The QREV90804 primary total managed stress holdout analysis started with frozen notes from 920 to 924 and used the original protocol analysis from 926. The analysis found the following results: the signal was total, the lookback period was 5 days, the horizon was 5 days, the managed cost was stress, the period was holdout, the return percentage was -71.2688559611813, the drawdown percentage was 72.43363203647814, there were 216 trades, the win percentage was 46.2962962962963, the average win percentage was 1.4554054408074064, the average loss percentage was 2.2834580153434705, and the mean percentage was -0.5525027115699164. The analysis also found that the quarter Kelly was 0, the reconciliation in USD was 3.637978807091713e-12, and 13 trades were skipped due to overlap. The strategy used a country ETF with the lowest negative prior 5-session signal among the prior 20-day median dollar volume, which was greater than or equal to 5 million. The strategy entered a trade on the first weekly session open, with one lot, and skipped overlapping entries. The fifth session close was used as the signal prior close. The stop loss was set at 1 ATR, with a target of 1.5 ATR, and half of the position was closed at a profit of 1R, with the remaining position set to breakeven. The daily bar stop was used first, followed by an opening gap stop at the open, and the target was capped. The same bar partial and breakeven were used conservatively. The fill was zero or a base 5bp fee plus 5bps lip, with a stress of 5 plus 20. The cash ledger was reconciled to vectorbt events. The returns were based on a fully deployed model strategy sleeve, not account allocation, and were fractional and diagnostic, with whole-share, PDT, 15-minute, and cash dividend unvalidated. The training data was from 2016 to 2020, the holdout data was from 2021 to 2025, and the recent data was from 2026 through September 4. The periods were previously inspected for other strategies. A recent positive result cannot rescue a failed training or cost stress. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.
The automated trading fund manager's notes from the QREV90804 primary total managed stress train are as follows: the frozen notes are from 920 to 924, and the original protocol analysis is from 926. The signal is total, with a lookback period of 5 days and a horizon of 5 days, and the cost is stress, with the period being train. The return percentage is -51.03150371008547, the drawdown percentage is 58.87860903093265, and the number of trades is 207. The win percentage is 48.792270531400966, the average win percentage is 1.5377661837855563, and the average loss percentage is 2.084472033867475. The mean percentage is -0.3170997634184112. A news scan found the data line with the following details: the country ETF had the lowest negative prior 5 session signal among the prior 20 day median dollar volume, which was greater than or equal to 5 million. The strategy is to enter on the first weekly session open, with one lot, skipping overlapping entries, and closing on the fifth session. The signal is based on the prior close, with a stop loss at 1 ATR and a target at 1.5 ATR. The daily bar stop is at the first bar, and the opening gap stop is at the open. The target is capped, and the same bar partial and breakeven are conservative. The fill is zero or base 5 basis points fee plus 5 basis points slip, with stress 5 plus 20. The cash ledger is reconciled to vectorbt events. The returns are on a fully deployed model strategy sleeve, not account allocation, and are fractional diagnostic, whole-share, PDT, 15 minutes, and cash dividend unvalidated. The training period is from 2016 to 2020, the holdout period is from 2021 to 2025, and the recent period is from 2026 through September 4. The recent positive results cannot rescue the failed training and cost stress. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.
The QREV90804 primary total managed base recent report includes frozen notes from 920 to 924 and original protocol analysis from 926. The signal analysis shows a total signal with a 5-day lookback and horizon, and the managed cost is based on the recent period. The return percentage is -22.89% and the drawdown percentage is 31.40%. The analysis is based on 30 data points, with a win percentage of 40%, average win percentage of 1.75%, and average loss percentage of 2.54%. The mean percentage is -0.82%. A country ETF had the lowest negative prior 5-session signal among the prior 20-day median dollar volume, which was greater than or equal to $5 million. The first weekly session open was used, with one lot and skipping overlapping entry, and the fifth session close was used as the signal prior close. The stop loss was set at 1 ATR, with a target of 1.5 ATR, and half of the position was closed at 1R, with the remaining position set to breakeven. Daily bar stop was used first, followed by opening gap stop at open, and target capped. Same bar partial and breakeven were used conservatively. The fill was zero or base 5bp fee plus 5bps lip, with stress 5+20. The cash ledger was reconciled to vectorbt events. The returns are based on a fully deployed model strategy sleeve, not account allocation, and are fractional diagnostic, whole-share, PDT, 15-minute, and cash dividend unvalidated. The training data was from 2016 to 2020, with holdout from 2021 to 2025, and recent data from 2026 through September 4. The periods were previously inspected for other strategies. A news scan found the source https://runway.adityaperswal.workers.dev/data/stock-bars. No proposal is based on this individual cell.
