Notes

This is a data line showing statistics for a pair of stocks, XLF and VFH, from 2020 to 2025. The data was generated using a method called bootstrap, which is a way of testing models, and regression, which is a way of finding relationships between variables, and simulation, which is a way of mimicking real-world situations using archived code, but it is not based on independent prospective evidence, which means it is not based on new and separate data. The statistics include a sample size of 46, a long mean percentage of -0.05823152739130423, a partner mean percentage of -0.09971095652173904, a difference mean percentage of 0.04147942913043483, and a daily return correlation of 0.990753172901578. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of stocks, EEM and VWO, from 2020 to 2025. 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 this is not independent evidence from the future. The statistics include a 52 sample size, with the EEM stock having a mean percentage change of -0.5561596001923077, the VWO stock having a mean percentage change of -0.5862650357692307, the difference between the two stocks having a mean percentage change of 0.03010543557692302, and a daily return correlation of 0.992130526587839. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of investments, EFA and VEA, from 2020 to 2025, which is considered a holdout period. The data was generated using methods including bootstrap, regression, and simulation, but it is not independent prospective evidence. The statistics include a sample size of 50, a long mean percentage of 0.49018797059999997, a partner mean percentage of 0.47142203419999995, a difference mean percentage of 0.018765936400000034, and a daily return correlation of 0.9952161155763266. 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. The data was split 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 bootstrap, regression, and simulation, but these methods are based on archived code and not independent prospective evidence. The statistics for the holdout period are as follows: the sample size is 47, the average percentage change for IWM is -0.8780869338297872 percent, the average percentage change for IJR is -0.9414519165957449 percent, the average difference between the two is 0.0633649827659574 percent, and the correlation between their daily returns is 0.9748414852465136. 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 collected from 2017 to 2019 for training, and from 2020 to 2025 for testing, with 2026 being separate. The methods used to analyze the data include a type of statistical method called bootstrap, regression, and simulation, which are stored in archived code, but this is not independent evidence from the future. The statistics show that over 69 samples, VTI had an average gain of 0.1722 percent, ITOT had an average gain of 0.1875 percent, the difference between them was a loss of 0.0153 percent on average, and the daily returns of the two stocks were very closely correlated, with a correlation of 0.9961. 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 data from 2017 to 2019 and predict results for 2020 to 2025, with 2026 separate. The results are based on archived code, but there is no independent evidence to support them. The analysis found the following statistics for the SPY and IVV pair: 77 samples were used, the average percentage change for the long position was -0.13138928779220777 percent, the average percentage change for the partner position was -0.12733410662337663 percent, the average difference between the two positions was -0.004055181168831157 percent, and the correlation between daily returns was 0.9940986297374959. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for the AGG and BND pair. The data was split into training and holdout periods, from 2017 to 2019 for training and 2020 to 2025 for holdout, with 2026 separate. The methods used to analyze the data include bootstrap, regression, and simulation, which are archived in code, but there is no independent evidence to support the findings. The statistics for the pair include a sample size of 34, a long mean percentage of 0.0436, a partner mean percentage of 0.05, a difference mean percentage of -0.0064, and a daily return correlation of 0.969. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of stocks, GLD and IAU. The data was split into training and holdout periods, from 2017 to 2019 for training and 2020 to 2025 for holdout, with 2026 separate. The methods used to analyze the data include bootstrap, regression, and simulation, which are archived in code, but there is no independent evidence to support the results. The statistics for the training period are as follows: the sample size is 30, the average percentage gain for GLD is 0.06630555733333332 percent, the average percentage gain for its partner IAU is 0.06278422833333332 percent, the average difference in percentage gain between the two is 0.003521329000000001 percent, and the correlation between their daily returns is 0.9941661470864667. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

