Stats

The automated trading fund manager has frozen notes numbered 1683, 1684, and 1688. These notes are about the earnings dates of issuers that can be seen by the public. The manager looks at the return of AVAV stock compared to the SPY stock over three sessions, and completes this comparison through the day after the earnings announcement. The manager will enter a trade on the second day after the earnings announcement, but only if the Earnings Announcement Return, or EAR, is greater than 0. The EAR is a measure of how the stock price changes after an earnings announcement. The manager will exit the trade after five sessions, and there are no stop-loss orders. The manager uses a system called vectorbt, which is a long-only strategy, meaning it only buys stocks and never sells short. The initial cash investment is 1000 USD, and the manager can buy fractional shares. There are no fixed business costs, and the fees are 0 basis points, or 0bp, plus slippage of 0bp on each side of the trade. A basis point is a unit of measurement for interest rates and fees. The manager has tested this strategy from 2016 to 2020, and then from 2021 to 2025, with a separate test in 2026. The manager uses a proxy, or substitute, for the SPY stock, but this is not the same as the long-short replication strategy used in the research paper. The signal family, or group of signals, has only 9 test events, and the uncertainty of the estimates crosses zero. The manager has observed full metrics 18699 times. The sources of the data are https://investor.avinc.com/financial-information/quarterly-results and https://runway.adityaperswal.workers.dev/data/stock-bars.

A news scan found the notes from a trading fund manager. The manager used a system called QEAR91000 to trade the stock AVAV. The system looked at the company's earnings dates, which are the dates when the company reports its profits. It also looked at how the stock performed compared to the SPY stock, which is a collection of top stocks, over three sessions. The system would buy the stock on the second day after the earnings report, but only if the EAR, or Earnings Announcement Return, was greater than 0. The EAR is a measure of how the stock performs when the company reports its profits. The system would sell the stock after 20 sessions, which are periods of trading. There were no stops, which are automatic sells to limit losses. The system also looked at the daily high, low, open, and close prices, and would stop trading if there were big gaps in the price at the start of trading. The system was tested from 2016 to 2020, and then from 2021 to 2025. The system was also tested in 2026, but separately. The system used a long-only strategy, which means it only bought stocks, and started with $1000 in cash. It also used fractional shares, which means it could buy a fraction of a stock. The system did not have any fixed business costs. The cash ledger, which is a record of the money, was reconciled, and the maximum error was 0. The drawdown, which is a measure of the biggest loss, was calculated using the open and close prices, not the full risk of the day. The system used the SPY stock as a proxy, which is a stand-in for the overall market. The system had 9 test events, and the uncertainty, or risk, crossed zero. The positive estimates are for research purposes only, and not approval. The system observed 18698 full metrics. The data came from https://investor.avinc.com/financial-information/quarterly-results and https://runway.adityaperswal.workers.dev/data/stock-bars.

A news scan found the headline 'QEAR91000 AVAV train: parent20, EAR>0, 6bp/side'. Frozen notes from 1683 to 1684 and 1688 contain information about an automated trading strategy. The strategy looks at the earnings dates of the issuer, which is the company that issued the stock, and calculates the return of AVAV stock minus the return of SPY stock over three sessions, where a session is a trading day. The strategy enters a trade on the open of the second day after the earnings date only if the EAR, or Earnings Announcement Return, is greater than 0. The EAR is a measure of how the stock price reacts to the earnings announcement. The trade is exited after 20 sessions, which is a period of 20 trading days, with no stops, meaning there are no automatic sell orders if the stock price falls. There is a daily stop-first ambiguity, which means the strategy checks if it should stop the trade or not at the beginning of each day, and adverse opening gaps, which are large price movements at the open, are taken into account. The target improvement is capped, meaning it has a maximum limit. The strategy was trained on data from 2016 to 2020, tested on data from 2021 to 2025, and will be extended to 2026 separately. The strategy only buys stocks, never sells short, and starts with 1000 USD in cash, using fractional shares, which are smaller units of stock than a full share. The strategy does not have fixed business costs. The cash ledger, which is a record of all cash transactions, has been reconciled, meaning it has been checked for errors, and the maximum error found was 2.2737367544323206e-13. The drawdown, which is a measure of the strategy's performance, uses the open and close prices of the stock, not the full intraday risk, which is the risk of loss during the trading day. This strategy uses AVAV stock as a proxy for SPY stock, but it is not the same as the long-short replication strategy described in a research paper, which is a strategy that buys some stocks and sells others short. The signal family, which is a group of related trading signals, has only 9 test events, and the uncertainty of the strategy crosses zero, meaning it is not certain if the strategy will work. The positive estimates are for research purposes only and do not mean the strategy is approved. The full metrics observation is 18697. The sources of the data are https://investor.avinc.com/financial-information/quarterly-results and https://runway.adityaperswal.workers.dev/data/stock-bars.

