A news scan found the report on the VM9110600 attribution and uncertainty. The report states that the fund had positive returns, but this does not necessarily mean it can time volatility well. The fund's performance is based on several premises. Firstly, the primary SPY stress adapter had a return of 5.5575% from 2019 to 2022 and 32.3755% from 2023 to August 26, with 48 out of 44 trades being successful. Secondly, the raw trade mean was 0.62035% and 0.84966%, with a 95% confidence interval of -0.59212% to 1.80894% and -0.20030% to 1.78505% for the three-month moving-block mean. The capital-weighted fund monthly confidence interval was -0.39509% to 0.64125% and -0.20727% to 1.52007%. Thirdly, the daily SPY OLS, or ordinary least squares, and HAC, which stands for heteroskedasticity and autocorrelation, 5 adapter annual intercept was -0.90499% during training and 0.21390% during the holdout period, with a holdout beta of 0.36583. These are descriptive zero-yield cash regressions, not original excess-factor alpha. Fourthly, the continuous monthly managed stress holdout was 72.7201% with a drawdown of 12.6491% and a Sharpe ratio of 1.33907, while the constant was 89.0037% with a drawdown of 16.3501% and a Sharpe ratio of 1.41453. The managed-minus-constant mean was -0.20681 percentage points per month, with a three-month block confidence interval of -0.53573 to 0.08946. Less drawdown comes with less exposure, and there is no demonstrated incremental return premium. Fifthly, the external stress adapter had returns of -19.2499% and 4.2771% for EFA, -24.7622% and 12.8840% for EEM, -16.3080% and -14.8836% for TLT, and 8.5946% and 37.2622% for GLD, with no promotion of GLD. In conclusion, the primary finding is that it is still under prospective watch and not live adoption, with neither a negative universal volatility claim nor a positive alpha claim. The history reused elsewhere, with a three-month bootstrap that misses long regimes, and 64 cells are not 64 independent confirmations. The sources of the data are https://runway.adityaperswal.workers.dev/data/stock-bars, research/results.json, and inference.json, with a fixed 2230.
This is a test of the VM9110600 GLD adapter, which is a tool used to connect and analyze data, specifically a type of financial data called a gold exchange-traded fund, or GLD. The test used a set of rules, called Protocol 2230, with some corrections made in 2233 and 2236. The test looked at data from January 3, 2023, to August 31, 2026, and used data from 2016 to 2018 to calibrate the system, and data from 2019 to 2022 to train it, with a holdout period from 2023 to August 26. The test entered the market monthly, with a limit on how much it could lose, and stopped trading when it lost a certain amount, which is measured in a unit called ATR, or average true range, and also had a target to make a certain amount, which is 6 times the ATR, and an extra 4 ATR for each quarter, with the goal of making a profit by the end of the month. The test also accounted for fees, which were 1 basis point, or 1/100th of a percent, per trade, and a slip of 15 basis points, and assumed that cash had a yield of 0. The results showed a return of 37.26 percent, with a maximum loss of 9.46 percent, and a win rate of 52.27 percent, over 44 months, with 44 trades. The test used a tool called vectorbt for daily reconciliation, which means checking the results every day, and found a maximum error of 3.637978807091713e-12, which is a very small number, with an initial investment of 10,000 units. The test did not validate the results over a 15-minute period or for whole shares, and used a dividend-adjusted proxy, which means it accounted for dividend payments, and did not touch the underlying data. The test was used as a diagnostic instrument, and did not promote a winning strategy. The data came from a source at https://runway.adityaperswal.workers.dev/data/stock-bars, and the results can be found in a file called research/test_vm.py/results.json, which is a type of file that stores data in a format called JSON.