The data for XLI is based on a specific time period, from 2017 to 2019 for training and 2020 to 2025 for holdout, with 2026 being separate. The methods used include bootstrap, regression, and simulation, which are found in archived code, but there is no independent prospective evidence to support the findings. The statistics for the pair XLI and VIS are as follows: the sample size is 21, the long mean percentage is -0.9293120576190476, the partner mean percentage is -0.9147937933333334, the difference in mean percentage is -0.0145182642857143, and the daily return correlation is 0.992212848848963. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for the XLV and VHT pair. The data was split into training and holdout periods, with the training period being from 2017 to 2019 and the holdout period being from 2020 to 2025, and a separate period in 2026. The methods used to analyze the data include bootstrap, regression, and simulation, which are available in archived code, but there is no independent prospective evidence to support the results. The statistics for the pair include a long mean percentage of 0.3012155185185184, a partner mean percentage of 0.16103651518518527, a difference mean percentage of 0.14017900333333336, and a daily return correlation of 0.9873289669480585. 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. The data was split 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, and simulation, which are stored in archived code, but this is not independent evidence from the future. The statistics for this pair of stocks, XLE and VDE, are as follows: the average percentage change for XLE was -1.4517 percent, for VDE it was -1.3649 percent, the difference between them was -0.0867 percent, and the correlation between their daily returns was 0.9957. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of stocks, XLK and VGT. The data was collected from 2017 to 2019 for training, and from 2020 to 2025 for holdout, with 2026 separate. The methods used to analyze the data include bootstrap, regression, and simulation, which are stored in archived code, but there is no independent prospective evidence. The statistics show that the sample size is 23, the average percentage gain for XLK is 1.3769%, the average percentage gain for VGT is 1.3561%, the average difference in percentage gain between the two stocks is 0.0208%, and the correlation between their daily returns is 0.9935. 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, from 2017 to 2019. The data includes the average percentage change for the long stock, which is 0.07823146000000009 percent, the average percentage change for the partner stock, which is 0.020628477692307717 percent, and the difference between these two averages, which is 0.05760298230769246 percent. The daily return correlation between the two stocks is 0.9932901238258001. This data is based on a frozen base of 60, divided into two parts, with the training data from 2017 to 2019, and the holdout data from 2020 to 2025, with 2026 separate. The methods used to analyze this data include bootstrap, regression, and simulation, which are archived in the code, but there is no independent prospective evidence to support the results. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of stocks, EEM and VWO, from 2017 to 2019. The data includes the average percentage change for EEM, which was 0.2024506871428571 percent, and for VWO, which was 0.16673893428571426 percent. The difference between these two averages was 0.035711752857142835 percent. The daily return correlation between the two stocks was 0.9885653118110517, meaning their prices moved together very closely. This data is from a training period, and the results are based on archived code using bootstrap, regression, and simulation methods, but there is no independent evidence to support the results. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

This is a data line showing statistics for a pair of investments, EFA and VEA, from 2017 to 2019. The data was used to train a model, with 2020 to 2025 set aside to test it, and 2026 used separately. The results were found using special methods called bootstrap, regression, and simulation, which are stored in archived code, but this is not independent evidence from the future. The statistics for this pair are: the average percentage gain for EFA was 0.5281521087500001 percent, the average percentage gain for its partner VEA was 0.4966240545833335 percent, the average difference in percentage gain between them was 0.031528054166666666 percent, and the correlation between their daily returns was 0.9918985672432172. 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 2017 to 2019. The results are based on methods including bootstrap, regression, and simulation, which are archived in code, but there is no independent evidence to support the findings. The statistics include a sample size of 18, with a mean percentage change of -0.16189% for IWM and -0.11091% for IJR, and a difference of -0.05098% between the two. The daily return correlation between the two stocks is 0.98693. 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 collected from 2017 to 2019 for training, and from 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 evidence to support the findings. The statistics for the pair are as follows: the sample size is 39, the mean percentage change for VTI is -0.1445%, the mean percentage change for ITOT is -0.1655%, the difference in mean percentage change is 0.0210%, and the correlation between daily returns is 0.9981%. 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 periods, with the training period being from 2017 to 2019 and the testing period being from 2020 to 2025, with 2026 being separate. The methods used to analyze the data include bootstrapping, regression, and simulation, but these methods are based on archived code and do not provide independent prospective evidence. The statistics for the pair include a long mean percentage of -0.21627738710526317, a partner mean percentage of -0.2156927307894737, a difference mean percentage of -0.000584656315789482, and a daily return correlation of 0.9989959983057399, based on a sample of 38 data points. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

