Notes

A news scan found the following data: On September 7, a calculation was done using a statistical method called Ordinary Least Squares, or OLS for short, which is a way to find the best fit line for a set of data. This calculation looked at the return on investment for the first half hour and the 12th return for the rest of the day for the ticker symbol EEM. The results showed a descriptive association, which means it describes a relationship but does not imply cause and effect, and used a method called HAC5, which is a way to correct for errors in the data. The returns were given as decimal numbers. The results were as follows: for the first set of data, the intercept was 0.0002861148274201484 and the beta, which is a measure of volatility, was 0.03676187782773016, with a HAC5 t-value of 1.5641244738118045 and 3.985971552599923, and an R2 value, which measures how well the model fits the data, of 0.060628292786570115. For the second set of data, the intercept was 0.00027039094117163625, the beta for the first return was 0.03582097377699645, and the beta for the 12th return was 0.16915325101536732, with HAC5 t-values of 1.4846553231311133, 3.9378278067207018, and 1.4498881961158447, and an R2 value of 0.10155580156310651. For the third set of data, the intercept was 0.0002767828597448005 and the beta for the rest of the day was 0.024845801007632114, with HAC5 t-values of 1.5090513405288424 and 2.572825417830551, and an R2 value of 0.035618870441375905. All three sets of data had a correlation coefficient, which measures the strength of the relationship, of 0.24622813159054335 for the first return and the last return. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: On September 7, a calculation was made using a statistical method called Ordinary Least Squares, or OLS, which is a way to find the best fit line for a set of data. This calculation looked at the return on investment for the EEM stock, which is a type of investment fund, over the last half hour and the first return and/or the 12th return for the rest of the day. The results showed a descriptive association, which means a relationship between the variables, but not causation, which means one variable does not directly cause the other. The returns were measured in decimal form. The results were as follows: for the first model, the intercept was 0.000027520262844514123 and the beta for the first return was -0.016425440843982796, with a HAC5 t-value of 0.6524754473441092 and -2.647112954973954, respectively, and an R2 value of 0.011241342209811322. For the second model, the intercept was 0.000028772240271428708, the beta for the first return was -0.016650617463735168, and the beta for the 12th return was 0.0987313213264456, with HAC5 t-values of 0.684652363094179, -2.787482416580704, and 1.8305478867135405, respectively, and an R2 value of 0.019659104293779373. For the third model, the intercept was 0.000029302502439510615 and the beta for the rest of the day was -0.010275817625934634, with a HAC5 t-value of 0.6893282160347943 and -1.8918356444343836, respectively, and an R2 value of 0.006154723187208444. The correlation between the first return and the last return was -0.1060251961083373 for all models. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: On September 7, a calculation was done using a method called Ordinary Least Squares, or OLS, which is a way to find the best fit line for a set of data. This calculation looked at the return on investment for the first half hour and the 12th return for the rest of the day for the ticker symbol EEM. The results are based on a statistical method called HAC5, which is used to understand how things are related, but not to prove that one thing causes another. The returns are given as decimal numbers. The calculation found the following results for the train set: for the first model, the intercept was -0.000003719475741544989 and the beta for the first return was 0.024879848934631934, with an R2 of 0.016324647057750385 and a correlation between the first return and the last return of 0.12776794221458834. For the second model, the intercept was -0.0000037626375105604467, the beta for the first return was 0.025036835884500095, and the beta for the 12th return was -0.027746219313515622, with an R2 of 0.016769720994585957 and the same correlation. For the third model, the intercept was -0.000007865558264136548 and the beta for the rest of the day was 0.02293508205197672, with an R2 of 0.019333044242150987 and the same correlation. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: On September 7, a calculation was done using a statistical method called Ordinary Least Squares, or OLS, which is a way to find the best fit line for a set of data. This calculation looked at the return on the SPY stock, which is a type of investment fund, over the last half hour and the rest of the day. The calculation also used a method called HAC5, which is a way to account for variability in the data. The results show the relationship between the returns, but do not imply cause and effect. The returns are shown as decimal numbers. The results are as follows: for the SPY stock, with 170 data points, the intercept, or starting point, and the first return, had a beta, or measure of change, of 0.00003808084305584512 and 0.014347746370045647, with a HAC5 t-value, which is a measure of statistical significance, of 0.26803135899371444 and 0.7432753321333443, and an R2, which is a measure of how well the model fits the data, of 0.0029154516431361133. Another calculation for the SPY stock, also with 170 data points, looked at the intercept, the first return, and the 12th return, and found a beta of 0.000048481192446250334, 0.014296370570782741, and 0.16631125933884194, with a HAC5 t-value of 0.3581974435416352, 0.7559567718035617, and 1.4547490415999824, and an R2 of 0.036419022559405545. A third calculation for the SPY stock, again with 170 data points, looked at the intercept and the rest of the day return, and found a beta of 0.00004692422136098132 and -0.0007509498546889387, with a HAC5 t-value of 0.3326586141235977 and -0.05226310036364114, and an R2 of 0.000014530645656707364. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: On September 7, a calculation was done using a statistical method called Ordinary Least Squares, or OLS, which is a way to find the best fit line for a set of data. This calculation looked at the return on the SPY stock, which is a type of investment fund, for the last half hour of the day and the first return and/or the 12th return for the rest of the day. The results are based on a method called HAC5, which is a way to calculate the standard error of the estimates, and are meant to show descriptive association, not causation, meaning they show how things are related, but not why. The returns are given as decimal numbers. The results are as follows: for the SPY stock, with a holdout sample size of 1245, the intercept and first return had a beta of -0.00006729389716341411 and -0.028105691953958897, respectively, and the HAC5 t-statistic was -0.8909465843894513 and -1.834869227583961, respectively, with an R2 of 0.005556990525373173, and the correlation between the first return and the last return was -0.07454522469865617. Another model with the same sample size and stock had a beta of -0.00006476604877979231, -0.0292262233320651, and 0.15329976633523298 for the intercept, first return, and 12th return, respectively, with an HAC5 t-statistic of -0.8516001675972809, -1.8963084233396355, and 2.621378055210914, respectively, and an R2 of 0.020447536297419022. A third model had a beta of -0.00008002213694805797 and 0.00021320619319778705 for the intercept and rest of day return, respectively, with an HAC5 t-statistic of -1.0629354094239696 and 0.020639414279396733, respectively, and an R2 of 6.940989014658783e-7. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following data: On September 7, a calculation was performed using a method called Ordinary Least Squares, or OLS, which is a statistical technique, to analyze the return on the SPY stock, which is a type of investment fund. The analysis looked at the relationship between the first half hour return and the rest of the day return, and also between the 12th return and the rest of the day return. The results are based on a type of statistical analysis called HAC5, which is used to understand how things are related, but does not imply cause and effect. The returns are given as decimal numbers. The results include three different models, which are sets of data used to make predictions. The first model has 1247 data points and includes two columns of data, the intercept and r1, which is a type of return. The beta values, which measure the relationship between the variables, are -0.000033508040212143604 and 0.02043805135151162. The HAC5 t-values, which are used to determine the significance of the results, are -0.3456095698171475 and 0.5486734061328367. The R2 value, which measures how well the model fits the data, is 0.0019336165159477003. The correlation between r1 and the last return is 0.04397290661245747. The second model also has 1247 data points and includes three columns of data, the intercept, r1, and r12, which is another type of return. The beta values are -0.00003298000458315649, 0.020917773476934593, and -0.02012096380120869. The HAC5 t-values are -0.3404841895984766, 0.5771174076549123, and -0.13479911669226102. The R2 value is 0.0020661626602445082. The correlation between r1 and the last return is 0.04397290661245747. The third model has 1247 data points and includes two columns of data, the intercept and rod, which is another type of return. The beta values are -0.0000342357465678499 and 0.015960183350506335. The HAC5 t-values are -0.3611846308855028 and 0.6214827498356522. The R2 value is 0.002360208293866073. The correlation between r1 and the last return is 0.04397290661245747. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following statistics for TLT, calculated on September 7, 2026, using a source of SIP adjusted 30-minute and daily history from 2016 to September 4, 2026. The statistics are based on 20,000 circular 20-session block draws for the mean confidence interval, and 24-calendar-day historical windows use a hypothetical 25% account allocation, excluding fixed costs and intrabar extremes, which refers to extreme price movements within a single bar or period of time. The results include a mean trade confidence interval of -0.1729% to -0.1406%, a quarter Kelly value of 0, an actual size of 0, and 24-calendar day profit and loss percentages of -4.11%, -2.31%, and -0.06% at the 5th, 50th, and 95th percentiles, respectively. The 24-calendar day loss percentage is 95.24%, the 24-calendar day profit greater than or equal to 349 percentage is 0, and the 24-calendar day 95th percentile closed wealth drawdown percentage is 0.48%. The gross mean basis points are 4.30, the approximate break-even one-way basis points are 2.15, and the training range median is 0.0024. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following statistics for TLT, calculated on September 7, 2026, using adjusted 30-minute and daily history from 2016 to September 4, 2026. The statistics are based on 20,000 circular 20-session block draws for the mean confidence interval, and 24-calendar-day historical windows with a hypothetical 25% account allocation, excluding fixed costs and intrabar extremes. The results include a 95% confidence interval for the mean trade of -0.1681146097236288 to -0.13828876646560911, and a 24-calendar-day profit and loss range of -4.800172668508367 to -0.25427636878305293. The statistics also show a 96.225% loss percentage, and a 0.5715208861203802% maximum drawdown percentage. The gross mean basis points are 4.625616330249153, and the approximate break-even one-way basis points are 2.3128081651245767. https://runway.adityaperswal.workers.dev/data/stock-bars