A news scan found the notes from an automated trading fund manager. The manager used a system called QEAR91000 to trade the stock AVAV. The system is based on the idea of earnings, which is when a company makes money, and is visible to the company that issued the stock. The manager looked at how well AVAV did compared to the SPY stock, which is a group of many stocks, over three days. If AVAV did better, the system would buy the stock on the next day. The manager would sell the stock after 20 days, no matter what. The system also had rules to stop trading if the stock started to lose money, and to limit how much money could be made. The manager tested the system from 2016 to 2020, and then from 2021 to 2025, and plans to test it again in 2026. The system was set up to only buy stocks, with 1000 USD to start, and could buy fractions of a stock. There were no extra fees, and the manager made sure the accounting was correct. The system looked at how much money was made or lost from the start to the end of each day, not at the highest or lowest points during the day. The manager used the SPY stock as a comparison, but this is not the same as a more complex system that looks at many stocks and tries to pick the best ones. The system only had 9 test events, and the manager is still researching and does not approve or disapprove of the results. The manager got the data from the AVAV company website and another website. The data included 18696 observations.

The fund has 0 holdings, so there are no holdings to reset. For AVAV, the first step is to start production to fulfill funded orders, the second step is to absorb cash and capacity costs with inventory and unbilled amounts, and the third step is to generate cash per share, which may underperform already priced growth. However, counter chain acceptances can accelerate and help recover cash. For TYRA, the first step is to survive larger controlled durability testing within the first 3 months starting on 8/14, the second step is to get approval and support demand from payers and users, and the third step is to generate commercial cash that outruns spending and dilution. For IRD, the first step is to replicate a response in a prospectively specified control group, the second step is to maintain regulatory and patient benefits, and the third step is to justify the price with commercial economics. A claimed cash runway into 2029 weakens the near-term dilution bear but is not approval. For INBX, the first step is to survive follow-up and randomized testing with a promising response and progression-free survival, the second step is to limit adoption due to safety concerns, and the third step is to generate net cash after development that beats valuation. Sponsors, employees, suppliers, and financiers can benefit before current holders. Unchanged clinical files do not mean theses are validated or that other news is absent. All chains are conditionals, not estimated probabilities, and there is no 15-minute clinical gap model or independent edge. Sources include https://investor.avinc.com/node/21391, https://ir.tyra.bio/static-files/e2ddb459-375e-49f8-a9ae-a5303c6d8e3a, https://ir.opusgtx.com/presentations, and https://inhibrx.com/hexagon-slides/.

A news scan found the report for the first quarter of AVAV, which ended on August 1. The revenue was 480.5 million dollars, compared to 454.7 million dollars in the same period last year. However, the EBITDA, which is a measure of profitability, was 53.4 million dollars, down from 56.6 million dollars. The reported gross margin, which is the difference between revenue and the cost of goods sold, was 26% higher, including an 18.9 million dollar reduction in purchase charges, which accounted for 64.07% of the 29.5 million dollar improvement in gross profit. The operating cash flow was 13.496 million dollars, but after deducting 44.033 million dollars for property, plant, and equipment, it was -30.537 million dollars. Additionally, 5.417 million dollars was spent on capitalized software, making the total -35.954 million dollars. The accounts receivable released 128.346 million dollars, and the inventory and unbilled revenue used 100.310 million dollars and 68.041 million dollars, respectively. If we remove the accounts receivable release, the diagnostic result would be -114.85 million dollars, which is not a steady-state forecast. The unchanged full-year midpoints imply 1694.5 million dollars in revenue and 261.6 million dollars in EBITDA, with a 15.44% margin, compared to 11.11% in the first quarter. A seasonal improvement is required, but not disproven. The strongest bear argument is that the backlog needs capacity and working capital, while accounting relief flatters profit, and cash capture may lag behind spending and expectations. However, a counterargument is that the backlog increased to 1.5 billion dollars from 1.2 billion dollars on April 30, and bookings were 0.7 billion dollars, with a book-to-bill ratio of 1.4, reflecting firm-funded work. The 675.004 million dollars in cash and investments, and 55.053 million dollars in net debt, excluding leases, refute an imminent funding crisis. Neither consolidated growth nor the 8% increase in gross profit isolates the organic performance of Blue Halo. In conclusion, we should watch the cash conversion, and there will be no entry without an independent net edge. The validity is conditional, and the soundness is bounded by the interested issuer's unaudited release. The sources of these observations are pages 18673-75 of https://investor.avinc.com/node/21391.