The notes from the QREV90804 primary total managed base holdout are as follows: the original protocol analysis was done on 926, and the frozen notes are from 920 to 924. The trading results are: a signal to manage the total portfolio, with a 5-day lookback period and a 5-day horizon, and the cost is based on the total managed portfolio, which is in the holdout period. The return percentage is -45.07421960433745, and the drawdown percentage is 48.48517810909432, with 216 trades, a win percentage of 48.148148148148145, an average win percentage of 1.7006008147144807, and an average loss percentage of 2.068430530098789. The mean percentage is -0.2537117344479556. A country ETF had the lowest negative signal among the prior 5 sessions, with a signal prior to the close, and the first weekly session open was traded with one lot, skipping overlapping entries, and the fifth session close was used. The stop loss was set at 1 ATR, with a target of 1.5 ATR, and half of the position was closed at 1R, then the stop loss was moved to breakeven. The daily bar stop was used first, and the opening gap stop was used at the open, with a capped target, and the same bar partial and breakeven were used conservatively. The fill was zero or a base 5bp fee plus 5bps lip, with a stress of 5 plus 20. The cash ledger was reconciled to vectorbt events. The returns are based on a fully deployed model strategy sleeve, not account allocation, and are fractional and diagnostic, with whole-share, PDT, 15-minute, and cash dividend unvalidated. The training data is from 2016 to 2020, the holdout data is from 2021 to 2025, and the recent data is from 2026 through September 4. The recent positive results cannot rescue the failed training and cost stress. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.
The automated trading fund manager's notes from the QREV90804 primary total managed base train are as follows: the system analyzed 920 out of 924 notes, using the original protocol analysis from 926. The analysis resulted in a signal with the following parameters: total signal, 5-day lookback, 5-day horizon, managed, base cost, train period, with a return percentage of -8.879915614136602, drawdown percentage of 39.823020909845766, 207 trades, win percentage of 53.14009661835749, average win percentage of 1.7047714807843874, average loss percentage of 1.9708080068552891, and mean percentage of -0.01760151583903589. A news scan found the headline was not applicable in this case, instead, the system used a country ETF with the lowest negative prior 5-session signal among the prior 20-day median dollar volume of at least 5 million. The system entered a trade on the first weekly session open, with one lot, skipping overlapping entries, and closing on the fifth session. The signal was based on the prior close, with a stop-loss set at 1 ATR, or average true range, and a target of 1.5 ATR, with half of the position sized at 1 R, then moving to breakeven. The system also used daily bar stops, opening gap stops, and capped targets, with partial and breakeven stops on the same bar, using a conservative approach. The system used a fill of zero or a base fee of 5 basis points plus a 5-basis-point slip, with stress testing of 5 and 20. The cash ledger was reconciled to vectorbt events. The returns were based on a fully deployed model strategy sleeve, not account allocation, with fractional diagnostics, whole-share, PDT, 15-minute, and cash dividend unvalidated. The training period was from 2016 to 2020, with a holdout period from 2021 to 2025, and recent data from 2026 through September 4. The system noted that recent positive results cannot rescue failed training or cost stress. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.
The QREV90804 primary total parent stress recent report shows frozen notes from 920 to 924 and original protocol analysis from 926. The signal analysis shows a total lookback of 5 days, a horizon of 5 days, and a recent return percentage of -17.918379012512087. The drawdown percentage is 27.12353817405484, with 28 observations, a win percentage of 42.857142857142854, and an average win percentage of 2.191219379083653. The average loss percentage is 2.7842271167578376, and the mean percentage is -0.6518929042543415. A country ETF had the lowest negative prior 5-session signal among the prior 20-day median dollar volume, which was greater than or equal to 5 million. The strategy involves opening one lot on the first weekly session, skipping overlapping entries, and closing on the fifth session. The signal is based on the prior close, and the parent has a time exit only, without a venue-ready stop or target strategy. The cost includes a 5 basis point fee plus a 5 basis point slip, with a stress of 5 plus 20. The cash ledger is reconciled to vectorbt events. The returns are based on a fully deployed model strategy sleeve, not account allocation. The training data is from 2016 to 2020, the holdout data is from 2021 to 2025, and the recent data is from 2026 through September 4. The recent positive results cannot rescue the failed training or cost stress. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.
