Stats

A command was given to run a test on a trading strategy using the stocks FRO and STNG. The test used a strategy called breakout, looking back 20 days, over 2080 days, with a stop loss of 10 percent and a target gain of 30 percent. The test returned 1426 sets of stock price data and used a method called signal-driven exits, as well as stop losses and target gains based on percentages. This test did not include costs of executing trades or a separate set of data to test the results. It was a diagnostic test, not a copy of a specific investment policy, and cannot validate that policy. The data came from https://runway.adityaperswal.workers.dev/data/stock-bars. The results of this test and another method were kept, even if they were not the same, to show the differences between the two methods.

The primary lookback period, L20, remains fixed. The L10 and L40 lookback periods are used for sensitivity analysis only, with no selection of the best lookback period after reviewing the holdout data. The split-only analysis excludes dividends, so it only considers price performance, not total shareholder return. Changing the adjustment also changes the signal dates and exits. The analysis uses the same parameters: 2 ADR stop, 3R target, 40 sessions, 1 basis point fees, and 5/15 basis points lip. The vectorbt open, execution, and close marks are used, with training data from 2021 to 2024 and testing data from 2025 to September 11. The results, which exclude open marks from the win percentage, are as follows: a list of results with different lookback periods, adjustments, start dates, and slip values, including return, drawdown, win percentage, and number of trades. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. All exact means, confidence intervals, and exit counts were recorded from 26226 to 26265. The test period is shared across variations, so the variations are not independent evidence.

The primary lookback period, L20, remains fixed. The L10 and L40 lookback periods are used for sensitivity testing only, with no selection of the best lookback period after reviewing the holdout data. The split-only method excludes dividends, so it only measures price performance, not the total return to shareholders. Changing the adjustment also changes the signal dates and exits. The same parameters were used for all tests, including a 2ADR stop, 3R target, and 40 sessions, with fees of 1 basis point and slippage of 5 or 15 basis points. The vectorbt open, execution, and close marks were used. The data was trained from 2021 to 2024 and tested from 2025 to September 11. The results, which exclude open marks from the win percentage, are as follows: a list of tests with different lookback periods, adjustments, start dates, slippage, returns, drawdowns, win percentages, and number of trades. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. All exact means, confidence intervals, and exit counts were recorded from 26226 to 26265. The test period is shared across all variations, so the variations are not independent evidence.

A trading fund manager analyzed the stock STNG. Before running the analysis, the manager set rules: if the stock's price broke out from its prior 20-day close and 50-day Simple Moving Average, which is a calculation of the stock's average price over 50 days, the manager would buy the stock at the next session's open. The manager would set a stop loss, which is an order to sell the stock when it falls to a certain price, at two times the stock's prior 20-day Average Daily Range, which is a measure of the stock's volatility. The target price, which is the price at which the manager wants to sell the stock, was set at three times the initial risk. The manager would hold the stock for a maximum of 40 sessions, including the entry session. The manager also set a rule to sell a quarter of the stock if it reached a 2R return, which means the stock's price increased by twice the initial risk, and make the stop loss break even the next day. The manager tested this strategy using historical data from September 11, 2025, and found that the return was 36.36363636363637% for winning trades, excluding open outcomes. The manager also found that the strategy had 1 target, 7 stops, and 3 timeouts, and that buying and holding the stock would have resulted in a 74.95342579176152% return. The manager used a dataset from https://runway.adityaperswal.workers.dev/data/stock-bars, which provides synthetic dividend-adjusted asset prices, not cash dividend payment timing or executable raw-price fills. The manager separated the data into training and test periods and found that the strategy had an uncertainty of -4.524399609507263% to 5.843595649618188% based on 10,000 bootstrap resamples. The manager notes that this analysis is not proof of a zero edge, which means that the strategy may still be profitable, and that the results should not be treated as an established stock edge due to holdout and stress weaknesses.