The Protocol 2230 with corrections 2233 and 2236 was used from January 2, 2019, to December 30, 2022, with calibration from 2016 to 2018 and training from 2019 to 2022, holding out data until August 26, 2023. The monthly entry was based on prior variance capped at 1, with a stop at 2 Average True Range (a measure of price volatility) and a target at 6 Average True Range, plus 4 Average True Range per quarter, and the next day's break-even point, with a month-end exit. Fees were 1 basis point (a unit of measurement for interest rates) per side, with a 15 basis point slip, and a cash yield of 0. The return was 8.594624456479094 percent, with a drawdown of 12.863200967894684 percent, a win rate of 47.91666666666667 percent, and 48 trades over 48 months. The vectorbt daily reconciliation had a maximum error of 3.637978807091713e-12 at 10,000 initial units. There was no 15-minute or whole-share validation, and the data used was dividend-adjusted, with a proxy for survivorship bias, and the history was not globally untouched. This was a diagnostic instrument, with no promotion of winning strategies. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the research results are from research/test_vm.py/results.json.
This is a test of the VM9110600 GLD adapter, which is a tool used to connect and manage data. The test used a set of rules, called Protocol 2230, with some corrections made in 2233 and 2236. The test looked at data from January 3, 2023, to August 31, 2026, and used data from 2016 to 2018 to calibrate the system, and data from 2019 to 2022 for training, with a holdout period from 2023 to August 26. The system made trades at the start of each month, with a limit on how much it could lose, and stopped trading if it lost too much, with a target of making six times the amount of a common measure of market volatility, called ATR. The system also had rules to exit trades at the end of each month. The test included fees of 1 basis point to buy and 5 basis points to sell, and assumed that cash did not earn any interest. The results showed a return of 43.29%, with a maximum loss of 8.48%, and 52.27% of trades were winners, out of 44 trades over 44 months. The test also checked the accuracy of the system, with a maximum error of 3.637978807091713e-12, using an initial investment of 10,000 units. The test did not validate the results against 15-minute data or whole-share data, and used a proxy that was adjusted for dividends, with a note that the data may not be perfect. The test was run as a diagnostic tool, without promoting any winning strategies. The data came from https://runway.adityaperswal.workers.dev/data/stock-bars, and the results can be found in research/test_vm.py/results.json.
This is a description of an automated trading system. The system uses a protocol called Protocol2230 with corrections 2233 and 2236. It was calibrated using data from 2016 to 2018 and trained on data from 2019 to 2022, with a holdout period from 2023 to August 26. The system enters a trade monthly, with a position size capped at 1 times the prior variance. It stops trading at 2 times the average true range, with a target of 6 times the average true range, and adds 4 times the average true range to the next day's closing price. The system exits at the end of the month. The fees are 1 basis point per trade, with a 5 basis point slip per side, and the cash yield is 0. The return is 13.220439532381523 percent, with a maximum drawdown of 13.176694279509316 percent, and a win rate of 47.91666666666667 percent, over 48 months. The system uses a daily reconciliation with a maximum error of 3.637978807091713e-12, at an initial investment of 10000 units. The system does not validate 15-minute or whole-share data, and uses a dividend-adjusted proxy, with survivorship bias, and a history that has not been globally untouched. This is a diagnostic instrument, and there is no promotion of winning trades. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the research and test results are from research/test_vm.py/results.json.
This is a report on a test of the VM9110600 GLD strategy, which uses a protocol called Protocol2230 with corrections from 2233 and 2236. The test ran from January 3, 2023, to August 31, 2026, and was calibrated using data from 2016 to 2018 and trained on data from 2019 to 2022, with a holdout period from 2023 to August 26. The strategy rebalances on the first monthly open and has a constant calibration exposure, with terminal liquidation. The test looked at the win frequency of the strategy separately each month, and applied fees of 1 basis point per side, with a 15 basis point slip, and assumed a cash yield of 0. The return on investment was 117.6517761730966 percent, with a maximum drawdown of 23.90681734597957 percent, and a win rate of 100 percent over 44 months. The test used a daily reconciliation with a maximum error of 0, and started with 10,000 initial units. The test did not validate the results over 15-minute intervals or whole shares, and used a dividend-adjusted proxy, with survivorship bias, and a history that was not globally untouched. This test is a diagnostic instrument and does not promote any winning strategy. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars, and the research results can be found in research/test_vm.py/results.json. A news scan found the headline was not available, this is a raw script output.