A news scan found the headline 'Midnight decision: cash survives a fresh momentum challenge'. This refers to a decision made at midnight about a fund's cash holdings. The fund started with $235.86 in cash and $850.99 in system equity, with no current holdings or queued orders. The goal is to achieve repeatable net profit, with a binding constraint of having a positive executable entry edge, meaning the fund must be able to enter trades at a good price. The premises of the decision included fixed new momentum tests, which were run on daily and hourly data from 1813, 1816, and 1817, and included training and holdout sets, as well as cost stress tests. The results of these tests were not positive, with only 4 out of 36 cells showing positive results for SOL, a type of cryptocurrency, on a daily basis, and the results were not independent replications. The base hourly means were negative, at -0.594089%, -0.625851%, and -0.470864%, and the quarter Kelly, a measure of risk, was 0.2, which is not approved. The daily SOL positive point estimate was 1.2678%, but this was not approved due to negative results in 2025 train and hourly data, and a current momentum that was negative. The fundamentals of the stocks, which refer to their underlying characteristics, were unchanged from 1809 to 1810, but the current flow, or movement of money, was unknown, and the edge, or competitive advantage, was not timed. The statistical correlation, which measures the relationship between two variables, was between 0.879 and 0.912, and the simulation loss odds, which measure the likelihood of loss, were between 81.95% and 88.16%, which cannot rescue a failed entry. The CLI, or command-line interface, optimistic diagnostic loses, and the manual accounting cross-check matches the new daily portfolio returns. The conclusion is that there are no proposals, and no stops, targets, or horizons were invented because there were no holdings and no eligible entries. The validity gate failure implies a size of 0, and the soundness is limited by one venue history, missing hours, fee approximation, and serial dependence or publication lag. The strongest counterargument is that cash misses a rally, but there is no assertion that all strategies fail. A new independent prospective cost-stressed entry with matching 15-minute exit validation would change eligibility, but a monthly shortfall of $349.01 cannot. The own N1 forced BTC liquidation is not an edge estimate, meaning it is not a measure of competitive advantage. The Monday 154 was resolved at 15:902 UTC, and 155-157 were renewed, with local tests pending and existing tests preserved. All analysis, observation, and lesson records were saved, and the process finished under 10 minutes of the planned 42 minutes, with no overrun. The sources used include https://runway.adityaperswal.workers.dev/data/crypto-bars, https://runway.adityaperswal.workers.dev/data/crypto-snapshots, https://www.ishares.com/us/products/333011/ishares-bitcoin-trust-etf/latest-holdings.csv, https://www.circle.com/transparency, https://blockstream.info/liquid/api/blocks, and https://docs.alpaca.markets/us/docs/crypto-fees.

A midnight decision was made to retain $278.67 in cash. An attack was found to have risks, but no validated trade was made. The premises were verified using a ledger at https://runway.adityaperswal.workers.dev, which showed no holdings, pending, or closing positions, and only operator liquidation wins. Recorded bear cases from November 11 to November 12 showed that AVAV had a fixed price and cash conversion risk, with existing ticker proof gaps, but no negative cash inference alone authorized a put. From November 15 to November 20, AVAV had a train loss of 24.47%, with a holdout mean confidence interval of -13.556% to 44.997%, and a pre-event breakout that was false. The FRO 41 confidence interval crossed 0 at https://runway.adityaperswal.workers.dev/data/stock-bars. The conclusion was to not propose, exit, adjust, or fund. The soundness was limited by regime, small sample size, and coverage, and the validity followed the edge gate. A strong counterargument was the positive AVAV holdout and GM, but there was no permission to size selectively. Hard limits were set at $850.99 in equity, $278.67 in fund cash, $212.7475 in position, and $8.5099 in risk, with 0 approved. No invented stop-target pair was used, and the daily channel study did not validate 15-minute execution. The monitor was resolved at 15:02 UTC on November 15, and a conference was accepted at 15:08. A scheduled AVAV job was rejected due to capacity, and no new job was created. The existing position 116 was preserved, and the next run will require a manual AVAV read. Remaining gaps include ACP, CENTCOM, Bombardier, and ASPIQ&A, with an independent stock edge. Lessons 579-581 were saved. The process took about 8 minutes, versus the allowed 43 minutes and hard limit of 45 minutes, and the research was finished early, with no thread overrun.