A trading fund manager's notes were analyzed. The manager used a system that froze certain settings before running the results. These settings included a breakout and a 50-day Simple Moving Average, which is a way to calculate the average price of a stock over a certain period. The system also used a stop-loss, which is a price level at which to sell a stock to limit losses, set at twice the average daily range of the past 20 days. The target price was set at three times the risk, and the maximum number of sessions was 40, including the entry session. The system was tested on the stock STNG. If the stock reached a certain level of profit, called 2R, the system would sell a quarter of the stock and make the stop-loss price equal to the purchase price the next day. The system used a 1 basis point fee and 5 basis points of slippage per side, which is a way to measure the cost of buying or selling a stock. The results showed a return of 44.44444444444444% and a mean bootstrap return of between -1.5149595070621042% and 8.708828524196868%. The system had 6 targets, 14 stops, and 7 timeouts. The data was retrieved from a website on September 12. The system's results are based on a model that adjusts for dividends, but does not reflect the actual timing of dividend payments or the prices at which trades can be executed. The test period was separate from the training period, but the test period had been previously inspected for other rules, so it was not completely unseen. The results show the payoff shape, but do not reflect the whole-share or 15-minute implementation. The holdout and stress weakness prevent the screen from being treated as an established stock edge.

A news scan found the results of a trading simulation for the stock STNG. The simulation was frozen before the results were generated, using a prior 20-day close breakout and a 50-day Simple Moving Average, which is a calculation of the average price of a stock over a certain period of time. The next session's open price was used, and the stop loss was set at 2 times the prior 20-day Average Daily Range, which is a measure of the average daily price movement. The target was set at 3 times the risk, and the maximum number of sessions was 40, including the entry session. The simulation used a prior 2020 warm-up period. The exits were fixed, with no discretionary trailing, which means that the exit points were predetermined and not subject to change. Gap exits used the open price, and ambiguous daily bars stopped at the first price, with entry day exits allowed, although none were observed. The costs included a 1 basis point fee and 5 basis points of slippage per side, with a stress test of 15 basis points of slippage. The vectorbt long-only fractional full-equity portfolio was reconciled to manual cash, including the entry fee, and the marks were ordered by open, execution, and close. The return included 1 open mark, with 11 losses and a win rate of 27.27%. The mean bootstrap of 10,000 independent and identically distributed resamples, with a seed of 91206, showed a 95% confidence interval of -5.20% to 5.85%, which indicates uncertainty and not proof of zero edge. The results showed 1 target, 7 stops, and 3 timeouts, with a buy and hold return of 74.95%. The data was sourced from https://runway.adityaperswal.workers.dev/data/stock-bars, retrieved on September 12, with a timeframe of 1 day and an adjustment for all dividends. The adjustment all returns model used synthetic dividend-adjusted assets, not cash dividend payment timing or executable raw price fills. The training and test periods were separated, and the test period had previously been inspected for other rules, making this a chronological holdout for this frozen specification, but not globally unseen evidence. The results quantify the payoff shape, but not the whole share or 15-minute implementation. The holdout and stress weakness prevent treating the screen as an established stock edge.

A trading fund manager analyzed the stock STNG from 2021 to 2024. The manager used a fixed exit strategy, which means they decided when to sell the stock before the results were known. The strategy was based on the stock's prior 20-day closing price and its 50-day moving average, which is a way to smooth out price changes. The manager also set a stop-loss, which is a price at which to sell the stock if it falls, at 2 times the stock's average daily range over the past 20 days. The target price was 3 times the risk, and the manager limited the trade to 40 sessions, including the day the stock was bought. The manager used a long-only strategy, which means they only bought the stock, and they reconciled the portfolio to manual cash, including the entry fee. The return on investment was calculated, excluding open outcomes, and the win rate was 46.15384615384615%. The manager also ran a simulation 10,000 times to estimate the uncertainty of the results, which showed a 95% confidence interval of -0.6130553619346064% to 10.616290391886833%. The results showed 6 targets, 12 stops, and 8 timeouts, and the buy-and-hold return was 377.8375088751394%. The data used was from the website https://runway.adityaperswal.workers.dev/data/stock-bars, retrieved on September 12, and the adjustment used was all, which means the returns were adjusted for dividends and other factors. The training and test periods were separated, and the test period was previously inspected for other rules, so the results are not necessarily representative of the whole market. The manager notes that the results do not prove a zero edge, but rather quantify the payoff shape, and that the holdout and stress weakness prevent treating the screen as an established stock edge.

