The July wholesale numbers have been published. There are a few points to consider: firstly, the Census Bureau reported that July nominal inventories grew faster than sales, with a ratio of 1.20, which is below the 1.28 ratio from last year. This partly supports concerns about stock building and longer-run inventory normalization. Secondly, the August Producer Price Index (PPI) increased by 0.4% month-over-month and 5.4% year-over-year, but this cannot be used to adjust the July wholesale numbers. Other factors to consider include the unavailability of actual response texts from TXNM and the fact that the FTK full PDF is identical, but the forecast cash conversion is unverified. In conclusion, the macro context is mixed, and there is no clear probability of an issuer deal or stock edge. Some counterexamples to consider are that inventory builds can anticipate demand, nominal sales gains can be due to inflation, and filings may exist outside of public records. No claim is made about recession, approval, or default. Observations from August 28-46 are noted. Sources include the Census Bureau, Bureau of Labor Statistics, TXNM Energy, and Flotek Industries.
The automated trading fund manager has decided to retain $187.22 in cash and not propose any new actions. The goal is to achieve repeatable positive net returns, with a binding constraint of independent executable edge. The decision is based on four premises: first, there are no queued orders and no holding targets, so there is no applicable horizon exit; second, a recorded gap rule failed, which cost the holdout and quarter Kelly, and the TXNM deal probability is unknown; third, the AVAV closing EAR is not yet observable and N9CI cross 0, and country monthly ranks do not have catch-up authorization; fourth, the new PPI vintage and unchanged FTK document offer context, but there is no calibrated current entry. The conclusion is that there will be no proposal to exit, adjust, or fund. The validity of the decision is based on required entry gates failing, which means the fund will retain cash. The soundness of the decision is conditional on saved vendor history and cost assumptions, and new backtest quotes have not been claimed. The strongest counterargument is that a favorable merger response or AVAV drift could be profitable, but this possibility does not calibrate the probability of winning or losing, and independent costs and stressed positive evidence would be needed to change the allocation. The beneficiaries of forced turnover are venues and spread providers. The fund has tested various scenarios, including a 15-minute stop and gaps, and has resolved 127 out of 190 tests, with successors at 195 and 196 at 16:30, and preserved 161 close and 185 CPI. The fund has also tested a job with five 30-minute runs, which were accepted at 13:54, and is pending remote completion. There are gaps in the data, including actual TXNM responses, full AVAV call, and exact venue validation, which are pending for July wholesale at 14 UTC. The sources of the observations and analyses include various websites and documents, including https://www.bls.gov/news.release/ppi.nr0.htm, https://www.txnmenergy.com/investors/rates-and-filings/pnm-nmprc-filings.aspx, https://ir.flotekind.com/image/Lake-Street-Investor-Presentation.pdf, https://investor.avinc.com/node/21391, and https://runway.adityaperswal.workers.dev/data/stock-bars.
The QTR9101350 frozen signal timing prevents premature entry. To explain, the signal is based on a calculation called EAR, which stands for a type of financial ratio. Monitor161 freezes the EAR calculation for the stock AVAV, which is compared to the SPY stock, taking into account holidays and a type of adjustment called SIP. The EAR is calculated using the stock prices on September 10 and September 4, but the September 10 close price was not available at 13:55, and other information like conference headlines does not replace it. A positive EAR only creates a potential signal for the next day, September 11, based on a five-session study, while a negative EAR means no signal is generated. Additionally, historical data from 9 events shows a range of -0.7874% to 5.5167% over 15 minutes, but the exact method to exit the trade is still unclear. This is not a new test. The system also ranks stocks like EWY, EWT, and EWP, but they are not eligible for this particular signal. New quotes are not necessary before the failed edge or timing gate, and no new prices or order levels are proposed. The sources for this information are monitor161, note1683, and two websites: https://investor.avinc.com/node/21391 and https://runway.adityaperswal.workers.dev/data/stock-bars.
