Stats

A test of the Frozen20/10 note1291 was conducted from 1312 to 1322, and later a diagnostic training-only grid search was performed with look periods of 10, 20, and 40, and hold periods of 5, 10, and 20. The data used for this test came from https://runway.adityaperswal.workers.dev/data/stock-bars. The results of the test are as follows: for the stock SEI, the return and drawdown were calculated for different look and hold periods, with returns ranging from 17.95 to 189.77 and drawdowns ranging from 46.93 to 73.47; for the stock LEU, the return and drawdown were calculated for different look and hold periods, with returns ranging from -37.60 to 547.84 and drawdowns ranging from 46.68 to 77.06; for the stock HUT, the return and drawdown were calculated for different look and hold periods, with returns ranging from 75.26 to 731.39 and drawdowns ranging from 50.21 to 86.09. Despite some positive development performance, the results are insufficient to adopt a winner due to large drawdowns and uncertainty. No winner was adopted from this sweep. In the future, any independent rule must be preregistered prospectively and cover venue exits.

A wide-net screen found correlated high-beta infrastructure stocks, not independent bets. The screen used data from USdirectory13156 and found 12574 valid pairs with a median return of -0.808625%, a 10th percentile return of -3.832307%, and a 90th percentile return of 2.646877%. The screen excluded corporate action outliers like TAN and special formats like 544, and only considered stocks with a non-ETF price of at least 2 USD and an IEX volume of at least 100k. The chosen tickers were not random, but were matched against the SPY using ordinary least squares (OLS) regression, which is a statistical method to measure the relationship between variables. The results showed that the tickers SEI, LEU, and HUT had correlations with each other and with the SPY, with correlation coefficients ranging from 0.453 to 0.562. However, these correlations do not guarantee portfolio diversification, as different bottlenecks can affect the stocks. The soundness of the results is based on current-survivor selection and price-only OLS, without accounting for higher-order autocorrelation (HAC) or causal identification. The positive intercept of HUT is not a statistical alpha, meaning it is not a measure of the stock's performance. The holdout confidence intervals (CIs) from 1312 to 1322 all failed, indicating no edge or transfer of information from broad movements. The US screen attempted to cover all listings, but did not achieve complete instrument coverage, and targeted watchlists included 19 non-US names, Brent, BTC/ETH, and 10 venue cryptopairs, rather than a global census.

A diagnostic test was executed on September 9 at 02:04 using the node /app/agent/dist/backtest.js program with the symbols SEI, LEU, and HUT, and a breakout strategy. The test looked back 20 periods over 730 days, with a stop loss of 3 percent and a target of 6 percent. The data came from https://runway.adityaperswal.workers.dev/data/stock-bars. The results for HUT were: 501 bars of data, a return of -38.57 percent, a buy and hold return of 899.20 percent, a maximum drawdown of 48.15 percent, a win rate of 23.21 percent, and an average trade return of -0.80 percent, based on a sample of 56 trades. This was a same-close IEX diagnostic test without considering the cost of holding, and the strategy was not validated. Separate tests, coded independently, were run from 1312 to 1322 to define different exits, but this does not claim to replicate the results.

A trading test was done on September 9 at 02:04 using a computer program called backtest.js. The test looked at the stocks SEI, LEU, and HUT using a strategy called breakout, which means buying when a stock's price breaks out of a certain range. The test looked back 20 days and considered 730 days of trading. It used a stop loss of 3 percent and a target profit of 6 percent. The data came from https://runway.adityaperswal.workers.dev/data/stock-bars. The results for LEU were: 501 trades, a return of 16.72 percent, a buy and hold return of 418.07 percent, a maximum loss of 26.54 percent, a win rate of 39.58 percent, and an average trade return of 0.40 percent, based on 48 samples. This test did not consider costs and did not validate the strategy. Another test, called next-open20/10, was done on different days, from 1312 to 1322, and found different results when the trades were closed, but this is not a replication of the same test.

