Notes

A news scan found the text: Seed90906 numpy; 20,000 paths, 12 monthly events from 20 holdout quarter blocks, sampled 4 quarters with replacement jointly across 3 assets. This means that a computer program used 20,000 possible paths to predict what might happen to investments, looking at 12 monthly events and using a special method to choose the events from a set of 20 blocks of time, and it did this for 4 quarters, choosing the events in a way that allowed the same event to be chosen more than once, and it did this for 3 different investments. The program tried to preserve the patterns that happen over 3 months and the relationships between the investments, and it assumed that the patterns would stay the same in the future, but it did not try to predict extreme events that might happen. The program used hypothetical positions of 212.7475 USD and 245.69 USD, which means it pretended to have investments of those sizes, but the actual size of the investments was 0, meaning this was just a thought experiment. The program found that there was a small chance that the investments could lose a lot of money, but it was not impossible, with possible losses of -32.84493261455071, -7.415221655240979, and 21.27322787137186. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

A news scan found the text describing a Monte Carlo simulation. The simulation used a seed from numpy and generated 20,000 paths with 12 monthly events from 20 holdout quarter blocks, sampled 4 quarters with replacement jointly across 3 assets. This method preserves 3 month serial and cross asset dependence, assuming stationarity, and does not model future tails. The simulation used individual hypothetical positions of 212.7475 USD and a thought experiment with equal sleeve separate positions of 245.69 USD, with actual size being 0, noting that no 349 hit is not an impossibility. The correlation matrix is as follows: the correlation between OEF and OEF is 1, between OEF and SPY is 0.9661616742754568, between OEF and IWM is 0.6002325704515783, between SPY and OEF is 0.9661616742754568, between SPY and SPY is 1, between SPY and IWM is 0.6143201520663915, between IWM and OEF is 0.6002325704515783, between IWM and SPY is 0.6143201520663915, and between IWM and IWM is 1. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data line: Seed90906 numpy, which is a type of mathematical software, used 20,000 paths and 12 monthly events from 20 holdout quarter blocks, sampled 4 quarters with replacement jointly across 3 assets. This method, called a Monte Carlo simulation, which is a way to model random events, preserves 3 month serial and cross asset dependence, and assumes stationarity, which means that the data does not change over time. It also does not model future tails, which are extreme events. The simulation used individual hypothetical positions of 212.7475 USD, and an equal sleeve, which means an equal amount, of 245.69 USD in a thought experiment. The actual size is 0, and there is a finite, or limited, chance that there will not be 349 hits, which is not an impossibility. The results of the simulation include the following data: there were 20,000 paths, 12 months, and a notional hypothetical value of 212.7475. The profit quantiles, which are a way to measure the range of possible profits, were -34.497646045266166, -5.857435349856291, and 29.76142146518492. The probability of loss was 0.6446, and the probability of a profit of 349 was 0. The drawdown quantiles, which are a way to measure the range of possible losses, were 7.63048238860452, 15.56292293284185, and 18.583605919065437 percent. The one window mean profit, which is the average profit over a certain period, was -0.4567188189971941. The one window profit quantiles were -6.109028058977542, -2.988840971523219, and 6.063730409872929. The exit frequencies, which are a way to measure how often a position is closed, were 0.43333333333333335 for a stop, which is a type of order to sell a security, 0.2 for a time, which is a type of order to sell a security at a certain time, 0.18333333333333332 for a target, which is a type of order to sell a security at a certain price, 0.1 for a target gap, which is a type of order to sell a security at a certain price with a certain gap, and 0.08333333333333333 for a stop gap, which is a type of order to sell a security at a certain price with a certain gap. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline 'SPY QOE90906 MonteCarlo SPY'. This refers to a simulation, called a Monte Carlo simulation, which is a method of modeling random events. The simulation used 20,000 paths and 12 monthly events from 20 holdout quarter blocks, sampled 4 quarters with replacement jointly across 3 assets. This means the simulation looked at how 3 assets might perform together over time. The simulation preserves 3 month serial and cross asset dependence, which means it takes into account how the assets have performed in relation to each other in the past. It assumes the future will be similar to the past, which is called stationarity, and does not model extreme future events, called future tails. The simulation used individual hypothetical positions of 212.7475 USD and equal sleeve separate positions of 245.69 USD as a thought experiment. The actual size of the positions is 0, meaning this is a theoretical exercise. The results show a probability of loss of 0.74905 and a probability of profit of 349 of 0, meaning it is not impossible but very unlikely to make a profit of 349. The simulation also calculated various metrics, including profit quantiles, drawdown quantiles, and exit frequencies. The profit quantiles are -28.74486851055603, -7.303961254082509, and 14.223307770825425. The drawdown quantiles are 6.077498682233079, 12.787008744071215, and 15.80555221784562. The one window mean profit is -0.6266033802530944 and the one window profit quantiles are -6.235260465493601, -1.7290266423373888, and 5.118839600464831. The exit frequencies are 0.4 for stop, 0.23333333333333334 for time, 0.18333333333333332 for target, 0.1 for stop gap, and 0.08333333333333333 for target gap. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