This is a description of an automated trading fund manager's notes. The protocol used is Protocol 2230 with corrections 2233 and 2236. The time period for this data is from January 2, 2019, to December 30, 2022, with calibration done from 2016 to 2018 and training from 2019 to 2022, and holdout from 2023 to August 26. The fund is rebalanced on the first monthly open with constant calibration exposure and terminal liquidation. The position is labeled as N1, and the monthly win frequency is calculated separately. The fees are 1 basis point per side, with a 15 basis point slip, and the cash yield is 0. The return is 34.92247805890547 percent, with a drawdown of 19.745224675675132 percent, and a win rate of 100 percent over 48 months. The vectorbt daily reconciliation has a maximum error of 0 at 10,000 initial units. There is no 15-minute or whole-share validation, and the data is dividend-adjusted and subject to survivorship bias, but the history has not been globally untouched. This is a diagnostic instrument, and there is no winner promotion. The source of this data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the research and test results are from research/test_vm.py/results.json.
This is a report on a test of the VM9110600 GLD strategy, which uses a protocol called Protocol2230 with corrections 2233 and 2236. The test ran from January 3, 2023, to August 31, 2026, using data from 2016 to 2018 for calibration and from 2019 to 2022 for training, with a holdout period from 2023 to August 26. The strategy rebalances on the first monthly open with constant calibration exposure and terminal liquidation. The test tracked the position, monthly win frequency, and other metrics separately. It applied fees of 1 basis point per side and a 5 basis point slip, with a cash yield of 0. The results showed a return of 118.07085269270567% and a drawdown of 23.903175817429066%, with a win rate of 100% over 44 months. The test used a daily reconciliation with a maximum error of 0 at 10,000 initial units. The data did not include 15-minute or whole-share validation, but used a dividend-adjusted proxy and accounted for survivorship bias, without globally untouched history. This is a diagnostic instrument and does not promote a winning strategy. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars and the research results are in research/test_vm.py/results.json. A news scan found the source to be a JSON output.
This is a description of an automated trading fund manager's notes. The protocol used is Protocol 2230 with corrections 2233 and 2236, which was applied from January 2, 2019, to December 30, 2022, after being calibrated from 2016 to 2018 and tested from 2019 to 2022, with a holdout period from 2023 to August 26. The fund was rebalanced on the first monthly open with constant calibration exposure and terminal liquidation. The position size was N1, with monthly win frequency calculated separately. The fees were 1 basis point per side, with a 5 basis point slip, and cash had a 0 yield. The return was 35.18074489362362 percent, with a drawdown of 19.73934171175278 percent, and a win rate of 100 percent over 48 months. The fund used a daily reconciliation with a maximum error of 0 at 10,000 initial units. There was no 15-minute or whole-share validation, and the data used was dividend-adjusted and subject to survivorship bias, but the history was not globally untouched. This was a diagnostic instrument, and there was no winner promotion. The data source was https://runway.adityaperswal.workers.dev/data/stock-bars, and the research was based on the file research/test_vm.py/results.json.
A news scan found the headline is not available, but a data line was found. The data line describes a test of a trading strategy called VM9110600 on the GLD stock from 2023-01-03 to 2026-08-31, using data from 2016 to 2018 for calibration and 2019 to 2022 for training, with a holdout period from 2023 to August 26. The strategy uses a protocol called Protocol2230 with corrections 2233 and 2236. The test was run with a monthly rebalance, where the first monthly open is used to rebalance the portfolio, with a capped prior variance of 1. The strategy also includes terminal liquidation, which means selling all assets at the end of the test. The test tracked the win frequency, which is the number of times the strategy made a profit, separately for each position, referred to as PositionN1. The fees for the strategy were 1 basis point, or 0.01%, per side, with an additional 15 basis points, or 0.15%, for the slip, which is the difference between the expected and actual price of a trade, and a cash yield of 0, meaning the strategy did not earn any interest on its cash holdings. The return on investment was 82.09329801816475%, with a maximum drawdown, which is the largest loss from peak to trough, of 10.650372817766629%, and a win rate of 100%. The strategy was tested over 44 months, with a daily reconciliation, which is a process of checking the strategy's performance, and a maximum error of 0, using 10,000 initial units. The test did not include validation of 15-minute intervals or whole-share validation, and used a dividend-adjusted proxy, which takes into account the dividends paid by the stock, and accounted for survivorship bias, which is the tendency of successful stocks to remain in the test, and did not use a globally untouched history, which means the test used real historical data. The test was run as a diagnostic instrument, and did not promote a winning strategy. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the research was conducted using the file research/test_vm.py/results.json.