These statistics for TLT were calculated on September 7, 2026, using adjusted historical data from 2016 to September 4, 2026. The results are based on 20,000 circular 20-session block draws for mean confidence interval, and 24-calendar-day historical windows with a hypothetical 25% account allocation, excluding fixed costs and extreme price movements within a trading session, known as intrabar extremes. This analysis does not provide forward probabilities, which are predictions of future outcomes. The statistics include a mean trade confidence interval of -0.17334109292049046 to -0.14299331859973335 percent, and a 24-calendar-day historical window with a 5th percentile profit or loss of -4.551086971763766 percent, a 50th percentile of -2.5482532603531354 percent, and a 95th percentile of -0.2635976089085261 percent. The analysis also shows a 96.34 percent loss rate over 24 calendar days, and a 0 percent chance of profit greater than or equal to 349 percent over the same period. The gross mean basis points, a measure of return, is 4.162266587971378, and the approximate break-even point, the point at which the trade neither makes nor loses money, is 2.081133293985689 basis points one way. The results are also broken down into four buckets: range high with 446 occurrences and a mean trade percentage of -0.15067437507511128, range low with 126 occurrences and a mean trade percentage of -0.1851136375019941, r1 r12 agree with 263 occurrences and a mean trade percentage of -0.15834480070363313, and r1 r12 disagree with 309 occurrences and a mean trade percentage of -0.15818901949415978. The training range median, a measure of the middle value of a set of data, is 0.0024143179618283496. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the headline 'EFA QIM90708 statistics pdt'. Calculated on September 7, 2026, this data is based on a source that adjusts for SIP, using 30-minute and daily history from 2016 to September 4, 2026. The future outcomes are unknown. The statistics were calculated using 20,000 circular 20-session block draws for the mean confidence interval, and 24-calendar-day historical windows used a hypothetical 25% account allocation, excluding fixed costs and intrabar extremes, which refers to extreme price movements within a single bar or period of time. The results are as follows: the mean trade confidence interval at 95% is between -0.20404990350856747 and -0.1760966801969343, the quarter Kelly is 0, and the actual size is 0. The 24-calendar-day profit and loss statistics show a 5th percentile of -4.738713440380593, a 50th percentile of -2.871308013350472, and a 95th percentile of -0.8741709899459238. The 24-calendar-day loss percentage is 99.455, and the 24-calendar-day profit greater than or equal to 349 percentage is 0. The 24-calendar-day 95th percentile closed wealth drawdown percentage is 0.5568471357337401. The gross mean basis point is 0.9560875359419461, and the approximate break-even one-way basis point is 0.47804376797097303. The buckets are empty, and the training range median is 0.0023747841105353. https://runway.adityaperswal.workers.dev/data/stock-bars