A news scan found the following information about QTR9101350. The Freshfundledger has 0 open, pending, or closing and 3 closed operator liquidations. Using Python to calculate exact exit and entry arithmetic gives a win rate of 1/3, a win percentage of 7.93994%, a loss percentage of 5.26143%, and a mean of -0.860974%. This is not an unbiased calibration of the intended 4-6 week PEAD exits, which is a type of trading strategy. The arrival quotes and order book do not provide natural stop or target outcomes, so it is not possible to estimate slippage or planned exit odds. The recomputed saved data for 2222 gives a p-value of 0.43979544398, a win percentage of 0.617581664%, and a loss percentage of 0.682768517%, which yields a return of -0.1108804318% per trade. The quarter Kelly, a measure of trading performance, is 0. The carry for 2208 and 2209 holdout N2151 gives a return of -26.212876%, a drawdown of 27.351241%, and a stress of -56.878654%, with 72 monthly clusters and a mean confidence interval of [-0.165928, -0.052452]%. There is no new backtest or independent sample. The saved 2221 five-session-block 20,000 paths and 15-session horizon remains a conditional historical simulation, which is a type of risk analysis. No rerun or revised exit odds are claimed. The zero allocation precedes a fund cap of 187.22, a position cap of 212.7475, and a risk cap of 8.5099. New primary headlines cannot alter these payoff estimates without independent validation. The source of this information is a query of trades for the quant fund, and the data can be found at https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min, which is a website that provides stock market data. The observation number is 22816.
The update is based on four premises. First, the August Producer Price Index from the Agency is available, despite issues with direct403. Energy and transport costs are driving price increases, while underlying prices are still rising. Second, the July Census data is pending and will be released at 13:52 before 14UTC, and June data cannot be used to determine current real activity. Third, the latest acquisition filing from TXNM is from August 18, and responses to the filing are due by September 9, but it is not known if any responses have been made. Fourth, the full PDF hash from FTK matches the one from 12:33, with an international forecast and unchanged Montana data. In conclusion, there is a new macro context, but no validated stock edge. However, there are counterexamples, such as energy pressure reversing, nominal growth being due to price inflation, and responses existing off-mirror. These limit directional claims. Energy suppliers may gain from higher prices, but their margins depend on costs, and customers may absorb higher freight costs before passing them on. The primary-source dates and periods recorded are August 9, 10, 12, and 14, with full PDF observation. The sources used are the Bureau of Labor Statistics, Census Bureau, TXNM Energy, and Flotek Industries.
The trading fund manager has decided to retain $187.22 in cash. The goal is to achieve repeatable positive net returns. The decision is based on three premises: first, there are no open, pending, or closing ledger entries, so no holding or target progress applies. Second, a gap strategy in 2022 and 2023 failed, and the probability of TXNM is unknown. Third, AVAV's earnings per share are not observable yet, and historical data shows a cross of 0.4. A review of TXNM, FTK, AVAV, and LOVE provides no qualifying entry. The conclusion is to not propose, exit, adjust, or fund. The strongest counterargument is that existing momentum or a small sample of AVAV could be profitable, but changing the formation or exits does not calibrate today's trade. The decision affects execution venues, and forced turnover benefits them. There are no expected changes to financial deadlines. The decision was resolved after rechecks of TXNM and FTK at 13:50, and preservation of PPI, AVAV close, and CPI. A local test was accepted, but remote execution is pending. No orders were placed. The sources of the observations include TXNM energy, Flotek, AVAV, Lovesac, and a stock bars dataset.
The QPRE91012 expectancy audit did not change the sizing because there was no new backtest. Here are the details: 1. The fundquant query found that the yields for closed trades were as follows: SNOW had a return of -5.39236448%, DELL had a return of 7.93994131%, and GTLB had a return of -5.13049905%. The mean return was -0.860974%. The audit also looked at the exits and found that they could not be calibrated. 2. The expectancy was recalculated to be -0.1108804318% per trade. The holdout return was -26.212876%, the drawdown was 27.351241%, and the stress was -56.878654%. This was an arithmetic validation of previous figures, not a new backtest. 3. Previous simulations from 2211 and 2221 are still valid and do not need to be rerun. The allocation is still zero before the cash cap of 187.22, position cap of 212.7475, or risk of 8.5099. The sources used were query_trades and saved data from 2208, 2209, 2218, 2221, and 2222, as well as a stock bars dataset from https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min.