A Monte Carlo simulation was run on the OEF QOE90906 with 20,000 paths and 12 monthly events. The simulation used data from 20 holdout quarter blocks, sampling 4 quarters with replacement across 3 assets. This method preserves 3-month serial and cross-asset dependence, assuming stationarity, but does not model future tail events. The simulation used individual hypothetical positions of $212.7475 and an equal sleeve of $245.69 for a thought experiment. The actual size is noted as 0, indicating it's a theoretical exercise. The results show a probability of loss of 0.68615 and a probability of profit of 349 at 0. The simulation also calculated various metrics, including profit quantiles, drawdown quantiles, and exit frequencies. A news scan found the following data: a dictionary with keys including paths, months, notional_hypothetical, profit_quantiles, prob_loss, prob_profit349, drawdown_quantiles_pct, one_window_mean_profit, one_window_profit_quantiles, and exit_frequencies. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline about the IWM QOE90906 indicator and its worst trade percentage. The IWM indicator was measured on September 9, with a fixed management period from 2021 to 2025, and a 6 basis point per side fee, using 60 third-Friday windows per exchange-traded fund, which is a type of investment fund that trades on a stock exchange like a stock. The indicator used a lagged 200-day simple moving average, which is a way to smooth out price data over time, a 5-session momentum measure, which looks at the speed of price changes, and an RV20 measure, which is a type of risk measurement. The high and low risk volatility threshold was set at the development median, meaning the middle value of a set of numbers, with no filter selected from the holdout, which is a set of data used to test the indicator. The results are described as pre-2023 and post-2023. The worst trade percentage was -3.3326290969262296. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

A news scan found the text: Measured Sep 9; fixed managed 2021–2025, 6 basis points per side, 60 third-Friday windows per exchange-traded fund. This uses a lagged 200-day simple moving average, a 5-session momentum indicator, and a 20-day realized volatility indicator. The high and low realized volatility threshold is the median from development data; no filter was selected from the holdout data. The data is descriptive, split into pre-2023 and post-2023 periods. 6 https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

The IWM QOE90906 indicator was measured on September 9. It was fixed and managed from 2021 to 2025, with a 6 basis point per side fee, and 60 third-Friday windows per exchange-traded fund. The indicator used a 200-session simple moving average, 5-session momentum, and a 20-session realized volatility, which is a measure of how much the price of a security moves. The high and low realized volatility threshold is based on the median of the development data, with no filter selected from the holdout data. The data is descriptive for the periods before and after 2023. The result is 2.95. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

The IWM QOE90906 indicator was measured on September 9. It was fixed and managed from 2021 to 2025, with a 6 basis point cost per side, and 60 third-Friday windows per exchange-traded fund. The indicator used a 200-day simple moving average, a 5-session momentum, and a 20-day realized volatility, which is a measure of how much the price of a security moves. The high and low threshold for realized volatility is the median from the development period, with no filter selected from the holdout period. The data is descriptive, comparing the periods before and after 2023. The indicator settings include a stop at 26, a time of 12, a target of 11, a target gap of 6, and a stop gap of 5. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

A news scan found the following data: Measured on September 9, the IWM QOE90906 indicator used a fixed management period from 2021 to 2025, with a 6 basis point cost per side, and 60 third-Friday windows per ETF. This indicator used a lagged 200-day Simple Moving Average, a 5-session momentum, and a 20-day Realized Volatility, referred to as RV20, which is a measure of how much the price of a security has moved over a given time period. The high and low RV threshold was set to the median of the development data, with no filter selected from the holdout data. The data is descriptive for the periods before and after 2023. The signal correlations are as follows: the correlation between the signal and the return is 1, the correlation between the signal and the realized volatility is -0.19215934353199307, and the correlation between the signal and the momentum is -0.17820655288574042. The correlation between the return and the realized volatility is -0.19215934353199307, the correlation between the return and the momentum is -0.17820655288574042, the correlation between the realized volatility and the momentum is 0.15213127479603955, the correlation between the realized volatility and itself is 1, and the correlation between the momentum and itself is 1. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

The IWM QOE90906 indicator was measured on September 9. It is a fixed strategy that was managed from 2021 to 2025, with a 6 basis point cost per side, and 60 third-Friday windows per exchange-traded fund. The indicator uses a lagged 200-day simple moving average, which is a type of market trend indicator, 5-session momentum, and RV20, which is a measure of volatility. The high and low RV threshold is set at the development median, with no filter selected from the holdout, which is a part of the data set used for testing. The data is descriptive for the periods before and after 2023. The results show the following statistics: the mean percentage change is -0.0657, the p-value is 0.5, the win percentage is 1.7247, the loss percentage is 1.8561, and the quarter Kelly criterion, which is a measure of risk, is 0. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

