Notes

A news scan found the following data: on September 27, 2021, there were four trades for CNXC91106 with the following metrics: the entry date was September 20, 2021, and the exit date was September 24, 2021, with an entry price of 146.89 and an exit price of 151.66. The metrics for each trade were as follows: the first trade had a slippage of 25 basis points, or 0.25%, and no barrier, the second trade had a slippage of 45 basis points, or 0.45%, and no barrier, the third trade had a slippage of 25 basis points, or 0.25%, and a barrier, and the fourth trade had a slippage of 45 basis points, or 0.45%, and a barrier. All trades had a net return, which is the return after fees, of either 0.0263 or 0.0222, and the reason for exit was time, meaning the trade was closed after a certain time period. The stock was not in a bull market, but the overall market was in a bull market, meaning prices were generally rising. The momentum, or rate of change, of the stock price over 20 days was 0.0281, and the moving average distance, which is the difference between the stock price and its average price over a certain period, was -0.0219. The realized volatility, or actual price movement, over 20 days was 0.2334, and the benchmark return, which is the return of a comparison investment, was 0.0208. The maximum favorable excursion, or highest price reached during the trade, was 1.3877, and the maximum adverse excursion, or lowest price reached during the trade, was -0.8300. The data was computed on September 11, 2026, and includes net decimal returns, fees of 5 basis points, and annual decimal realized volatility. The data does not represent actual fund trades. https://ir.concentrix.com/news/news-details/2021/Concentrix-Schedules-Release-of-Fiscal-Third-Quarter-2021-Financial-Results-and-Webcast-of-Investor-Conference-Call-09-07-2021/default.aspx ; https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data line for the CNXC91106 event on 2021-09-27: the event had multiple trades with the same metrics. Each trade had a k value of 3, an entry date of 2021-09-22, an exit date of 2021-09-24, an entry price of 146.44, and an exit price of 151.66. The average daily range, or adr, was 4.230999999999997. The reason for exiting the trade was time. The trades had different slippage values, which refer to the difference between expected and actual trade prices, and barrier values, which refer to a price level that triggers a trade. The slippage values were 25 and 45 basis points, or bp, which is a unit of measurement for percentages. The net returns were 0.029450715962236806 and 0.025341086124726964. The stock was not in a bull market, but the overall market was in a bull market. The momentum over 20 days, or mom20, was -0.01030718112158413, and the moving average distance, or ma_distance, was -0.0481904532100339. The realized volatility over 20 days, or rv20, was 0.24030411201977556. The benchmark return was 0.01802705280923611. The maximum favorable return, or mfe_R, was 1.394469392578589, and the maximum adverse return, or mae_R, was -0.47270148900969067. This data was computed on 2026-09-11, and the net returns are in decimal form, with fees of 5 basis points. The realized volatility is annualized and in decimal form, and these trades are not from a fund. https://ir.concentrix.com/news/news-details/2021/Concentrix-Schedules-Release-of-Fiscal-Third-Quarter-2021-Financial-Results-and-Webcast-of-Investor-Conference-Call-09-07-2021/default.aspx ; https://runway.adityaperswal.workers.dev/data/stock-bars