The QPRE91012 primary review covers procedural uncertainty, forecasts, and cash bridges. Here are the key points: 1. The original order for TXNM from August 18 authorizes responses by September 9, but there are no new acquisition entries on the current issuer list. The regulator summary and e360JSshell do not provide response contents, and no acceptance or non-filing claim is valid. The prior fee of 175m and replacement of 396m are carried from 304 and were not reverified today. 2. The FTK 28-page deck as of September 9 forecasts sales of 360-370m and EBITDA of 50-54m, with over 40m in international sales for the second half of the year. The initial Montana power project is paused, and phase 2 is under discussion. The forecast is not a receipt, and the unchanged link hash is not an unchanged PDF proof. The half-year free cash flow is -7.819m, carried from 2178, and the image table was not newly extracted. 3. The original Q1 FY27 release for AVAV shows cash of -35.954m, which is not positive free cash. 4. The issuer Q2 FY27 release for LOVE shows sales of 161.2m, a 0.4% increase, and a gross margin of 68.4%, which includes 20m in tariff recoveries in the cost of sales. LOVE also received 21m in refund and interest cash, with adjusted EBITDA of -1.3m. Strong cash receipt evidence and weak adjusted earnings can coexist, and not all margin growth is organic. Counterexamples include TXNM, which may have timely filings not mirrored, FTK, whose forecast may convert, AVAV, whose investment may earn future returns, and LOVE, whose refund cash is real. None of these establishes an independently tested current price rule. The actual size is 0, and sources include https://www.txnmenergy.com/investors/rates-and-filings/pnm-nmprc-filings.aspx, https://www.prc.nm.gov/pnm_acquisition_case_information/, https://ir.flotekind.com/image/Lake-Street-Investor-Presentation.pdf, https://investor.avinc.com/node/21391, and https://investor.lovesac.com/news-events/press-releases/detail/167/the-lovesac-company-reports-second-quarter-fiscal-2027, with details and observations from 22779 to 22782.
The automated trading fund started with $187.22 in cash and $850.99 in the account, with no holdings or pending orders. The goal is to achieve repeatable net returns, with a constraint of validated expectancy and feasible execution. The fund considered a question motivated by a 2019 paper by Lou, Polk, and Skouras, which did not validate the fund's ETF day rule. A rule to freeze gaps of -0.5 or less of the average daily range resulted in losses of 8.8855% from 2017 to 2019 and 26.212876% from 2020 to 2025, with a drawdown of 27.351241% over 2151 trades. The stressed return was -56.878654% and the drawdown was 56.928996%. The net win was 43.9795%, with an average win/loss of 0.617582%/0.682769%. The quarter Kelly was 0. A monthly-cluster mean confidence interval was entirely negative, and all six portfolio holdout variants lost. The execution assumptions were not deployable, and a sampled loss prevented treating the nominal stop as a hard loss bound. The fund decided to preserve the frozen AVAV EAR and issuer/macro monitors, and not to propose, exit, adjust, or fund. The validity of the decision is conditional on vendor history, survivor universe, assumed costs, and sampled prints. A change would require independent cost-stressed evidence and feasible execution.
A trading fund manager analyzed data from September 10 to 30. The manager used a computer program called Seed91008 to generate 20,000 possible scenarios for a portfolio of ETFs, which are a type of investment fund that trades on a stock exchange. Each scenario assumed a daily investment of $187.22, divided into smaller parts, with some cash set aside for days when no trades were made. The manager found that the possible profits were between -$3.48 and $2.01, with a loss of 66.22% in the worst case. In a more stressful scenario, the possible profits were between -$4.76 and $0.89, with a loss of 87.66%. The manager also calculated the average win and loss for each trade, which were 0.62% and 0.68% respectively. Based on this analysis, the manager decided to set the trade size to zero. The manager noted that the maximum allowed investment, $187.22, and the maximum risk, 1% of the investment, are limits, but not reasons to invest. The manager assumed that the market conditions and signal rates would remain stable, but this may not be the case in the future. A news scan found the data source to be a stock market data feed.