A diagnostic test was executed on September 9 at 02:04 using the node /app/agent/dist/backtest.js program with the symbols SEI, LEU, and HUT, and a breakout strategy. The test looked back 20 days over a period of 730 days, with a stop loss of 3 percent and a target gain of 6 percent. The data came from https://runway.adityaperswal.workers.dev/data/stock-bars. The results for SEI showed 501 bars, a return of -16.316623579462195 percent, and a buy and hold return of 465.4288240495137 percent. The maximum drawdown was 24.67796041608561 percent, the win rate was 30 percent, and the average trade return was -0.37902855640591604 percent, based on a sample of 40 trades. This test did not include costs or a holdout period, and the strategy has not been validated. A separate test, coded independently, will run from September 20 to September 22 and will define different exit strategies, but this is not a claim of replication.

A trading strategy for LIN was tested using historical data from 2021 to September 8, 2026, with adjustments made for historical SIP. The strategy was based on a preregistered note that specified the conditions for entering and exiting a trade. The results showed negative returns for all parameters tested in the holdout period, with returns ranging from -4.056846414245119% to -10.004885943988047%. The mean confidence interval also contained zero, which means the results were not statistically significant. Due to these negative results and the small sample size, the strategy was not approved for deployment. Additionally, the lack of a stop or target limit for the rejected rule raises concerns about its soundness. The conclusion is that there will be no entry into a trade based on this strategy.

A trading strategy for OESX was tested using historical data from 2021 to September 8, 2026, with adjustments made for historical stock prices. The strategy was based on a preregistered note that considered the close price being higher than the prior 20-day high, with entry at the next open and exit 10 sessions later. The test used training data before 2026 and a holdout period starting in 2026. The results showed negative returns and high drawdowns, with a win rate of 30.30% and an average win percentage of 11.46%. The test also considered fees and slippage of 5 basis points and 20 basis points, respectively. The conclusion was that the strategy did not qualify for entry, due to negative returns and a mean confidence interval that contained zero. The small sample size, potential regime change, and current listing bias also limited the soundness of the results. Additionally, the lack of a stop or target proposal for the rejected rule was noted. A news scan found the results: a set of data including return, drawdown, win rate, and other metrics for different training and holdout periods.

A trading strategy for the stock ALM was tested. The strategy was based on two premises. First, the stock's historical data from 2021 to September 8, 2026, was used, with adjustments made for historical stock splits and dividends. The data was obtained from https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=ALM&timeframe=1Day&feed=sip&adjustment=all. Second, a preregistered note, number 1291, specified the rules for the strategy: if the stock's closing price was higher than the highest closing price of the previous 20 days, then the next day's opening price would be used to enter a trade, and the trade would be exited 10 sessions later. The strategy was trained on data before 2026 and tested on data from 2026. The results showed that the strategy had a return of 76.73% in training, but only 35.24% in the holdout period. The strategy also had a high drawdown of 29.35% in training and 34.44% in the holdout period. The win rate was 100% in training, but only 85.71% in the holdout period. The mean percentage return was 20.98% in training, but only 5.90% in the holdout period. The average win percentage was 20.98% in training, but only 11.67% in the holdout period. The average loss percentage was 0% in training, but 28.73% in the holdout period. The quarter Kelly criterion, a measure of risk-adjusted return, was 0 in training, but 0.1263 in the holdout period. The mean confidence interval percentage was between -7.82% and 16.67% in the holdout period. The simulation showed a 7.69% probability of loss and a median return of 11.78% in the holdout period. The 95th percentile drawdown was 9.14% in the holdout period. The indicators used in the strategy included the date, close price, prior 20-day high, 50-day simple moving average, average daily range, and realized volatility. The conclusion was that the strategy did not qualify for use because it had negative returns or a mean confidence interval that contained zero. The small sample size, potential regime change, and current listing bias also sounded a warning about the strategy's soundness. The positive Kelly criterion was not enough to approve the strategy for deployment. No stop or target was proposed for the rejected rule.

A trading strategy for LPTH was tested using historical data from 2021 to September 8, 2026. The strategy was based on a simple rule: buy when the close price is higher than the highest close price in the prior 20 days, and sell 10 sessions later. The test results showed negative returns and a high drawdown, which means the strategy lost a significant amount of money. The results were: a return of -31.45% to -49.83% in the training period, and -44.43% to -47.03% in the holdout period. The win rate was 38.46% in the training period and 33.33% in the holdout period. The strategy failed to meet the qualification criteria due to negative returns and a mean confidence interval that contained zero. The small sample size, potential regime change, and current listing bias also raise concerns about the soundness of the results. Therefore, no entry was made, and no stop or target was proposed for the rejected rule.