A trading fund manager's notes were frozen before the results of this run. The notes show that the fund used a prior 20-day close breakout and a 50-day Simple Moving Average, which is a calculation of the average price of a stock over 50 days. The next session's open price was used, and the stop loss was set at 2 times the prior 20-day Average Daily Range, which is a measure of the average daily price range of a stock over 20 days. The target was set at 3 times the risk, and the maximum number of sessions was 40, including the entry session. The fund also used a prior 2020 warm-up period. On a surviving day when the fund reached 2 times the risk, it sold a quarter of the position and made the stop loss breakeven the next day. The fund tested the full stop loss and target first, so intraday ordering and 15-minute management were not reconstructed. Gap exits used the open price, and ambiguous daily bars stopped first. Entry day exits were allowed, but none were observed. The fund had costs of 1 basis point fee and 5 basis points slippage per side, and a stress test of 15 basis points slippage. The vectorbt long-only fractional full-equity portfolio was reconciled to manual cash, including the entry fee, and marks were ordered open, execution, and close. The return included 1 open mark, and the fund had 18 losses and a win rate of 44.44444444444444%, excluding open outcomes. The mean bootstrap of 10,000 independent and identically distributed resamples with a seed of 91206 showed a 95% confidence interval of -2.240298785942834% to 8.466477223104828%, which is a measure of uncertainty, not proof of zero edge. The fund had 6 targets, 11 stops, and 1 timeout, and the buy and hold return was 280.5877803557618%. The data source was https://runway.adityaperswal.workers.dev/data/stock-bars, retrieved on September 12, and the adjustment all returns model used synthetic dividend-adjusted assets, not cash dividend payment timing or executable raw-price fills. The training and test periods were separated, and the test period was previously inspected for other rules, so this was a chronological holdout for this frozen specification, but not globally unseen evidence. The result quantifies the payoff shape, not the whole-share or 15-minute implementation. The positive result retains the watch, but the upcoming raw stop distribution mechanics must be resolved.

A news scan found the report of an automated trading fund manager for the stock FRO. The manager's rules were: if the stock's price breaks out above its prior 20-day close and 50-day Simple Moving Average, which is a calculation of the stock's average price over 50 days, then buy the stock at the next session's open. The stop loss, which is the price at which to sell the stock to limit losses, was set at 2 times the stock's prior 20-day Average Daily Range, which is a measure of how much the stock's price typically moves each day. The target price, which is the price at which to sell the stock for a profit, was set at 3 times the amount risked. The manager also decided to sell one quarter of the stock if it reached a 2R profit, which means twice the amount risked, and to make the stop loss break even the next day. The manager tested these rules using historical data from September 11 to September 12, and found that the strategy had a return of 42.42424242424242% excluding open outcomes, with 33 losses and 7 targets reached out of 24 stops and 2 timeouts. The manager also found that buying and holding the stock would have resulted in a return of 191.44447020635292%. The manager used a mean bootstrap of 10000 resamples to estimate the uncertainty of the results, and found that the 95% confidence interval was between -1.7832491318441552% and 5.371609867705768%. The manager retrieved the historical data from https://runway.adityaperswal.workers.dev/data/stock-bars on September 12 at 23:40Z.

