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.
This is a test of the VM9110600 EEM adapter, which is a type of automated trading system. The test used a protocol called Protocol2230 with corrections 2233 and 2236, and it ran from January 3, 2023, to August 31, 2026. The system 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 made monthly entries based on prior variance, with a cap of 1, and used a stop loss of 2 ATR, or average true range, and a target of 6 ATR, with an additional 4 ATR added each quarter and on the next day's break even point, and exited at the end of each month. The fees were 1 basis point per side, with a slip of 15 basis points, and the cash yield was 0. The return was 12.88 percent, with a drawdown of 18.85 percent, and a win rate of 47.73 percent, over 44 months and 44 trades. The system used a daily reconciliation with a maximum error of 3.637978807091713e-12, and an initial investment of 10,000 units. 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 results are in the file research/test_vm.py/results.json.
This is a description of a trading strategy, which is a set of rules for buying and selling stocks. The strategy uses a protocol called Protocol2230 with corrections 2233 and 2236, which were applied from January 2, 2019, to December 30, 2022. The strategy was calibrated, or tested, using data from 2016 to 2018, and then trained, or learned, using data from 2019 to 2022, with a holdout period from 2023 to August 26. The strategy enters a trade, or buys a stock, on a monthly basis, with a limit on how much it can lose, which is capped at 1 times the prior variance, a measure of how much the stock price has changed in the past. The strategy also has a stop loss, which is set at 2 times the average true range, a measure of how much the stock price has changed, and a target, or profit goal, of 6 times the average true range, with an additional 4 times the average true range added each quarter, and the trade is exited at the end of the month or the next day if a certain condition is met, called a breakout even, or BE. The strategy has fees of 1 basis point, a measure of the cost of trading, and 15 basis points per trade, and it does not earn any interest on cash, which is a yield of 0. The strategy had a return of -24.76 percent and a maximum drawdown, or loss, of 44 percent, with a win rate of 33.33 percent, over 48 months, with 48 trades. The strategy was tested using a tool called vectorbt, which checks the strategy's performance daily, and it found a maximum error of 3.637978807091713e-12, which is a very small number, using an initial investment of 10,000 units. The strategy does not validate its trades using 15-minute intervals or whole shares, and it uses a dividend-adjusted proxy, which means it takes into account the dividends paid by the stocks, and it does not account for survivorship bias, which means it does not exclude stocks that have gone out of business, and it uses a history that has not been globally untouched, meaning it has been adjusted in some way. The strategy is a diagnostic instrument, which means it is used to test and evaluate, and it does not promote winning trades. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars, and the research and test results are in a file called research/test_vm.py/results.json.
This is a test of the VM9110600 EEM adapter, specifically the slip5 scale1 configuration. The test used a protocol with corrections from 2230, 2233, and 2236, and the data range 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 had a 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 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%, per side, with an additional 5 basis points for slippage, and a cash yield of 0. The return was 19.83%, with a maximum drawdown of 17.78%, and a win rate of 47.73%, over 44 months, with 44 trades. The test used a daily reconciliation with a maximum error of 3.637978807091713e-12, at an initial investment of 10000 units. 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 data source is https://runway.adityaperswal.workers.dev/data/stock-bars, and the research results are from research/test_vm.py/results.json.
This is a report on the performance of the VM9110600 EEM adapter. The protocol used for corrections is Protocol2230 with corrections 2233 and 2236. The data used for calibration was from 2016 to 2018, and the training data was from 2019 to 2022, with a holdout period from 2023 to August 26. The monthly entry was based on prior variance capped at 1, with a stop loss at 2 ATR and a target at 6 ATR, and an additional 4 ATR for the next quarter, with a buy and exit at the end of the month. The fees were 1 basis point per side, with a 5 basis point slip, and a cash yield of 0. The return was -14.87%, with a drawdown of 42.92%, and a win rate of 35.42%, over 48 months, with 48 trades. The vectorbt daily reconciliation had a maximum error of 3.637978807091713e-12, at 10000 initial units. There was no 15-minute or whole-share validation, and the data used was dividend-adjusted, with survivorship bias, and the history was not globally untouched. This is a diagnostic instrument, with no winner promotion. 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.
