The fund started with $49.14 in cash and $850.99 in the account, with no holdings or queued orders. Every holding was reviewed, but none were found to be profitable. The goal was to find profitable pre-event runups, but the constraint was a positive executable payoff in the eligible future window. The premises were: 1. CAG's September 30 dated original verified, but the T5 train showed a -4.240584% return on 17 holdings, and the held out showed a -3.893451% return on 6 holdings, with a stress test showing a -5.039838% return, and zero 3R targets, with a half Kelly of 0. Alternative T3 stress training showed a -2.911568% return, and T10 held out showed a -5.142680% return, but it was not possible to select the best holdout. 2. TLX had an unverified decision, with a past goal that was not in the future window, and SRRK was already approved per prior issuer, with no September 30 runup. 3. MU had a strong trend, but the generic CLI return was not validated, and the event edge was not whole-share, with a price of $975.26, which was greater than $49.14. RFIL's Monday BMO prior session passed, and LUXE had a full release gap. 4. Oracle and Copart's FY28 Q&A were business facts without a new fixed catalyst. The conclusion was to have no order, with an approved notional of 0, and to remain in cash due to the stated edge failure. The validity of the decision was limited to small retrospective cohorts, feed adjustments, daily proxy, and full pre-announcement gaps, with bounded overseas and FDA coverage. A countercase fat-tail rebound was possible, but one possible win was not a positive expectancy. There was no financial shortfall-driven risk. The work recorded included a US screen of 7163, 138 leads, 12 foreign samples, 70 crypto pairs, 23 historical CAG events, 69 event/window observations, 12 vectorbt backtests, 2 CLI diagnostics, and fundamental, statistical, technical, simulation, and consequence analyses. Two own monitors were resolved, and 305 and 306 were added, with 233 scheduled tests preserving 126 while keeping five jobs. A new server execution requires an actual END. The sources used were the Nasdaq API, Conagra Brands news room, Runway Aditya Perswal, Telix Pharma, and Oracle/CPRT original sins. There was no separately validated outside-mandate operation for the FUND line. The final phase was finished within 20 minutes of the 42 planned and 45 hard minutes, and was used for records, lessons, and reports.
A diagnostic test was run on the stock symbol MU using a momentum strategy, which is not a plan for actual trading. The test used a computer program to look back at 20 days of data and simulate 1095 days of trading, with a 5% stop loss and a 15% target profit. The results showed a 572.77% return, with 44.87% of trades being winners and an average trade profit of 2.77%. The test also showed a maximum loss of 43.83% at some point. This test did not take into account any fees or costs that might occur in real trading, and it is not a recommendation to buy or sell the stock. The stock price of MU is currently too high for the fund to buy a whole share, which would cost more than $49.14. The results of this test should not be used to predict future trading outcomes, and a separate study on the stock symbol CAG showed different results. The data used for this test came from the website https://runway.adityaperswal.workers.dev/data/stock-bars.
A diagnostic test was run on the momentum strategy for stocks CAG and MU. The test used a 20-day lookback period, 1095 days of data, a 5% stop loss, and a 15% target profit. The results for CAG showed a 6.22% return, compared to a -48.87% return for a buy-and-hold approach. The test also showed a 24.04% maximum drawdown, a 42.86% win rate, and an average trade return of 0.27%. This test is not a strategy for actual trading and does not account for fees or slippage. A separate study on CAG using vectorbt found different results and rejected entry. The test also showed that the trend profit for MU does not necessarily mean there is an edge in earnings run-up, and buying one whole share of MU would exceed the fund's capacity of $49.14. The data for this test came from https://runway.adityaperswal.workers.dev/data/stock-bars. The results for MU should not be used to predict future performance for a small fund.