The IWM QOE90906 indicator was measured on September 9. It is a fixed strategy that was managed from 2021 to 2025, with a 6 basis point cost per side, and 60 third-Friday windows per exchange-traded fund, which is a type of investment fund that trades on a stock exchange. The indicator used a 200-day simple moving average, which is a way to smooth out price data, and 5-session momentum, which measures the speed of price changes, and RV20, which is a measure of volatility, or how much prices fluctuate. The high and low volatility threshold is set at the median, or middle value, of the development data, with no filter selected from the holdout data, which is a portion of the data set aside for testing. The results are described for the periods before and after 2023. The results show the following statistics: the number of trades is 2, the average percentage change is -1.444619886616545, the p-value is 0, the win percentage is 0, the loss percentage is 1.444619886616545, and the quarter Kelly criterion, which is a measure of risk, is 0. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

The IWM QOE90906 indicator was measured on September 9. It is a fixed strategy that was managed from 2021 to 2025, with a 6 basis point cost per side, and 60 third-Friday windows per exchange-traded fund. The indicator uses a lagged 200-day simple moving average, which is a calculation of the average price of a stock over the past 200 days, 5-session momentum, which measures the speed of price changes over 5 sessions, and RV20, which is a measure of volatility. The high and low volatility threshold is set at the development median, which is the middle value of a set of data. No filter was selected from the holdout data, which is a portion of data set aside for testing. The data is descriptive for the periods before and after 2023. The results show the following statistics: there were 58 data points, the mean percentage change was -0.1723, the p-value was 0.4655, the win percentage was 1.7937, the loss percentage was 1.8846, and the quarter Kelly criterion, which is a measure of risk, was 0. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

A news scan found the data line for the IWM QOE90906 indicator, which is a set of instructions for an automated trading fund manager. The indicator was measured on September 9 and is based on a fixed management system from 2021 to 2025, with a 6 basis point cost per side and 60 third-Friday windows per exchange-traded fund, which is a type of investment fund. The system uses a lagged 200-day simple moving average, which is a way to smooth out price changes, and a 5-session momentum measure, which looks at price changes over a short period. It also uses a realized volatility measure over 20 days, which is a way to measure how much prices are changing. The high and low threshold for this measure is based on the development median, which is a middle value. No filter was selected from the holdout data, which is a set of data not used for training. The data is descriptive for the periods before and after 2023. The result is 0.0092793136679547. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

The IWM QOE90906 indicator was measured on September 9. It was fixed and managed from 2021 to 2025, with a 6 basis point cost per side and 60 third-Friday windows per exchange-traded fund, which is a type of investment fund. The indicator used a lagged 200-day simple moving average, which is a way to smooth out price changes, and 5-session momentum, which measures price changes over a short period, and RV20, which likely refers to a 20-day realized volatility measure, showing how much prices actually changed. The high and low threshold for the indicator was set at the median, or middle value, of a development set, with no filter applied from a holdout set, which is a group of data not used for training. The data is descriptive for the periods before and after 2023. The results include the following statistics: there were 36 observations, the mean percentage change was 0.33861657697635467, the p-value was 0.5833333333333334, the win percentage was 1.690629001118571, the loss percentage was 1.5542008168227484, and the quarter Kelly criterion, which is a measure of risk, was 0.05007257310035433. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline is not available, but a data line was found. Measured on September 9, the IWM QOE90906 indicator was fixed and managed from 2021 to 2025, with a 6 basis point cost per side and 60 third-Friday windows per exchange-traded fund, which is a type of investment fund that trades on a stock exchange like a stock. The indicator used a lagged 200-day simple moving average, which is a way to smooth out price changes over time, a 5-session momentum measure, which looks at the speed of price changes, and RV20, which is a measure of volatility, or how much prices fluctuate. The high and low volatility threshold is set at the median, or middle value, of the development data, with no filter selected from the holdout data, which is a portion of the data set aside for testing. The data is descriptive of the time periods before and after 2023. The results include the following statistics: the mean percentage change was -1.0446160357452572, the p-value was 0.25, the win percentage was 2.1545455908678552, the loss percentage was 2.1110032446162945, and the quarter Kelly criterion, which is a measure of investment performance, was 0. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