A data scan found the following metrics for the CNXC91106 event on 2021-06-23: the event had four different scenarios, each with the following characteristics: a k value of 10, which refers to a specific trading strategy parameter, entry date of 2021-06-09, exit date of 2021-06-22, entry price of 136.66, and exit price of 139.45. The scenarios differed in their barrier, which refers to a price level that triggers a trade, and slippage_bp, which refers to the percentage of price movement due to the trade itself, values: one scenario had no barrier and 25 slippage_bp, another had no barrier and 45 slippage_bp, one had a barrier and 25 slippage_bp, and the last had a barrier and 45 slippage_bp. The reason for exit was time, meaning the trade was closed after a certain time period. Other metrics included adr, or average daily return, of 4.8835, net returns ranging from 0.0103 to 0.0143, stock_bull, indicating the stock was performing well, and market_bull, indicating the overall market was not performing well, both set to true and false respectively. The mom20, or momentum over 20 periods, was -0.0184, ma_distance, or distance from the moving average, was 0.0071, rv20, or realized volatility over 20 periods, was 0.3259, and benchmark return was 0.0031. The mfe_R, or maximum favorable excursion return, was 1.8368, and mae_R, or maximum adverse excursion return, was -0.8826. These metrics were computed on 2026-09-11, with net decimal returns, fees of 5 basis points, and RV annual decimal, and do not represent actual fund trades. https://ir.concentrix.com/news-releases/news-release-details/concentrix-schedules-release-fiscal-second-quarter-2021/ ; https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: on 2021-06-23, metrics for the CNXC91106 event were reported. The event had the following details: the stock was bought on 2021-06-16 and sold on 2021-06-22 at prices of 135.74 and 139.45 respectively. The average daily range, or the average amount the stock price moved each day, was 4.264999999999999. The reason for selling the stock was because a certain amount of time had passed, which is referred to as a time exit. The net return, or profit, was 0.021186117812361127 and 0.01710948075306362 for two different scenarios. The stock was considered to be in a bull market, meaning its price was rising, but the overall market was not. The momentum, or rate of change, of the stock price over 20 days was 0.0021361225692400065. The moving average distance, which is the difference between the stock price and its average price over a certain period, was 0.006164188542078897. The realized volatility, or the actual amount the stock price moved, over 20 days was 0.25851887138847585. The benchmark return, which is the return of a comparison stock or index, was -0.00032864799271914436. The maximum favorable excursion, which is the maximum amount the stock price moved in a favorable direction, was 2.318874560375144. The maximum adverse excursion, which is the maximum amount the stock price moved in an unfavorable direction, was -0.5416178194607275. These metrics were computed on 2026-09-11 and include net decimal returns and fees of 5 basis points. The realized volatility is annualized, meaning it is adjusted to reflect a full year. These trades were not made by a fund. https://ir.concentrix.com/news-releases/news-release-details/concentrix-schedules-release-fiscal-second-quarter-2021/ ; https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: on June 23, 2021, metrics were reported for the CNXC91106 event. The data included four sets of information, each with the following details: the entry date was June 18, 2021, and the exit date was June 22, 2021, with an entry price of 138.22 and an exit price of 139.45. The average daily range, or the average amount the stock price moved each day, was 4.3555. The reason for the trade was time. The stock was considered to be in a bull market, meaning its price was expected to rise, but the overall market was not considered to be in a bull market. The momentum over 20 days, or the rate of change of the stock price over that time, was 0.0454, and the distance from the moving average, which is the average stock price over a certain period, was 0.0260. The realized volatility over 20 days, or the actual amount the stock price moved over that time, was 0.2578, and the benchmark, or the standard against which the stock's performance is measured, was 0.0144. The maximum favorable excursion, which is the maximum amount the stock price moved in a favorable direction, was 1.7013, and the maximum adverse excursion, which is the maximum amount the stock price moved in an unfavorable direction, was -0.3628. The net returns were 0.0029 and -0.0011, depending on the slippage, which is the difference between the expected and actual prices, and the barrier, which is a price level that, if reached, triggers a trade. The slippage was 25 and 45 basis points, or 0.25 and 0.45 percent. The data was computed on September 11, 2026, and included net decimal returns, fees of 5 basis points, and annual decimal realized volatility. The data did not represent actual trades of a fund. https://ir.concentrix.com/news-releases/news-release-details/concentrix-schedules-release-fiscal-second-quarter-2021/ ; https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: on 2021-03-24, metrics for the CNXC91106 event were reported. The event had the following details: the stock was bought on 2021-03-10 at a price of 121.66 and sold on either 2021-03-23 at a price of 115.43 or 2021-03-22 at a price of 116.6635. The reason for selling was either time or a stop, which is a pre-set price level to limit losses. The average daily range, or the average difference between the high and low prices, was 4.9965. The net return, which is the profit or loss after fees, was between -0.0468 and -0.0606. The stock was considered