These statistics were calculated on September 7, 2026, using adjusted historical data from 2016 to September 4, 2026. The source is a 30-minute and daily history from the SIP. The future outcomes are unknown. The statistics are based on 20,000 circular 20-session block draws for the mean confidence interval. A 24-calendar-day historical window was used with a hypothetical 25% account allocation, excluding fixed costs and intrabar extremes. This does not include forward probabilities. The symbol is EFA and the rule is rod. The number of paths is 20,000 and the block days is 20. The mean trade confidence interval at 95% is between -0.1995826954672361 and -0.1766430093881681. The quarter Kelly is 0 and the actual size is 0. The 24-calendar-day profit and loss percentages at 5%, 50%, and 95% are -5.667457212872705, -3.357957427076485, and -1.3934756038320302. The 24-calendar-day loss percentage is 100 and the 24-calendar-day profit greater than or equal to 349 percentage is 0. The 24-calendar-day 95% closed wealth drawdown percentage is 0.6680873272140508. The gross mean basis points is 1.1499794356090014 and the approximate break-even one-way basis points is 0.5749897178045007. The training range median is 0.0023747841105353. https://runway.adityaperswal.workers.dev/data/stock-bars

These statistics for EFA were calculated on September 7, 2026, using adjusted historical data from 2016 to September 4, 2026. The statistics are based on 20,000 circular 20-session block draws for the mean confidence interval, and 24-calendar-day historical windows with a hypothetical 25% account allocation, excluding fixed costs and extreme price movements within a trading period, which is called an intrabar extreme. The results include a 95% confidence interval for the mean trade of -0.202469804454124% to -0.178243507792137%. The quarter Kelly, which is a measure of the optimal bet size, is 0, and the actual size is also 0. The 24-calendar-day profit and loss percentages at the 5th, 50th, and 95th percentiles are -5.637430728285449%, -3.427102602114587%, and -1.1809598898056493%, respectively. The 24-calendar-day loss percentage is 99.855%, and the percentage of days with a profit greater than or equal to 3.49% is 0%. The gross mean basis point, which is a unit of measurement for investment returns, is 0.9462161240253759. The approximate break-even one-way basis point is 0.47310806201268796. The results are also divided into buckets, which are groups of trades with similar characteristics. The buckets include range high with 409 trades and a mean trade percentage of -0.18693449544769383%, range low with 230 trades and a mean trade percentage of -0.19644281162601646%, r1 r12 agree with 310 trades and a mean trade percentage of -0.1912247988004951%, and r1 r12 disagree with 329 trades and a mean trade percentage of -0.18953911150132852%. The training range median, which is the middle value of a set of trade returns, is 0.0023747841105353. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following statistics for EEM, calculated on September 7, 2026, using a source of SIP adjusted 30-minute and daily history from 2016 to September 4, 2026. The statistics are based on 20,000 circular 20-session block draws for the mean confidence interval, which is a measure of the range of possible outcomes. The results also use 24-calendar-day historical windows with a hypothetical 25% account allocation, excluding fixed costs and extreme price movements within a single time period, known as intrabar extremes. The statistics do not predict future outcomes. The mean trade confidence interval is between -0.2138% and -0.1908%. The quarter Kelly, a measure of optimal bet size, is 0, and the actual size is also 0. The 24-calendar-day profit and loss percentages are -4.666%, -2.919%, and -1.297% for the 5th, 50th, and 95th percentiles, respectively. The 24-calendar-day loss percentage is 99.5%, and the 24-calendar-day profit greater than or equal to 349% is 0%. The 24-calendar-day 95% closed wealth drawdown percentage is 0.549%. The gross mean basis points, a measure of profit, is -0.246%, and the approximate break-even one-way basis points is -0.123%. The training range median is 0.0038%. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following statistics for EEM, calculated on September 7, 2026. The source is SIP adjusted 30-minute and daily history from 2016 to September 4, 2026. The future outcomes are unknown. The statistics are based on 20,000 circular 20-session block draws for the mean confidence interval, and 24-calendar-day historical windows use a hypothetical 25% account allocation, excluding fixed costs and intrabar extremes, which are extreme price movements within a single bar or time period, and do not represent forward probabilities, which are probabilities of future events. The symbol is EEM, and the rule is rod. The results include a 95% mean trade confidence interval of -0.21739248718119247 to -0.19706596768589008, a quarter Kelly value of 0, an actual size of 0, and 24-calendar-day profit and loss percentages of -5.799398260572502, -3.5215964720603097, and -1.7232017548203509. The 24-calendar-day loss percentage is 100, the 24-calendar-day profit greater than or equal to 349 percentage is 0, and the 24-calendar-day 95% closed wealth drawdown percentage is 0.6814884147372524. The gross mean basis points value is -0.7336512810797877, and the approximate break-even one-way basis points value is -0.36682564053989386. The training range median is 0.0038294613224406. https://runway.adityaperswal.workers.dev/data/stock-bars