A trading fund manager made notes about a trading strategy. The strategy was frozen before the latest results came in, based on a prior 20-day close breakout and a 50-day simple moving average, or SMA, which is a way to smooth out price changes. The next session's open price was used, and the stop loss was set at 2 times the prior 20-day average daily range, or ADR, which is a measure of how much prices move. The target was set at 3 times the risk, and the maximum number of sessions was 40, including the entry session. The strategy was backtested using data from 2020 as a warm-up period. The strategy used full fixed exits, with no discretionary trailing stops, which means the stop loss was not adjusted manually. Gap exits used the open price, and ambiguous daily bars stopped at the first sign of trouble. Entry day exits were allowed, but none were observed. The strategy included costs of 1 basis point fee plus 5 basis points of slippage per side, which is a measure of how much prices move when a trade is made, and stress tested with a 15 basis point slippage. The portfolio was reconciled to manual cash, including the entry fee, and marks were ordered by open, execution, and close. The return included 1 open mark, and the win rate was 47.05882352941176%. The mean bootstrap return, which is a way to estimate uncertainty, was calculated using 10,000 independent and identically distributed resamples with a seed of 91206, and the 95% confidence interval was -1.3523231382960088% to 10.722254655961946%, which is a measure of uncertainty, not proof of zero edge. The strategy had 7 targets, 9 stops, and 1 timeout, and the buy and hold return was 280.5877803557618%. The data source was https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FRO&timeframe=1Day&feed=sip&adjustment=all, retrieved on September 12 at 23:40Z. The adjustment all returns model used synthetic dividend-adjusted asset prices, not cash dividend payment timing or executable raw price fills. The training and test periods were separated, and the test period had previously been inspected for other rules, so this was a chronological holdout for this frozen specification, but not globally unseen evidence. The strategy quantifies payoff shape, not whole share or 15-minute implementation. A positive result retains watch, and the upcoming raw stop distribution mechanics must be resolved.

A trading fund manager has written notes about a training program for the stock FRO. The program uses a fixed exit strategy, which means it sells stocks at a set price. The strategy is based on two things: the stock's price compared to its average price over 50 days, and its previous day's closing price. If the stock's price is higher than these two things, the program buys it. The program also sets a stop loss, which is a price at which it automatically sells the stock if it starts to lose value. The stop loss is set at twice the stock's average daily range over 20 days. The program aims to make three times the amount it risks, and it limits the time it holds a stock to 40 sessions. The program was tested using data from 2020 and 2021. The test included costs such as a 1 basis point fee and 5 basis points of slippage per trade. The results showed a return of 33.33333333333333% of winning trades, excluding trades that are still open. The program used a statistical method called bootstrapping to estimate its uncertainty, which showed a 95% confidence interval of -1.9720576853637237% to 6.135799986935027%. The program had 9 successful trades, 21 stopped trades, and 3 trades that timed out. The stock FRO had a return of 191.44447020635292% if it was bought and held. The data used for the test was retrieved from a website on September 12. The program adjusts the stock's price to account for dividends, but it does not account for the timing of dividend payments or the actual price at which trades are executed. The test was done in two parts: a training period and a test period. The test period was not used to develop the program, but it was used to test other rules. The program's results are positive, but it needs to be improved to handle stop losses in a more realistic way.

A diagnostic and sensitivity audit was performed on a trading strategy using the command line interface. The command used was to run a node with the following parameters: the file backtest.js, the symbol FTK, the breakout strategy, a lookback period of 20 days, a total of 2080 days, a stop loss percentage of 10, and a target percentage of 30. The results showed a return of 13.7774%, a drawdown of 49.9074%, and 66 trades with a win rate of 33.3333%. This test did not account for costs or adjustments and was not an independent holdout. The data used can be found at https://runway.adityaperswal.workers.dev/data/stock-bars. A sensitivity audit was also performed with different parameters, including a 10, 20, and 40 period sensitivity, using a SIP adjustment, a warmup period in 2020, training from 2021 to 2024, and a holdout period from 2025 to September 11, 2026, with fees of 1 basis point and a slip of 5 or 15. All 12 tests had negative results. The correct open and close marks were used, superseding earlier drawdown only marks. The training drawdown for the 10 period sensitivity was 86.7031% and 87.1476%, while the holdout drawdown was 46.9088% and 47.8559%. The training drawdown for the 40 period sensitivity was 59.3906% and 60.6103%, while the holdout drawdown was 31.7072% and 32.8585%. The sample size for the 10 period sensitivity was 24 trades for training and 15 trades for holdout, each with 1 unfinished trade. The sample size for the 40 period sensitivity was 16 trades with no change in returns from 2847 to 2850 and 2855 to 2858. There was no favorable lookback selection or strategy adoption. The command line interface sample of 66 unadjusted trade histories and SIP costed samples answer different questions.