This is a report on a trading strategy called VM9110600 GLD. The strategy was tested using data from 2016 to 2022 and then applied from 2019 to 2022, with the remaining period held out for testing. The strategy was rebalanced on the first day of each month, with a cap on prior variance. The strategy had a return of 22.780768644632985% and a drawdown of 17.556571194272973%. The strategy won 100% of the time over 48 months. The fees were 1 basis point per side, with an additional 15 basis points for slippage. The cash yield was 0. The strategy was tested using a daily reconciliation with a maximum error of 7.275957614183426e-12. The test used 10,000 initial units. The data used was dividend-adjusted and included survivorship bias, but was not globally untouched. The strategy was not validated for 15-minute intervals or whole-share trading. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars and the results can be found in research/test_vm.py/results.json.
This is a report on a trading test called VM9110600 GLD. The test used a set of rules called Protocol2230 with some corrections, which were made on specific dates. The test was run from January 3, 2023, to August 31, 2026, using data from 2016 to 2018 to calibrate the system and data from 2019 to 2022 for training, with the remaining data held out for testing until August 26, 2023. The test rebalanced its portfolio on the first day of each month, using a method that considers past volatility, with a cap on how much it can change. The test also had a rule to liquidate everything at the end of the test. It tracked the frequency of winning months separately for each position. The test charged a fee of 1 basis point for management and 5 basis points for each trade, with cash having a 0% yield. The results showed a return of 84.12249185590099% with a maximum drawdown of 10.591120908468277%, and 100% of the months were winning months out of 44 months. The test used a daily check to ensure accuracy, starting with 10,000 units, and did not validate its results against 15-minute data or whole-share data. It used a method to adjust for dividends and ensured that the data used was consistent over time, without globally untouched history. This test was used as a diagnostic tool and did not promote any winning strategy. The data source is https://runway.adityaperswal.workers.dev/data/stock-bars, and the results can be found in research/test_vm.py/results.json.
This is a report on the performance of the VM9110600 GLD monthly trading strategy. The strategy was tested using historical data from 2016 to 2022, with the years 2016-2018 used for calibration and 2019-2022 used for training, and the period from 2023 to August 26 used as a holdout period. The strategy uses a protocol called Protocol2230 with corrections 2233 and 2236. The strategy rebalances on the first monthly open, with a capped prior variance of 1, and terminal liquidation. The position size is denoted as N1, and the monthly win frequency is calculated separately. The fees for the strategy are 1 basis point per side, with a 5 basis point slip, and cash has a 0 yield. The return for the strategy is 24.385365922605274 percent, with a drawdown of 17.386666203685543 percent, and a win rate of 100 percent over 48 months. The strategy was tested using vectorbt daily reconciliation, with a maximum error of 7.275957614183426e-12 at 10000 initial units. The data used for the strategy does not include 15-minute or whole-share validation, and is dividend-adjusted and subject to survivorship bias, with the history not globally untouched. This is a diagnostic instrument, and there is no winner promotion. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the research and test results can be found in research/test_vm.py/results.json.