to be in a bull market, meaning its price was rising, but the overall market was not. The momentum, or rate of change, of the stock price over 20 days was 0.2123. The moving average distance, which is the difference between the stock price and its average price over a certain period, was 0.1373. The realized volatility, or the actual fluctuation in price, over 20 days was 0.3790. The benchmark return, which is the return of a comparison investment, was 0.0031. The maximum favorable excursion, which is the maximum profit during the investment, was 1.8533, and the maximum adverse excursion, which is the maximum loss during the investment, was -1.4890. The data was computed on 2026-09-11, and the net decimal returns and fees were 5 basis points, which is a unit of measurement for interest rates and investment returns. The annual decimal return for the realized volatility was also reported. https://ir.concentrix.com/news/news-details/2021/Concentrix-Schedules-Release-of-Fiscal-First-Quarter-2021-Financial-Results-and-Webcast-of-Investor-Conference-Call-03-04-2021/default.aspx ; https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: on 2021-03-24, metrics for CNXC91106 were reported. The data included four trades with the following details: the trades had a k value of 5, which refers to a specific trading strategy, and different slippage values, measured in basis points, which is a unit of measurement for interest rates and investment returns. Two trades had a slippage of 25 basis points and two had a slippage of 45 basis points. The entry date for all trades was 2021-03-17 and the exit dates were 2021-03-23 for two trades and 2021-03-17 for the other two trades. The entry price was 128.07 and the exit prices were 115.43 for the two trades that exited on 2021-03-23 and 122.3025 for the two trades that exited on 2021-03-17. The average daily range, or adr, was 5.7675, which is a measure of the average daily price movement. The reason for exit was time for the two trades that exited on 2021-03-23 and stop for the two trades that exited on 2021-03-17, where stop refers to a stop-loss order, which is an order to sell a security when it falls to a certain price. The net returns were -0.1041, -0.1077, -0.0507, and -0.0545, which are decimal values representing the percentage return on investment. The stock was considered bullish, meaning it was expected to increase in value, but the market was not, and the momentum, or mom20, was 0.2859, which is a measure of the rate of change of a security's price. The moving average distance, or ma_distance, was 0.1375, which is a measure of the difference between the security's price and its moving average. The realized volatility, or rv20, was 0.3927, which is a measure of the security's price movements over a certain period. The benchmark return was -0.0092, which is a measure of the return of a reference portfolio. The maximum favorable excursion, or mfe_R, was 0.4543, which is a measure of the maximum gain from the trade, and the maximum adverse excursion, or mae_R, was -2.4014, which is a measure of the maximum loss from the trade. The data was computed on 2026-09-11 and included net decimal returns and fees of 5 basis points. The realized volatility was annualized and represented as a decimal value. The trades were not actual fund trades. https://ir.concentrix.com/news/news-details/2021/Concentrix-Schedules-Release-of-Fiscal-First-Quarter-2021-Financial-Results-and-Webcast-of-Investor-Conference-Call-03-04-2021/default.aspx ; https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: on 2021-03-24, metrics for CNXC91106 were reported for four trades. The trades had the following characteristics: they were all made with a k value of 3, which is a measure of a trade's parameters, and they all started on 2021-03-19 and ended on 2021-03-23. Two of the trades had a barrier, which is a price level that, if reached, triggers a trade, and two did not. The trades also had different slippage values, which is the difference between the expected price of a trade and the actual price, measured in basis points, with values of 25 and 45. All trades entered at a price of 120.33 and exited at a price of 115.43. The reason for exiting the trades was time, meaning they were ended after a certain period. The average daily range, or adr, which is the average difference between the high and low prices of a stock over a certain period, was 6.28. The net return, which is the return after fees, was -0.04645979900293673 for two trades and -0.05026638945017292 for the other two. The stock was considered to be in a bull market, meaning its price was rising, but the overall market was not. The momentum, or mom20, which is a measure of a stock's price movement over 20 days, was 0.18935376153997252, and the moving average distance, or ma_distance, which is the difference between a stock's price and its moving average, was 0.055558461028886175. The realized volatility, or rv20, which is a measure of a stock's price movement over 20 days, was 0.4400483694577791. The benchmark return, which is the return of a comparison stock or index, was -0.0006608111456813948. The maximum favorable excursion, or mfe_R, which is the maximum amount a trade was in the money, was 0.38853503184713345, and the maximum adverse excursion, or mae_R, which is the maximum amount a trade was losing money, was -0.9729299363057325. The data was computed on 2026-09-11, and the net returns were given as decimal values, with fees of 5 basis points. The realized volatility was also given as an annual decimal value, and the data did not represent actual trades made by a fund. https://ir.concentrix.com/news/news-details/2021/Concentrix-Schedules-Release-of-Fiscal-First-Quarter-2021-Financial-Results-and-Webcast-of-Investor-Conference-Call-03-04-2021/default.aspx ; https://runway.adityaperswal.workers.dev/data/stock-bars