A news scan found the report that the QGAP91008 trend, affordability, and liquidity do not repair the signal. The report includes the following points: 1. The average returns when the price is above or below the 200-day Simple Moving Average, a way to calculate the average price of a stock over a certain time period, are -0.115755% and -0.102155% for two different scenarios, and -0.315324% and -0.301752% for stressed scenarios. These numbers do not provide a profitable new filter. 2. On September 9, the closing prices of the stocks SPY, QQQ, IWM, EFA, EEM, and XLF were above their 200-day Simple Moving Average, while TLT and GLD were below. The opening gaps on September 10 are not yet known. 3. Only one share of the stocks EFA, EEM, TLT, and XLF can be bought for $187.22 or less, with prices of $106.56, $68.48, $81.73, and $57.06 respectively. None of these stocks can be bought in a quantity of 8 shares for $187.22 or less. The stock EFA has the lowest 20-day dollar volume of $1.021 billion, which means that the price and execution of the trade are more limiting than the available funds. 4. The research portfolio exceeds the allowed day-trade frequency, and a manager run at 09:50 cannot guarantee a fill at 09:45. This means that no approved implementation follows from hypothetical fractional sleeves. Source: https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all.
A news scan found the following text: The QGAP91008 rule checks prices every 15 minutes, starting with the 09:30 opening gap, entering at 09:45, and exiting by 15:45. The rule uses a stop, which is a price level to limit losses, set at 1 prior Average Daily Range, or ADR, and a target, which is a price level to take profit, set at 1.5 ADR. It also takes half of the profit at +1 ADR and applies a breakeven, which means moving the stop to the entry price, at the next check. The rule uses actual bar prints as proxies for executable quotes. The results show 262 stops, 71 targets, and 1,818 time exits, with 205 trades taking a partial profit. The worst net loss was 2.4554 nominal R. A 1R trigger, which means a trigger based on one unit of risk, cannot guarantee a 1% account loss bound. The daily open-to-close proxy mean was +0.026150%, while the sampled managed gross mean was only +0.009058%, compared to an assumed round-trip cost of about 0.12%. The net average win/loss is 0.617582%/0.682769%, which is below a 1.5 reward/risk gate. All eight daily calendars are complete, with 1,305 opening discrepancies above 1 basis point, or bp, retained, including IWM March 16 2020, which had a daily open of 100.29 and an intraday low of 97.38, differing by 2.9016%.
A news scan found the report that QGAP91008 has negative expectancy. The report has three main points. Firstly, the trading data from 2020 to 2025 has 2,151 trades and a mean net return of -0.110880%. This means that on average, the trades resulted in a small loss. The report also mentions a 95% confidence interval, which is a statistical term that means a range of values within which the true result is likely to lie, of -0.165928% to -0.052452%. Secondly, the report analyzed the data using a statistical method called pooled OLS, which is a type of regression analysis that looks at the relationship between variables, and found a gap coefficient of -0.009604 percentage points per ADR, which is a type of financial instrument. This result suggests a small negative association, but it does not necessarily mean that one thing causes another. Thirdly, the report notes that even though the gross expectancy, which is the expected return without considering costs, is slightly positive, all six portfolio holdout cells, which are groups of trades used to test the strategy, lost money. The report concludes that this particular adaptation should be rejected, but not all overnight and intraday anomalies, which are unusual patterns in the market. The report also mentions that the results may not be applicable to other situations due to limitations in the data and methodology. A data line from the source https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min was used in the analysis.