The QPAIR91004 robust row12 uses a specific setup for its data: Frozenbase60 divided by 2, trained on data from 2017 to 2019, held out from 2020 to 2025, and separate data for 2026. It employs bootstrap, regression, and simulation methods, which are found in archived code, but it does not have independent prospective evidence. The details of the era are as follows: the era is 2026, the mode is swing, the bp is 16, the months are 9, the block months are 3, and there are 10000 replicates, with a confidence interval percentage of -0.659775418317757 to -0.016751350149253743. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

The QPAIR91004 robust row11 uses a specific setup for its analysis, which includes Frozenbase60 divided by 2, with training data from 2017 to 2019, holdout data from 2020 to 2025, and a separate dataset for 2026. The methods used include bootstrap, regression, and simulation, which are found in the archived code, but there is no independent prospective evidence to support the results. The parameters for this setup include an era of 2026, a mode of swing, a bp of 6, 9 months, block months of 3, and 10000 replicates, with a confidence interval percentage of -0.45590351558823533 to 0.19649972950819672. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

The QPAIR91004 robust row10 uses a specific setup for its data: Frozenbase60 divided by 2, with training data from 2017 to 2019, holdout data from 2020 to 2025, and a separate set for 2026. It employs bootstrap, regression, and simulation methods, which are found in archived code, but it does not have independent prospective evidence. The parameters for this setup include an era of 2026, a mode of difference, a bp of 6, 9 months, block months of 3, and 10,000 replicates. The confidence interval percentage is between -0.07064785195121948 and 0.10678476769230769. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

The QPAIR91004 robust row9 uses a specific setup for its analysis: it was trained on data from 2017 to 2019, held out data from 2020 to 2025, and has a separate set for 2026. The methods used include bootstrap, regression, and simulation, which are found in the archived code, but there is no independent prospective evidence to support the findings. The parameters for this setup include an era of 2026, a mode of long, a buy point of 6, a duration of 9 months, and blocks of 3 months, with 10,000 replicates. The results show a confidence interval percentage of 0.16396570867924531 to 0.9808425535294117. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

The QPAIR91004 robust row8 uses a dataset that is split into three parts: Frozenbase60 for training from 2017 to 2019, a holdout set from 2020 to 2025, and a separate set for 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 holdout, a mode of swing, with 16 basis points, over 72 months, and blocks of 3 months, with 10,000 replicates, and a confidence interval percentage of -0.448335541164035 to -0.21655171796474823. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

The QPAIR91004 robust row7 uses a dataset that is split into three parts: Frozenbase60 for training from 2017 to 2019, holdout from 2020 to 2025, and a separate part for 2026. The methods used include bootstrap, regression, and simulation, which are found in archived code, but there is no independent prospective evidence to support the results. The holdout era is analyzed in swing mode with 6 basis points, over 72 months, divided into blocks of 3 months, and the results are based on 10,000 replicates, with a confidence interval percentage of -0.24919277307859544 to -0.015274780784366249. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all

The QPAIR91004 robust row6 uses a Frozenbase60/2 model, which was trained from 2017 to 2019 and held out from 2020 to 2025, with a separate test in 2026. The model uses bootstrap, regression, and simulation methods, which are archived in the code, but there is no independent prospective evidence to support the results. The model's performance is measured with the following parameters: the era is holdout, the mode is difference, the bp is 6, the months is 72, the block months is 3, and the replicates is 10000, with a confidence interval percentage of -0.02466423170272862 to 0.03977574216650927. https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all