On September 10, the close was 54.41, the prior 20-day high was 55.20, the Simple Moving Average of 50 days, or SMA50, was 45.5232, and the Average Daily Range of 20 days, or ADR20, was 1.690275. The 20-day annual volatility was 0.3578195092, which resulted in a signal of false. There were 14 sessions with less than 26 Regular Trading Hours, or RTH, bars on the following dates: 2021-04-19 with 1 bar, 2021-10-25 with 1 bar, 2021-11-26 with 15 bars, 2022-01-24 with 5 bars, 2022-03-08 with 1 bar, 2022-11-25 with 15 bars, 2023-07-03 with 15 bars, 2023-11-24 with 16 bars, 2024-07-03 with 17 bars, 2024-11-29 with 15 bars, 2024-12-24 with 15 bars, 2025-07-03 with 18 bars, 2025-11-28 with 16 bars, and 2025-12-24 with 15 bars. Some dates are expected to have shortened sessions, but no reconciliation with the exchange calendar was performed. The data for extreme days with only 1 or 5 bars is unknown and does not provide continuous 15-minute proof. All modeled entries start with the 09:30 bar. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=LPG&timeframe=15Min&feed=sip&adjustment=split

A news scan found the following data about CNXC91106 on 2021-03-24: the system made three trades. The first trade had a slippage of 25 basis points, which is a measure of the difference between expected and actual trade prices, and it entered the market on 2021-03-19 at a price of 120.33 and exited on 2021-03-23 at a price of 115.43. The average daily range, which is the average difference between high and low prices, was 6.28. The reason for exiting the trade was time, meaning a predetermined time limit was reached. The net result was a loss of 0.0465, or 4.65 percent. The stock was considered to be in a bull trend, meaning its price was rising, but the overall market was not. The momentum over 20 days was 0.1894, which measures the speed of price changes, and the distance from the moving average, which is a line that smooths out price changes, was 0.0556. The realized volatility over 20 days was 0.4400, which measures actual price fluctuations. The benchmark result was a loss of 0.0007, or 0.07 percent. The maximum favorable excursion, which is the highest price reached during the trade, was 0.3885, or 38.85 percent, and the maximum adverse excursion, which is the lowest price reached, was -0.9729, or -97.29 percent. The second trade had a slippage of 45 basis points and the same entry and exit dates and prices as the first trade. The third trade had a barrier, meaning a price level that, if reached, would trigger a trade, and a slippage of 25 basis points, and the same entry and exit dates and prices as the first trade. https://ir.concentrix.com/news/news-details/2021/Concentrix-Schedules-Release-of-Fiscal-First-Quarter-2021-Financial-Results-and-Webcast-of-Investor-Conference-Call-03-04-2021/default.aspx ; https://runway.adityaperswal.workers.dev/data/stock-bars

A computer program tested a trading strategy on the stock LPG. The program used a method called breakout, which is a way to decide when to buy or sell, and it looked at the last 20 days of data to make decisions. The test ran for 2000 days and used rules to stop losses at 8 percent and take profits at 24 percent. The test results showed 1372 price changes, 102 trades, a return of 74.13259941 percent, a biggest loss of 13.36461095 percent, and a win rate of 38.23529412 percent. For comparison, simply buying and holding the stock would have given a return of 306.80882903 percent. The average trade made a profit of 0.62576532 percent. This test used data from IEX and did not validate the results independently or consider the size of the trades. The test also used its own rules to exit trades, rather than a separate signal. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=LPG&feed=iex

A news scan found the headline 'LPG R91106 completed-only raw holdout metrics'. The metrics are for the period from September 10, 2025, to September 10, 2026. During this time, there were 12 completed trades. The results of these trades, when combined, showed a gain of 21.73642708 percent. Of these trades, 58.333333 percent were winners, with an average gain of 2.02234159 percent. In stressful conditions, the results were a gain of 13.30909177 percent, with 50 percent of trades being winners, and an average gain of 1.41426211 percent. As of August 18, there was one unfinished trade that had been open for 17 sessions. By September 10, the net value had increased by 11.51107868 percent, or by 10.84400675 percent if stressful conditions were excluded. When including the value of the unfinished trade, the total gain was 35.74960299 percent or 25.59633734 percent. The largest decline in value, known as the drawdown, was 26.04481869 percent or 29.07742228 percent. The training data showed a gain of 10.25087765 percent under normal conditions and a loss of 8.32795666 percent under stressful conditions. These metrics do not take into account the actual cash available for reinvestment or the final prices at which trades were made. https://runway.adityaperswal.workers.dev/data/stock-bars?symbols=LPG&timeframe=15Min&feed=sip&adjustment=split

A news scan found the following hashes for files: the file bars.json has a hash of 917e6880861699d5205ae818148c224449dbaee28552b9a1808e18ba05915173, the file test_vm.py has a hash of b3521cfb6f39fc41907760ac216645d9d270f5cea9e11916c84447834c1c8f98, the file results.json has a hash of def99176a73ecb72fe541d3637a849dca67f5a5cc6811d95e5e0566e85935426, and the file inference.py has a hash of 3c190dbbae2043376e4be7ce5b1eda08012c67092622d32b08e6095821a002b5. This was measured on September 11, and it was noted that the primary empirical inference was frozen and not forecast. https://runway.adityaperswal.workers.dev/data/stock-bars ; research/inference.py