This update corrects the marks for FTK as of 2025-01-01 with a 15bp change. It only changes the drawdown in the main analyses, which are sections 2851-2854, and keeps the rule from 2531 that freezes certain values. The original marks used the closing prices for both parts, which incorrectly marked the exit day close before the modeled intraday exit. The corrected marks use the actual open and close prices, alternating between them, with entry happening in the first slot and exit in the second slot. The drawdown marked by open and close is not the full worst-case scenario within a day. The data comes from https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FTK&timeframe=1Day&feed=sip&adjustment=all. The strategy uses a close breakout with a 20-period limit and a 50-period simple moving average, with the next open, a 2 average daily range stop, and a 3 times return target, over 40 sessions, with 1 basis point fees and 15 basis points slip per side, from 2020 for warm-up, and from 2025-01-01 to 2026-09-11. There were 14 completed trades and 0 open trades; the strategy stops at the first ambiguous bar, allows gap open exits, and retains entry day exits. The compounded cash return reconciliation passed. The strategy still does not allow trading due to the absence of 15-minute management and a plus 2 times return management. All 12 sensitivity revised drawdown tables have been updated in the latest observation without retuning any parameters.

This correction replaces the previous drawdown analysis in sections 2851-2854, but keeps the rule that was in place since 2531, including samples, fills, and returns. The original analysis used closing prices for both entry and exit points, which incorrectly marked the exit day close before the modeled intraday exit. The corrected analysis uses actual open and close prices, alternating between the two, with entry occurring at the start of the period and exit at the end. This means that the drawdown, which is the decrease in value, is not the full worst-case scenario for the entire day. The data comes from a stock market data source. The trading strategy used is based on a 20-day closing price breakout and a 50-day moving average, with a stop loss and target return. The strategy was tested from January 1, 2025, to September 11, 2026, with 14 completed trades and no open trades. The analysis still does not recommend trading due to missing risk management and other factors. All sensitivity analyses have been revised in the latest observation, with no changes to the parameters.

This update replaces the previous drawdown information in analyses 2851-2854, but keeps the rule that was in place since 2531, along with samples, fills, and returns. The original marks used closing prices for both entry and exit, which incorrectly marked the exit day close before the modeled intraday exit. The corrected marks now alternate between actual open and close prices, with entry happening in slot 0 and exit in slot 1. This means the drawdown marked by open and close prices does not show the full worst-case scenario that could happen within a day. A news scan found the data source https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FTK&timeframe=1Day&feed=sip&adjustment=all. The trading strategy used is L20 close breakout with a 50-day Simple Moving Average, next open, 2 Average Daily Range stop, and a 3 Reward target, over 40 sessions, with 1 basis point fees and 15 basis points slip per side, from 2020 warmup to 2021-01-01 to 2024-12-31. There were 26 completed trades and 0 open trades. The strategy stops at the first ambiguous bar, retains gap open exits and entry day exits. The compounded cash return reconciliation passed. However, the strategy still rejects trading due to the absence of 15-minute management and a +2 Reward management. All 12 sensitivity revised drawdown tables have been updated in the latest observation without any parameter retuning.

A news scan found the text: Supersedes drawdown only in primary analyses 2851-2854; retains frozen 2531 rule, samples, fills and returns. Original two-slot marks used closing prices in both slots, incorrectly marking exit-day close before modeled intraday exit. Corrected vectorbt, a backtesting library, price marks alternate actual open/close, while entry occurs slot 0 and exit slot 1; open/close marked drawdown is not full intraday worst case. Source is a data line from https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FTK&timeframe=1Day&feed=sip&adjustment=all. The strategy uses L20 close breakout and SMA50, next open, 2 ADR stop, and 3R target, with 40 sessions, 1bp fees, and 5bps slip per side, from 2020 warmup, 2021-01-01 to 2024-12-31. There were 26 completed trades and 0 open trades; stop first ambiguous bar, gap open exits, and entry day exits were retained; compounded cash return reconciliation passed. The system still rejects trading; 15min and +2R management are absent. All 12 sensitivity revised DD table in latest observation; no parameter retuning was done.

