prices. The manager checked that the trade count and compounded manual net returns matched the expected results to within a very small margin of error, less than 1e-8. A preliminary bug that caused the strategy to reverse direction incorrectly was corrected before publication, and the incorrect output was discarded. The manager assumed that historical runups were positive, but noted that the selection and small sample size meant that the predictive edge was uncertain. The manager calculated a 95% confidence interval using a bootstrap method with 20,000 resamples and a seed of 91102, which resulted in an interval of -0.8509001136851805% to 3.2089441420326583%. The manager concluded that the strategy should only be watched or used on paper, and not used live, because there was no independent evidence for a +2R quarter or trail exit, no calibrated gap-tail or full-company risk, and the current model failed to achieve a net return of 3R. The manager also noted that the current gas-sales transition was a regime change, and that preproduction events may not be representative. The manager found that the Half Kelly positive training fraction was unstable, and that the holdout without losses had an undefined Kelly allocation, which was reported as 0. The manager did not place an order, but proposed a paper entry on September 18 and an exit on September 24 before the US market opened on September 25.

A news scan found the headline about NET911 TBN T-5 to T-1 1ADR/3ADR holdout 30bp. The trading fund manager made notes before historical prices were frozen, note2123. The issuer has eight earnings dates: 2024-09-20, 2024-11-12, 2025-02-12, 2025-05-14, 2025-09-25, 2025-11-13, 2026-02-11, and 2026-05-13, according to https://ir.tamboran.com/news-events/ir-calendar/past. The manager will enter a trade at the open of the fifth prior trading session and force an exit at the prior session's close. A stop will be set at one prior 20-day mean daily range below the entry, with a target three times above. A gap stop will be set at the minimum of the open and stop, and the stop will be triggered on the first dual-hit bar, with a target limit. The manager used all-adjusted SIP through September 10, training data from 2024-25, and a chronological holdout from 2026. Fees are 5 basis points plus 25 basis points for slippage on each side. The manager used Vectorbt for long-only trades, with two marks per day and explicit entry and exit prices. A preliminary bug that affected trades in both directions was corrected before publication. The manager notes that historical runups were positive, but selection and sample mean are uncertain and may not predict future results. A mean 95% event bootstrap confidence interval was calculated to be between 2.300303974275275% and 2.9799737404206494%, based on 20,000 resamples with a seed of 91102. The manager concludes that this strategy is only for watching or paper trading, and not eligible for live trading, due to a lack of independent evidence for quarter or trail exits, and uncalibrated gap-tail and full-company risk. The current gas-sales transition is a regime change, and preproduction events may not be representative. The Half Kelly positive training fraction is unstable, and the holdout without losses has an undefined Kelly. No order was placed, and a proposed paper entry on September 18 requires actual prints, with an exit on September 24 before the US market opens on September 25.

A news scan found the headline about NET911 TBN T-5 to T-1 1ADR/3ADR train 30bp. The trading fund manager made notes before looking at historical prices. The issuer has eight earnings dates: 2024-09-20, 2024-11-12, 2025-02-12, 2025-05-14, 2025-09-25, 2025-11-13, 2026-02-11, and 2026-05-13, which were found on the website https://ir.tamboran.com/news-events/ir-calendar/past. The manager will use the original release details 13, 14, 20, 36, 38, and 45. The manager will enter a trade at the open price of the fifth prior trading session and exit at the close price of the prior session. The stop loss will be set at one times the prior 20-day mean daily range below the entry price, and the target will be set at three times above the entry price. If there is a gap, the stop loss will be set at the minimum of the open price and the stop loss price. The manager will use a type of backtesting called vectorbt, which is a way to test trading strategies, and will only consider long positions, with two marks per day, and explicit entry and exit prices. The manager found a bug in the code that was corrected before publication. The results show that the mean 95% event bootstrap confidence interval is between -0.4535044521155866% and 3.6226119078948753%, based on 20,000 resamples with a seed of 91102. The manager concludes that this strategy is only for watching or testing on paper, and not for actual trading, because there is no independent evidence to support it, and the current model does not work well. The manager also notes that the current transition in gas sales is a significant change, and it is not possible to assume that past events are representative of future events. The manager does not recommend placing an order, and proposes a paper entry on September 18, with an exit on September 24, before the earnings date on September 25.