A news scan found the headline about a test of VM9110600 EEM with constant parameters. The test used Protocol 2230 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, trained on data from 2019 to 2022, and held out data from 2023 to August 26. The test rebalanced on the first monthly open with constant calibration exposure and terminal liquidation. It tracked the position of N1 and the monthly win frequency separately. The fees were 1 basis point per side, with a 15 basis point slip, and the cash yield was 0. The return was 73.49998728871863 percent, with a drawdown of 14.972165090313162 percent, a win rate of 100 percent, and 44 months of data. The test used vectorbt for daily reconciliation with a maximum error of 0 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 the history was not globally untouched. The test was a diagnostic instrument and did not promote a winner. 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 description of a trading protocol, specifically Protocol 2230 with corrections 2233 and 2236. The trading period is from January 2, 2019, to December 30, 2022, with calibration done from 2016 to 2018 and a holdout period from 2023 to August 26. The strategy involves rebalancing on the first monthly open with constant calibration exposure and terminal liquidation. The position size is denoted as N1, with monthly win frequency calculated separately. The fees are 1 basis point per side, with a 15 basis point slip, and cash has a 0 yield. The return is 6.9403397381326615 percent, with a drawdown of 35.27627543391352 percent, a win rate of 100 percent, and 48 months of trading. The strategy uses vectorbt for daily reconciliation with a maximum error of 0 at 10,000 initial units. There is no validation for 15-minute or whole-share trades, and the data is dividend-adjusted with a proxy for survivorship, but the history has not been globally untouched. This is 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 results can be found in research/test_vm.py/results.json.
This is a report on a test of the VM9110600 strategy, which is a set of rules for buying and selling stocks. The test was run from 2023-01-03 to 2026-08-31, using data from 2016 to 2018 to calibrate the strategy and data from 2019 to 2022 to train it, with the remaining data held out for testing until August 26, 2023. The strategy was rebalanced on the first day of each month, with the goal of maintaining constant exposure, and all positions were liquidated at the end of the test. The test looked at the performance of the strategy separately for each position and for the frequency of monthly wins. The strategy was charged a fee of 1 basis point, or 0.01%, per trade, with an additional 5 basis point slip, and cash had a 0% yield. The strategy returned 73.82%, with a maximum drawdown of 14.97%, and won 100% of the time, with 44 months of data. The test used a daily reconciliation with a maximum error of 0, starting with 10,000 units, and did not validate the results against 15-minute data or whole-share data. The test also used a dividend-adjusted proxy and accounted for survivorship bias, but did not use globally untouched data. This test was run as a diagnostic instrument and did not promote a winning strategy. The data for the test came from https://runway.adityaperswal.workers.dev/data/stock-bars and the results can be found in research/test_vm.py/results.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, and holdout from 2023 to August 26. The strategy involved rebalancing on the first monthly open with constant calibration exposure and terminal liquidation. The position size was N1, with monthly win frequency calculated separately. Fees were 1 basis point per side, with a 5 basis point slip, and cash had a 0 yield. The return was 7.143491049706818 percent, with a drawdown of 35.27153425719338 percent, a win rate of 100 percent, and 48 months of data. The vectorbt daily reconciliation had a maximum error of 0 at 10,000 initial units. There was no 15-minute or whole-share validation, and the data was dividend-adjusted, with survivorship bias, and the history was not globally untouched. This was a diagnostic instrument, with 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.
This is a report on a test of the VM9110600 strategy, which is a set of rules for an automated trading fund manager. The test used data from 2016 to 2022 to train the strategy and data from 2023 to August 26, 2023, to test it. The strategy was rebalanced on the first monthly open, with a cap on prior variance of 1. The test also included terminal liquidation, which means selling all positions at the end of the test. The results showed a return of 68.54% and a maximum drawdown of 15.55%. The strategy had a win frequency of 100% over 44 months. The test used a fee of 1 basis point per side, with a slip of 15 basis points. The initial investment was 10,000 units. The test also included daily reconciliation with a maximum error of 1.8189894035458565e-12. The data used was dividend-adjusted and included survivorship bias, but was not globally untouched. The test was run using the vectorbt library and the results can be found at https://runway.adityaperswal.workers.dev/data/stock-bars and research/test_vm.py/results.json. A news scan found the source of the data.
This is a report on the performance of the VM9110600 EEM monthly train slip15 scale1. The protocol used for corrections is Protocol2230 with corrections made on dates 2233 and 2236. The data used for calibration was from 2016 to 2018, and the training data was 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 N1 and monthly win frequency were calculated separately. The fees were 1 basis point per side, with a slip of 15 basis points, and a cash yield of 0. The return was -0.9303762412577687 percent, with a drawdown of 31.475732190328763 percent, and a win rate of 0 percent over 48 months. The vectorbt daily reconciliation had 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, 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 and test results are from research/test_vm.py/results.json.