This is a test of the TLT adapter, specifically the slip15 scale1 configuration. The test used a protocol with corrections from 2230, 2233, and 2236, and was run from January 3, 2023, to August 31, 2026, with calibration from 2016 to 2018 and training from 2019 to 2022, and a holdout period from 2023 to August 26. The test entered the market monthly, with a capped prior variance of 1, and used a stop loss of 2 ATR and a target of 6 ATR, with an additional 4 ATR added quarterly and a next-day break-even point, and exited at the end of each month. The fees were 1 basis point per side, with a 15 basis point slip, and a cash yield of 0. The return was -14.88%, with a drawdown of 18.09%, and a win rate of 38.64%, over 44 months, with 44 trades. The test was run using vectorbt, with daily reconciliation and a maximum error of 1.8189894035458565e-12, at an initial unit size of 10,000. The test did not include 15-minute or whole-share validation, and used a dividend-adjusted proxy, with survivorship bias, and a history that was not globally untouched. This is a diagnostic instrument, and there is no winner promotion. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the research was conducted using the test_vm.py script, with results stored in results.json.
The trading protocol used corrections 2233 and 2236. The data used was from January 2, 2019, to December 30, 2022, with calibration from 2016 to 2018 and a holdout period from 2023 to August 26. The monthly entry was based on prior variance capped at 1, with a stop at 2 Average True Range (a measure of price volatility) and a target at 6 Average True Range, plus 4 Average True Range for the next quarter, and a buy exit at the end of the month. Fees were 1 basis point (a unit of measurement for interest rates) per side, with a 15 basis point slip, and a cash yield of 0. The return was -16.31%, with a drawdown of 19.12%, a win rate of 27.08%, and 48 trades over 48 months. The vectorbt daily reconciliation had a maximum error of 3.637978807091713e-12 at 10,000 initial units. There was no 15-minute or whole-share validation, and the data used was dividend-adjusted and subject to survivorship bias (the tendency for successful companies to be overrepresented in historical data), but the history was not globally untouched. This was a diagnostic instrument, with no winner promotion. The source of the data was https://runway.adityaperswal.workers.dev/data/stock-bars, and the research was based on the test_vm.py/results.json file.
A test of the VM9110600 TLT adapter was conducted using the Protocol 2230 with corrections 2233 and 2236. The test period was from 2023-01-03 to 2026-08-31, with calibration from 2016 to 2018 and training from 2019 to 2022, and a holdout period from 2023 to August 26. The test used a monthly entry strategy with a prior variance cap of 1 and a stop loss of 2 Average True Range (ATR), with a target of 6 ATR and a quarter adjustment of +4 ATR, and a next-day break-even point and month-end exit. The fees were 1 basis point per side, with a 5 basis point slip and a cash yield of 0. The results showed a return of -9.23425662628673% and a drawdown of 15.754348610633851%, with a win rate of 40.909090909090914% over 44 months and 44 trades. The test used vectorbt for daily reconciliation, with a maximum error of 1.8189894035458565e-12 at 10,000 initial units. The test did not include 15-minute or whole-share validation, and used a dividend-adjusted proxy, with survivorship bias and a non-globally untouched history. The test was a diagnostic instrument and did not promote a winning strategy. The data source was https://runway.adityaperswal.workers.dev/data/stock-bars and the research results were from research/test_vm.py/results.json.
A news scan found the headline is not available, but a data line was found. The data line describes a trading protocol called Protocol2230 with corrections 2233 and 2236. The trading period was from January 2, 2019, to December 30, 2022, with calibration from 2016 to 2018 and a training period from 2019 to 2022, holding out until August 26, 2023. The protocol allowed for monthly entry with a capped prior variance of 1 and a stop loss of 2 ATR, or Average True Range, which is a measure of price volatility, with a target of 6 ATR, and an additional 4 ATR for the next quarter, with a next-day break-even point and a month-end exit. The fees were 1 basis point, or 0.01%, for each side of the trade, with an additional 5 basis points for slippage, which is the difference between the expected and actual price of a trade, and a cash yield of 0. The return was -11.494672649605132% with a drawdown, or maximum loss, of 17.750262144248484%, a win rate of 29.166666666666668%, and 48 trades over 48 months. The vectorbt daily reconciliation, which is a process of comparing and adjusting trading records, had a maximum error of 3.637978807091713e-12 at 10,000 initial units. There was no validation for 15-minute or whole-share trades, and the data used a dividend-adjusted proxy, which is a way of accounting for dividend payments, and included survivorship bias, which is the tendency for successful trades to be more visible, with a history that was not globally untouched. The instrument was used for diagnostic purposes only, with no promotion of winning trades. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars and the research/test_vm.py/results.json file.