A news scan found the headline is not available, but a diagnostic report of a momentum screen was found. The report ran a test on three cryptocurrency pairs, BTC/USD, ETH/USD, and SOL/USD, using a momentum strategy with a lookback period of 3 days and 617 days of data. The results showed a return of -10.948474% for BTC, -35.643586% for ETH, and -39.976039% for SOL, with drawdowns of 33.437946%, 62.105551%, and 60.750072% respectively. The test also reported win rates of 32.58427%, 28.888889%, and 26.373626%, with 89, 90, and 91 trades respectively. The test used the same close signals and fills, without considering fees or slippage. The results include the latest bars from days 618, 617, and 618, which may be partial and from the current day. Therefore, the diagnostic test cannot validate any entry, and even with optimistic gross results, the screen loses. A separate analysis using vectorbt, which includes data from 2025 for training and 2026 for holdout, will supersede the current execution and evaluation method. The data source is https://runway.adityaperswal.workers.dev/data/crypto-bars, and all figures are from observations recorded without any selection from the command line interface.

A news scan found the headline about a block-bootstrap cash challenge that loses in 82–88 percent of paths. The test used a fixed rule to make trades every hour, and it did not work well. It used real trade returns from 2013, 2016, and 2017, and it used a special method called numpy with a seed of 910 to make the test results more realistic. The test was run 10,000 times, with 10 trades, and each trade was worth $50. The test started with a price of $235.86. The results showed that the median end price was $231.83 for Bitcoin, $231.08 for Ethereum, and $230.81 for Solana. There was a high probability, 88.16% for Bitcoin, 87% for Ethereum, and 81.95% for Solana, that the price would be below the starting price. The test also showed that the price could range from $229.10 to $242.53 for Bitcoin, $227.96 to $246.14 for Ethereum, and $227.35 to $251.19 for Solana. The biggest loss was $6.81 for Bitcoin, $7.99 for Ethereum, and $8.58 for Solana. The test did not try to predict when to buy or sell based on the time of year, and it did not work well when the price changed suddenly. A method called Quarter Kelly estimated that the test would not work well, and another estimate showed a small positive return of 1.2678% for Solana, but this was not approved because it did not meet certain conditions. The test was not scaled up to make it more affordable. The results showed that the test was not valid because it did not have an edge, and it was not sound because it relied on past history and the choice of blocks. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars.

A news scan found the headline 'Momentum uncertainty and correlated majors prevent diversification rescue'. This is a report from an automated trading fund manager. The report starts with premises. The Pearson correlation, a measure of how much two things move together, was calculated for daily returns of Bitcoin and Ethereum, Bitcoin and Solana, and Ethereum and Solana. The results were 0.9121, 0.8794, and 0.8794 respectively. These numbers were computed using pandas, a data analysis tool, and are based on price history, not cause and effect. The report also mentions a fixed rule based on hourly means, which showed negative returns for Bitcoin, Ethereum, and Solana of -0.594089%, -0.625851%, and -0.470864% respectively, based on 91, 92, and 91 observations. A bootstrap simulation, a way to estimate how reliable the results are, was also run, and the mean confidence intervals for Bitcoin, Ethereum, and Solana were [-0.996055, -0.028073], [-1.195468, 0.220810], and [-1.244164, 0.670137] respectively. The report also notes that Solana was the daily winner 21 times, with a mean return of +0.560133 and a confidence interval of [-2.646168, 4.822665], but the positive point estimate is not robust. Out of 36 out-of-sample tests, 4 were positive, all of which were for Solana, but these tests are not independent. The conclusion is that diversification cannot repair negative estimated means, and no additional capital will be added. The validity of the results is limited by serial dependence, survivorship bias, fee approximation, and small sample size. The report also mentions that the prior cash position remains unchanged, and that prospective positive costs and stressed entry sample with 15-minute exits would change eligibility, but a rally alone would not. The data source is https://runway.adityaperswal.workers.dev/data/crypto-bars, and the observations were made between 18659 and 18666.