A news scan found the correlation data for 2022: the SPY stock has a correlation of 1 with itself, 0.8624812876997651 with EFA, 0.710881576391769 with EEM, 0.08490518149170549 with TLT, and 0.19437033055580202 with GLD. The EFA stock has a correlation of 0.8624812876997651 with SPY, 1 with itself, 0.8229418417753886 with EEM, 0.09559542486120301 with TLT, and 0.31308272726595243 with GLD. The EEM stock has a correlation of 0.710881576391769 with SPY, 0.8229418417753886 with EFA, 1 with itself, 0.05331224488779405 with TLT, and 0.29100536042057085 with GLD. The TLT stock has a correlation of 0.08490518149170549 with SPY, 0.09559542486120301 with EFA, 0.05331224488779405 with EEM, 1 with itself, and 0.34265446952136064 with GLD. The GLD stock has a correlation of 0.19437033055580202 with SPY, 0.31308272726595243 with EFA, 0.29100536042057085 with EEM, 0.34265446952136064 with TLT, and 1 with itself. This data was measured on September 11 and is based on empirical inference, not a forecast. https://runway.adityaperswal.workers.dev/data/stock-bars ; research/inference.py

A correlation test was done on September 11. The results show how closely the prices of certain stocks and funds move together. The stocks and funds are SPY, EFA, EEM, TLT, and GLD. The correlation between them is as follows: SPY and EFA have a correlation of 0.758451592357553, SPY and EEM have a correlation of 0.6722159395237813, SPY and TLT have a correlation of 0.11834935545819468, SPY and GLD have a correlation of 0.14781949029978084, EFA and EEM have a correlation of 0.7876002845720026, EFA and TLT have a correlation of 0.21903565760089785, EFA and GLD have a correlation of 0.34808110044401414, EEM and TLT have a correlation of 0.1526060670661739, EEM and GLD have a correlation of 0.3837628971166462, and TLT and GLD have a correlation of 0.17729034764039708. This is a measurement, not a forecast, based on empirical inference, which means it is based on observed data, and the primary data was frozen, meaning it was not changed or updated. https://runway.adityaperswal.workers.dev/data/stock-bars ; research/inference.py

A simulation called VM9110600 was run with the following parameters: it used 10000 paths, had 21 block sessions, and a seed of 9110600. The fund started with 187.22 USD. The results showed that over 21 sessions, the profit and loss median ranged from -7.14047330736388 to 9.14849703139084, with a 1.125154853843443 median. There was a 0.4126 probability of loss over 21 sessions and 0 gain of 349 count. Over 252 sessions, returns ranged from -7.376897558668151 to 26.104634610707905 percent, with a median of 7.643081752785874 percent. The maximum drawdown, or largest loss from a peak, ranged from 7.191690568235187 to 13.960921829242853 percent, with a median of 13.960921829242853 percent. This data was measured on September 11 and is based on empirical inference, not a forecast, and the primary data is frozen. https://runway.adityaperswal.workers.dev/data/stock-bars ; research/inference.py

A news scan found the following data: an attribution test for GLD with a seed of 9110600 and 10000 three-month blocks. The test used half Kelly as a binary risk unit proxy, not an allocation method, and log wealth sizing was separate. The results included HAC regressions, which are a type of statistical analysis that stands for Heteroskedasticity and Autocorrelation Consistent, and are descriptive. The test measured the following: adapter beta was 0.22351920148388565, annual intercept percentage was 3.136744265647853, and intercept HAC t was 0.9294568376521414. Monthly beta was 0.495164279696505, annual intercept percentage was 4.221299849098135, and intercept HAC t was 1.1668790672879124. Constant beta was 0.8934671972248269, annual intercept percentage was -0.3925229446176951, and intercept HAC t was -1.3438249468134835. The monthly minus constant mean percentage per period was -0.4589406092176363, and the monthly minus constant confidence interval percentage per period was between -1.081790913100364 and 0.3603212788200001. The correlation between lag variance and current variance was 0.5702596348777869, and the correlation between lag variance and return was -0.14183169737114673. The variance AR1 slope was 0.5735739712277674, and the variance AR1 HAC t was 5.7516902692946585. The return on lag variance HAC t was -1.003554860434899. The test also identified two regimes: one with high variance being false, lasting 5 months, with an asset mean percentage of 2.091748670133846, an asset standard deviation percentage of 5.747157445649563, a managed mean percentage of 2.019369818712524, and a constant mean percentage of 1.865802575679405; and one with high variance being true, lasting 39 months, with an asset mean percentage of 2.1561790946447785, an asset standard deviation percentage of 5.217062946774644, a managed mean percentage of 1.352509083551276, and a constant mean percentage of 1.8899763404933685. The measurement was taken on September 11. https://runway.adityaperswal.workers.dev/data/stock-bars ; research/inference.py