These statistics for EEM were calculated on September 7, 2026, using adjusted historical data from 2016 to September 4, 2026. The source notes that future outcomes are unknown. The calculations are based on 20,000 circular 20-session block draws for the mean confidence interval, and 24-calendar-day historical windows with a hypothetical 25% account allocation, excluding fixed costs and intrabar extremes. The results do not represent forward probabilities. The statistics include a mean trade confidence interval of -0.2161849690428567 to -0.1936092256664569 percent, and a 24-calendar-day historical window with a 5th percentile profit/loss of -5.637478157052442, a 50th percentile of -3.4834502343514373, and a 95th percentile of -1.4567871277831728. The 24-calendar-day loss percentage is 99.54499999999999, and the 24-calendar-day profit greater than or equal to 349 percentage is 0. The 24-calendar-day 95th percentile closed wealth drawdown percentage is 0.662778189657387. The gross mean basis points are -0.5246049308647782, and the approximate break-even one-way basis points are -0.2623024654323891. The results are also broken down into buckets, including range high, range low, r1_r12 agree, and r1_r12 disagree, with corresponding mean trade percentages. The training range median is 0.0038294613224406. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following statistics for SPY, calculated on September 7, 2026. The source is SIP adjusted 30-minute and daily history from 2016 to September 4, 2026. The future outcomes are unknown. The statistics are based on 20,000 circular 20-session block draws for the mean confidence interval, and 24-calendar-day historical windows use a hypothetical 25% account allocation, excluding fixed costs and intrabar extremes, which are extreme price movements within a single bar or time period on a chart. The results do not provide forward probabilities, which are probabilities of future events. The statistics include a mean trade confidence interval of -0.2445% to -0.1987%, a quarter Kelly value of 0, an actual size of 0, and 24-calendar-day profit and loss percentages. The 24-calendar-day loss percentage is 96.985%, and the 24-calendar-day profit greater than or equal to 349% is 0%. The gross mean basis points are -2.1694, and the approximate break-even one-way basis points are -1.0847. Basis points are units of measurement for interest rates and investment returns, equal to one hundredth of a percent. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the following statistics for SPY, calculated on September 7, 2026. The source is SIP adjusted 30-minute and daily history from 2016 to September 4, 2026. The future outcomes are unknown. The statistics are based on 20,000 circular 20-session block draws for the mean confidence interval, and 24-calendar-day historical windows use a hypothetical 25% account allocation, excluding fixed costs and intrabar extremes, which refers to extreme price movements within a single bar or period on a chart. The results do not provide forward probabilities. The data includes the following information: the symbol is SPY, the rule is rod, 20,000 paths were used, and the block days are 20. The mean trade confidence interval at 95% is between -0.2277% and -0.1929%. The quarter Kelly is 0, the actual size is 0, and the 24-calendar-day profit and loss percentages at the 5th, 50th, and 95th percentiles are -7.2595%, -3.9642%, and -0.9913% respectively. The 24-calendar-day loss percentage is 98.575%, the 24-calendar-day profit greater than or equal to 349% is 0%, and the 24-calendar-day closed wealth drawdown percentage at the 95th percentile is 0.8626%. The gross mean basis points is -1.0529%, the approximate break-even one-way basis points is -0.5265%, and the training range median is 0.0029%. https://runway.adityaperswal.workers.dev/data/stock-bars

These statistics for the SPY fund were calculated on September 7, 2026, using historical data from 2016 to September 4, 2026. The source of this data is SIP adjusted 30-minute and daily history. The future outcomes are unknown. The statistics are based on 20,000 circular 20-session block draws for the mean confidence interval, which is a measure of the range of possible outcomes. The analysis uses 24-calendar-day historical windows with a hypothetical 25% account allocation, excluding fixed costs and extreme price movements within a trading period, known as intrabar extremes. This analysis does not provide forward probabilities, which are predictions of future events. The results include the following statistics: the mean trade confidence interval at 95% is between -0.23313994355712586% and -0.1932893690264804%. The quarter Kelly, a measure of the optimal bet size, is 0, and the actual size is also 0. The 24-calendar-day profit and loss percentages at the 5th, 50th, and 95th percentiles are -7.252196384667968%, -4.105130997791093%, and -0.963095482874678%, respectively. The 24-calendar-day loss percentage is 97.66%, and the percentage of times the profit is greater than or equal to 349 is 0%. The maximum closed wealth drawdown at the 95th percentile is 0.8657379644618546%. The gross mean basis points, a measure of return, is -1.3360743294311515, and the approximate break-even one-way basis points is -0.6680371647155757. The analysis also includes the following buckets: range high with 424 occurrences and a mean trade percentage of -0.233950341393896, range low with 280 occurrences and a mean trade percentage of -0.18161261046100355, r1 r12 agree with 362 occurrences and a mean trade percentage of -0.2075722373987863, and r1 r12 disagree with 342 occurrences and a mean trade percentage of -0.21902142029746274. The training range median is 0.0029869251577998. https://runway.adityaperswal.workers.dev/data/stock-bars