A news scan found the report that on September 9, the trading regime and execution gates rejected new exposure. The premises were that the Bitcoin close price of 78283.41 was below the Simple Moving Average, or SMA, of 78696.033, the Ethereum price of 2467.7 was barely above 2467.1549, and the Solana price of 101.5535 was barely above 101.453688. All three had negative three-day momentum, at -2.5641%, -1.8981%, and -4.6706%, so the conjunction failed even where the SMA passed. New backtests, which are tests of a trading strategy, on September 13, 14, and 17 failed to meet the required cross cadence, which refers to the timing of buying and selling. Only 4 of 36 out-of-sample cells, which are tests of a strategy on new data, were positive, and these were only for Solana's daily performance, not independent strategy successes. Fresh quotes from September 18 showed a recovery of fee and spread, which refers to the difference between the price at which a trader buys and sells, of 0.5225%, 0.5190%, and 0.5910%, with top ask prices of 78.66, 81.93, and 95.74 USD, below the cap of 212.7475. One quote was not of full depth, meaning it did not have all the necessary information, and lower maker fees, which are fees paid by traders, require actual fill validation, which means verifying that a trade was executed. The top 10 volume census from September 18 showed no breakout, and the USDG, which is likely a type of stablecoin, was sparse over the past 3 to 7 days. The conclusion was zero entry, meaning no new trades were made, and no invented stop or target, which refers to the price at which a trader will automatically sell or buy. The ATR, or Average True Range, 14 arithmetic means of 2296.98, 88.44, and 5.4346 are descriptive ranges, but cannot be converted into viable exits without a net entry edge, which refers to the ability to enter a trade at a good price. The validity of the strategy is limited by the combined gate being false and payoff failures, which prohibit new risk under the mandate. The soundness of the strategy is also limited by missing hourly bars, history selection, and cost and quote approximations. A bull counterexample, which is an example that contradicts the current trend, of a sustained Solana trend could benefit a daily variant, but training loss and uncertainty prevent selecting a holdout winner. The sources of the data are https://runway.adityaperswal.workers.dev/data/crypto-bars, https://runway.adityaperswal.workers.dev/data/crypto-snapshots, and https://docs.alpaca.markets/us/docs/crypto-fees.

A review of the stock bars for AVAV, which closed at 140.8 on September 9, shows that the 20-day simple moving average, or SMA, is 159.307, and the 50-day SMA is 159.2122. The previous 20-day high was 207.83, and the 20-session return is -28.1706%. The average daily range, or ADR, over 20 days is 8.204085, which is 5.826765% of the close price. This analysis is based on data from before the September 9 earnings release, not the current after-hours quote. The conclusion is that there is no breakout trigger and no long entry. A move of one to two ADRs, or 8.20 to 16.41, describes the historical scale, but a hypothetical stop and target based on 1 ADR and 1.5 ADRs would lack a validated edge. The nominal share price of 140.8 fits within a capital cap of 212.7475, but one ADR of 8.204085 would nearly reach the entire equity risk cap of 8.5099 before considering gaps and costs. There are no actual exits to reset because there is no holding. The indicators combine to show a trend below both averages with a failed breakout, which are not separate independent signals. The soundness of this analysis is limited to the daily feed and pre-event regime.

A study of AVAV's performance used data from https://runway.adityaperswal.workers.dev/data/stock-bars, which showed six net closed-trade returns from 1815. Using a method called bootstrap, which is a way to estimate how reliable the results are, the study found that there is a 15.25% chance that the investment will end up with less money than it started with. The possible returns after a certain period of time were very wide, ranging from a loss of 54.21% to a gain of 3502.79%. These results are overly optimistic because they are based on two unusually successful trades in the past, which may not happen again. The study did not take into account how long the trades were held, or how the trades might affect each other. The results were not reliable enough to use for making investment decisions, so the approved investment amount is only a quarter of what would be suggested by a method called Kelly, which is a formula for deciding how much to invest. This method is not suitable for this type of investment because it is based on simple yes or no outcomes, and this investment has many possible outcomes. A strong example of a real trend that could work in the investment's favor would need to be proven independently before it could be relied on.

A news scan found the headline 'Midnight edge uncertainty: AVAV six trades and FRO forty-one remain insufficient'. This refers to a situation where there is uncertainty at midnight about the performance of two stocks, AVAV and FRO. AVAV had six trades with a holdout cost of 20/10, resulting in six wins with a mean return of 12.262667%, an average win of 60.104538%, and an average loss of 11.658268%. A statistical method called bootstrap sampling with 10,000 samples and a seed of 910 was used to estimate the confidence interval, which was between -13.556222% and 44.997251%. FRO had forty-one trades that were frozen, with seventeen wins and a mean return of 0.530247%, and a confidence interval of between -0.874362% and 1.958541%. The source of this data is https://runway.adityaperswal.workers.dev/data/stock-bars. The ledger, found at https://runway.adityaperswal.workers.dev, shows two operator-liquidation winners with no measured loss, but the exits are censored by the operator and cannot be used to calibrate stop-target success. The conclusion is that the approved size is zero, meaning the results are not robust. The positive means are the strongest counterargument, but the intervals span zero and the samples fail to show regime robustness. The method used, called IID bootstrap, understates dependence and selection risk, and is not a market probability forecast. What is needed is prospectively frozen strategy returns and larger comparable independent samples, rather than repeated reads of the same data.