A news scan found the raw trade data with a probability of 0.5227272727272727, a win-loss ratio of 1.7437437571504693, and a half-Kelly value of 0.12451075149577587, which is a binary risk-unit proxy. The mean percentage change was 1.156883181190205, with a mean win percentage of 4.645716001599482 and a mean loss percentage of 2.6642194316390024. The monthly fund data showed a probability of 0.5227272727272727, a win-loss ratio of 1.8924630688304855, and a half-Kelly value of 0.13526534278698155. The mean percentage change was 0.7539657674908142, with a mean win percentage of 2.7869879747326474 and a mean loss percentage of 1.4726776023454795. The trade mean confidence interval percentage was between -0.2881342249072965 and 2.3222796686171248, while the fund month mean confidence interval percentage was between 0.01373467667745678 and 1.4555121959554778. The reasons for trade decisions included time, gap stop, target, stop, and gap target. The target hit rate was 0.25, with a target Wilson 95 of 0.14574066080685744 and 0.39440849808414946. There were 16 partials, and the R quantiles were -1.959755413307422, -1.3046508896221773, 0.15738871032945762, 2.756317595246988, and 2.7815737898311736. The same day exits were 0, and the mean calendar days were 19.704545454545453. This data is from a September 11 measurement, using a seed of 9110600 and 10,000 three-month blocks. The half-Kelly value is not an allocation, but a binary risk-unit proxy, and log wealth sizing is separate. The HAC regressions are descriptive. https://runway.adityaperswal.workers.dev/data/stock-bars ; research/inference.py

The GLD fund's attribution analysis shows the following results: the adapter's beta is 0.34407744455387385, annual intercept percentage is -0.9131940158626164, and intercept HAC t is -0.2937257327549947. The monthly analysis has a beta of 0.6993729838228316, annual intercept percentage of -0.8997592156742243, and intercept HAC t of -0.3902269627410152. The constant analysis has a beta of 0.891720594891813, annual intercept percentage of -0.11579082233651371, and intercept HAC t of -1.6881293982451433. The monthly minus constant mean percentage point is -0.2166204083689447, with a confidence interval of -0.6013459502178562 to 0.1755379277895631. The correlation between lag variance and current variance is 0.1559189870926584, and the correlation between lag variance and return is 0.16280959466108585. The variance AR1 slope is 0.15538275284595088, with a HAC t of 2.3745860181116263. The return on lag variance HAC t is 1.5317803983212177. The regimes are as follows: one regime has low variance, lasts 12 months, with an asset mean percentage of 0.4873846949298044, asset standard deviation percentage of 3.9745062947810745, managed mean percentage of 0.48588903113111664, and constant mean percentage of 0.4157041221854729. Another regime has high variance, lasts 36 months, with an asset mean percentage of 0.8860077116600936, asset standard deviation percentage of 4.306554855552968, managed mean percentage of 0.47305214263676476, and constant mean percentage of 0.7852743234439056. This analysis is based on a September 11 measurement, with a seed of 9110600, and 10000 three-month blocks. The half Kelly is a binary risk unit proxy, not an allocation, and log wealth sizing is separate. HAC regressions are descriptive. https://runway.adityaperswal.workers.dev/data/stock-bars ; research/inference.py