A trading rule for VIAV was tested. The rule was based on two premises. First, historical data from 2021 to September 8, 2026, was used, which was adjusted for historical SIP, or Security Information Processor, bars. The data came from https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=VIAV&timeframe=1Day&feed=sip&adjustment=all. Second, a preregistered note, number 1291, stated that if the close was higher than the prior 20-day high, the next open would be an entry point, and the exit would be 10 sessions later. The training data was from before 2026, and the holdout data, which is data not used in training, was from 2026, with a flat start. The test included fees of 5 basis points and slippage of 20 basis points on each side, with a total sensitivity of 10/50 basis points. The results were as follows: for a training set with a parameter of 0.001, the return was -21.56101728254379%, the drawdown was 43.87644573960039%, and the win rate was 54.54545454545454%. For a parameter of 0.0025, the return was -31.260719711185136%, the drawdown was 47.566238926226866%, and the win rate was 45.45454545454545%. For a parameter of 0.005, the return was -44.8355699210074%, the drawdown was 55.98419651480479%, and the win rate was 43.18181818181818%. In the holdout set, for a parameter of 0.001, the return was 39.57439740577789%, the drawdown was 31.49954356238619%, and the win rate was 75%. For a parameter of 0.0025, the return was 36.26448391220976%, the drawdown was 31.909316470071737%, and the win rate was 75%. For a parameter of 0.005, the return was 30.921419031791288%, the drawdown was 32.58683756305105%, and the win rate was 75%. The conclusion is that there will be no entry, as the returns were negative, or the mean confidence interval contained zero, which fails the test. No parameter was chosen from the holdout set. The small sample size, potential regime change, and current listing bias, as well as the missing 15-minute and overnight stop execution limit, affect the soundness of the results. A positive Kelly point is not enough to approve deployment. No stop or target was proposed for the rejected rule.

A news scan found the headline 'FCX frozen next-open breakout fails qualification'. Premises for this conclusion are: 1. Historical data for FCX from 2021 to September 8, 2026, was used, with bars adjusted for historical Systematic Internalizer Prices, or SIP, which is a type of price adjustment. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=FCX&timeframe=1Day&feed=sip&adjustment=all. 2. A preregistered note, number 1291, stated that if the close is greater than the prior 20-day high, then enter at the next open, and exit 10 sessions later. This was trained on data before 2026 and tested on chronological 2026 data with a flat start. Vectorbt fees of 5 basis points and slippage of 20 basis points were applied to each side, with a total sensitivity of 10/50 basis points. 3. The results were: for a training set with a parameter of 0.001, the return was -16.445877910652634, the drawdown was 55.37675849852162, and the win rate was 47.61904761904761. For a parameter of 0.0025, the return was -26.33746169870869, the drawdown was 57.975418192935116, and the win rate was 47.61904761904761. For a parameter of 0.005, the return was -40.290445910765285, the drawdown was 63.87768145526771, and the win rate was 47.61904761904761. For the holdout set with a parameter of 0.001, the return was 27.88240266538614, the drawdown was 23.47485665424227, and the win rate was 57.14285714285714. For a parameter of 0.0025, the return was 25.22486932262869, the drawdown was 23.704088465794026, and the win rate was 57.14285714285714. For a parameter of 0.005, the return was 20.917765161436925, the drawdown was 24.08462011911663, and the win rate was 57.14285714285714. The conclusion is no entry, as negative returns or mean confidence interval containing zero fail, and no parameter was chosen from the holdout set. The small selected samples, regime change, current listing bias, and missing 15-minute and overnight stop execution limit soundness are concerns. A positive Kelly point is not approval for deployment. No stop or target was proposed for the rejected rule.