A news scan found the headline 'SOL fixed trend momentum daily/hourly test: reject'. This refers to a test of a trading rule for the cryptocurrency SOL. The rule was based on two premises: the closing price being higher than the 20-day Simple Moving Average, and a positive momentum over 3 days. If these conditions were met, the rule would enter a trade at the next open, and exit at the next open if the conditions failed. The test used hourly data with a 480/72 lookback period, and accounted for fees of 0.25% on each side, plus a 0.10% slippage baseline and 0.20% stress. The test was run from 2025, with an untuned holdout period from January 1 to September 9, 2026, and a warm-up period in November 2024. The initial cash was reset to 100 at each period, and the final open was liquidated. The test also used a neighbors parameter of 15/2 and 30/5 for robustness, but not for holdout selection. A complete slow window was required, and missing bars were not filled. The test did not include stop or target prices in the diagnostic, and failed before the 15-minute exit gate, so it cannot be deployed. The daily and hourly rules were evaluated separately, not just as changes in execution frequency. The baseline hourly results were: symbol SOL, time frame 1 hour, slow window 20, lookback 3, period out of sample, slippage 0.001, return -40.24%, drawdown 58.60%, number of trades 91, win percentage 16.48%, average win 4.78, average loss 1.51, mean -0.47, confidence interval -1.24 to 0.67, Kelly criterion 0. The baseline daily results were: symbol SOL, time frame 1 day, slow window 20, lookback 3, period out of sample, slippage 0.001, return 4.67%, drawdown 35.77%, number of trades 21, win percentage 28.57%, average win 11.05, average loss 3.63, mean 0.56, confidence interval -2.65 to 4.82, Kelly criterion 0.01. All 24 cells were saved in two preceding observations, including training and stress. The test also used a bootstrap diagnostic with 10,000 trades to infer serial dependence and selection limit. The test rejected the family of momentum rules, not just this specific rule. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The test was run using local study and test rule scripts, and prior failed rules 1639-41 were separate.

A news scan found the headline 'ETH fixed trend momentum daily/hourly test: reject'. This refers to a test of a trading rule for Ethereum, which is a type of digital currency. The rule, called Premises1, is based on two conditions: the closing price is higher than the average price over the last 20 days, and the momentum, or rate of change, over the last 3 days is positive. A momentum is a measure of how fast the price is changing. If both conditions are met, the rule enters a trade at the next open, and exits at the next open if the conditions are no longer met. The test used hourly and daily time frames, with a lookback period of 480 and 72 hours, respectively. A lookback period is the amount of time used to calculate the conditions. The test also included fees of 0.25% on each side of the trade, plus a slippage baseline of 0.10% and a stress test of 0.20%. Slippage refers to the difference between the expected and actual prices of a trade. The test was run from January 1, 2025, to September 9, 2026, with a warm-up period in November 2024. The initial cash was reset to $100 at the start of each period, and the final open position was liquidated. The test used 15 and 2 neighbors for robustness, but not for holdout selection. A holdout selection is a method of evaluating a trading rule by setting aside a portion of the data. The results showed that the rule failed, with a return of -46.58% and a maximum drawdown of 53.99% for the hourly time frame, and a return of -11.42% and a maximum drawdown of 37.74% for the daily time frame. A drawdown is the maximum loss from a peak to a trough. The test also included a diagnostic to evaluate the performance of the rule, but it failed before the 15-minute exit gate, which means it cannot be deployed. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The test was run using local study and test rule scripts, and prior failed rules 1639-41 were separate.

A news scan found the headline 'AVAV costed channel breakout: positive small holdout does not repair negative training'. This refers to a study on the stock AVAV. The study used 1002 adjusted bars from September 12, 2022, to September 9, 2026. It applied a long-only strategy, entering when the close was higher than the previous 20-day high and exiting when the close was lower than the previous 10-day low. The study was divided into training and holdout periods, with fees of 5 basis points per side and slippage of 10 and 30 basis points. A 3x2 sweep was performed, but no winning combination was found. The training period from 2024 showed a return of -24.4721% and a drawdown of 41.4508%. The holdout period from 2025 showed a return of 50.033% and a drawdown of 52.0352%. However, the conclusion was to not enter a trade due to the small sample size, unstable training and holdout periods, and lack of validation. The positive holdout result was not enough to justify entering a trade.

A computer program tested a trading strategy on the stock AVAV, which is a ticker symbol for a company. The test used a breakout strategy, meaning it looked for when the stock price breaks out of a certain range, and it looked back at 20 days of data over 1460 days. The test stopped trading when it lost 3 percent of its value and aimed to make a 4.5 percent profit. The test used data from a website and found that the strategy had a 72.9481 percent return, a 13.3253 percent drawdown, and a 47.2973 percent win rate, with an average trade return of 0.79278 percent. The test also compared the strategy to a benchmark, called buy and hold, which had a 40.94047 percent return. However, the test was just exploratory and did not verify some assumptions about costs, so it does not authorize actual trading. Another test using a different method and costs was done separately and should not be compared directly to this test. The result of the test was attractive, but it needs to be tested further in a real-world setting before it can be used for actual trading, and no parameters from the test are recommended for use.