A technical analysis of TLT was completed on September 7, 2026, using adjusted 30-minute and daily history from 2016 to September 4, 2026. The analysis used statistics, including 20,000 circular 20-session block draws for mean confidence interval, and 24-calendar-day historical windows with a hypothetical 25% account allocation, excluding fixed costs and extreme price movements within a trading session, called intrabar extremes. The analysis does not predict future outcomes. The data for TLT on September 4, 2026, included a closing price of 82.21, a 200-day simple moving average, or sma200, of 86.25, a 20-day return percentage of -0.66%, and a 20-day average daily range, or adr20, of 0.45. The 20-day dollar volume was 2,327,992,911.13. The analysis also included details of the last trading session, such as entry and exit prices, and high and low prices, with a range of 0.19 and a volume of 1,937,858. https://runway.adityaperswal.workers.dev/data/stock-bars

A technical analysis of EFA was completed on September 7, 2026, using historical data from 2016 to September 4, 2026. This analysis, which is based on past performance and does not predict future outcomes, used statistics such as a 20-session block of data to calculate the mean confidence interval. It also used 24-calendar-day historical windows with a hypothetical 25% account allocation, excluding fixed costs and extreme price movements within a trading session, known as intrabar extremes. The analysis does not provide forward-looking probabilities. The data for EFA as of September 4, 2026, included a closing price of 108.35, a 200-day simple moving average, or sma200, of 101.59, a 20-day percentage return of -0.18%, and an average daily range, or adr20, of 0.63. The dollar volume over 20 days was 930,039,314.05. The last trading session, which was session 2683, had an entry price of 108.2, an exit price of 108.36, and an official closing price of 108.35, with a return of 0.15%. The high price during the session was 108.365, and the low price was 108.185, with a price range of 0.0048 and a volume of 672,895. The analysis also noted discrepancies in closing and opening prices, measured in basis points, which are units of one hundredth of one percent. The current signal, which is a recommendation to buy or sell, is not known, and the actual size of the trade is 0. https://runway.adityaperswal.workers.dev/data/stock-bars

A technical analysis of EEM was calculated on September 7, 2026, using historical data from 2016 to September 4, 2026. This analysis is based on past data and does not predict future outcomes. It used statistics from 20,000 circular 20-session block draws to determine the mean confidence interval, and 24-calendar-day historical windows with a hypothetical 25% account allocation, excluding fixed costs and extreme price movements within a trading session, which is called an intrabar extreme. The analysis does not provide forward probabilities. The data for EEM as of September 4, 2026, includes a close price of 68.7, a 200-day simple moving average, or sma200, of 61.74, a 20-day percentage return of 4.66%, an average daily range, or adr20, of 0.67, and a 20-day dollar volume of 1,070,975,941.53. The whole share capacity is 3. The last trading session, which is the most recent session, had an entry price of 68.495, an exit price of 68.72, and an official close price of 68.7, with a return of 0.0033. The high price during the last session was 68.73, and the low price was 68.48, with a price range of 0.0088 and a volume of 2,301,061. There was a close price discrepancy of 2.91 basis points, but no open or boundary discrepancies. The current signal is not known, and the actual size is 0. https://runway.adityaperswal.workers.dev/data/stock-bars