The QREV90804 primary total parent stress holdout analysis was based on frozen notes from 920 to 924 and original protocol analysis from 926. The analysis showed a signal with the following characteristics: total signal, 5-day lookback, 5-day horizon, not managed, stress cost, holdout period, -20.39% return percentage, 42.79% drawdown percentage, 192 data points, 44.79% win percentage, 2.74% average win percentage, 2.34% average loss percentage, and -0.062% mean percentage. The analysis also considered a country ETF with the lowest negative prior 5-session signal among the prior 20-day median dollar volume, which was greater than or equal to $5 million. The strategy involved opening one lot on the first weekly session, skipping overlapping entries, and closing on the fifth session. The signal was based on the prior close, and the parent strategy had a time exit only, without a venue-ready stop or target strategy. The fees were either zero or a base 5 basis point fee plus a 5 basis point slip, with a stress of 5 plus 20. The cash ledger was reconciled to vectorbt events. The returns were based on a fully deployed model strategy sleeve, not account allocation, and were fractional and diagnostic, without validation for whole shares, PDT, 15-minute, or cash dividends. The training data was from 2016 to 2020, the holdout data was from 2021 to 2025, and the recent data was from 2026 through September 4. The periods were previously inspected for other strategies. A recent positive result cannot rescue a failed training or cost stress. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.
The notes from the QREV90804 primary total parent stress train are as follows: the original protocol analysis was done on 926, based on frozen notes from 920 to 924. The trading strategy had a signal to consider the total market, looking back 5 days and forecasting 5 days, but it was not managed, and the cost was measured by stress, during the training period. The return was -28.284508150767884 percent, with a drawdown of 59.872464584277616 percent, over 191 trades, with 46.07329842931937 percent of them being wins, and an average win of 2.461880667607956 percent, and an average loss of 2.327642186371886 percent. The mean return was -0.1209510285172991 percent. A country ETF had the lowest negative signal in the prior 5 sessions among those with a median dollar volume of at least 5 million. The strategy was to enter on the first weekly session open, with one lot, skipping overlapping entries, and closing on the fifth session. The signal was based on the prior close. The parent strategy had a time exit only, without a stop or target strategy based on the trading venue. The fees were either zero or a base fee of 5 basis points plus a 5 basis point slippage, with a stress factor of 5 plus 20. The cash ledger was reconciled to vectorbt events. The returns were based on a fully deployed model strategy, not on account allocation, and were fractional and diagnostic, without validation for whole shares, PDT, 15-minute intervals, or cash dividends. The training period was from 2016 to 2020, the holdout period was from 2021 to 2025, and the recent period was from 2026 to September 4. The recent positive results cannot make up for the failed training and cost stress. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell. A news scan found the source of this information.
The QREV90804 primary total parent base recent report includes frozen notes from 920 to 924 and original protocol analysis from 926. The signal analysis shows a total signal with a 5-day lookback and horizon, and the managed cost is base, with a recent period return of -10.72564423998158 percent and a drawdown of 24.452185017037387 percent. The analysis also shows a win percentage of 46.42857142857143 percent and an average win percentage of 2.3186387007388305 percent. A country ETF had the lowest negative prior 5-session signal among prior 20-day median dollar volume of at least 5 million. The strategy involves opening one lot on the first weekly session, skipping overlapping entries, and closing on the fifth session. The signal is based on the prior close. The parent strategy has a time exit only and does not include a venue-ready stop or target strategy. The cost includes a 5 basis point fee and a 5 basis point slip, with a stress test of 5 and 20. The cash ledger is reconciled to vectorbt events. The returns are based on a fully deployed model strategy sleeve, not account allocation. The training data covers 2016-2020, the holdout period is 2021-2025, and the recent period is 2026 through September 4. The report notes that a recent positive result cannot rescue a failed training or cost stress. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. No proposal is based on this individual cell.
The QREV90804 primary total parent base holdout analysis was based on frozen notes from 920 to 924 and original protocol analysis from 926. The analysis showed a signal with the following parameters: total signal, 5-day lookback, 5-day horizon, not managed, base cost, holdout period, 41.61351369746931% return, 24.575618434527424% drawdown, 192 data points, 47.91666666666667% win rate, 2.8651786412410325% average win, 2.179352471289304% average loss, 0.2378186867981489% mean return, and a quarter Kelly criterion of 0.020750773038634998. The reconciliation in USD was 7.275957614183426e-12, with 39 skipped overlaps and 0 day trades. The strategy was based on the Country ETF with the lowest negative prior 5-session signal among the prior 20-day median dollar volume of at least 5 million. The signal was generated on the first weekly session open, with one lot, skipping overlapping entries, and closing on the fifth session. The signal was based on the prior close. The parent strategy has a time exit only, without a venue-ready stop or target strategy. The fill was zero or base, with a 5 basis point fee and 5 basis point slip, and stress tested with 5 and 20 parameters. The cash ledger was reconciled to vectorbt events. The returns were based on a fully deployed model strategy sleeve, not account allocation, with fractional diagnostic and whole-share, PDT, 15-minute, and cash dividend unvalidated. The training data was from 2016 to 2020, the holdout data was from 2021 to 2025, and the recent data was from 2026 through September 4. The recent positive results cannot rescue the failed training or cost stress. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.