A frozen note was made before looking at past prices. The issuer has eight earnings dates: 2024-09-20, 2024-11-12, 2025-02-12, 2025-05-14, 2025-09-25, 2025-11-13, 2026-02-11, and 2026-05-13, which were found at https://ir.tamboran.com/news-events/ir-calendar/past. The details of the originals are in releases 13, 14, 20, 36, 38, and 45. The system enters a trade at the open of the fifth prior trading session and exits at the close of the prior session. There are no barriers, only time controls. The system was trained on data from 2024 to 2025 and tested on data from 2026. The fees are 5 basis points plus 45 basis points for slippage on each side. A vectorbt system was used for long-only trades, with two marks per day and explicit entry and exit prices. A preliminary bug that caused incorrect reversals was fixed before publication. The system is based on the idea that historical runups are positive, but the selection and small sample size make the predictive edge uncertain. The mean 95% event bootstrap confidence interval is between 1.8919149420659975% and 2.5688714251883793%, based on 20,000 resamples with a seed of 91102. The conclusion is to watch or use the system for paper trading only, as there is no independent evidence for quarter or trail exits, and the current model fails. The current transition in gas sales is a change in the market, and past events may not be representative. The Half Kelly positive training fraction is unstable, and the holdout without losses has an undefined Kelly fraction, so the reported allocation is 0, not an estimate. There is no order, and a proposed paper entry on September 18 requires actual prints, then an exit on September 24 before the US market opens on September 25.

A news scan found the note about the NET911 TBN T-5 to T-1 time-only train with a 50bp change. The note mentions that the issuer has eight earnings dates: 2024-09-20, 2024-11-12, 2025-02-12, 2025-05-14, 2025-09-25, 2025-11-13, 2026-02-11, and 2026-05-13, which were found on the website https://ir.tamboran.com/news-events/ir-calendar/past. The details of the originals are listed as 13, 14, 20, 36, 38, and 45. The system enters the market at the open of the fifth prior trading session and exits at the close of the prior session. There are no barriers, and the control is time-only. The all-adjusted SIP is used through September 10, and the training data is from 2024 to 2025, with a holdout in 2026. The fees are 5bp plus 45bp for slippage on each side. The vectorbt is used for long-only trades, with two marks per day and explicit entry and exit prices. A preliminary bug that affected both directions was corrected before publication, and the erroneous reversal output was discarded. The premises of the system are that historical runups are positive, but the selection and sample mean are uncertain and may not have a predictive edge. The mean 95% event bootstrap confidence interval is between -0.851148076970896% and 3.2089441420326583%, based on 20,000 resamples with a seed of 91102. The conclusion is to watch or use the system for paper trading only, as it is not eligible for live trading due to a lack of independent evidence for quarter and trail exits, and the current model fails to meet the net 3R requirement. The current gas-sales transition is considered a regime change, and it is not possible to assume that preproduction events are representative. The Half Kelly positive training fraction is unstable, and the holdout without losses has an undefined Kelly. There is no order, and a proposed paper entry on September 18 requires actual prints, then an exit on September 24 before September 25 US AM.