A news scan found the raw trade data for the GLD fund with a probability of 0.4791666666666667, a win-loss ratio of 1.4300968246654404, and a half-Kelly value of 0.057486105946237376, which is a measure of binary risk. The mean percentage change was 0.39022782352469954, with a mean win percentage of 3.394105559086327 and a mean loss percentage of 2.373339693191998. The monthly fund data showed a probability of 0.4791666666666667, a win-loss ratio of 1.3245988137716957, and a half-Kelly value of 0.042982925753962425. The mean percentage change was 0.19983464724921177, with a mean win percentage of 2.3245817233694233 and a mean loss percentage of 1.7549326627813828. The trade mean confidence interval percentage was between -0.6187108737982553 and 1.2444438822666493, and the fund month mean confidence interval percentage was between -0.5278162184117247 and 0.839501250860123. The reasons for trade exits were stop losses, which occurred 19 times, time stops, which occurred 14 times, gap stops, which occurred 7 times, target hits, which occurred 5 times, and gap target hits, which occurred 3 times. The target hit rate was 0.16666666666666666, and the target Wilson 95 percentage was between 0.08695410039453222 and 0.29578100037396254. There were 12 partial trades, and the R quantiles were -1.692227471270397, -1.331577429736301, -0.5892282000623725, 2.7157358058627517, and 3.668527393305773. One trade had a same-day exit, and the mean calendar days per trade was 16.895833333333332. This data was measured on September 11, using a seed of 9110600 and 10,000 three-month blocks. The half-Kelly value is a binary risk unit proxy, not an allocation, and log wealth sizing is separate. HAC regressions are descriptive. https://runway.adityaperswal.workers.dev/data/stock-bars ; research/inference.py

A news scan found the following data: this is a test attribution for TLT VM9110600. The attribution includes an adapter with a beta of 0.28727918837873684, an annual intercept percentage of -4.1719994547878825, and an intercept HAC t of -1.725531422978228. The monthly attribution has a beta of 0.5840040736293871, an annual intercept percentage of -2.301737510044549, and an intercept HAC t of -1.1661324024074227. The constant attribution has a beta of 0.8931008315709146, an annual intercept percentage of -0.746205473729226, and an intercept HAC t of -1.0926298801278915. The monthly minus constant mean percentage point is -0.12311707750222696, with a confidence interval of -0.678661595442801 to 0.40531402648628134. The correlation between lagged variance and current variance is 0.4509539650913504, and the correlation between lagged variance and return is 0.24158811300427543. The variance AR1 slope is 0.41628732589189393, with a HAC t of 3.8629202147792965. The return on lagged variance HAC t is 1.3312122172633625. There are two regimes: one with high variance set to false, lasting 10 months, with an asset mean percentage of -0.04718678230574147, an asset standard deviation percentage of 3.0104450948192696, a managed mean percentage of -0.06690069903038998, and a constant mean percentage of -0.0580095749627918; and one with high variance set to true, lasting 34 months, with an asset mean percentage of -0.011651905611059122, an asset standard deviation percentage of 4.318516123485614, a managed mean percentage of -0.2455806176667414, and a constant mean percentage of -0.08886767150727069. This data is from a September 11 measurement, with a seed of 9110600 and 10000 three-month blocks. The half Kelly is a binary risk unit proxy, not an allocation, and log wealth sizing is separate. HAC regressions are descriptive. https://runway.adityaperswal.workers.dev/data/stock-bars ; research/inference.py

A news scan found the raw trade data with the following statistics: the probability of winning is 0.38636363636363635, the win-loss ratio is 1.284032890053771, and the mean percentage loss is -0.27452659080791236. The monthly fund data shows a probability of winning of 0.38636363636363635, a win-loss ratio of 0.9932709403848013, and a mean percentage loss of -0.3511272856472731. The trade mean confidence interval percentage is between -1.2089827292150432 and 0.7535874981654227, and the fund month mean confidence interval percentage is between -0.8267283107660485 and 0.1767716272584237. The reasons for trade exits are: stop loss 16 times, time 15 times, gap stop 10 times, and target 3 times. The target hit rate is 0.06818181818181818. The target Wilson 95 percent confidence interval is between 0.023458970172840127 and 0.1822532133661719. There are 8 partial trades, and the R quantiles are -1.5535137227171283, -1.3055367916879892, -1.0608043307292947, 2.5681412785272917, and 2.7653524050775. The same day exits are 0, and the mean calendar days are 15.931818181818182. This data is from a September 11 measurement with a seed of 9110600 and 10000 three-month blocks. The half Kelly is a binary risk unit proxy, not an allocation, and log wealth sizing is separate. HAC regressions are descriptive. https://runway.adityaperswal.workers.dev/data/stock-bars ; research/inference.py