A news scan found the headline is not available, but a data line was found. The data line describes a test of a trading strategy called VM9110600 TLT constant test slip15 scale1. The test used a protocol called Protocol2230 with corrections 2233 and 2236, and it ran from January 3, 2023, to August 31, 2026. The test was calibrated using data from 2016 to 2018 and trained on data from 2019 to 2022, with a holdout period from 2023 to August 26. The test rebalanced its portfolio on the first day of each month, using a constant calibration exposure, and it liquidated its positions at the end of the test. The test reported a return of -6.074126769098475% and a drawdown of 20.392947490245728%. The test also reported a win frequency of 0% and a total of 44 months. The test used a fee of 1 basis point per side, with a slip of 15 basis points, and it assumed a cash yield of 0%. The test was run using a daily reconciliation with a maximum error of 0, and it started with 10,000 initial units. The test did not validate its results using 15-minute or whole-share data, and it used a dividend-adjusted proxy and accounted for survivorship bias. The test was run as a diagnostic instrument, and it did not promote any winning strategies. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the results are available in research/test_vm.py/results.json.
This is a report on an automated trading fund manager's notes. The protocol used is Protocol 2230 with corrections 2233 and 2236, which were applied from January 2, 2019, to December 30, 2022. The data was calibrated from 2016 to 2018 and used to train the model from 2019 to 2022, with a holdout period from 2023 to August 26. The fund was rebalanced on the first monthly open with constant calibration exposure and terminal liquidation. The position size was N1, and the monthly win frequency was calculated separately. The fees were 1 basis point per side, with a 15 basis point slip, and the cash yield was 0. The return was -10.4546 percent, with a drawdown of 40.629 percent, and a win rate of 0 percent over 48 months. The model used vectorbt for daily reconciliation with a maximum error of 0 at 10,000 initial units. There was no validation for 15-minute or whole-share trades, and the data was dividend-adjusted and subject to survivorship bias, but the history was not globally untouched. This is a diagnostic instrument, and there is no winner promotion. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the research results are from research/test_vm.py/results.json.
A news scan found the text describing a test of a trading strategy called VM9110600 TLT constant test slip5 scale1. The test used a protocol called Protocol2230 with corrections 2233 and 2236, and it ran from January 3, 2023, to August 31, 2026. The test was calibrated using data from 2016 to 2018 and trained on data from 2019 to 2022, with a holdout period from 2023 to August 26. The test rebalanced its portfolio on the first day of each month, using a constant calibration exposure, and it liquidated its positions at the end of the test. The test looked at the performance of one position, called PositionN1, and it calculated the frequency of monthly wins separately. The test charged fees of 1 basis point per side, with a 5 basis point slip, and it assumed a cash yield of 0. The test reported a return of -5.89794101997626 percent and a drawdown of 20.39163041743831 percent, with a win frequency of 0 percent over 44 months. The test used a daily reconciliation with a maximum error of 0, starting with 10,000 initial units. The test did not validate its results using 15-minute or whole-share data, and it used a dividend-adjusted proxy, with survivorship bias, and a history that was not globally untouched. The test was a diagnostic instrument and did not promote any winning strategy. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars and the results are in research/test_vm.py/results.json.