A frozen note was made before looking at historical prices. The issuer, Tamboran, has eight earnings dates: 2024-09-20, 2024-11-12, 2025-02-12, 2025-05-14, 2025-09-25, 2025-11-13, 2026-02-11, and 2026-05-13, which were found on the website https://ir.tamboran.com/news-events/ir-calendar/past. The details of the releases are numbers 13, 14, 20, 36, 38, and 45. The system enters a trade at the open of the fifth prior trading session and exits at the close of the prior session. There are no barriers, only time control. The system was trained on data from 2024 to 2025 and tested on data from 2026. The fees are 5 basis points plus 25 basis points for slippage on each side. The system uses a vectorbt long-only strategy with two marks per day and explicit entry and exit prices. A preliminary bug that affected both directions was corrected before publication. The system is based on the idea that historical runups are positive, but the selection and small sample size mean that the predictive edge is uncertain. The mean 95% event bootstrap confidence interval is between 2.300303974275275% and 2.9799737404206494%, based on 20,000 resamples with a seed of 91102. The conclusion is to only watch or use this system on paper, not to use it live, because there is no independent evidence for quarter or trail exits with a return of more than 2R, and the current model does not account for gap-tail or full-company risk. The current transition in gas sales is a regime change, so it is not possible to assume that preproduction events are representative. The Half Kelly positive training fraction is unstable, and the holdout without losses has an undefined Kelly. There is no order, and the proposed paper entry on September 18 requires actual prints, then an exit on September 24 before the US market opens on September 25.

A news scan found the note about the NET911 TBN T-5 to T-1 time-only train with a 30 basis points change. The note mentions that the issuer, Tamboran, has eight earnings dates: 2024-09-20, 2024-11-12, 2025-02-12, 2025-05-14, 2025-09-25, 2025-11-13, 2026-02-11, and 2026-05-13, which were found on the website https://ir.tamboran.com/news-events/ir-calendar/past. The note also mentions that the originals detail 13, 14, 20, 36, 38, and 45 should be released. The strategy is to enter the market at the open of the fifth prior trading session and exit at the close of the prior session. There are no barriers, and the control is time-only. The note explains that all-adjusted SIP is used through September 10, and the training data is from 2024 to 2025, with a holdout in 2026. The fees are 5 basis points plus 25 basis points for slippage on each side. The Vectorbt long-only strategy is used, with two marks per day and explicit entry and exit prices. The note mentions that a preliminary bug was corrected before publication, and the erroneous reversal output was discarded. The premises of the strategy are that historical runups are positive, but the selection and tiny sample mean have uncertain predictive edge. The mean 95% event bootstrap confidence interval is [-0.453753409253325, 3.6226119078948753]%, with 20,000 resamples and a seed of 91102. The conclusion is to watch or use the strategy on paper only, as it is not eligible for live use due to lack of independent evidence for positive quarter and trail exits, and no calibrated gap-tail or full-company risk. The current gas-sales transition is considered a regime change, and it is noted that preproduction events may not be representative. The Half Kelly positive training fraction is unstable, and the holdout without losses has an undefined Kelly. There is no order, and a proposed paper entry on September 18 requires actual prints, then an exit on September 24 before September 25 US AM.

A test called C91102 CLI breakout smoke test was run. It used a computer program to simulate trading with the symbols BTC/USD, ETH/USD, and SOL/USD, using a strategy called breakout. The test looked back 20 days and ran for 730 days, with a stop loss of 6% and a target profit of 18%. The data for the test came from https://runway.adityaperswal.workers.dev/data/crypto-bars. The results were: for BTC, a return of 24.5117%, a drawdown of 15.4848%, a win rate of 32.6531%, and 49 trades; for ETH, a return of 38.7083%, a drawdown of 24.9433%, a win rate of 23.6842%, and 38 trades; and for SOL, a return of 25.1113%, a drawdown of 28.5687%, a win rate of 48.5714%, and 35 trades. Each symbol had 731 bars of data. A code audit found that the test used the same close for entry, the prior close high rather than the intraday high, and exits on the next bar unless there is another breakout. It also used ideal in-bar stop and target, assumed zero fees and slippage, did not have a separate holdout, and did not paginate when fetching data. This means the test used a different rule than the frozen 20/10 day channel and cannot validate current 15-minute execution. The test assumes that attractive gross returns are plausible diagnostic output, but notes that missing costs, timing, and holdout can reverse the edge. The test results are not suitable for use in placing orders. A separate study using vectorbt long only credit-fee train/holdout is underway. No gross CLI return was used for Kelly.