A trading strategy was tested on the stock FTK. The strategy had three main rules: first, it only bought FTK if the previous day's closing price was higher than the highest closing price of the last 40 days and the average closing price of the last 50 days; second, it bought FTK at the next day's opening price, with a stop-loss at 2 times the average daily range of the last 20 days below the entry price, and a target price at 6 times the average daily range above the entry price, and it sold FTK after 40 days; third, it accounted for 1 basis point in fees and 15 basis points in slippage for each buy and sell, and it used data from 2020 as a warm-up, from 2021 to 2024 for training, and from 2025 to September 11, 2026, as a hold-out period. The strategy used a long-only portfolio and retained entry-day exits. The results showed 11 closed trades, with no unfinished trades or entry-day exits. The conclusion was to reject the strategy due to a negative geometric return, compared to a buy-and-hold return of 185.580%. The test was not event-specific and did not select parameters from the hold-out period. FTK was selected retrospectively, and corporate or regime changes may weaken the transferability of the results.

A trading strategy was tested on the stock FTK. The strategy had three main rules: first, it only considered buying FTK if the previous day's closing price was higher than the highest closing price of the last 40 days and the average closing price of the last 50 days; second, it bought FTK at the next day's opening price, with a stop-loss set at 2 times the average daily range of the last 20 days below the entry price, and a target price set at 6 times the average daily range above the entry price, and it sold FTK after 40 days; third, it accounted for 1 basis point in fees and 5 basis points in slippage for each buy and sell, and it used data from 2020 as a warm-up, from 2021 to 2024 for training, and from 2025 to September 11, 2026, as a holdout period. The strategy was tested using a long-only portfolio that allowed for two trades per day, and it included fees in the calculation of returns. The test resulted in 11 closed trades, with no unfinished trades or same-day exits. However, the strategy was rejected due to a negative geometric return, compared to a buy-and-hold return of 185.580%. This test was not designed to evaluate the strategy's performance in response to specific events, and it did not involve selecting parameters based on the holdout period or using 15-minute exits or other implementation details. The stock FTK was selected for this test after the fact, and changes in the company or market conditions may limit the applicability of the results.

This is a description of a trading strategy test. The test had three main points: first, it only considered buying a stock if the previous day's closing price was higher than the highest closing price of the last 40 days and the average closing price of the last 50 days; second, it bought at the next day's opening price, with a stop-loss set at 2 times the average daily range of the last 20 days below the entry price, and a target price set at 6 times the average daily range above the entry price, and it sold the stock after 40 days; third, it accounted for 1 basis point in fees and 15 basis points in slippage for each buy and sell, and it used data from 2020 as a warm-up, from 2021 to 2024 for training, and from 2025 to September 11, 2026, as a separate test. The test used a type of moving average called SMA50, which is a way to calculate the average price of a stock over a certain period, in this case, 50 days. A basis point is a unit of measurement, equal to 0.01%, used to express the percentage change in the value of a financial instrument. The test also used a type of risk measurement called ADR20, which stands for Average Daily Range over 20 days, and is a way to measure the average price movement of a stock over a certain period. The source of the data is a website that provides stock market data. The test resulted in 16 closed trades, with 2 of them being closed on the same day they were opened. The conclusion of the test was to reject the strategy because it had a negative geometric return, which means that the strategy lost money over time. For comparison, simply buying and holding the stock would have resulted in a loss of 25.779%. This test was not meant to be used for actual trading decisions, and the stock, FTK, was chosen after the fact, which may not be representative of future results.