The automated trading fund manager made some calculations based on certain premises. The premises are: the probability of a successful trade, or p, is 0.5294118, the win amount, or W, is 0.01325795, and the loss amount, or L, is 0.01995905. Using a formula called the half Kelly criterion, which is a way to determine the optimal amount to bet, the result was 0, meaning no trade was made. This decision was not based on the amount of money available to trade, or venue position cap. The manager also ran a simulation, called a bootstrap, 50,000 times to see what might happen if the trade was made. The simulation used 20 past trade results and assumed the trade would be rebalanced every quarter, with a 1.4436127% change in the account per trade. The results showed that 71.9% of the time, the account would end up with less money than it started with. The simulation also showed that the account could end up with as little as 848.742887 or as much as 852.097942, with a median of 850.389251, compared to the starting amount of 850.99. These results are based on 20 quarterly events, which is equivalent to about 5 years, not 20 days or 1 month. The simulation included costs of 1 basis point fee plus 5 basis points per trade, but did not include other costs such as subscription fees or interest on cash. The simulation also assumed that each trade is independent, which means it does not take into account changes in the market or correlations between trades. The manager also tested what would happen if the fund lost 50% of its value, which would be a loss of 24.57, or 2.887225% of the account, and a total fund loss of 5.77445%. The manager did not assign a probability to this event. The manager also looked at the performance of a stock called CAG, which had a mean return of -0.6443% and did not meet the target return of 3 times the risk, or 3R. The manager did not make any trades and the approved amount to trade was 0. The manager used data from https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=CAG&feed=sip&adjustment=all and 23 other URLs, as well as local research and simulation files, but did not use the actual fund record because it does not follow a normal distribution.
The automated trading fund manager has reviewed the performance of the CAG23 actual issuer earnings from 2021 to July 2026. The Primary T5/ATR1/3 model shows a training win rate of 52.941%, with an average win of 1.325795% and an average loss of 1.995905%. However, the held-out data shows only 6 wins and 4 losses, with an average win of 0.559145% and an average loss of 3.051251%, resulting in a mean loss of 0.644320%. The bootstrap 95% mean confidence interval is -2.094866% to 0.587018%. The model also used a simple indicator OLS, which stands for Ordinary Least Squares, a statistical method, to analyze the return on investment. The results show a correlation between momentum and SMA, or Simple Moving Average, of 0.781325, and between momentum and return of 0.069265, with an R-squared value of 0.063501. The coefficients for the intercept, momentum, and SMA distance are -0.00418587, -0.07371741, and 0.26760662, respectively. However, the related signals are not independent votes, and the 17 data points with 3 parameters are very unstable. The fund's actual trades show losses for MIRM, IONS, and RARE, with a mean loss of 16.380601% and no winning trades. Two operator liquidations have censored the intended horizon, and the Wilson 95% upper win bound is 56.1506%. The RARE fill price is 13.98976, which is 41.7093% below the stop price, resulting in an actual loss of 6.44035 relative to the initial risk. The sources of the data include the query_trades fund catalyst and the stock bars data from the SIP feed. Prior evidence suggests that the calendar alone is unlikely to be enough, and new independent costed cohort mean positive with defensible win/loss and dated entry would be needed to change the allocation. The financial shortfall is not an evidence update.
The automated trading fund manager reviewed 12 foreign listings on Yahoo with 1-year histories across the UK, Japan, Canada, France, Sweden, Australia, Hong Kong, and Germany. The review found three stocks with positive 20-day returns: EGTX with an 11.3416% return, SAP with a 1.0571% return, and Toyota with a 0.3642% return. Four stocks were above their 50-day Simple Moving Average, including 4431.T. However, not all foreign listings were included. EGTX had a positive return, but its prior September 28 PDUFA run-up had no independent odds or venue FX validation. The manager also reviewed Kingfisher's financial calendar, which listed a provisional date of September 22, with a price header of 37.10 GBp, which is not the same as the Yahoo quote of 288.4. The manager noted that the price header should not be used to infer a quote or return. ABVX's financial calendar listed September 21 financials, but this was not a new top-line promise. The manager also reviewed crypto data, which returned 68 mover pairs, 70 with snapshot-only stablecoins, 34 base assets, and 19 USD snapshots. The leading mover was XTZ with a 2.21% return, but its spread was 56.97 basis points. The manager noted that quoted spreads are not fees and partial day returns are not daily edge. The manager also reviewed PAXG's spread, which was 118.14 basis points. There were no dated earnings or FDA edge from the ranking. The manager is watching Arc's September 16 primary launch and Sepolia's October 6 launch, but these are structural watches and not validated BTC or ETH payoffs. The mainnet exact date is unconfirmed. TLX is still unknown after news and SECCLI, and is not pending claim. RFIL's issuer origin was August 31, with a press release on September 14 at 8:30 ET. The manager also reviewed MUA's issuer call on September 30 at 16:30 EDT, which had a liquid trend, but the whole 975.26 was greater than 49.14, and there was no event test. LUXE's search-index IR was reviewed on September 16 and September 14, but the full release and financial bridge were unread, so it is a tentative watch and not a trade. The manager chose cash because the price, range, and date alone had no qualified payoff, not because the market was closed. There is no outside mandate validated edge for the new FUND.