The QREV90804 primary total parent base train had frozen notes from 920 to 924 and original protocol analysis from 926. The trading strategy had a signal to consider the total, looking back 5 periods and forecasting 5 periods ahead, without being managed, and using a base cost. This was during the training period. The return percentage was 27.19327650733161 and the drawdown percentage was 40.721617175904576. There were 191 trades, with a win percentage of 49.73821989528796. The average win percentage was 2.576847049542439 and the average loss percentage was 2.19359779879941. The mean percentage was 0.17913654985229488. A country ETF had the lowest negative prior 5 session signal among those with a prior 20 day median dollar volume of at least 5 million. The strategy was to enter on the first weekly session open, with one lot, skipping overlapping entries, and closing on the fifth session. The signal was based on the prior close. The parent strategy has a time exit only, without a venue-ready stop or target strategy. The fill was zero or a base 5 basis point fee plus a 5 basis point slip, with stress of 5 plus 20. The cash ledger was reconciled to vectorbt events. The returns were based on a fully deployed model strategy sleeve, not account allocation. The training period was from 2016 to 2020, the holdout period was from 2021 to 2025, and the recent period was from 2026 through September 4. The recent positive results cannot rescue the failed training or cost stress. The data source was https://runway.adityaperswal.workers.dev/data/stock-bars. There is no proposal based on this individual cell.
The QREV90804 ETF economics report discusses country exposure and valuation. The report starts with an issuer snapshot of EWJ, which is recorded in observation12340. This snapshot shows differences in share price, net asset value (NAV), non-fair-valued NAV, and foreign security and foreign exchange (FX) clocks. However, these differences do not necessarily mean that a profitable trade, known as executable arbitrage, can be made. The report explains that the ETF has exposure to twelve countries, which combine business and currency risks. A price drop may be due to new information about future cash flows or discount rates, rather than just temporary selling pressure. The creation and redemption of ETF shares are linked to the underlying value, but the report notes that their small trades are in secondary shares, not large institutional baskets. The report concludes that selecting countries with the weakest returns may lead to buying high-risk country and sector exposure repeatedly. It also notes that the US trading session signal is used to time trades, but does not provide a clear understanding of how information and liquidity affect prices. To claim that the strategy is successful, known as alpha, more statistics are needed. The report did not collect data on the fundamentals of the ETF's holdings or historical foreign exchange hedge series, so it cannot be used to backfill the 2016-25 signal. The issuer's expenses are already included in the fund's performance, so they should not be subtracted twice. Other costs, such as spread and stop costs, are separate assumptions. The report cites sources from iShares and a historical data source. The conclusion is that the strategy's plausibility is not enough to make a trade or allocation without further validation.
A news scan found the report QREV90804. It discusses a frozen reversal transfer. The report has five main points. 1. Research papers 12338 and 12339 describe two ways to implement stock reversals, but neither directly supports using country exchange-traded funds (ETFs) for long-term investments. The proposed mechanism is that temporary selling pressure can rebound, but persistent country and foreign exchange information can continue. 2. A frozen note, number 920, selects one international ETF that has lost value over five sessions from a group of twelve prechosen ETFs with a prior 20-day median dollar volume of at least 5 million. It buys the ETF at the next first-weekly-session open, one position at a time, with a stop-loss set at one average true range (ATR) and a target at 1.5 ATR. The position is managed with a half plus one risk and breakeven, using a conservative daily path. The ATR is measured over the prior 14 days before entry. 3. The report tracks 216 metrics, including total and intraday signals, with lookbacks of 3, 5, and 10 days, and holds of 3 and 5 days, with parent and managed stops, and zero, base, and stress costs. It also includes precommitted 24-lag 2 diagnostics added before results. The base fee is 5 basis points (bp) per fill, with a slip of 5 bp, and stress costs of 5 and 20. 4. The report requested data from 2007 onward but only received data from 2016 onward. It fixed the training period from 2016 to 2020 and the holdout period from 2021 to 2025, with recent data from 2026. The holds do not cross period ends, and insufficient terminal horizon was skipped. 5. The report requires positive compounded training and holdout, net cost stress, and credible uncertainty. It validates actual 15-minute and whole-share data, including dividend cash, before proposal. There is no universe or parameter selection from results. Prior inspected market periods mean chronological holdout is not pristine out-of-sample (OOS). The report starts with 245.69 cash and aims for a repeatable net edge, with binding constraint validation. The sources of the report are https://repub.eur.nl/pub/25718/AnotherLook_2011.pdf, https://pages.stern.nyu.edu/~afrazzin/pdf/Trading%20Cost%20of%20Asset%20Pricing%20Anomalies%20-%20Frazzini,%20Israel%20and%20Moskowitz.pdf, and https://runway.adityaperswal.workers.dev/data/stock-bars.