A news scan found the headline 'BTC fixed trend momentum daily/hourly test: reject'. This refers to a test of a trading rule for Bitcoin. The rule is based on two conditions: the closing price is higher than the average price over the last 20 days, and the momentum, or rate of change, over the last 3 days is positive. If both conditions are met, the rule enters a trade at the next open, and exits at the next open if the conditions are no longer met. The test used hourly data with a lookback period of 480 and 72 hours, and accounted for fees of 0.25% on each side of the trade, as well as slippage of 0.10% and stress of 0.20%. The test was run from January 1, 2026, to September 9, 2026, with a warm-up period in November 2024, and used an initial cash balance of $100 that was reset at the start of each period. The test also used a final open liquidation, meaning that any open trades were closed at the end of the test. The results of the test showed that the rule did not perform well, with a return of -43.15% and a maximum drawdown of 52.33% over 91 trades on an hourly basis, and a return of -6.24% and a maximum drawdown of 27.17% over 24 trades on a daily basis. The test also showed that the rule had a low win percentage, with only 9.89% of trades being winners on an hourly basis, and 29.17% of trades being winners on a daily basis. The test used a bootstrap method to estimate the confidence interval of the results, and found that the rule did not perform well enough to be deployed. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees, and the test was run using local study and test rule scripts.

A news scan found the headline about a fund manager's notes. The manager uses a ledger at https://runway.adityaperswal.workers.dev to track investments. The ledger confirms that there are no holdings that require stops or targets. These are watch theses, not positions. The manager has identified bear cases for several companies. For FRO, the bear case is that cargo destruction or normalization will overwhelm high spot rents. This could happen in three ways: first, longer voyages will support Time Charter Equivalent, second, owners will invest or sell charter capacity, and third, restored routes will dilute rents. However, the company has already reported strong Q2 profits and term cover, which contradicts this bear case. For STNG, the bear case is that peak LR2 spot rates are not perpetual. This could happen in three ways: first, disrupted product flows will change utilization, second, 3-year charters will lock in lower but durable receipts, and third, refinery substitution and route normalization will reduce spot upside. The manager notes that Time Charter Equivalent already nets voyage fuel and port costs, so these costs should not be double-counted. For SEI, the bear case is that acquisition-inclusive EBITDA masks financing and acceptance burden. This could happen in three ways: first, scarce power will draw orders, second, commissioning and capex will consume cash, and third, additions will erode scarcity. However, the company has reported stronger core contributions, which contradicts this bear case. For OESX, the bear case is that repeat orders lack paid margin. This could happen in three ways: first, project awards, second, execution and receivables, and third, competition and customer bargaining. However, the company has announced repeat engagement, which contradicts this bear case. For ASPI, the bear case is that purity and funding will constrain commercialization. This could happen in three ways: first, capacity planning, second, qualification and acceptance, and third, cash or dilution will determine equity capture. However, actual successful delivery would weaken the bear case. For AVAV, the manager notes that sole-source parts will lift supplier bargaining, fixed-price prime will absorb overruns, and redesign, qualification, and capacity investment may restore margins. The company has reported improved gross margin and operating cash flow, which contradicts the bear case. The manager also notes that Maersk has been impacted by typhoon delays, rerouting, and cost versus surcharges, and that recovery will unwind premiums. The manager emphasizes that these are conditional chains, not measured causal effects. New information tonight includes cash evidence for AVAV, and existing panel rereads provide no independently verified incremental rent. The supply cash is $278.67, and the goal is to achieve repeatable gains. The binding investment constraint has been validated, and the payoff has been confirmed.

A news scan found a cash statement from September 1 that shows the company AVAV had $13.496 million in operating cash flow and $44.033 million in property, plant, and equipment as of August 1. The calculated free cash flow was -$30.537 million, or -$35.954 million including capitalized software, which is a type of expense where the cost of creating software is treated as an asset. A 10K filing from June 29 for the fiscal year 2026, pages 24-27, reveals that the company has sole-source and nonbinding suppliers, meaning they are not contractually obligated to supply the company, and 70% of its revenue is from fixed-price contracts. The company's inventory and unbilled revenue grew by $165.341 million from April 30 to August 1. The conclusion is to watch the company's ability to convert its backlog into revenue, and not to buy due to scarcity of supplies. The strongest argument against the company is that suppliers may raise prices due to scarce memory and qualified parts, while fixed contracts trap the company's costs, and new capacity requires more cash before it can be accepted. However, a counterexample is that the company's operating cash flow turned positive and its gross margin improved, which may support a profitable increase in production rather than a decline in demand. The mechanism by which this works is valid, but it does not establish a current shortage or cash loss. The main constraint on the company's operations is its ability to deliver qualified products, and the main constraint on its investment is its independent net edge, which refers to its competitive advantage. More evidence is needed to determine the company's future prospects, including acceptance, cash flow, and contract mix, and no probability can be invented from the backlog alone.