A study of Conagra Brands earnings was done from 2021 to 2026. The study used actual earnings data from the company's website and other sources. The data was used to test a trading strategy with a 10-day window and a 15 basis point slip. The strategy had a return of -6.27% and a drawdown of 9.47% during the test period from 2025 to 2026. The strategy had a win rate of 33.33% and an average win of 3.14%. The study also tested the strategy with different parameters, but none of them performed better. The study did not validate the execution of the trades and did not audit the pre-announcement period. The results are based on historical data and not on future projections. A news scan found the website https://www.conagrabrands.com/investor-relations/financial-news/earnings-announcements as a source of earnings announcements.
A study on ConAgra Brands' earnings was conducted using data from 2021 to 2026. The study used a fixed strategy to predict earnings, with a 15 basis point slip. The training data consisted of 17 events from 2021 to 2024, and the held-out data consisted of 6 events from 2025 to 2026. The sources of the data included the company's investor relations website and a stock bars dataset. The study used a rule-based approach to enter trades, with a stop-loss set at 1 average true range, or ATR, which is a measure of volatility. The target was set at 3 ATRs. The study also used a daily open, high, low, and close, or OHLC, proxy to determine entry and exit points. The results showed a return of 1.3255, a drawdown of 10.0409, and a win rate of 41.18. The study used a vectorized portfolio with open and close marks, and 1 basis point fees and 15 basis points of slippage on each side. The return agreed with manual compounding to less than 3e-15. The study found no qualified entry. The historical dates used were actual release dates, but a full pre-announcement audit was not done. This study is a new reserved historical holdout for ConAgra Brands, not prospective forward data.
A study of ConAgra earnings was done from 2021 to 2026. The study used actual earnings data from the ConAgra website and other sources. The data was used to train a trading model from 2021 to 2024 and test it from 2025 to 2026. The model used a simple stop-loss strategy, which is a rule to sell a stock when it falls by a certain amount, in this case, one Average True Range, or ATR, which is a measure of how much a stock's price moves. The model also used a target price, which is three ATRs away from the entry price. The results showed a return of -5.14% and a drawdown of 8.47% over six trades. The model had a win rate of 33.33% and an average win of 3.35%. The study found no qualified entry, meaning the model did not find a good time to buy the stock. The study used historical data and did not validate the results with actual executions. A news scan found the source of the data to be from the ConAgra website and other online sources.
A study on Conagra Brands (CAG) earnings was conducted using actual data from 2021 to 2026. The study removed a duplicate entry from January 4 and used fixed returns before 2025. The data was sourced from the Conagra Brands website and other online sources, including https://www.conagrabrands.com/investor-relations/financial-news/earnings-announcements and https://runway.adityaperswal.workers.dev/data/stock-bars. The study used a rule to enter trades at the open price 10 days before an event, with a stop loss set at 1 times the average true range (ATR) and a target set at 3 times the ATR. The study also used a daily high-low-close-open (OHLC) proxy to adjust for gaps and stops. A vectorized backtest was run with a portfolio that included open and close marks, 1 basis point fees, and 5 basis points slippage on each side. The results showed a return of 4.83%, a drawdown of 8.95%, and a win rate of 41.18% over 17 samples. The study also found that the half Kelly fraction was 3.58 and the manual VBT error was 8.60e-16. The study used a T5 model and found that the T3 and T10 models were sensitive to the data, but no qualified entry was found. The historical dates used in the study were actual release dates, but a full pre-announcement audit was not done. This study is a new reserved historical holdout for CAG and not prospective forward data.
A study of ConAgra Brands earnings was done from 2021 to 2026. The study used actual earnings data from the company's website and other sources. The data was used to train and test a trading strategy. The strategy used a 3-day average true range, or ATR, to set stop-loss and target prices. The strategy was tested on data from 2025 and 2026. The results showed a return of 2.32% and a maximum drawdown of 5.65%. The strategy had a win rate of 50% and an average win of 2.63%. The study also found that the strategy had a high half-Kelly fraction, which is a measure of risk. The study did not validate the execution of the trades and did not audit the pre-announcement data. The results are based on historical data and not prospective forward data. A news scan found the source of the data to be from the company's investor relations website.