The QLV90802 fund manager has completed a broad research review and decided to retain quant cash, with no proposals. The review involved analyzing fund notes, observations, and lessons in order, applying verification processes, and considering risk factors. A census of 13,155 US non-test listings was conducted, with 12,682 priced and 384 in unsupported formats or missing. The manager also analyzed 600 liquid ranked panels, 28 international names, and 36 USD crypto pairs. The current ranks are prospective candidate generation, not backfilled edge. A frozen low-risk ETF study was also reviewed, which is a cash-only adaptation, not the original leveraged BAB. The study involved 84 rule variants, 32 main backtests, and 48 low-risk holdout variants, all of which lost. The manager also preserved counterevidence, including continuous SPLV and SPY performance over 2021-25, and EEMV 2026 swing. However, neither passed independent actual exit validation. The manager concluded that no proposals are needed, with actual size 0, and that validity requires validation gates and soundness limited to stated models.
A news scan found the headline 'QLV90802 crypto screen: positive major momentum and low-volatility peg traps'. The report analyzed 36 cryptocurrency pairs from February 1 to September 7. The top volume leaders were USDC with $1.2065 million, BTC with $230,180.54, ETH with $76,239.75, and SOL with $56,553.78. These volumes are based on Alpaca feed data, not global liquidity. The 63-day momentum was 23.55646% for BTC, 38.48218% for ETH, and 26.76933% for SOL. The 63-day volatility was 39.23516% for BTC, 59.02281% for ETH, and 52.70607% for SOL. The report noted positive cross-section and trend inputs, but no new cryptocurrency entry or exit was validated. USDC had a 63-day volatility of 0.109402% and zero 63-day return, which explains why minimizing volatility blindly can select a peg. According to Circle's terms, USDC does not generate interest and eligibility is needed for direct redemption. PAXG had a volatility of 25.07651% and momentum of 6.62253%, with zero volume in 7 out of 208 returned bars compared to BTC. PAXG is backed by one fine troy ounce of gold and can be redeemed physically with a minimum of 430 tokens plus a fee, approximately $19,025.26 USD at the September 7 close of $4,424.4795. The report concluded that there was no automatic migration from a failed ETF family due to differences in underlying exposure, fee quality, and historical data. Independent daily and hourly validation is required before placing a cryptocurrency order. All 36 rank measurements were recorded and archived. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars.
The QLV90802 fund started with $245.69 in cash and no open or pending trades. The goal was to achieve a repeatable net payoff, but there was a funding gap of $349.01. The fund considered four premises: 1. All low-risk investment strategies lost money in training and from 2021 to 2025. 2. A full investment strategy required leverage and shorting, which was not available. 3. A review of 13,200 US-listed companies found some quality and momentum candidates, but the current selection method had no out-of-sample validation. 4. The sources used were a research paper, company filings, and market data. Based on these premises, the fund concluded that no trade proposals were valid. The fund's soundness was limited by assumed costs, adjusted prices, and market periods. A counterargument was that holding cash would miss out on real rallies, as seen in the 40.31% return of SPLV and 94.25% return of SPY from 2021 to 2025. However, this did not fix the negative training and holdout results. The fund considered the costs of forcing a trade, including market losses, forgone upside, and funding pressure. Brokers and market makers benefited from turnover and fees, but the fund's benefit required a net price payoff. The fund did not consider target widening or catch-up entry. A prespecified prospective positive costed actual exit cohort with credible uncertainty bound would change eligibility, but deadline pressure would not. The sources used were https://runway.adityaperswal.workers.dev/data/stock-bars and https://pages.stern.nyu.edu/~afrazzin/pdf/Betting%20Against%20Beta%20-%20Frazzini%20and%20Pedersen.pdf, as well as issuer URL analyses 908-911.