This is a description of a trading strategy test. The test had three main points: first, it only considered buying a stock if its previous closing price was higher than its highest closing price in the last 40 days and its 50-day moving average, which is a calculation of the average price of a stock over 50 days. Second, the test entered a trade at the next opening price, with a stop-loss set at 2 times the average daily range of the last 20 days below the entry price, and a target price set at 6 times the average daily range above the entry price, and the trade was closed after 40 trading sessions. Third, the test included fees of 1 basis point, which is a unit of measurement for interest rates and fees, and slippage of 5 basis points, which is the difference between the expected price of a trade and the actual price, on both the buy and sell sides, and used data from 2020 as a warm-up, trained on data from 2021 to 2024, and tested on data from 2025 to September 11, 2026. The test used a type of trading strategy called vectorbt, which is a long-only and full-cash portfolio, meaning it only buys stocks and does not short sell, and it uses two ordered events per day to allow for same-day exits and gap exits at the open. The test also used a type of stop-loss called ambiguous high/low stopfirst. The results of the test included 16 closed trades, with 2 of them being exited on the same day they were entered, and the test concluded that the strategy should be rejected due to a negative geometric return, which is a measure of the return of an investment over time. The test also compared the results to a buy-and-hold strategy, which had a return of -25.779%. The test was not event-specific and did not select parameters from the holdout data, and the stock FTK was selected retrospectively, meaning it was chosen after the fact, and corporate and regime changes may weaken the transferability of the results.

A trading strategy called R91204 was tested on the stock FTK. The strategy had three main rules: first, it only considered buying FTK if the previous day's closing price was higher than the highest closing price of the last 20 days and the average closing price of the last 50 days; second, it bought FTK at the next day's opening price, with a stop-loss set at 2 times the average daily range of the last 20 days below the entry price, and a target price set at 6 times the average daily range above the entry price, and it sold FTK after 40 trading sessions; third, it accounted for 1 basis point in fees and 15 basis points in slippage for each buy and sell, and it used data from 2020 as a warm-up, from 2021 to 2024 for training, and from 2025 to September 11, 2026, as a holdout period. The strategy was tested using a long-only portfolio that allowed for two trades per day, and it included fees in the calculation of returns. The test resulted in 14 closed trades, with 1 trade being closed on the same day it was opened. The strategy was found to have a negative geometric return, which means it performed poorly. For comparison, a simple buy-and-hold strategy would have returned 185.580%. The test was not designed to evaluate the strategy's performance in response to specific events, and it did not involve selecting the best parameters for the strategy or using 15-minute exits. The stock FTK was chosen for the test after the fact, and changes in the company or market conditions may affect the strategy's performance in the future.

A trading strategy was tested on the stock FTK. The strategy had three main rules: first, it only bought FTK if the previous day's closing price was higher than the highest closing price of the last 20 days and the average closing price of the last 50 days; second, it bought FTK at the next day's opening price, with a stop-loss set at 2 times the average daily range of the last 20 days below the entry price, and a target price set at 6 times the average daily range above the entry price, and it sold FTK after 40 days; third, it accounted for 1 basis point in fees and 5 basis points in slippage for each buy and sell, and it used data from 2020 as a warm-up, data from 2021 to 2024 for training, and data from 2025 to September 11, 2026, as a holdout test. A basis point is one hundredth of a percent. The average daily range is a measure of how much a stock's price moves in a day. The test used a type of analysis called vectorbt, which allows for two events per day to keep the same day's exits, and it used a type of stop-loss called gap exits at open, which sells a stock if it opens below a certain price. The test also used a type of stop-loss called ambiguous high/low stopfirst, which sells a stock if it reaches a certain high or low price. The results included 14 closed trades, and the strategy was found to have a negative geometric return, which means it did not perform well. For comparison, a buy-and-hold strategy would have returned 185.580%. The test was not meant to be used for a specific event, and it did not try to find the best parameters using the holdout data. FTK was chosen for the test after the fact, and changes in the company or market conditions may affect how well the strategy works in the future. A news scan found the source https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FTK&timeframe=1Day&feed=sip&adjustment=all.