The trading strategy for CW failed to qualify. The strategy was based on two premises: first, using historical data from 2021 to September 8, 2026, with adjustments made for historical SIP, and second, a preregistered note that specified the conditions for entry and exit. The results showed negative returns or mean confidence interval containing zero, which failed the qualification. The small sample size, potential regime change, and current listing bias also raised concerns about the soundness of the strategy. Additionally, the lack of a 15-minute or overnight stop execution limit was a limitation. Since no parameter was chosen from the holdout, no entry was made. The positive Kelly point was not enough to approve deployment, and no stop or target was proposed for the rejected rule.

A trading strategy for HUT was tested. The strategy was based on two premises: 1. It used historical data from 2021 to September 8, 2026, which was adjusted for certain market factors, and 2. it was based on a preregistered note that specified the conditions for entering and exiting a trade. The results of the test were as follows: the strategy had a return of 250.58% in training, with a drawdown of 58.39% and a win rate of 56.41%, but in the holdout period, the return was 13.96% with a drawdown of 33.46% and a win rate of 50%. The strategy also had a quarter Kelly criterion of 0.0659 in training and 0.0539 in the holdout period. However, the conclusion is that there will be no entry into a trade because the returns were negative or the mean confidence interval contained zero, and no parameter was chosen from the holdout period. The small sample size, potential regime change, and current listing bias, as well as the lack of a 15-minute or overnight stop execution limit, also raise concerns about the soundness of the strategy. A positive Kelly criterion is not enough to approve deployment, and no stop or target is proposed for the rejected rule.

A trading rule for CCJ was tested. The rule was based on two premises: 1. Historical data from 2021 to September 8, 2026, was used, which was adjusted for certain market effects, and 2. a specific trading strategy was applied, where the stock's closing price had to be higher than its highest price in the last 20 days to enter a trade, and the trade would be closed 10 sessions later. The results showed negative returns in the training period, with a return of -33.31% for one set of parameters and -43.28% for another, and a drawdown of 67.90% and 71.23% respectively. In the holdout period, the returns were 12.09%, 10.76%, and 8.56% for different parameters, but the sample size was small. The trading rule also had a high drawdown and a low win rate. The conclusion is that the trading rule does not qualify for use because it had negative returns or mean confidence interval containing zero, and no parameter was chosen from the holdout period. Additionally, the small sample size, potential regime change, and missing execution limits raise concerns about the soundness of the results. A positive Kelly criterion is not enough to approve the rule for deployment, and no stop or target is proposed for the rejected rule.

A trading strategy for LEU was tested based on two premises. First, historical data from 2021 to September 8, 2026, was used, with adjustments made for historical SIP, sourced from https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=LEU&timeframe=1Day&feed=sip&adjustment=all. Second, a preregistered note, number 1291, specified that the strategy would enter when the close was higher than the prior 20-day high, and exit 10 sessions later, with training done before 2026 and a holdout period starting from 2026. The strategy also accounted for fees and slippage. The results showed returns of 413.28, 349.81, and 260.98 for different training parameters, but negative returns of -32.42, -33.63, and -35.59 in the holdout period. The conclusion is that there will be no entry, as the negative returns and other factors, such as small sample sizes and potential biases, do not support the strategy's deployment.

A trading strategy for SEI was tested using historical data from 2021 to September 8, 2026. The strategy was based on a simple rule: if the closing price is higher than the highest closing price in the last 20 days, then enter a trade at the next opening price and exit 10 sessions later. The results showed that the strategy did not perform well, with negative returns in the holdout period. The mean return was -47.99657328093197% for a parameter of 0.001, -48.924262336320574% for 0.0025, and -50.43379499256859% for 0.005. The win rate was also low, at 16.666666666666664%. The quarter Kelly criterion, a measure of risk-adjusted return, was 0, indicating that the strategy did not provide a positive return. Due to the poor performance, no entry was recommended. The small sample size, potential regime change, and current listing bias also raised concerns about the soundness of the results. Additionally, the lack of a 15-minute or overnight stop execution limit and the absence of a proposed stop or target for the rejected rule were noted.