The IWM QOE90906 indicator was measured on September 9. It is a fixed strategy managed from 2021 to 2025, with a 6 basis point cost per side, and 60 third-Friday windows per exchange-traded fund. This strategy uses a lagged 200-day simple moving average, a 5-session momentum indicator, and a 20-day realized volatility indicator. The high and low volatility threshold is set at the development median, with no filter selected from the holdout sample. The results are described pre-2023 and post-2023. A news scan found the following data: the indicator has 33 data points, with a mean percentage change of -0.0812, a p-value of 0.4545, a win percentage of 2.0403, a loss percentage of 1.8492, and a quarter Kelly criterion of 0. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

The IWM QOE90906 indicator was measured on September 9. It is a fixed strategy managed from 2021 to 2025, with a 6 basis point cost per side, and 60 third-Friday windows per ETF. The indicator uses a lagged 200-day simple moving average, which is a calculation of the average price of a stock over the past 200 days, 5-session momentum, which measures the speed of price changes over 5 sessions, and RV20, which is a measure of volatility. The high and low volatility threshold is set at the development median, with no filter selected from the holdout, which is a portion of data set aside for testing. The data is descriptive for the periods before and after 2023. The results show the following statistics: there are 27 data points, the mean percentage change is -0.3777846491772612, the p-value is 0.4444444444444444, the win percentage is 1.4854894776825334, the loss percentage is 1.8684039506650967, and the quarter Kelly criterion, which is a measure of risk, is 0. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

The IWM QOE90906 indicator showed a downtrend measured on September 9. The indicator was fixed and managed from 2021 to 2025 with a 6 basis point per side and 60 third-Friday windows per exchange-traded fund. It used a lagged 200-day simple moving average, which is a way to smooth out price changes over time, 5-session momentum, which measures price changes over a short period, and RV20, a measure of volatility. The high and low threshold for RV, or realized volatility, was set at the development median, which is the middle value of a set of numbers. No filter was selected from the holdout, which is a set of data not used to train the indicator. The results are described as pre-2023 and post-2023. The indicator's performance is as follows: it had a mean percentage change of -0.17075551581538304, a p-value of 0.5, a win percentage of 1.8122509320685618, a loss percentage of 2.153761963699328, and a quarter Kelly criterion of 0. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

The IWM QOE90906 indicator showed an uptrend measured on September 9. The indicator was fixed and managed from 2021 to 2025 with a 6 basis point per side and 60 third-Friday windows per exchange-traded fund. It used a lagged 200-day simple moving average, which is a way to smooth out price data over time, 5-session momentum, which measures price changes over a short period, and RV20, a measure of volatility. The high and low volatility threshold is based on the development median, which is a middle value. No filter was selected from the holdout, which is a set of data not used in training. The data is descriptive for pre-2023 and post-2023 periods. The results are as follows: the number of observations is 40, the mean percentage change is -0.2366, the p-value is 0.425, the win percentage is 1.7828, the loss percentage is 1.7293, and the quarter Kelly criterion, a measure of risk, is 0. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

A news scan found the headline about the SPY QOE90906 indicator and its worst trade percentage. Measured on September 9, the indicator was fixed and managed from 2021 to 2025, with a 6 basis point cost per side and 60 third-Friday windows per exchange-traded fund, which is a type of investment fund. The indicator used a lagged 200-day simple moving average, which is a way to smooth out price changes, and 5-session momentum, which measures price changes over a short period, and RV20, which is a measure of volatility, or how much prices change. The high and low threshold for RV, or realized volatility, was set at the median, or middle value, from a development set, with no filter selected from a holdout set, which is a way to test the indicator. The results are described as pre-2023 and post-2023. The worst trade percentage was -2.9877007192556904. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

A news scan found the text: Measured Sep 9; fixed managed 2021–2025, 6 basis points per side, 60 third-Friday windows per exchange-traded fund. This uses a lagged 200-day simple moving average, a 5-session momentum indicator, and a realized volatility indicator over 20 days. The high and low realized volatility threshold is the median from development data; no filter was selected from the holdout data. The data is descriptive for the periods before and after 2023. The number 5 is also mentioned. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

Measured Sep9; fixed managed2021–2025,6bp/side,60third-Friday windows perETF. Lagged200SMA,5sessionmomentum andRV20. High/lowRV threshold is development median; no filter selected from holdout. Pre2023/post2023 descriptive. {"stop":24,"time":14,"target":11,"stop_gap":6,"target_gap":5} https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all

Measured Sep9; fixed managed2021–2025,6bp/side,60third-Friday windows perETF. Lagged200SMA,5sessionmomentum andRV20. High/lowRV threshold is development median; no filter selected from holdout. Pre2023/post2023 descriptive. {"r":{"r":1,"rv":-0.20146595154215996,"mom":-0.16258189890520836},"rv":{"r":-0.20146595154215996,"rv":1,"mom":0.09305785631293405},"mom":{"r":-0.16258189890520836,"rv":0.09305785631293405,"mom":1}} https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=OEF,SPY,IWM&timeframe=1Day&feed=sip&adjustment=all