A news scan found the headline about a trading fund test called VM9110600 TLT. The test used a protocol called Protocol2230 with corrections 2233 and 2236, and it ran from January 3, 2023, to August 31, 2026. The test was calibrated using data from 2016 to 2018 and trained on data from 2019 to 2022, with a holdout period from 2023 to August 26. The test rebalanced on the first monthly open, capping prior variance at 1, and had a terminal liquidation. The test looked at position N1 and monthly win frequency separately. Fees were 1 basis point per side, with a 15 basis point slip, and cash had a 0 yield. The return was -9.777625061966788 percent, with a drawdown of 16.00312591960593 percent, and a win frequency of 0 percent over 44 months. The test used a daily reconciliation with a maximum error of 3.637978807091713e-12 at 10,000 initial units. The test did not validate 15-minute or whole-share data and used a dividend-adjusted proxy, with survivorship bias, and a history that was not globally untouched. The test was a diagnostic instrument and did not promote winners. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars and the research results are in research/test_vm.py/results.json.
This is a report on a trading strategy called Protocol2230 with corrections 2233 and 2236. The strategy was tested on data from 2019-01-02 to 2022-12-30, and it was calibrated using data from 2016 to 2018 and tested from 2019 to 2022, with a holdout period from 2023 to August 26. The strategy rebalances on the first monthly open, capping prior variance at 1, and has a terminal liquidation. The position size is N1, and the monthly win frequency is calculated separately. The fees are 1 basis point per side, with a 15 basis point slip, and the cash yield is 0. The return is 8.730427505708471 percent, with a drawdown of 23.750118307164904 percent, and a win rate of 100 percent over 48 months. The strategy was tested using vectorbt with daily reconciliation and a maximum error of 5.4569682106375694e-12 at 10000 initial units. The test did not include 15-minute or whole-share validation, and used a dividend-adjusted proxy with survivorship bias, and the history was not globally untouched. This is a diagnostic instrument, and there is no winner promotion. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the research results are from research/test_vm.py/results.json. A news scan found the report.
This is a report on a trading protocol called Protocol2230 with corrections 2233 and 2236. The report covers the period from 2023-01-03 to 2026-08-31, and the data was calibrated from 2016 to 2018 and trained from 2019 to 2022, with a holdout period from 2023 to August 26. The first monthly open rebalance was done with a capped prior variance of 1 and terminal liquidation. The position was labeled as N1, and the monthly win frequency was calculated separately. The fees were 1 basis point per side, with a 5 basis point slip, and the cash yield was 0. The return was -8.806069127829652 percent, with a drawdown of 15.501575312076199 percent, and a win rate of 0 percent over 44 months. The vectorbt daily reconciliation had a maximum error of 3.637978807091713e-12 at 10,000 initial units. There was no 15-minute or whole-share validation, and the data was dividend-adjusted and subject to survivorship bias, but the history was not globally untouched. This is a diagnostic instrument, and there is no winner promotion. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the research results can be found in research/test_vm.py/results.json. A news scan found the headline was not available, this is a raw script output.
This is a report on an automated trading fund manager's performance, specifically the VM9110600 TLT strategy. The report covers the period from 2019-01-02 to 2022-12-30, with calibration done from 2016 to 2018 and a holdout period from 2023 to August 26. The strategy involves a monthly rebalance, where the portfolio is adjusted to minimize risk, with a cap on prior variance, and terminal liquidation, meaning all positions are sold at the end of the period. The position size is determined by a factor called N1, and the monthly win frequency is calculated separately. The fees for this strategy are 1 basis point, or 0.01%, per transaction, with an additional 5 basis points per side for a type of risk called slippage, and cash has a 0% yield, meaning it does not earn interest. The return on investment is 9.8575%, with a drawdown, or maximum loss, of 23.2936%, and a win rate of 100% over 48 months. The strategy was backtested using a tool called vectorbt, which checks for errors in the trading strategy, and found a maximum error of 1.81899e-12, which is very small, using 10,000 initial units of currency. The data used for this strategy does not include validation for 15-minute intervals or whole-share trading, and uses a dividend-adjusted proxy, which means it takes into account the impact of dividend payments on stock prices, and survivorship bias, which means it only considers companies that have survived over the period, and the data has not been globally untouched, meaning it has been adjusted in some way. This strategy is used as a diagnostic instrument, and there is no promotion of winning strategies. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the research and test results can be found in the file research/test_vm.py/results.json.