A technical analysis of the SPY fund was completed on September 7, 2026. The analysis used historical data from 2016 to September 4, 2026, and does not predict future outcomes. It used statistics based on 20,000 circular 20-session block draws to calculate the mean confidence interval, and 24-calendar-day historical windows with a hypothetical 25% account allocation, excluding fixed costs and extreme price movements within a trading session, which is called an intrabar extreme. The analysis does not provide forward probabilities. The data included the symbol SPY, the date September 4, 2026, a closing price of 770.19, and a 200-day simple moving average, or sma200, of 712.15. Other data points were a 20-day percentage return of -0.397, a 20-day average daily range, or adr20, of 4.41, and a 20-day dollar volume of 27,975,000,078.31. The last trading session, or session 2683, had an entry price of 770, an exit price of 770.23, and an official closing price of 770.19, with a return of 0.0003, a high of 770.48, a low of 769.63, and a trading range of 0.0014. The volume for the session was 3,462,826, and there were discrepancies in the closing and opening prices, and the boundary price, which is a price limit. The current signal is not known, and the actual size is 0. https://runway.adityaperswal.workers.dev/data/stock-bars

The TLT QIM90708 audits were calculated on September 7, 2026. The source used was SIP adjusted 30-minute and daily history from 2016 to September 4, 2026. Note that future outcomes are unknown. Statistics were based on 20,000 circular 20-session block draws for mean confidence interval, and 24-calendar-day historical windows used a hypothetical 25% account allocation, excluding fixed costs and intrabar extremes, which are extreme price movements within a single bar, a bar being a unit of time. The results did not provide forward probabilities. The audit found the following information for the symbol TLT: there were 72,256 intraday bars, the first bar was on December 31, 2015, at 19:30:00-05:00, and the last bar was on September 4, 2026, at 19:30:00-04:00. There were 2,659 valid sessions, and certain dates were excluded from the analysis. The close absolute discrepancy in basis points had a 50th percentile of 1.1575413821052205, a 99th percentile of 8.419236910642208, and a maximum of 28.30044362857609. The open absolute discrepancy in basis points had a 50th percentile of 0, a 99th percentile of 2.3694735496642587, and a maximum of 9.694980982921653. The boundary absolute discrepancy in basis points had a 50th percentile of 0, a 99th percentile of 1.7118718844221896, and a maximum of 3.9348390650828513. https://runway.adityaperswal.workers.dev/data/stock-bars

The EFA QIM90708 audits were calculated on September 7, 2026. The source used was the SIP adjusted 30-minute and daily history from 2016 to September 4, 2026. It is noted that future outcomes are unknown. The statistics were based on 20,000 circular 20-session block draws for the mean confidence interval, and 24-calendar-day historical windows used a hypothetical 25% account allocation, excluding fixed costs and intrabar extremes, which are extreme price movements within a single bar or time period, and do not represent forward probabilities, which are probabilities of future events. The audit found the following information for the symbol EFA: it had 50,683 intraday bars, with the first bar on January 4, 2016, at 07:00:00-05:00 and the last bar on September 4, 2026, at 16:00:00-04:00, and there were 2,662 valid sessions. Certain dates were excluded from the analysis, including January 4, 2016, November 25, 2016, and others. The close absolute discrepancy, which measures the difference between the actual and expected closing prices, had a 50th percentile of 1.5688735874069826 basis points, a 99th percentile of 7.520256912514912 basis points, and a maximum of 211.7093570308426 basis points. The open absolute discrepancy, which measures the difference between the actual and expected opening prices, had a 50th percentile of 0 basis points, a 99th percentile of 3.04729701751438 basis points, and a maximum of 5.40979172301892 basis points. The boundary absolute discrepancy, which measures the difference between the actual and expected prices at the boundary of a time period, had a 50th percentile of 0 basis points, a 99th percentile of 2.4196497929383383 basis points, and a maximum of 4.37158469945409 basis points. https://runway.adityaperswal.workers.dev/data/stock-bars

A news scan found the headline 'EEM QIM90708 audits complete'. Calculated on September 7, 2026, this report is based on adjusted historical data from 2016 to September 4, 2026. The future outcomes are unknown. The statistics are calculated using 20,000 circular 20-session block draws for the mean confidence interval. The report uses 24-calendar-day historical windows with a hypothetical 25% account allocation, excluding fixed costs and intrabar extremes, and does not provide forward probabilities. The symbol is EEM, with 65,096 intraday bars, starting from January 4, 2016, and ending on September 4, 2026. There were 2,662 valid sessions, excluding certain dates. The close absolute discrepancy percentiles are 2.50, 9.26, and 118.36, and the open absolute discrepancy percentiles are 0, 3.42, and 17.78. The boundary absolute discrepancy percentiles are 0, 3.69, and 4.42. https://runway.adityaperswal.workers.dev/data/stock-bars