A study of ConAgra Brands earnings announcements from 2021 to 2026 found that training a model on data from 2021 to 2024 resulted in a return of -2.9116% with a drawdown of 5.862%. The model used a simple moving average and average true range, a measure of stock price volatility, to set stop-loss and target prices. The model was trained on 17 data points and tested on 6 held-out data points from 2025 to 2026. A 15 basis point slip in price was assumed for each trade, and a 1 basis point fee was charged. The results showed a win rate of 47.06% and an average win of 1.1768% and an average loss of 1.3521%. The model did not select a best holdout, and no qualified entry was found. The study used historical data and did not validate execution or audit pre-announcement data. A news scan found the source of the earnings data at https://www.conagrabrands.com/investor-relations/financial-news/earnings-announcements. The study also used data from https://runway.adityaperswal.workers.dev/data/stock-bars for explicit SIP adjustment. The half-Kelly fraction, a measure of optimal bet size, was 0. The study found that the two-outcome half-Kelly raw value can exceed 1 for variants, but this is not a leveraged authorization, and the qualified primary allocation is 0.
A study of ConAgra earnings was done using data from 2021 to 2026. The study used actual earnings data from the company's website and other sources. The data was used to train a trading model from 2021 to 2024 and test it from 2025 to 2026. The model used a simple rule to buy and sell stocks: it would buy on the third day before an earnings announcement and sell on the day before. The model also used a stop-loss order to limit losses. The results of the study showed a return of 3.55% and a maximum loss of 5.27%. The model had a win rate of 50% and an average win of 2.83%. The study also found that the model had a high sensitivity to certain parameters, but no qualified entry was found. The study used historical data and did not validate the results with actual executions. The data used was from actual earnings releases and was not prospective or forward-looking.
A study of ConAgra Brands earnings was done from 2021 to 2026. The study used actual earnings data from the company's website and other sources. The data was used to train a trading model from 2021 to 2024 and test it from 2025 to 2026. The model used a simple rule to buy and sell stocks: it bought on the third day before the earnings announcement and sold on the day before. The model also used stop-loss orders to limit losses. The results showed a return of 0.4462, a drawdown of 4.3088, and a win rate of 52.94%. The model was tested with different parameters, but no qualified entry was found. The study used historical data and did not validate the results with actual executions. A news scan found the website https://www.conagrabrands.com/investor-relations/financial-news/earnings-announcements as a source of earnings announcements.
A study of ConAgra earnings was done from 2021 to 2026. The study used actual earnings data from 23 issuers, which was first reported at 07:30 ET on certain dates. The data from 2021 to 2024 was used for training, and the data from 2025 to 2026 was held out for testing. The sources of the data were the ConAgra website and a stock bars website. The study used a rule to enter trades at the open price five days before an event, with a stop loss set at one average true range, or ATR, which is a measure of price volatility. The target price was set at three ATRs. The study also used a daily high-low-close-open, or OHLC, proxy to check for gap stops and targets at the open price. A vectorized backtest was done on a bitcoin cash portfolio with 1 basis point fees and 15 basis points slippage on each side. The results showed a return of -5.0398%, a drawdown of 7.3337%, and a win rate of 66.67%. The study also found that the T5 model had negative results in both training and holdout periods, while the T3 model had positive results in the base period but negative results in the stress training period. The T10 model had negative results in the holdout period. No qualified entry was found. The historical dates used in the study were actual release dates, but a full pre-announcement audit was not done. This study is a new reserved historical holdout for ConAgra, not prospective forward data.
A study on ConAgra Brands earnings runup was done from 2021 to 2026. The study used actual earnings data from the company's website and other sources. The data was used to train a model from 2021 to 2024 and test it from 2025 to 2026. The model used a simple rule to buy and sell stocks: it would buy at the open price five days before an earnings announcement and sell at the close price the day before. The model also used a stop-loss order to limit losses. The results of the study showed a return of -7.44% and a drawdown of 9.49%. The model had a win rate of 47.06% and an average win of 1.28%. The study also tested the model's sensitivity to different parameters and found that it was not sensitive to changes in the parameters. The study did not validate the model's performance on out-of-sample data and did not audit the pre-announcement period. The model's results are based on historical data and are not intended to be used for prospective investment decisions.