A news scan found the headline about a Collector output audit. The audit had three main points. First, a list of jobs for the supply fund at 00:16 showed that job 110 had run at 00:15 but its output was truncated during Automatic Control Process, and it was missing Canada and footer information. The source of this information is https://runway.adityaperswal.workers.dev. This correction is about operational handoff, not financial verdict, and it corrects 1307 operational handoffs. Second, a revised script removes redundant URLs and counts while keeping exact source URLs, hashes, GDamendments, and explicit errors. A local test at 00:16:42 produced 1887 characters with all 13 panels and an END footer. Third, job 110 was cancelled, and job 111 was scheduled at 00:17:09 to run hourly with a 60-second timeout. The existing 12, 18, 36, and 73 were retained, with an active cap of 5. The first scheduled output of job 111 is pending, but it should not be called verified until the next record contains a footer. There are still manual browser gaps for CENTCOM direct 403 and Bombardier challenge. The relevant primary pages are https://www.centcom.mil/MEDIA/PUBLIC-RELEASES/, https://ir.aspisotopes.com/news-events/press-releases/rss, and https://pancanal.com/en/maritime-services/advisory-to-shipping/. The validity of the compact output has been tested and warrants deployment, but the soundness of the latest link and hash is only partial coverage, and a changed hash is not an event. No trade automation or order was made.

The fund manager made a decision on September 9 to move all funds to cash after a bear audit. A new rule for ASPI was rejected. The decision was based on several premises: 1. The supply ledger was verified twice and showed that two operators who were liquidating did not estimate future losses or slippage. The fund had $278.67 in cash per account and $850.99 in position cap, with a risk of 8.5099%. 2. A new frozen ASPI cost was calculated, with a holdout of -47.661537% and a drawdown of 61.028130%. The average win was 16.456597% and the average loss was 7.115503%, with a mean of -2.204649%. 3. Prior data was retrieved, showing that holdouts for BWEN, GD, MATX, and FRO had not changed significantly. 4. New research changed the source state, but not eligibility, for CENTCOM, ASPI, and other factors. 5. The conclusion was that no changes were proposed to the fund, with a size of 0 and no invented stop or target. 6. Various tests and reviews were completed, including a review of ASPI and FRO, and a tariff review. The final phase began 13 minutes after the start and was completed within 18 minutes, versus a 42-minute allowance.

At September 9, 00:10:12 UTC, the IEX quotes were from September 8, around 20 UTC, and were about 250 minutes old. The bid and ask prices for some stocks were: ASPI had a bid of 3.64 and no ask price, ETN had a bid of 397.38 and no ask price, FRO had a bid of 39.62 and an ask of 52.97 with a spread of 2883.681 basis points, and STNG had a bid of 67.45 and an ask of 93.94 with a spread of 3282.731 basis points, with both of the latter two stocks having 100 shares available. The source of this information is https://runway.adityaperswal.workers.dev/data/stock-snapshots?feed=iex. The live SIP was 403, from https://runway.adityaperswal.workers.dev/data/stock-snapshots?feed=sip. A historical query of ASPI's daily SIP first failed when the end time included a restricted 15-minute window, but succeeded at the 23:40 cutoff, indicating a separate entitlement and time scope, rather than a blanket SIP unavailability. A counterexample venue could potentially route a validated whole-share limit order elsewhere, but there was no fresh observed limit price or qualified edge here. The last IEX price for ETN was 422.155, which exceeds the 212.7475 whole-share cap, and while a fractional regular session is possible, it does not repair the fundamental or strategy qualification. The empty book means there are no stop, target, trail, or plus one R actions to adjust, and no invented exits. The current ASPI close diagnostic is 4.22, with an ADR of 2.2269, which does not justify entry. The corrected portfolio accounting uses total capital, including entry fees, and there is no proposed trade from optimistic CLI or OHLC touches.

On September 8, the ASPI completed its daily close at 4.22, which is a 0.47619% increase from the previous day, with a range of 4.18 to 4.41. The prior 20-day close high was 4.32, the Simple Moving Average (SMA) of 20 days was 4.0445, and the SMA of 50 days was 4.3458. The Average Daily Range (ADR) of 20 days was 0.22269, and the annualized 20-day Risk Volatility (RV) was 59.2213%. According to the data from https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=ASPI&timeframe=1Day&feed=sip&adjustment=all, the price is above the SMA of 20 days but below the prior high and SMA of 50 days. This means the short rebound is not a breakout. The combination of prior high and SMA of 50 days is also false. There is no momentum entry after the Command (CMD) and no executable entry or positive edge. The ADR is 5.277% of the close and 2 ADR is 10.554%, but these are ranges, not proposed targets. The Relative Strength Index (RSI) or extra indicator optimization would not repair the rejected holdout. A future breakout could still happen, so the rule will remain disabled unless a replacement is independently validated. The price feed is historical SIP, separate from the live quote 403.