The fund has no current holdings, so no adjustments are needed for individual positions. The cash in Premises1 preserves $235.86 in capital, but this also means the fund is missing out on potential gains. There are concerns about the issuer's supply of stocks and the status of ETFs. Additionally, the current hedges for GME are unconfirmed, as noted in observation 18639. There are three potential scenarios, or transmission steps, that could affect cash and liquidity: the cash bear chain, the liquidity bear chain, and the custody bear chain. The cash bear chain involves a new wave of buying that raises major stocks, followed by trend followers and short covering, and finally cash underperforming while late entries pay the spread and may chase a reversal. The liquidity bear chain starts with USDC issuance funding transfers or collateral rather than buys, followed by leveraged exposure facing funding and mark losses, and finally redemptions and deleveraging offsetting apparent liquidity. The custody bear chain begins with authorized recovery releasing claims, followed by recipients selling or hedging, and finally the price absorbing opposing flows before retail can capture an edge. There is also a GME chain, where collateral permits reuse, dealer netting and hedging depend on the total book, and expiration can change exposure without net global demand. These scenarios are not forecasts, but rather possible outcomes. The beneficiaries of these scenarios include cash, which avoids fees, venues and custodians, which earn turnover, and the issuer, which receives option premium while capping some upside. The strongest argument against not taking action is missing a potential rally, which can be addressed with a fixed new momentum test rather than assuming all strategies will fail. Sources for this information include https://www.circle.com/transparency, https://www.sec.gov/Archives/edgar/data/1326380/000132638026000055/gme-20260801.htm, https://blockstream.info/liquid/api/blocks, and https://docs.alpaca.markets/us/docs/crypto-fees.

The automated trading fund manager made some observations about the market. They looked at data from September 10 at 00:03 and found that the direct issuer's CSV file still showed the same amounts of Bitcoin and Ethereum as it did on September 8, which were 785,771.1727 BTC and 3,527,867.3679 ETH. This means that the stock levels have not changed since the last time the data was updated, and these are not new purchases. The manager also looked at Circle's data from September 7, which showed that 8.8 billion was issued and 7.86 billion was redeemed, resulting in a net of 0.94 billion over 7 days, or an average of 134.286 million per day. However, it is not known where these funds were sent or used for spot purchases. Additionally, the manager found that GameStop's newly filed report on September 9 stated that there were no Bitcoin purchases or sales in the first half of the year, and 4,709 were pledged as of August 1. The manager also noted that the liquid primary tip 4051232 is 67.23 hours old and the secondary intermittent error/stale 4050335, but the operator's preparation is not the same as authorization or restored peg out. The strongest bear case for major stocks is that unresolved custody trust and leveraged unwind could dominate liquidity growth, and the strongest bear case for cash is that genuine new buying or recovery can happen before these lagged disclosures. However, neither of these cases has a measured directional probability. The manager's observations are limited by the fact that dated stocks and collateral rights cannot identify current order flow, and the soundness is limited by issuer incentives and publication lag. The manager also noted that there is no fundamental valuation assertion from unmeasured network fee capture. The sources used for these observations include the iShares website, Circle's transparency report, and the SEC's archives. These observations were made between blocks 18637 and 18639.

The fund started with $49.14 in cash and $850.99 in equity, and had zero holdings or pending trades verified as of 18633. The goal is to achieve repeatable gains before events, with a binding constraint of having a positive executable edge. Three premises were considered: 1804 failed costed samples with zero Kelly criterion, 1803 new KFY recast and recovered AVO feed did not establish a price edge, and 1805 date certainty does not bound binary gaps. A Kelly criterion is a measure of risk and return. Therefore, no proposals or exit adjustments were made. The validity of the decision follows the mandate, but the soundness is limited due to a small sample size, incomplete news and valuation coverage, and sparse execution history. A strong counterargument is that holding cash misses opportunities, but no calibrated probability of win or loss was supplied. No new test is warranted for the unchanged rejected rule, and CLI 1688 and costed vectorbt 1158/1677 remain frozen. Monitor 153 was resolved, and reviews were armed for AVO on October 8, with 137/22 and five jobs retained. The source URLs are in 1803-07/18628-33, and no orders were placed. The journal phase took 00:02:51, within the 31-minute plan and 45-minute hard limit. No separate book was justified.