A news scan found the following data: TLT VM9110600 train attribution. The attribution includes adapter, monthly, and constant components. The adapter has a beta of 0.18898920319319581, an annual intercept percentage of -3.971017804322722, and an intercept HAC t of -1.5293024063451097. The monthly component has a beta of 0.5344816406319213, an annual intercept percentage of 3.4447867043977163, and an intercept HAC t of 1.6522398081945386. The constant component has a beta of 0.8990896485416479, an annual intercept percentage of -0.14177507271437362, and an intercept HAC t of -1.8918033664943312. The monthly minus constant mean percentage point is 0.37305938237054187, with a confidence interval of -0.08586043078996769 to 0.9726493356885827. The correlation between lag variance and current variance is 0.04462492816416884, and the correlation between lag variance and return is -0.05081207419134459. The variance AR1 slope is 0.04468430259685598, with a HAC t of 0.7188267460323502. The return on lag variance HAC t is -0.5522330240943266. There are two regimes: one with high variance being false, lasting 11 months, with an asset mean percentage of 1.6057403691954197, an asset standard deviation percentage of 4.847595454332281, a managed mean percentage of 1.6193661900427088, and a constant mean percentage of 1.42123429841291; and one with high variance being true, lasting 37 months, with an asset mean percentage of -0.6868055066793897, an asset standard deviation percentage of 4.1687739202319625, a managed mean percentage of -0.19713549854731716, and a constant mean percentage of -0.62220035113808. This data is from a September 11 measurement, with a seed of 9110600, using 10000 three-month blocks, and a half Kelly binary risk unit proxy, which is not an allocation, but rather a measure of risk, and log wealth sizing is separate. HAC regressions are descriptive, meaning they are used to describe the relationships between variables, with HAC standing for Heteroskedasticity and Autocorrelation Consistent. https://runway.adityaperswal.workers.dev/data/stock-bars ; research/inference.py

A news scan found the raw trade data for TLT VM9110600, which includes a probability of 0.2708333333333333, a win-loss ratio of 1.3582093371950779, and a mean percentage change of -0.9172123763907651. The monthly fund data shows a probability of 0.2708333333333333, a win-loss ratio of 1.7623577587260084, and a mean percentage change of -0.35187396209676153. The trade mean confidence interval percentage is between -1.735295068249758 and -0.03360142317442397, while the fund month mean confidence interval percentage is between -0.7798694477865459 and 0.1740682865775698. The reasons for trade exits include 25 stop losses, 9 gap stops, 8 time stops, 5 targets, and 1 gap target. The target hit rate is 0.125, and the target Wilson 95 is between 0.05856971750400844 and 0.24700727086054822. There are 8 partials, and the R quantiles are -1.413164134902296, -1.1803605244198914, -1.0650782822396985, 2.6683140247275388, and 3.3389347150391493. The same day exits are 0, and the mean calendar days are 13.708333333333334. This data is from a September 11 measurement, using seed 9110600 and 10,000 three-month blocks. Half Kelly is a binary risk unit proxy, not an allocation, and log wealth sizing is separate. HAC regressions are descriptive. https://runway.adityaperswal.workers.dev/data/stock-bars ; research/inference.py

A news scan found the following data: the attribution results for EEM VM9110600 test are given. The adapter results show a beta of 0.3809806030909822, an annual intercept percentage of -3.5608608270545847, and an intercept HAC t of -0.854273444443563. Monthly results show a beta of 0.802969548618368, an annual intercept percentage of -0.11658285846390978, and an intercept HAC t of -0.04568083471415283. Constant results show a beta of 0.8592135509470493, an annual intercept percentage of -0.4103246131894796, and an intercept HAC t of -1.3570767130615387. Other results include a monthly minus constant mean percentage per period of -0.06393957342545054, a monthly minus constant confidence interval percentage per period of -0.5858323444733271 to 0.2789684510595115, a lag variance current variance correlation of 0.42869296578437954, a lag variance return correlation of 0.032974157692675296, a variance AR1 slope of 0.42821631854421616, a variance AR1 HAC t of 2.7433460526169378, and a return on lag variance HAC t of 0.18573220251596553. Regimes are also given, with two regimes: one with high variance false, 27 months, asset mean percentage of 2.5745674928308286, asset standard deviation percentage of 3.5301876417464753, managed mean percentage of 2.5066136470697624, and constant mean percentage of 2.167861259927719; and one with high variance true, 17 months, asset mean percentage of 0.03873472726572582, asset standard deviation percentage of 5.956204839121442, managed mean percentage of -0.6817767847511411, and constant mean percentage of 0.0217323731050349. This data is from a September 11 measurement, with a seed of 9110600 and 10000 three-month blocks. The half Kelly is a binary risk unit proxy, not an allocation, and log wealth sizing is separate. HAC regressions are descriptive. https://runway.adityaperswal.workers.dev/data/stock-bars ; research/inference.py