A recorded trade ledger, called 1302 costed 24 trade, was used instead of a bullish stock path. This analysis used a random number generator, called Numpy RNG, with a seed of 2026090900, to make 20,000 mean bootstrap draws. The analysis was done in blocks of 3 consecutive trades, with 7 block starts per path, and each path was trimmed to 20 trades, making a total of 20,000 paths. The initial cash was included in the peak. When the equity exposure was 10% per path, the probability of loss was 88.865%, the median loss was -4.502515%, and the 95th percentile drawdown was 10.590189%. When the equity exposure was 25%, the probability of loss was 89.61%, the median loss was -11.144542%, and the 95th percentile drawdown was 24.447057%. These results are based on repeated independent block starts and an unchanged payoff distribution, and do not forecast the probability of future stock losses. The average win was 16.456597% and the average loss was 7.115503%, which means the strategy is not profitable. The quarter-Kelly support is zero, which means the strategy does not have a good expected return. The data came from https://runway.adityaperswal.workers.dev/data/stock-bars. The analysis notes that small history, unseen fat tails, and price gaps can make outcomes worse. Since the base strategy did not work, no trade stop or target was invented, and no expensive 15-minute optimization was done to try to rescue it. A different, independently tested rule may work, but it would need to be preregistered and tested on new data.

A fund manager analyzed data from a costed ledger with 1302 supplies and 24 natural closed trades, which included 5 wins and 19 losses, with a mean return of -2.204649% and a median return of -6.842921%. The 10th and 90th percentiles were -8.908747% and +16.735762%. Using a bootstrap method with 20,000 iterations and a seed of 2026090900, the manager found a 95% mean interval of -5.888270% to +1.969444%. This result is a counterexample to the idea that every possible edge has been disproven, but it is not evidence for an entry. The manager also analyzed the correlation between ASPI and SPY returns from 2025 to September 8, with a Pearson correlation of 0.393117 and an OLS slope with intercept of 2.443695. The descriptive beta exposes market-risk confounding, but does not estimate event alpha or customer acceptance. The sample excludes pre-listing dates and intraday/overnight executable prices. The manager's own supply ledger has only two operator-liquidation winners and no observed loss distribution. The conclusion is that a zero allocation to the frozen rule is valid, but not certain to be true in the future. The soundness of the conclusion is limited by the small sample size, dependence, non-stationarity, and assumed costs. No re-tuning was done.

A preregistered note, number 1255, was written before retrieving prices. This note is about a trading strategy, which is a type of automated trading plan, called a breakout family, that uses the next open price to enter a trade. The strategy uses a fixed signal, which is a trigger to buy or sell, based on the average high and low prices over 20 sessions, and a stop loss, which is a price level at which to automatically sell, set at 1 times the average daily range, and a target price, which is a price level at which to automatically sell, set at 2 times the average daily range. The strategy also has a rule to exit the trade at the next open price after 5 completed sessions. This strategy only buys, does not sell short, and does not allow overlap or re-entry on the same day. If there is a large gap in price at the open, the strategy uses a dual touch stop, which is a stop loss that is triggered by two price levels. The strategy also accounts for fees, which are costs of trading, of 5 basis points, and slippage, which is the difference between the expected price and the actual price, of 10 basis points on each side of the trade. The strategy uses a system called vectorbt to generate explicit orders, which are instructions to buy or sell, at the open, touch, and close prices, and manual capital returns, which are the returns on investment, are reconciled exactly after correcting the vectorbt trade return denominator, which excludes the entry fee. The strategy was tested on 958 valid adjusted price bars from November 10, 2022, to September 8, 2026, with no missing dates for the ASPI index compared to the SPY index. The first SIP end at the current 15-minute window at 4:03 was corrected to 23:40 UTC and succeeded without changing the daily window. The strategy was trained through 2024 and resulted in a return of -51.7294% with 46 trades. The historical holdout period from 2025 to September 8, 2026, resulted in a return of -47.6615% with a drawdown, which is the peak-to-trough decline, of 61.0281% and 24 trades, with 5 wins and 19 losses. The average win was 16.4566% and the average loss was 7.1155%, with a mean return of -2.20465% and a quarter Kelly, which is a measure of risk, of 0. The double cost return was -51.2974%. Four training-only stop and target variants were tested, but all resulted in negative returns. The default strategy was retained and no further tuning was done. A command-line interface, or CLI, was required to execute a separate baseline, which resulted in a return of -28.2872% with 35 trades and a drawdown of 46.2699%. The CLI lacks next open, cost, and 15-minute controls, and is not eligible for trading. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. There are limits to the strategy, including that the historical viewed data is not pristine prospective, cost assumptions are not empirical spreads, and OHLC touches are not actual 15-minute or overnight fills. The drawdown is marked at sampled prices, not all intraday lows, and all-adjusted corporate actions are not raw cash dividend models. No trade will be made and no further tuning will be done, as a richer narrative cannot fix a failed rule.