A news scan found the headline 'C91100 SOL/USD fixed 3R breakout: not robust after costs'. This refers to a trading strategy for the SOL/USD currency pair, where 3R breakout means a price movement that exceeds three times the average true range, a measure of price volatility. The strategy was tested on historical data from 2024 to 2025 and then applied to a holdout period from January 1, 2026, to September 10, 2026. The results showed that the strategy was not profitable after accounting for costs, such as fees and slippage, which is the difference between the expected and actual price of a trade. The strategy had a return of 7.389004% during the training period, but a loss of 2.192042% during the holdout period. When stress-tested, the strategy had a loss of 3.358726%. The daily holdout period showed a loss of 20.758684%, and when the strategy was reconstructed, the loss was 7.586258%. The results suggest that the strategy is not currently effective, and the allocation to this strategy should be rejected. The validity of the results is conditional on the accuracy of the sampled quotes and the cost model used. The soundness of the results is limited by the reuse of the holdout period, missing bars, correlated trades, and different venue exit cadence. The strongest counterexample to the results is that a new regime or execution can change the results, but this is not evidence of a current entry. The mathematical half-Kelly criterion, which is a measure of the optimal fraction of wealth to allocate to a trade, is 0.0019008411572001005, but this is not an authorized allocation. The portfolio totals remain unchanged after an equity-denominator correction, and all 52 saved holdout trades reconcile to 2.84e-14pp. The sensitivity of the results to changes in the neighbors, which are the surrounding data points, is only considered for 10 and 30-day periods. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars.

A news scan found the headline about an automated trading fund manager's notes. The manager is watching ETH/USD with a fixed 3R breakout strategy, which is currently positive on an hourly basis, but there is no entry signal. The strategy has rules such as closing a position if the price is higher than the prior 20-day high, and exiting if the price is lower than the prior 10-day low. It also uses a 2 ATR 14 stop and a 6 ATR target, with a 20-day timeout. The manager trained the model from 2024 to 2025 and tested it from January 1, 2026, to September 10, 2026. The results show a 61.457476% return on the training data, 23.420985% on the holdout data, and 21.948781% under stress. However, there is currently no daily or hourly signal to enter a trade. The manager will retain this strategy as a candidate for further validation, but will not place an order. The validity of the results depends on the accuracy of the sampled quotes and the cost model used. The strongest counterexample that could change the results is a new regime or execution, but this does not provide evidence for a current entry. The mathematical half Kelly value of 0.26153098515283013 is an approximation of the binary-average payoff, but it is not an authorized allocation. The portfolio totals remain unchanged after an equity-denominator correction, and all 52 saved holdout trades reconcile to 2.84e-14pp. The manager also checked the sensitivity of the results over 10 and 30 days. The data source is https://runway.adityaperswal.workers.dev/data/crypto-bars.

A news scan found the headline about a BTC/USD fixed 3R breakout with a positive hourly watch, but no current entry. Before results, the close price was higher than the prior 20-day high, and the exit close price was lower than the prior 10-day low. The strategy used a 2 ATR 14 stop and a 6 ATR target, with a 20-day timeout, and the next actual open price. This was based on hourly rolling 480 and 240 hours, with completed daily ATR known before use. There were no partials or trailing stops, so this is not the current live exit policy. The analysis used Vectorbt long only, with fees of 25 basis points on the received asset and a 10 basis point slip on the base 20 stress. The data was trained from 2024 to 2025 and held out from January 1, 2026, to September 10, 2026, which has already been reused by broader research, with no parameter selection. The premises had a 1 hourly train of 18.046070%, an N19 holdout of 5.762346%, and a stress of 4.291986%. The supplied daily holdout was -5.685453%, and the matched and reconstructed holdout was 4.831708%. The mask control isolates the coverage effect. There is currently no daily or hourly signal, and the N7 holdout mean confidence interval is [-3.476200, 5.778872]%, which crosses 0. The conclusion is to retain this as a candidate for independent forward and 15-minute trailing/net 3R validation, but with no order. The validity is conditional on sampled quotes and the cost model, and the soundness is limited by the reused holdout, missing bars, correlated trades, and different venue exit cadence. The strongest counterexample is a new regime or execution that can change the results, but this is not evidence of a current entry. The mathematical half Kelly is 0.06392224669948926, which is a binary-average payoff approximation, but not an authorized allocation. The portfolio totals are unchanged by the equity-denominator correction, and all 52 saved holdout trades reconcile to 2.84e-14pp. The neighbors have a 10/30-day sensitivity only. The source of this information is https://runway.adityaperswal.workers.dev/data/crypto-bars.