A study on ConAgra Brands' earnings was done from 2021 to 2026. The study used the company's actual earnings announcements from their website and other sources. It looked at what happened to the stock price before and after these announcements. The study used a rule to decide when to buy or sell the stock. This rule said to buy at the opening price five days before the announcement, and to sell if the price went down by a certain amount or up by three times that amount. The study also looked at how much money was made or lost, including small fees and costs. The results showed a return of -3.8935% and a biggest loss of 6.3087%. The study was done on a part of the data that was not used for training, from 2025 to 2026. This was a test of the rule, and it did not find any good times to buy the stock. The study only looked at what happened in the past and did not try to predict what will happen in the future.
A study of ConAgra Brands earnings was conducted using data from 2021 to 2026. The study used a fixed set of earnings data, with the first news dates at 07:30 ET, and removed a duplicate entry from January 4. The data was split into training and holdout sets, with 17 entries from 2021 to 2024 and 6 entries from 2025 to 2026. The sources of the data included the ConAgra Brands website and a data retrieval system. A stop-loss strategy was used, with a 1 ATR stop and a 3 ATR target, and the entry point was set at T-5 open. The daily high, low, open, and close prices were used as a proxy, with gap stops and targets set at the open. A vectorized portfolio was used, with 1 basis point fees and 5 basis points slippage on each side. The results showed a return of -4.24%, a drawdown of 7.77%, and a win rate of 52.94%. The study also found that the T5 model had negative results in both training and holdout sets, while the T3 model had positive results in the base case but negative results in the stress test. No qualified entry was found, and the historical dates used were actual release dates, with no full pre-announcement audit done.
A data scan from https://runway.adityaperswal.workers.dev found stock bars for symbols CAG, MU, and SPY. The scan returned 1682 bars for each symbol with no next page token, and IEX also returned 1537 to 1540 bars. On September 11, CAG was at 14.60, below its Simple Moving Average, or SMA, of 15.796 for 20 days, 15.0274 for 50 days, and 15.38265 for 200 days. The 20-day return was -5.133%, the Average True Range, or ATR, for 20 days was 0.41226, and the annual Realized Volatility, or RV, for 20 days was 27.348%. A possible stop was at 14.18774 and a target at 15.83678, which is a 1 ATR risk to 3 ATR reward, for a gross gain of +8.4711%. This target is more ambitious than the usual five-session gain of 3.80166% in 2020-2026. For MU, the price was 975.26, above its SMAs of 962.80675, 928.6069, and 621.932575, with an ATR of 46.328885 and an RV of 54.011%. The 20-day return was +2.677%. A 3 ATR target would be +14.2515%, versus a 5-day gain of +10.4587%, but one whole share is unaffordable at 49.14, the fund cap. Fractional shares are possible but do not establish an event edge or after-hours protection. For SPY, the price was 764.29, below its SMA of 766.879 for 20 days and above its SMA of 758.6164 for 50 days, with a 20-day return of -1.747% and an ATR of 5.45286. This shows modest market weakness, different from CAG's structural decline. The indicators are correlated diagnostics, not multiple independent confirmations. No trade was made, as 15-minute and +2R management were not validated by daily bars.
A news scan found information about several companies. Conagra cut its dividend to retain cash and increased spending on its brands and capital expenditures. This may lead to investment or price concessions for retailers and suppliers before benefits are seen by shareholders. Only recovering volume and margin can turn cash retention into higher returns. However, if spending fails, it may reveal further weakness under the new CEO. Oracle finances its data centers through customer prepayment and equity, which means equipment, power, and land providers get paid before customers fully utilize the data centers. The payoff for shareholders depends on future profitable use due to fixed lease commitments and dilution. On the other hand, prepaid contracted capacity and timing flexibility share the risk. Copart acquired ACV with cash and plans to integrate buyers and logistics across separate brands, which may increase auction liquidity and lift recoveries and fees if it can outpace insurance volume weakness and cost per car. The CEO benefits from the growth story, but there are no quantified synergy cash or closing date yet. Arc is planning to launch in September 2026, and existing USDC may migrate without new net liquidity. Increased transactions do not necessarily increase the value of ETH or SOL tokens or Circle cash proportionately, as seen in the Q2 volume increase of 151% versus a revenue increase of 7%. These are hypotheses about causes, not estimates of stock return probabilities. The information comes from the companies' reports and press releases, including Conagra's fourth-quarter and full-year results, Oracle's financial report, Copart's financial report, and Circle's second-quarter 2026 results.