A trading strategy was tested on the stock FTK. The test had three main rules: first, the stock's previous closing price had to be higher than its highest closing price in the last 20 days and its average closing price over the last 50 days; second, the strategy would buy the stock at the next opening price, with a stop-loss set at 2 times the stock's average daily range over the last 20 days, and a target price set at 6 times the average daily range, with the trade closing after 40 sessions; third, the test included fees of 1 basis point and slippage of 15 basis points for each buy and sell, with the data from 2020 used for warm-up, 2021-2024 for training, and 2025 to September 11, 2026, for holdout. A basis point is one hundredth of a percent. The test used a long-only portfolio, meaning it only bought stocks, and it used two events per day to allow for same-day exits and exits at the opening price. The test results showed 26 closed trades, with 2 of them closing on the same day they were opened. The conclusion was to reject the strategy due to a negative geometric return, meaning the strategy lost money. For comparison, simply buying and holding the stock would have lost 25.779%. This test was not meant to predict specific events and did not use the holdout data to select the best parameters. The stock FTK was chosen after the fact, and changes in the company or market conditions might affect the results. A news scan found the data source https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FTK&timeframe=1Day&feed=sip&adjustment=all.

A trading strategy was tested on the stock FTK. The test had three main rules: first, the stock's previous closing price had to be higher than its highest closing price in the last 20 days and its average closing price over the last 50 days; second, the trade would start at the next opening price, with a stop-loss set at 2 times the average daily range of the last 20 days below the entry price, and a target set at 6 times the average daily range above the entry price, and the trade would end after 40 trading sessions; third, each trade would have a 1 basis point fee and a 5 basis point slippage on both the buy and sell sides, with the years 2020 used for warm-up, 2021-2024 used for training, and a separate holdout period from 2025 to September 11, 2026. The data for the stock FTK came from the website https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FTK&timeframe=1Day&feed=sip&adjustment=all. The test used a type of trading strategy called vectorbt, which only buys stocks and uses cash for the rest of the portfolio, and it allowed for two trades per day to keep the trades that ended on the same day they started, and it also allowed for trades to end at the opening price if there was a big gap. The test results included the fees paid to start trades in the total returns, and the test passed a check to make sure the returns were calculated correctly. There were 26 trades that ended, and none of them were still open when the test ended, so they were all included in the results. Two trades ended on the same day they started. The test concluded that the strategy did not work well because it had a negative return. For comparison, simply buying and holding the stock would have resulted in a loss of 25.779%. This test was not done to see how the strategy would work in a specific situation, and it did not try different parameters to see which ones worked best. The stock FTK was chosen after the fact, and any big changes in the company or the market could make the results less reliable.

The automated trading fund manager made some premises to test a trading strategy. The premises were: the previous day's closing price was higher than the highest closing price of the previous 10 days and the 50-day simple moving average, which is a calculation to find the average price of a stock over a certain period, in this case 50 days. The manager then entered the trade at the next day's opening price, with a stop loss set at 2 times the average daily range of the previous 20 days, and a target price set at 6 times the average daily range. The trade was exited after 40 sessions. The manager also accounted for 1 basis point fees and 15 basis points slippage on each side of the trade, where basis points are a unit of measurement for interest rates and slippage refers to the difference between the expected price of a trade and the actual price. The data used for the test was from 2020 to September 11, 2026. The manager used a long-only full-cash portfolio, which means the portfolio only buys stocks and does not short sell, and uses two ordered events per day to allow for same-day exits. The results showed 15 closed trades and 1 unfinished trade, which was excluded from the analysis. The conclusion was to reject the strategy due to a negative geometric return, which is a measure of the return on investment. The return was compared to a buy-and-hold strategy, which returned 185.580%. The manager noted that this was not an event-specific backtest and the parameters were not selected from the holdout data. The stock FTK was selected retrospectively, meaning after the fact, and corporate or regime changes may affect the transferability of the results.