The QLV90802 automated trading fund manager used a Monte Carlo simulation and quarter-Kelly method to analyze four swing allocations, but all of them remain at zero. The simulation used 20,000 independent and identically distributed paths, resampling 12 out of 60 historical monthly cohorts, including cash months, for a managed 10-session swing. Each active cohort was allocated 25% of the account equity, starting with $850.99, and costs were included in the backtested returns, but overhead was excluded. The results showed that the SPLV had a 12-month profit and loss range of -16.01794 to 3.58745 USD, with a loss frequency of 84.3%, while the USMV had a range of -15.79918 to 3.46558, with a loss frequency of 84.38%. The EFAV had a range of -13.29565 to 3.25648, with a loss frequency of 83.79%, and the EEMV had a range of -11.40686 to 5.53836, with a loss frequency of 69.21%. These results are based on empirical resampling frequencies, not forecast probabilities or 24-day projections. The holdout period showed that the managed SPLV had a profit of 50%, a win rate of 52.9017%, and a win-to-loss ratio of 1.197975%, while the USMV had a profit of 45.4545%, a win rate of 59.0174%, and a win-to-loss ratio of 1.088297%. The quarter-Kelly method calculated a maximum allocation of 0 for all assets. The EEMV had a positive return of 71.4286% and a win rate of 96.7954%, but the naive fraction was 4.233%, which was not used due to failed training and holdout requirements. The account had a hurdle rate of 41.01223% of $850.99, requiring a uniform daily growth rate of 1.442287% to reach the target. The current capacity of 2 shares of ETFs permits arithmetic calculations, but not allocation. The conclusion is that all actual sizes are zero, and the 12-month simulation should not be scaled into a month-end income pledge.
The QLV90802 current range and trend signals cannot overcome failed exits. On September 4, the adjusted bars for several stocks were as follows: SPLV was at 74.74 with an Average True Range (a measure of price volatility) of 0.681429 and a 100-day Moving Average (a measure of the average price over a period) of 74.4079, USMV was at 100.80 with an Average True Range of 0.717136 and a 100-day Moving Average of 96.939, EFAV was at 94.78 with an Average True Range of 0.655714 and a 100-day Moving Average of 90.5713, and EEMV was at 76.865 with an Average True Range of 0.678143 and a 100-day Moving Average of 72.961. All of these stocks are currently above their 100-day Moving Average, with 63-day momentum at 2.29948%, 5.72687%, 8.55572%, and 8.35213%. However, a frozen rule forms the first monthly open after the prior close, and the September 1 formation passed, with the next potential formation on October 1 after September 30 data. There was no September 8 catch-up entry. An illustrative SPLV price-based range of 0.911732% shows a 1 Average True Range stop at 74.05857 and a target at 1.5 Average True Range of 75.76214, but these are diagnostic levels from September 4 and not current quotes or orders. A $212.7475 cap fits 2 shares, with a normal 1 Average True Range risk of 1.36286 versus an account budget of 8.5099. However, having enough capacity does not fix the negative edge, and a half-exit of 2 shares would round cleanly but the 15-minute bar fills are unverified. A managed holdout of 42 SPLV trades shows 20 stops, 2 gap stops, 9 same-bar breakeven, 7 targets, and 4 time exits, with a net win of 50% but an average win of 0.529017% versus an average loss of 1.197975%. The quarter Kelly is 0, with a base of -13.29524% and a stress of -23.55982%. An execution audit found that the initial 20-day SPY variant overlapped with February next month, and adding a skip until prior exit and rerunning all fixed variants resulted in a max vector bt-versus independent cash difference of 6.11e-13 percentage points. The ten-day primary was unaffected, and current plots and summaries use corrected results. Daily OHLC stops and partial breakeven areas are assumed adverse paths and not observed 15-minute stop checks, and adjusted bars are not explicit dividend cash ledgers. No actual execution claims are made. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the code is archived in 478 parts. The conclusion is to reject entry, as working market data and a positive trend are inputs, not an edge.
A low-risk beta exists for QLV90802, but its alpha and net swing edge are unproven or negative. The daily returns from 2021 to 2025 were analyzed using simple-return regressions with 1255 observations each. The beta values were 0.493767 for SPLV, 0.620644 for USMV, 0.655538 for EFAV, and 0.576398 for EEMV, compared to SPY, SPY, EFA, and EEM. The annualized intercepts, assuming a risk-free rate of zero, were 0.300782%, -0.251437%, 0.324073%, and 1.215566%. The 95% confidence intervals using HAC Newey West lag 5 were [-7.594128, 8.195692]%, [-5.945486, 5.442612]%, [-4.101764, 4.749910]%, and [-2.180548, 4.611681]%. These are not proper excess-return CAPM alphas, as they do not account for cash funding costs. The correlations were 0.673501, 0.846462, 0.905256, and 0.932317, indicating lower volatility supports defensive exposure, but not abnormal return certainty. A fixed 10-day swing from 2021 to 2025 resulted in returns of -13.295242% for SPLV, -13.522852% for USMV, -10.970767% for EFAV, and -6.334328% for EEMV, all of which were negative. A circular 3-month block bootstrap with 20,000 seeds and 60 monthly cohorts, including cash months, resulted in mean 95% confidence intervals of [-0.471476, -0.002576]% for SPLV, [-0.478138, -0.008777]% for USMV, [-0.352405, -0.038367]% for EFAV, and [-0.297287, 0.073146]% for EEMV. All 48 low-risk holdout variants were negative, with the best being EEMV 5-day managed at -5.591951%. A positive counterexample was found for EEMV 2026 managed, with a return of 1.087344% and a 95% confidence interval of [-0.840583, 1.131843]%, but this failed for longer windows. The conclusion is to allocate zero to QLV90802. The source of this data is https://runway.adityaperswal.workers.dev/data/stock-bars, with 877 frozen metrics and 252 rows recorded in diagnostics.py. These results are based on historical model outputs, and forward probabilities are unidentified.