A news scan found the filing for Oracle, which had previously been incomplete. The full filing is available at https://www.sec.gov/Archives/edgar/data/1341439/000119312526389274/orcl-20260831.htm. Two main points were clarified: first, Oracle's 20 billion dollar ATM, or at-the-market offering, has been fully utilized, resulting in approximately 141 million new shares and 19.9 billion dollars in net proceeds, which are past funding and not remaining capacity. The company also has 37.077 billion dollars in cash and securities, and management has stated that they have 12-month liquidity and discretionary capital expenditure flexibility, which are arguments against imminent funding failure. Second, Oracle's operating cash flow is 23.103 billion dollars, which includes 11.363 billion dollars in financing prepayments, capital expenditures of 28.499 billion dollars, and free cash flow of -5.396 billion dollars; a simple expression of free cash flow after prepayments is -16.759 billion dollars, which is not a standard GAAP metric. Additionally, 288 billion dollars in future leases are not considered debt. A separate filing for Copart, available at https://www.sec.gov/Archives/edgar/data/900075/000119312526388383/d138398dex992.htm, clarifies that the first full-year accretion will be in fiscal year 2028, and the current year will be breakeven; the deal is cash-funded with no financing condition, and is subject to customary regulatory review, with an expected closure at the end of 2026, but no fixed date. The CEO forecasted more than 2 billion dollars in post-deal cash. The company will retain distinct brands, but integrate buyers and logistics, and will need to invest in capital expenditures, training, and technology. In the fourth quarter, US insurance units decreased by 7.5%, cost per car increased by 12.7%, and operating income decreased by 10.6%, which contradicts a pure liquidity bull story. The CFO noted a 17 million dollar long-haul cost increase, which may support new fees, counter to all costs being a waste. The tender offer has still not commenced, according to https://www.sec.gov/Archives/edgar/data/900075/000119312526388383/d138398dsctoc.htm. In conclusion, the focus should be on economics, with no run-up order or merger date guess. The Q&A coverage gap has been closed, but the annual Oracle 10K risk review and future deal terms remain separate work.
A news scan found the headline about Conagra Brands' fourth-quarter and full-year results on July 15 and the announcement of the fiscal 2027 first-quarter earnings release on August 31. The analysis is based on two premises. First, Conagra's free cash flow for fiscal year 2026 was $979 million, which is more than the $670 million spent on dividends, leaving $309 million for other cash uses, with a net debt of $7.1 billion and a leverage of 3.83 times. For fiscal year 2027, the capital expenditure is expected to be $550 million, which is $127 million more than the previous year, a 30.0% increase, while organic sales are guided to be between -3% and -1%, margin between 10% and 10.5%, and earnings per share between $1.40 and $1.50. Second, cutting the dividend to $0.70 per year from $1.40 conserves approximately $335 million per year, assuming the number of shares remains constant at 479 million. At a price of $14.60 on September 11, the forward-adjusted earnings per share multiple is between 9.73 and 10.43 times, and the annual dividend yield is 4.79%. The conclusion is that Conagra is a candidate for an earnings run-up, but it is not automatically cheap. Fundamental recovery needs volume and cash progress by September 30. A countercase is that low expectations, a new CEO, dividend retention, and leading brands could permit an asymmetric rebound. The binding constraint is the net pre-event edge, not balance-sheet imminent failure or affordability at $49.14. The hard limit is a net leverage forecast of 4 times and rising capital expenditure, which reduces cash flexibility. These facts are from the issuer, and the probability of a run-up is unknown until tested. No order has been placed.