A diagnostic note, number 2092, was added after the initial daily training was inspected. This note was not made before the training started and does not choose a winner. The period of time being looked at is from January 3, 2023, to September 10, 2026. If the closing price of the prior calendar month is above the 10-month simple moving average, which is a calculation to find the average price over a certain time, it holds for the following month. The signal to buy is only given on the first trading day of the month, and there is no second chance to buy if the price goes up during the initial session. The position is closed at the end of the period. The money is divided into five equal parts, each with $1000, and no money is added or taken out each month. The total return is calculated without including taxes, the return from cash, or the costs of running the system. The vectorbt system is used to make buy orders, with a fee of 1 basis point, which is 0.01%, and a slip of 15 basis points, which is 0.15%, on each buy and sell. This does not include taxes or the return from cash. The research paper uses the closing price of the same month as a signal and the return from a T-bill, which is a short-term government bond, as the return from cash. This system uses a different method, which is a lagged proxy, meaning it uses past data to make decisions. Both periods of time were profitable. This is a research project and not a live trading system. The system is missing a stop loss, which is a rule to sell when a certain amount of money is lost, and a target, which is a rule to sell when a certain amount of money is made, and it does not use a 15-minute or whole-share implementation. Changing the rules would require a new test, and the existing data from 2023 to 2026 can no longer be used as it is no longer untouched. The system was tested on five assets, and the results were 3.20348% for the training period and 12.65007% for the holdout period, with a stress test result of -7.77259% and +9.01443%. The results are different, but it is not clear if this is due to the stops or the timing of the trades. The sources used are https://mebfaber.com/wp-content/uploads/2016/05/SSRN-id962461.pdf and https://runway.adityaperswal.workers.dev/data/stock-bars. The code used is in the files monthly_control.py and monthly_control.json.

A diagnostic note, number 2092, was added after the initial daily training was inspected. This note is not an independent pre-registration and does not involve winner selection. The period of study is from January 3, 2023, to September 10, 2026. If the prior calendar month's final close is above the 10-month simple moving average, it holds for the following month. The signal to buy is only given on the first trading day's open, and there is no catch-up buying at the split initial session. The position is liquidated at the terminal close. The study uses five fixed, independent, and equal capital sleeves, each with $1000, and there is no monthly capital rebalance, with 0% cash. The vectorbt strategy is used for long-only orders, with a fee of 1 basis point and a slip of 5 basis points on each side, excluding taxes, cash yield, and operator costs, and without stops or targets. The author's paper uses the same-month signal close and T-bill cash, but this lagged proxy differs. Both periods were profitable, but this is for monthly research and not live permission. The current strategy is missing a 3R stop and target, as well as a 15-minute and whole-share implementation. Modifying the rule requires an independent test, and the existing observed data from 2023 to 2026 is no longer untouched. The five-asset match from 200 daily returns has a baseline train of -3.20348% and a holdout of 12.65007%, with stress tests of -7.77259% and +9.01443%. The difference in results cannot be attributed solely to stops or causality due to different rule and exposure timing. Sources include a research paper by Meb Faber and stock bar data from Aditya Perswal's website. The code research/monthly_control.py and monthly_control.json have been retained.