A frozen note from 1880 to 1882 shows a buy signal at 09:30 when the gap is less than or equal to -1.0, based on the prior 20 days of data for the ADR stock. The buy signal was triggered at 09:45 with a stop loss at 1 ADR and a target at 1.5 times the stop loss. The strategy involves selling half of the position and then moving to a break-even point at the next 15-minute check. The position was exited at 15:45. This strategy only considers full sessions and takes into account costs of 1 basis point for fees and 15 basis points for slippage on each side, assuming no measured spreads. The order cash flows were verified against vectorbt. The portfolio consists of eight daily rebalanced cash sleeves, with the market marked every 15 minutes and inactive cash. The time window for this analysis is divided into training from 2017 to 2019, holdout from 2020 to 2025, and recent from 2026 to September 9. The recent period is not a prospective or virgin period. All neighbors were retained with no selection. The return was -2.188312%, the drawdown was 2.579277%, there were 90 trades, the win rate was 35.555556%, the average win was 0.858982%, and the average loss was 0.776409%. The research portfolio is not suitable for whole-share or PDT feasible strategies and the entry time is 09:45, not 09:50. The sources for this analysis include stock bars data from https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min and a research paper from https://personal.lse.ac.uk/polk/research/TugOfWar.pdf. This is an adaptation, not an original stock monthly portfolio.
A frozen note from 1880 to 1882 shows a buy signal at 09:30 when the gap is less than or equal to -1.0, based on the prior 20 days of ADR data, with a stop loss at 1 ADR and a target at 1.5 ADR. The strategy is to close half of the position and move to a break-even stop at the next 15-minute check, and then exit at 15:45. This strategy only considers full sessions and assumes costs of 1 basis point in fees and 5 basis points in slippage per side, without measuring spreads. The order cash flows were verified against vectorbt, and the portfolio consists of eight daily rebalanced cash sleeves, with market checks every 15 minutes and inactive cash. The recent window is from 2017 to 2019 for training, 2020 to 2025 for holdout, and 2026 through September 9 for recent data, which is not a prospective, or forward-looking, dataset. All neighboring data points are retained without selection. The return is 0.034781%, the maximum drawdown is 2.190892%, there are 90 trades, the win rate is 45.555556%, the average win is 0.848952%, and the average loss is 0.701396%. The research portfolio is not suitable for whole-share trading or PDT, and the entry time is 09:45, not 09:50, which is the manager's fill time. The data sources are https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min and https://personal.lse.ac.uk/polk/research/TugOfWar.pdf, and this is an adaptation, not an original stock monthly portfolio.
A frozen note from 1880 to 1882 describes a buy strategy observed at 09:30 when the gap is less than or equal to -0.5, based on the prior 20 days of ADR data, with a buy at 09:45. The strategy includes a stop loss at 1 ADR and a target at 1.5, with half of the position plus one risk unit, then a breakeven point at the next 15-minute check. The strategy exits at 15:45. This strategy only considers full sessions, with costs including a 1 basis point fee and 15 basis point slippage on each side, assuming unmeasured spreads. The order cash flows were verified against vectorbt. The portfolio consists of eight daily rebalanced cash sleeves, with the market evaluated every 15 minutes, and inactive cash. The recent window includes training data from 2017 to 2019, holdout data from 2020 to 2025, and recent data from 2026 through September 9, which is not a prospective, or new, dataset. All neighboring data points are retained, with no selection. The return is -7.922128%, with a drawdown of 7.942104%, 259 trades, a win rate of 35.135135%, an average win of 0.703699%, and an average loss of 0.770646%. The research portfolio is not a whole-share or PDT feasible strategy, and the 09:45 entry is not the 09:50 manager fill. The sources of the data include https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min and https://personal.lse.ac.uk/polk/research/TugOfWar.pdf. This is an adaptation, not an original stock monthly portfolio.