This is a report on a trading test called VM9110600 EEM. The test used a set of rules called Protocol 2230 with corrections 2233 and 2236. The test ran 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 the portfolio on the first day of each month, using a method to limit risk called capping prior variance at 1, and the portfolio was liquidated at the end of the test. The test looked at the performance of the first position, called Position N1, and the frequency of monthly wins separately. The test included fees of 1 basis point for each transaction and a 5 basis point slip per side, with cash having a 0% yield. The return on investment was 69.42229454318145% with a maximum drawdown of 15.518137983819958%, and 100% of the months were winning months, with 44 months of data. The test used a daily reconciliation method with a maximum error of 7.275957614183426e-12, starting with 10,000 initial units. The test did not validate 15-minute intervals or whole-share trading, and used a dividend-adjusted proxy with survivorship bias, without altering the global history. 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 test results can be found in research/test_vm.py/results.json.
This is a report on the performance of the VM9110600 EEM monthly train slip5 scale1. The protocol used for corrections is Protocol2230 with corrections 2233 and 2236, and the data range is from 2019-01-02 to 2022-12-30, with calibration done from 2016 to 2018 and training from 2019 to 2022, and holdout from 2023 to August 26. The first monthly open rebalance is done with prior variance capped at 1 and terminal liquidation. Position N1 and monthly win frequency are calculated separately. Fees are 1 basis point per side, with a slip of 5 basis points, and cash has a 0 yield. The return is -0.048481014134449385 percent, with a drawdown of 31.193884881492362 percent, and a win rate of 0 percent, with 48 months of data. The vectorbt daily reconciliation has a maximum error of 1.8189894035458565e-12 at 10000 initial units. There is no 15-minute or whole-share validation, and the data is dividend-adjusted with a proxy for survivorship, and the history has not been 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 are from research/test_vm.py/results.json.
This is a test of the VM9110600 EFA adapter, specifically the slip15 scale1 configuration. The test used the Protocol 2230 with corrections 2233 and 2236, and ran from 2023-01-03 to 2026-08-31, 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 test made monthly entries based on prior variance, capped at 1, with a stop loss at 2 ATR and a target at 6 ATR, and also considered a quarter with a next-day break even point and a month-end exit. The fees were 1 basis point per side, with a 15 basis point slip and a cash yield of 0. The test resulted in a return of 4.277085141387316 percent, with a drawdown of 17.797992253073534 percent, a win rate of 45.45454545454545 percent, and 44 trades over 44 months. The test used vectorbt for daily reconciliation, with a maximum error of 3.637978807091713e-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. 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 from research/test_vm.py/results.json.
A news scan found the headline is not available, but a data line was found with the following information: The Protocol 2230 with corrections 2233 and 2236 was used from 2019-01-02 to 2022-12-30, with calibration from 2016 to 2018 and training from 2019 to 2022, and holdout from 2023 to August 26. The monthly entry was based on prior variance capped at 1, with a stop at 2 ATR, or Average True Range, which is a measure of volatility, and a target at 6 ATR, with an additional 4 ATR for the next quarter and a next-day break-even point, and an exit at the end of the month. The fees were 1 basis point, or 0.01%, per side, with a 15 basis point slip, and a cash yield of 0. The return was -19.25% with a drawdown of 26.85%, a win rate of 39.58%, and 48 trades over 48 months. The vectorbt daily reconciliation had a maximum error of 1.8189894035458565e-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 this data is https://runway.adityaperswal.workers.dev/data/stock-bars and the research/test_vm.py/results.json file.
This is a test of the VM9110600 EFA adapter, specifically the slip5 scale1 configuration. The test used a protocol called Protocol2230 with corrections 2233 and 2236, and the data range 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 had a monthly entry based on prior variance capped at 1, and a stop loss at 2 ATR, or average true range, with a target at 6 ATR, and an additional 4 ATR for the next quarter, with a buy and exit at the end of the month. The fees were 1 basis point per side, with a 5 basis point slip, and a cash yield of 0. The return was 11.00021993637197 percent, with a drawdown of 16.478975701870823 percent, and a win rate of 45.45454545454545 percent, over 44 months, with 44 trades. The test used a daily reconciliation with a maximum error of 3.637978807091713e-12, at an initial investment of 10000 units. 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 test was used as a diagnostic instrument, and not to promote a winning strategy. The data source was https://runway.adityaperswal.workers.dev/data/stock-bars, and the test results can be found in research/test_vm.py/results.json.