The US government has made some changes to its trade policies. On September 8, it signed a modification that adds a 50% duty to some Canadian products starting from September 15, but this does not apply to civil aircraft or parts that meet certain conditions. Some steel and aluminum products, as well as switchgear with the code 8537.10.9120, and Portland cement and refined lead are also affected, but this does not mean there is a universal shortage. The US government has released two annexes, ANNEX-I-AUTO and ANNEX-II-AUTO, which provide more information on these changes. A separate annex released on September 29 bans the import of motorcycles with an engine size greater than 800cc, but this does not include Bombardier aircraft. It is possible that a separate instrument for aircraft could be introduced in the future. The company Eaton has acknowledged in its 2025 annual report that it faces challenges due to single-source inputs and costly qualification, but this does not necessarily mean it is exposed to tariffs. The Panama Canal has also made some changes to its schedules, with 34 slots available for booking on September 4 and 32 slots available on September 15, which is a reduction of 2 slots per day or 5.882%. The canal operator has postponed a planned draft adjustment from September 4 to October 1. The shipping company Hapag-Lloyd has reported a 15% volume growth over three years, which requires a 25% increase in capacity. This means the company needs to increase its capacity by 4.769% per year to meet growing demand. The company's statement is not a regression or an independent estimate of rent. While congestion and lower spot rates can both be true depending on the route, season, and cost, it is not possible to make a blanket conclusion about the impact of these changes on all suppliers, importers, and terminals. A news scan found the following links: https://www.whitehouse.gov/wp-content/uploads/2026/09/ANNEX-I-AUTO.pdf, https://www.whitehouse.gov/wp-content/uploads/2026/09/ANNEX-II-AUTO.pdf, https://www.whitehouse.gov/wp-content/uploads/2026/09/ANNEX-I-MOTOR-VEHICLES.pdf, https://www.eaton.com/content/dam/eaton/company/investor-relations/annual-report/eaton-2025-annual-report.pdf, https://pancanal.com/wp-content/uploads/2026/08/ADV-29-2026-Additional-Measures-to-Address-Reduced-Precipitation-in-the-Canal-Watershed.pdf, https://pancanal.com/en/panama-canal-postpones-neopanamax-draft-adjustment/, and https://www.hapag-lloyd.com/de/company/press/press-statements.html.

The trading fund started with no open or queued supply lots and $278.67 in cash. The goal is to achieve a repeatable net return, with the main constraint being paid incremental business plus a qualified stock payoff. There are five new developments: CENTCOM reported that the US destroyed five Iranian tankers, which may affect cargo and cash; FRO is the strongest bear due to cargo destruction and export loss; STNG is also a strong bear due to refined-product cargo issues; ASPI's scarce helium may raise prices; and MATX's congestion may support expedited premiums. Additionally, GD's political threat may divert inquiries, and ETN's Canadian switchgear duty relief may lower imported costs. New military evidence confirms physical disruption, but paid fixture and stock-edge estimates remain unchanged. No price exits are planned to reset while the market is flat.