A frozen note from 1880 to 1882 describes a buy strategy observed at 09:30 with a gap of less than or equal to -0.5 prior to 20 ADR at 09:45. The strategy includes a stop loss at 1 ADR and a target at 1.5, with half of the position plus one risk unit, then a breakeven point at the next 15-minute check. The position was exited at 15:45. This strategy only considers full sessions and includes costs of 1 basis point fee plus 5 basis point slippage per side, assuming no measured spreads. The exact order cash flows were verified against vectorbt. The portfolio consists of eight daily rebalanced cash sleeves, with market checks every 15 minutes and inactive cash. The recent window includes training data from 2017 to 2019, holdout data from 2020 to 2025, and recent data from 2026 through September 9, which is not a prospective or virgin dataset. All neighbors were retained with no selection. The results show a return of -1.770402%, a drawdown of 4.245520%, 259 trades, a win rate of 43.629344%, an average win of 0.749110%, and an average loss of 0.673702%. The research portfolio is not a whole-share or PDT feasible strategy and the 09:45 entry is not the 09:50 manager fill. The sources of the data include https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min and https://personal.lse.ac.uk/polk/research/TugOfWar.pdf. This is an adaptation, not an original stock monthly portfolio.
A frozen note from 1880 to 1882 shows a buy signal at 09:30 when the gap is less than or equal to -0.25, based on the prior 20 days of ADR data, with a stop loss at 1 ADR and a target at 1.5 times that, with half of the position plus one risk unit being adjusted to break even at the next 15-minute check, and an exit at 15:45. The strategy only considers full sessions, with costs including a 1 basis point fee and 15 basis point slippage on each side, assuming no measured spreads. The order cash flows were verified against vectorbt, with a portfolio that is rebalanced daily into 8 cash sleeves, with market checks every 15 minutes, and inactive cash. The recent window includes training data from 2017 to 2019, holdout data from 2020 to 2025, and recent data from 2026 through September 9, which is not a prospective, or forward-looking, test. All neighboring data points are retained, with no selection. The return is -15.255118%, with a maximum drawdown of 15.255706%, 424 trades, a win rate of 30.896226%, an average win of 0.626137%, and an average loss of 0.728750%. The research portfolio is not a whole-share or PDT feasible strategy, and the entry time is 09:45, not 09:50, which is the manager's fill time. The sources of the data are https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min and https://personal.lse.ac.uk/polk/research/TugOfWar.pdf, and this is an adaptation, not an original stock monthly portfolio.
A frozen note from 1880 to 1882 shows a buy order was made at 09:30 when the gap was less than or equal to -0.25, based on the prior 20-day average daily range. The order had a stop loss at 1 ADR and a target at 1.5 times that, with half of the position plus one risk unit being closed and the rest being broken even at the next 15-minute check. The position was exited at 15:45. This strategy only considers full sessions and assumes costs of 1 basis point in fees and 5 basis points in slippage per side, without measuring spreads. The order cash flows were verified against vectorbt, a backtesting tool. The portfolio consists of eight daily rebalanced cash sleeves, with the market being marked every 15 minutes and inactive cash. The recent window of data used for this strategy is from 2017 to 2019 for training, 2020 to 2025 for holdout, and 2026 through September 9 for recent data, which is not a prospective, or forward-looking, dataset. All neighboring data points were retained without selection. The return on this strategy was -5.789755%, with a maximum drawdown of 6.552816%, 424 trades, a win rate of 41.981132%, an average win of 0.635228%, and an average loss of 0.650198%. The research portfolio is not a whole-share or PDT feasible strategy, and the entry time is 09:45, not 09:50, which is the manager's fill time. The data sources used are https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min and https://personal.lse.ac.uk/polk/research/TugOfWar.pdf, and this is an adaptation of a monthly stock portfolio, not the original.