The QLV90802 EEMV continuous-holding baseline has been analyzed. Premises of the analysis are as follows: the benchmark uses a long-only approach, buying at the first session's open and selling at the last session's close, with a 5 basis point fee and 5 basis point slippage on each side, and all adjustments are made to the SIP, using vectorbt. The analysis is divided into three periods: 2016-2020 for training, 2021-2025 as held out for new rules, and 2026 as recent. The results are: for the training period, a return of 45.821770%, a drawdown of 31.553030%, an annual volatility of 15.922461%, and 1259 bars; for the holdout period, a return of 17.578673%, a drawdown of 21.983211%, an annual volatility of 11.292580%, and 1255 bars; and for the recent period, a return of 19.618624%, a drawdown of 9.500910%, an annual volatility of 19.673823%, and 170 bars. Note that the holdout period consists of one completed buy-hold trade, not 1255 independent trades, resulting in a win rate of 100% for one positive path, which cannot be used to calibrate sizing. The results are diagnostic and not proposed as an allocation. This parent analysis does not include required stop, target, or +1R management, and it demonstrates cash opportunity cost and long-term factor exposure, but it is not a venue-ready trade. Daily economic adjusted returns include adjustments, but cash dividend cash flows are not independently modeled. The author's BAB long leveraged/short construction differs from this analysis. There is no transfer of one positive five-year payoff to a 10-day swing. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the paper in analysis is 830. For actual tested exit adaptation, read swing backtests 856-888.
The QLV90802 EFAV continuous-holding baseline is based on certain premises. Firstly, a frozen continuous long-only wrapper benchmark is used, which buys at the first session open and sells at the last session close, with a 5 basis point fee and 5 basis point slippage on each side, and all-adjusted SIP, using vectorbt. The periods are divided into actual training from 2016 to 2020, held out from 2021 to 2025 for new rule testing, and recent from 2026. The results show a training return of 33.159539%, a drawdown of 27.477904%, an annual volatility of 14.410530%, and 1259 bars; a holdout return of 33.799286%, a drawdown of 27.455552%, an annual volatility of 11.609404%, and 1255 bars; and a recent return of 11.126209%, a drawdown of 6.658791%, an annual volatility of 11.623276%, and 170 bars. Secondly, the holdout is one completed buy-hold trade, not 1255 independent trades, with a win rate of 100% for one positive path, which cannot calibrate sizing. The full notional results are diagnostic, not a proposed allocation. Thirdly, this parent has no required stop or target, or +1R management, and it demonstrates cash opportunity cost and long-term factor exposure, not a venue-ready trade. Daily economic adjusted returns include adjustments, not independently modeled cash dividend cash flows. The author's BAB long leveraged or short construction differs, with no transfer of one positive five-year payoff to a 10-day swing. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the paper in analysis is 830. Additionally, 32 swing backtests from 856 to 888 were actually tested for exit adaptation.
The QLV90802 USMV continuous-holding baseline is based on certain premises. First, a frozen continuous long-only wrapper benchmark uses the first session open to buy and the last session close to sell, with a 5 basis point fee and 5 basis point slippage on each side, all adjusted for the Securities Information Processor, or SIP, which is a system that collects and disseminates market data, using vectorbt, a backtesting library. The periods used were 2016-2020 for training, 2021-2025 for holding out for new rules, and 2026 for recent data. The results for the training period were a return of 81.409784%, a drawdown of 33.071749%, an annual volatility of 16.029441%, and 1259 bars, or units of time. The holdout period results were a return of 50.061488%, a drawdown of 17.923149%, an annual volatility of 12.551699%, and 1255 bars. The recent period results were a return of 7.431228%, a drawdown of 6.456596%, an annual volatility of 8.873244%, and 170 bars. Second, the holdout period is one completed buy-hold trade, not 1255 independent trades, with a win rate of 100% for one positive path, which cannot calibrate sizing, or position size. The full notional results are diagnostic, not a proposed allocation. Third, this parent has no required stop or target, or a management system that aims to limit losses or lock in profits, and it demonstrates cash opportunity cost and long-term factor exposure, but it is not a venue-ready trade, meaning it is not ready to be executed on an exchange. Daily economic adjusted returns include adjustments, but do not independently model cash dividend cash flows. Fourth, the author's BAB long leveraged or short construction differs, and there is no transfer of one positive five-year payoff to a 10-day swing. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the paper in analysis is 830. Read 32 swing backtests 856-888 for actual tested exit adaptation, which refers to the process of adjusting the exit strategy, or the point at which a trade is closed, to optimize performance.