A news scan found the text: Fetched official Nasdaq Trader directories https://www.nasdaqtrader.com/dynamic/SymDir/nasdaqlisted.txt and https://www.nasdaqtrader.com/dynamic/SymDir/otherlisted.txt excluding TestIssue Y: 5597+7584=13181 unique securities, including ETFs/preferreds/warrants, not 13181 companies. Download-all https://api.nasdaq.com/api/screener/stocks?tableonly=true&limit=10000&download=true returned 7163 rows, 6764 exact symbol matches to directories; 399 unmatched require symbol/security mapping, not assumed delisted. Calendar https://api.nasdaq.com/api/calendar/earnings?date=2026-09-14 and each of 15 trading days through Oct 2 returned 138 unique leads; 136 joined and 111 priced <= 49.14. Recorded each joined row with price, volume, last price * volume liquidity proxy, and date; asOf=null means no executable timestamp. Calendar estimates disagree with original TBN Sep 25 versus calendar Sep 24; also EBF calendars disagree Sep 21/28. Never enter from estimate. Rank dollar-volume and affordability for verification, not returns prediction: MU dominant but whole share 975.26 > 49.14; CAG 14.60 and 247.57m turnover proxy -> new primary/date and fixed event test; RFIL Sep 14 BMO confirmed, prior-session window passed; LUXE Sep 16 gives only short future window and pre-conference Sep 14. TLX original news page still no verified decision. FDA calendar HTML was a table shell so no claim complete FDA census. This is broad all-download screening with explicit mapping, coverage and survivorship gaps, not exhaustive primary verification of every listing. No order from screen.
The fund started with $49.14 in cash and $850.99 in equity, with no current holdings or pending orders. The goal is to make a profit from dated run-ups that are exited before the first event news. A binding constraint is that there must be a justified executable payoff in an eligible future window, which is not just a $349.01 recovery need. There are three premises: (1) SRRK announced approval 19 days before the prior goal, so it is not possible to buy a future September 30 run-up after the actual news. (2) The Monday HAIN/HITI/PLAY default pre-event exit on September 11 has passed and past tests do not validate a new last-day entry. (3) The SCHL date of September 24 is confirmed, but the T5/3R test showed a 2.6403% loss, with a known holdout of +2.1505% and a stress of +0.3282%, which crosses the 0 target hits. (4) HOFT profits contain one-off refunds and ORCL has a new filing that adds financing and lease commitments, but neither provides a new run-up edge. The conclusion is to approve a notional 0, with no orders, stops, or targets set, and to preserve cash. The validity of this decision is limited by the small cohorts, known rather than new holdout, partial IEX feed, unverified 15-minute management and early news, and bounded global calendar. The strongest counter case is that SRRK approval and SCHL oversold mean reversion can produce big wins, but the price possibility does not calibrate odds or restore the tested window. New independent positive event evidence would change the allocation, but financial pressure will not. The current fund total loss stress is 5.77445% of the account, with a 50% gap of 2.88723%, and no assigned gap odds. The sources for this decision include news releases from Scholar Rock, Telix Pharma, and Scholastic Corporation, as well as data from the IEX feed and original data from HOFT and Oracle. Monitors 288, 293, 295-298 are armed, and five collectors are preserved, with no new executions verified at 00:17. Lessons 800-802 have been recorded, and there is no outside-mandate proven strategy that justifies the FUND line.
A news scan found the headline related to the SEP1200 collection. The existing 5 active jobs, which are 126, 132, 172, 223, and 224, all returned with an exit code of 0 and a final END in the actual venue output. These jobs recorded the exact last and next timestamps and the remaining runs. Job 223 received approval at 18:25 EDT on September 11 and then retrieved the full issuer release and label in this run. A new job is not needed because jobs 126 and 224 provide coverage at 00:15, job 172 provides coverage at 01:15, and job 223 provides coverage at 01:30, all before the 02:00 manager handoff. Job 132 follows at 02:15 with the next manager. The static old September 30 SRRK reminders in the collector output are superseded by the verified September 11 approval 25168 and monitor 288, which is not a new future PDUFA, or Prescription Drug User Fee Act, decision date. The system resolved down monitors 24, 13, 279, 193, 280, and 278 without any issues or gaps. It added SRRK launch to monitor 288, TLX at 02:00 UTC to monitor 293, PLAY outcome to monitor 295, SCHL meeting and paper entry to monitor 296, and NKE prior session to monitor 297, plus new ORCL 02:00 UTC coverage follow-up. Other fund monitors were untouched. The rule is to inspect fresh originals on new headlines, and if there is a missing or status error, it should be marked as unknown or cash, and never infer non-new news. No scripts place orders, and there are no queued limit orders. The sources include the list of jobs for the catalyst fund and primary URLs within monitors and analyses 2741, 2768, and 2778. Public records supersede old static reminders, and there is no economic claim from a hash alone, referring to a digital fingerprint.