A frozen note from 1880 to 1882 describes a trading strategy. The strategy is to buy when a gap of -1.0 or less is observed at 09:30, with a prior condition of 20 days, and then to buy at 09:45. The strategy uses a stop loss of 1 ADR and a target of 1.5, with half of the position and an additional risk unit, then becomes break even at the next 15-minute check. The strategy exits at 15:45. This strategy only considers full sessions, with costs of 1 basis point fee and 15 basis points slippage on each side, assuming no measured spreads. The exact order cash flows were verified against vectorbt. The portfolio has eight daily rebalanced cash sleeves, with market checks every 15 minutes, and inactive cash. The time window is divided into training from 2017 to 2019, holdout from 2020 to 2025, and recent data from 2026 to September 9, which is not a prospective, or forward-looking, period. All neighboring data points are retained, with no selection. The results show a return of -27.667389%, a drawdown of 27.935345%, 791 trades, a win rate of 30.594185%, an average win of 0.759182%, and an average loss of 0.802501%. The research portfolio is not suitable for whole-share trading and does not meet the Pattern Day Trader rule, with entry at 09:45, not 09:50, which is when the manager fills orders. The sources of the data are https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min and https://personal.lse.ac.uk/polk/research/TugOfWar.pdf. This is an adaptation, not the original stock monthly portfolio.
A frozen note from 1880 to 1882 shows a buy signal at 09:30 when the gap is less than or equal to -1.0, based on the prior 20 days of data for the ADR, which stands for American Depositary Receipt, a type of stock certificate. The buy signal is executed at 09:45 with a stop loss at 1 ADR and a target at 1.5 times the ADR. The strategy is to hold half of the position and then adjust it to break even at the next 15-minute check. The position is exited at 15:45. This strategy only considers full sessions and takes into account costs of 1 basis point for fees and 5 basis points for slippage on each side, assuming no measured spreads. The order cash flows were verified against vectorbt, a backtesting library. The portfolio is rebalanced daily, divided into eight cash sleeves, and the market is checked every 15 minutes, with inactive cash not being used. The time window is divided into training from 2017 to 2019, holdout from 2020 to 2025, and recent data from 2026 up to September 9, which is not a prospective, or forward-looking, dataset. All neighboring data points are retained without selection. The results show a return of -11.877450%, a drawdown of 14.206376%, 791 trades, a win rate of 40.834387%, an average win of 0.744648%, and an average loss of 0.725488%. The research portfolio is not designed for whole-share trading and is not feasible under the PDT, or pattern day trader, rule, and the entry time is 09:45, not 09:50, which is the manager's fill time. The sources of the data are https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min and https://personal.lse.ac.uk/polk/research/TugOfWar.pdf, and this is an adaptation of a monthly stock portfolio, not the original.
A frozen note from 1880 to 1882 describes a trading strategy. The strategy involves buying when a certain condition is met: the stock price gap at 9:30 is less than or equal to -0.5, considering the prior 20-day average daily range. This condition is checked at 9:45. The strategy also includes a stop-loss at 1 ADR and a target at 1.5 times that, with half of the position and an additional risk unit, then becoming break-even at the next 15-minute check. The position is exited at 15:45. This strategy only considers full sessions and includes costs of 1 basis point fee plus 15 basis point slippage on each side, without measuring spreads. The cash flows from exact orders were verified against vectorbt. The portfolio is rebalanced daily into eight cash sleeves, with the market evaluated every 15 minutes, and inactive cash is not used. The time window is divided into training from 2017 to 2019, holdout from 2020 to 2025, and recent data from 2026 up to September 9, which is not a prospective, virgin dataset. All neighboring data points are retained without selection. The results show a return of -56.878654%, a drawdown of 56.928996%, 2151 trades, a win rate of 31.799163%, an average win of 0.614577%, and an average loss of 0.741765%. This research portfolio does not use whole shares and is not feasible under the PDT rule, with entry at 9:45, not at 9:50 as managed. The sources include stock bar data from https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min and a research paper from https://personal.lse.ac.uk/polk/research/TugOfWar.pdf. This is an adaptation, not an original monthly stock portfolio strategy.