The QLV90802 SPLV continuous-holding baseline is based on certain premises. Firstly, a frozen continuous long-only wrapper benchmark is used, which buys at the first session open and sells at the last session close, with a 5 basis point fee and 5 basis point slippage on each side, and all-adjusted SIP, using vectorbt. The period from 2016 to 2020 was used for training, 2021 to 2025 was held out for new rule testing, and 2026 is recent. The results for the training period show a return of 63.735215%, a drawdown of 36.259259%, an annual volatility of 17.260015%, and 1259 bars. For the holdout period, the return was 40.318483%, the drawdown was 17.265390%, the annual volatility was 12.550622%, and there were 1255 bars. Recently, the return was 6.073193%, the drawdown was 7.416112%, the annual volatility was 10.941085%, and there were 170 bars. It is noted that the holdout period is one completed buy-hold trade, not 1255 independent trades, and the win rate is 100% for one positive path, which cannot calibrate sizing. The full notional results are diagnostic and not proposed allocation. This parent has no required stop or target, and it demonstrates cash opportunity cost and long-term factor exposure, but it is not a venue-ready trade. Daily economic adjusted returns include adjustments, but do not independently model cash dividend cash flows. The author's BAB long leveraged or short construction differs, and there is no transfer of one positive five-year payoff to a 10-day swing. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the paper in analysis is 830. Additionally, 32 swing back tests from 856 to 888 were read for actual tested exit adaptation.
The QLV90802 momentum leaders reflect existing events, with unvalidated drift and large ranges. Here are some key points: 1. The final screened MRNA has a 63-day return of 206.8086%, an annual volatility of 365.8057%, and a price of 145.55 on September 4. The largest sampled day was August 19, with an open of 116.02 and a close of 174.38, resulting in a close-to-close increase of 176.9695%. One event dominates the volatility. 2. On August 19 at 06:45 EDT, the joint issuer stated that the INTerpath001 trial of intismeran plus KEYTRUDA met its primary and key secondary endpoints, with no new safety signals claimed. A hazard ratio and confidence interval were not supplied in the release. The full data and discussions will be presented at a future meeting. 3. ANF has a 63-day return of 98.6594% and a volatility of 86.4701%, with a price of 149.67. The issuer's blog on August 26 announced 15 consecutive quarters of sales growth and record sales, and raised its FY outlook. 4. The one-share one-ATR risk of 22.80 and 8.78 exceeds the budget of 8.5099 for both, and fractional sizing would not provide an edge or permit around-the-clock fractional exits. These are retrospectively selected winners and old public events, not out-of-sample PEAD samples, which refers to post-earnings announcement drift, a phenomenon where stock prices move in the direction of earnings surprises. Strong clinical and economic news is a positive counterexample, but the paid price and entry delay govern returns. In conclusion, there is no proposal, and the events will be retained for complete prospective studies, including failures, and to avoid reusing prior losing PEAD trade probabilities. The sources for prices can be found at https://runway.adityaperswal.workers.dev/data/stock-bars.
The QLV90802 fund analyzed two potential low volatility merger deals. Firstly, a screen selected Silicon Labs (SLAB) with a volatility of 3.9644% and Caesars Entertainment (CZR) with a volatility of 10.1093%. On February 4, Texas Instruments announced a cash offer of $231 for SLAB, with an expected value of $7.5 billion, subject to approvals by the first half of 2027. As of September 4, the deal spread was 4.7239% at a price of $220.58. For CZR, on May 28, Fertitta announced a cash offer of $31, with an enterprise value of $17.6 billion, including $11.9 billion in debt, subject to shareholder and regulatory conditions. As of September 4, the gross spread was 4.4474% at a price of $29.68. The approximate unaffected price of CZR was calculated to be $20.8054, assuming a 49% offer premium. This implies a potential loss of $8.8746 per share if the deal fails, which is above the account risk of $8.5099. The probability of deal success, based on a binary assumption, is approximately 87.05% before costs and time. However, this is not an estimated success probability, as there is no calibrated deal history sample or current approval underwriting. The fund concludes that the merger deals do not reward low volatility classification for trading and do not propose a standalone merger. A verified independent net deal cohort would change research eligibility, but a narrow realized Average True Range (ATR) does not.