Notes

A trading fund used a method called Bootstrap, which is a way to test models, and regression and simulation methods, which are stored in archived code, but this was not tested with independent prospective evidence. The fund worked in a mode called hedged diagnostic, with a cost of 6 basis points on the side, from 2017 to 2019 for training and 2020 to 2025 for holdout, and 2026 separate. The results for the holdout period were a return of -8.56982548022306 percent, a drawdown of -8.56982548022306 percent, with 693 samples, a win rate of 15.151515151515152 percent, an average win of 0.1638875388825972 percent, an average loss of 0.21198345841403582 percent, and a mean trade of -0.15503330730848536 percent. The borrow rate was 3 percent per year, the gross exposure was 1, and the actual size was 0. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A news scan found the headline 'QPAIR91004 hedge row2'. The details are as follows: Frozenbase60/2, train from 2017 to 2019, holdout from 2020 to 2025, and a separate period in 2026. The methods used include bootstrap, regression, and simulation, which are found in archived code, but there is no independent prospective evidence. The results show an era of training, in hedged diagnostic mode, with a cost of 16 basis points on the side, a return percentage of -9.0927, a drawdown percentage of -9.0927, 327 samples, a win rate of 1.8349, an average win percentage of 0.1499, an average loss percentage of 0.3591, a mean trade percentage of -0.3497, a borrow annual percentage of 3, a gross exposure of 1, and an actual size of 0. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A hedge fund used a method called Bootstrap, which is a way to test models, along with regression and simulation methods, found in archived code, but this is not independent evidence from the future. The fund's performance from 2017 to 2019 was used for training, 2020 to 2025 for holdout, and 2026 is separate. The results show a return of -3.9994773698029396 percent, a drawdown of -3.9994773698029396 percent, a win rate of 11.62079510703364 percent, an average win of 0.11403664609731172 percent, an average loss of 0.18432832887387857 percent, and a mean trade of -0.14965594646132435 percent. The borrow rate was 3 percent per year, the gross exposure was 1, and the actual size was 0. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A simulation was run on the QPAIR91004 using a Frozenbase60/2 model, trained on data from 2017 to 2019, with a holdout period from 2020 to 2025, and a separate period in 2026. The simulation used bootstrap, regression, and simulation methods from archived code, but this is not independent prospective evidence. The simulation was run in swing mode with 16 basis points, 20,000 paths, and a horizon of 21 sessions. The results showed a loss probability of 0.7049, with end return percentages of -1.0296, -0.2069, and 0.4129 at the 5th, 50th, and 95th percentiles. The drawdown at the 5th percentile was -1.2252, and the fund dollar amounts at the 5th, 50th, and 95th percentiles were -1.9277, -0.3873, and 0.7731. The gap hit fraction was 0. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A simulation was run on a dataset that was split into three parts: training from 2017 to 2019, holding out from 2020 to 2025, and a separate part for 2026. The methods used for the simulation, including bootstrap and regression, are found in archived code, but this is not independent prospective evidence. The simulation was run in swing mode with 6 basis points, 20,000 paths, and a horizon of 21 sessions. The results showed a loss probability of 0.5838, with end returns of -0.8378%, -0.0693%, and 0.5752% at the 5th, 50th, and 95th percentiles. The drawdown at the 5th percentile was -1.0306%. The fund's dollar returns were -1.5686, -0.1298, and 1.0769 at the 5th, 50th, and 95th percentiles. The gap hit fraction was 0. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A simulation was run on the QPAIR91004 with the following parameters: Frozenbase60/2, train2017–19/holdout2020–25/2026separate. The methods used were Bootstrap, regression, and simulation, which can be found in the archived code. It is noted that this is not independent prospective evidence. The simulation was run in long mode with 16 base points, 20,000 paths, and a horizon of 21 sessions. The results showed a loss probability of 0.45585. The end return percentages were -2.4744, 0.0714, and 1.6074 for the 5th, 50th, and 95th percentiles. The drawdown percentage for the 5th percentile was -3.4946. The fund dollar amounts were -4.6326, 0.1337, and 3.0093 for the 5th, 50th, and 95th percentiles. The gap hit fraction was 0. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A simulation was run on a dataset that was divided into three parts: training from 2017 to 2019, holding out from 2020 to 2025, and a separate part for 2026. The simulation used methods including bootstrap and regression, which were taken from archived code, but this is not independent prospective evidence. The simulation was run in long mode with 6 basis points, 20,000 paths, and a horizon of 21 sessions. The results showed a loss probability of 0.40485, and the end return percentages were -2.1279675844255608 at the 5th percentile, 0.2060072635894361 at the 50th percentile, and 1.8079718083520602 at the 95th percentile. The drawdown at the 5th percentile was -3.347564394112079 percent. The fund dollar amounts were -3.983980911561535 at the 5th percentile, 0.3856867988921423 at the 50th percentile, and 3.384884819596727 at the 95th percentile. The gap hit fraction was 0. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A trading analysis used a method called bootstrap, which is a way to test models, and regression, which is a way to understand relationships, and simulation, which is a way to mimic real-life scenarios, on a set of data from 2017 to 2019, and then tested the model on data from 2020 to 2025, with a separate test in 2026. The results are based on archived code, but there is no independent evidence to support the findings. The analysis found the following statistics for the AGG and BND pair in 2026: the sample size was 10, the average percentage change for AGG was -0.1827%, the average percentage change for BND was -0.1896%, the difference in average percentage change was 0.0069%, and the correlation between daily returns was 0.9953. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data row about the GLD and IAU pair. The data was split into training and testing sets, with the training set using data from 2017 to 2019, and the testing set using data from 2020 to 2025, with 2026 being separate. The analysis used bootstrap, regression, and simulation methods, which are statistical techniques, in archived code, but this is not independent prospective evidence, meaning it is not new or separate confirmation. The results for 2026 show that the GLD had a mean percentage change of 2.7709%, the IAU had a mean percentage change of 2.7774%, the difference between them was -0.0064%, and the daily return correlation between them was 0.9999. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of stocks, XLI and VIS, from 2026. The data was generated using a method called bootstrap, which is a way of testing a model, and regression and simulation methods, which are stored in archived code, but there is no independent evidence to support the results. The statistics include a sample size of 7, a long mean percentage of -1.2069, a partner mean percentage of -1.3108, a difference mean percentage of 0.1039, and a daily return correlation of 0.9913. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of stocks, XLV and VHT, from 2026. The data was prepared using a method called Bootstrap, which is a way to test models, and regression and simulation methods, which are stored in archived code, but this is not independent evidence from the future. The numbers show that on average, XLV went up 0.4392 percent and VHT went up 0.5051 percent, with a difference of -0.0658 percent, and the daily returns of the two stocks were very closely correlated, at 0.9885. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data row about a stock pair. The data was split into groups for training from 2017 to 2019, holding out from 2020 to 2025, and a separate group for 2026. The analysis used methods including bootstrap, regression, and simulation, which are stored in archived code, but this is not independent evidence from the future. The data shows information about the stock pair XLE and VDE in the year 2026, with 9 samples. The average percentage change for XLE was -0.3572590944444446 percent, and for VDE it was -0.5437325788888889 percent. The difference between these averages was 0.18647348444444448 percent. The daily return correlation between the two stocks was 0.9958380030330954. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data row about the XLK and VGT pair. The data was split into three parts: training from 2017 to 2019, holding out from 2020 to 2025, and a separate part for 2026. The methods used to analyze the data include a type of statistical method called bootstrap, regression, which is a way to understand relationships between variables, and simulation, which is a way to model real-world situations using computers. The code for these methods is archived, but the results are not based on independent prospective evidence, which means the results are based on past data, not new, independent tests. The data shows that for the XLK and VGT pair in 2026, the sample size is 6, the average percentage change for XLK is 0.6858516333333334%, the average percentage change for VGT is 1.085953881666666%, the average difference between the two is -0.4001022483333332%, and the correlation between their daily returns is 0.9917806930488856. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of stocks, XLF and VFH. The data was split into training and testing periods, with the training period from 2017 to 2019 and the testing period from 2020 to 2025, and a separate period in 2026. The analysis used methods including bootstrap, regression, and simulation, but this was based on archived code and not independent prospective evidence. The results for 2026 show a mean percentage return of -1.05510179 for XLF and -1.02505714 for VFH, with a difference of -0.03004464999999995. The daily return correlation between the two stocks was 0.9951143516497548. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for the EEM/VWO pair. The data was split into training and holdout periods, from 2017 to 2019 for training and 2020 to 2025 for holdout, with 2026 being separate. The methods used to analyze the data include bootstrap, regression, and simulation, which are archived in code, but there is no independent prospective evidence. The statistics for the pair in the 2026 era include a sample size of 7, a long mean percentage of 0.31701450714285706, a partner mean percentage of 0.6717225199999998, a difference mean percentage of -0.35470801285714293, and a daily return correlation of 0.9450252329384082. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of stocks, EFA and VEA, from 2026. The data was generated using methods including bootstrap, regression, and simulation, which are archived in code, but there is no independent evidence to support the results. The statistics include a sample size of 7, a long mean percentage of 0.4269960642857143, a partner mean percentage of 0.5260547642857143, a difference mean percentage of -0.09905869999999996, and a daily return correlation of 0.9760816884606963. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of stocks, IWM and IJR, from 2026. The data was created using a method called bootstrap, which is a way of testing how well a model works, and regression and simulation methods, which are stored in archived code, but it is not independent prospective evidence, meaning it is not based on real-time market data. The statistics include a sample size of 4, with a long mean percentage of 1.8619125900000002, a partner mean percentage of 0.6796308500000001, a difference mean percentage of 1.1822817399999999, and a daily return correlation of 0.9323434104154688. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of stocks, VTI and ITOT. The data was split into training and testing periods, with the training period from 2017 to 2019 and the testing period from 2020 to 2025, and a separate period in 2026. The statistics were calculated using methods including bootstrap, regression, and simulation, which are stored in archived code, but this is not independent prospective evidence. The statistics for the pair in 2026 are as follows: the sample size is 7, the average percentage change for VTI is 1.032819777142857 percent, the average percentage change for ITOT is 1.04461069 percent, the difference in average percentage change is -0.011790912857142892 percent, and the correlation between daily returns is 0.9995321175217114. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of stocks, specifically SPY and IVV. The data was split into training and testing sets, with the training set covering the years 2017 to 2019, and the testing set covering the years 2020 to 2025, with 2026 being separate. The analysis used bootstrap, regression, and simulation methods, which are stored in archived code, but this is not independent prospective evidence. The statistics for the pair are as follows: the era is 2026, the sample size is 12, the mean percentage return for the long stock is 0.3235 percent, the mean percentage return for the partner stock is 0.3227 percent, the mean percentage difference between the two stocks is 0.0007 percent, and the correlation between the daily returns of the two stocks is 0.9989. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A trading fund manager used a method called bootstrap, which is a way to test models, and regression, which is a way to find relationships, and simulation, which is a way to mimic real-life situations, to analyze a pair of stocks, AGG and BND. The analysis was done on a set of data from 2017 to 2019, and then the results were tested on a separate set of data from 2020 to 2025, and also on data from 2026. The results are based on archived code, but there is no independent evidence from outside sources to confirm them. The analysis found the following statistics for the holdout period: the sample size was 74, the average percentage change for AGG was -0.2052266037837838 percent, the average percentage change for its partner BND was -0.20410323621621626 percent, the average difference between the two was -0.0011233675675675681 percent, and the correlation between their daily returns was 0.8799163319044446. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for the GLD and IAU pair. The data is divided into training and testing periods, from 2017 to 2019 for training and 2020 to 2025 for testing, with 2026 separate. The methods used to analyze the data include a type of statistical method called bootstrap, regression, which is a way to understand relationships between variables, and simulation, which is a way to model real-world situations using computers. The results are based on archived code, but there is no independent evidence to support the findings. The statistics for the pair include a sample size of 76, a long mean percentage change of -0.24218712868421055, a partner mean percentage change of -0.24450092, a difference mean percentage change of 0.0023137913157894813, and a daily return correlation of 0.9968533037403523. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data analysis of the XLI and VIS pair, using a method called bootstrap, which is a way to estimate how accurate a model is, and regression, which is a way to understand the relationship between variables, and simulation, which is a way to mimic real-world scenarios. The analysis was done using code that is archived, meaning it is stored and not currently being used, and it is not independent prospective evidence, meaning it is not new or separate proof. The results show that for a sample of 50 days, the average percentage change for XLI was 0.7153449008000001%, and for VIS it was 0.7797831508%, with an average difference of -0.06443825000000003% between the two, and the daily return correlation, which measures how closely the two move together, was 0.993522363862892. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of stocks, XLV and VHT. The data was split into training and testing periods, with the training period from 2017 to 2019 and the testing period from 2020 to 2025, and a separate period in 2026. The methods used to analyze the data include bootstrap, regression, and simulation, but these methods are not based on independent prospective evidence. The statistics for the holdout period are as follows: the sample size is 48, the mean percentage return for XLV is -0.07808418770833334, the mean percentage return for VHT is -0.13415400458333349, the difference in mean percentage return is 0.056069816875000074, and the correlation between daily returns is 0.9860267711023821. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of stocks, XLE and VDE, from 2020 to 2025, with a separate test in 2026. The data was analyzed using a method called bootstrap, which is a way of testing how well a model works, and regression, which is a way of finding the relationship between two things, and simulation, which is a way of modeling real-life situations using computers. The results are based on archived code, but there is no independent evidence to confirm them. The statistics show that the sample size is 51, the average percentage change for XLE is 0.20477373960784323, the average percentage change for VDE is 0.13235847392156858, the average difference between the two is 0.07241526568627456, and the correlation between their daily returns is 0.9925357275754584. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

A trading fund manager used a method called bootstrap, which is a way to test models, and regression, which is a way to find relationships, and simulation, which is a way to mimic real-life situations, to analyze a pair of stocks, XLK and VGT. The analysis was done on a set of data from 2017 to 2019, and then the results were tested on a separate set of data from 2020 to 2025, and also on data from 2026. The results show that for 53 samples, the average percentage change for XLK was 0.23139598339622633 percent, and for VGT it was 0.3084507258490566 percent. The difference between these two averages was -0.07705474245283017 percent. The daily return correlation, which measures how closely the two stocks move together, was 0.992102031681954. This analysis is based on archived code, but it is not independent prospective evidence, meaning it is not new and was not tested in real-time. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all