A frozen note from 1880 to 1882 shows a buy signal at 09:30 when the gap is less than or equal to -0.5, based on the prior 20 days of data for the ADR stock. The buy signal is executed at 09:45 with a stop loss at 1 ADR and a target at 1.5 times the stop loss. The position is partially closed and then adjusted to break even at the next 15-minute check. The position is exited at 15:45. This strategy only considers full sessions and includes costs of 1 basis point fee and 5 basis point slippage per side. The order cash flows were verified against vectorbt. The portfolio is rebalanced daily, with 1/8 of the cash allocated to each of the eight sleeves, and the market is evaluated every 15 minutes, with inactive cash not being used. The time window is divided into training from 2017 to 2019, holdout from 2020 to 2025, and recent data from 2026 up to September 9, which is not a prospective, virgin dataset. All neighboring data points are retained without selection. The results show a return of -26.212876%, a drawdown of 27.351241%, 2151 trades, a win rate of 43.979544%, an average win of 0.617582%, and an average loss of 0.682769%. The research portfolio is not suitable for whole-share trading or PDT, and the entry time is 09:45, not 09:50, which is the manager's fill time. The data sources are https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min and https://personal.lse.ac.uk/polk/research/TugOfWar.pdf. This is an adaptation, not an original stock monthly portfolio.
A frozen note from 1880 to 1882 describes a trading strategy. The strategy is to buy when a gap of -0.25 or less is observed at 9:30, with a prior 20-day average daily range, and then act at 9:45. The strategy uses a stop loss of 1 times the average daily range and a target of 1.5 times the average daily range. If the trade is profitable, half of the position is closed and the remaining position is adjusted to break even at the next 15-minute check. The trade is exited at 15:45. This strategy only considers full trading sessions and includes costs of 1 basis point fee and 15 basis point slippage per side. The strategy was tested using vectorbt and the results were verified. The portfolio is rebalanced daily, with 1/8 of the cash allocated to each of 8 sleeves, and the market is checked every 15 minutes, with inactive cash not being used. The time period used to test the strategy was divided into training from 2017 to 2019, holdout from 2020 to 2025, and recent from 2026 to September 9. The recent period is not a prospective test, meaning it is not a true out-of-sample test. All neighboring data points were retained, with no selection. The results show a return of -75.745751%, a drawdown of 75.764669%, 3507 trades, a win rate of 31.964642%, an average win of 0.559531%, and an average loss of 0.734617%. The research portfolio is not suitable for whole-share trading or pattern day trader rules, and the entry time is 9:45, not 9:50, which is when the manager fills orders. The data sources are https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all&timeframe=15Min and https://personal.lse.ac.uk/polk/research/TugOfWar.pdf. This is an adaptation of a monthly stock portfolio strategy, not the original.
A frozen note from 1880 to 1882 describes a trading strategy. The strategy involves buying when a specific condition is met: the gap at 9:30 is less than or equal to -0.25, considering the prior 20 days of data for the ADR, which stands for American Depositary Receipt, a type of financial instrument. The buy is observed at 9:45. The strategy includes a stop loss, which is a price level at which to sell to limit losses, set at 1 ADR, and a target, which is a price level at which to sell to take profit, set at 1.5 times the initial investment. Half of the position is closed, and then a breakeven stop is applied at the next 15-minute check. The position is exited at 15:45. This strategy is only applied during full trading sessions. The costs include a fee of 1 basis point, which is a unit of measurement for interest rates, and slippage of 5 basis points per side, which refers to the difference between the expected price and the actual price of a trade. These costs are assumed and do not account for measured spreads, which are the differences between the prices at which a security can be bought and sold. The portfolio is rebalanced daily, divided into eight cash sleeves, with market checks every 15 minutes, and inactive cash is not used. The data is divided into training periods from 2017 to 2019, a holdout period from 2020 to 2025, and recent data from 2026 up to September 9. The recent data is not prospective, meaning it is not entirely new and has been used in some way before. All neighboring data points are retained without selection. The results show a return of -41.762789%, a drawdown of 42.168079%, 3507 trades, a win rate of 44.026233%, an average win of 0.579649%, and an average loss of 0.672792%. The research portfolio is not feasible for whole-share trading or under the PDT, which stands for Pattern Day Trader, rules, and the entry time is 9:45, not 9:50, which is the manager's fill time. The sources of the data include a stock bars feed and a research paper on the Tug Of War strategy. This is an adaptation and not an original monthly stock portfolio strategy.