Cumulative distribution function (tScore and zScore) This script provides the calculation of the cumulative distribution function (i.e., probability). The measure allows you to calculate the chances of a value of interest being above or below a hypothesized value over the measurement period—nothing fancy here, just good old statistics and mathematics. The closer...

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Creates a Histogram for Statistical Analysis of any source. Input Parameters: Sample Source: Select your source here, can be any numerical source. Sample Period: Sample size for Mean and Standard Deviation Calculations. Enable Cumulative Mode: Will attempt to calculate the bin for every sample in the entire dataset. Window Period: Used only in Window Mode...

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A way to see whether RSI is overbought or oversold inside its Bollinger Bands in the form of an oscillator. Z-score tells you how far the data is from the mean in terms of standard deviations. The numbers shown in the indicator are the number of standard deviations away from the average or mean. Like Bollinger Bands, if it is above the standard deviation border...

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A Z-score is a numerical measurement of a value's relationship to the mean in a group of values. If a Z-score is 0, it represents the score as identical to the mean score. Z-scores may also be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean. Positive and negative scores also...

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This calculates normal distance of price from VWAP. This is a mean reverting idea (something like ZScore), but using both "volume" and "close". Useful for finding OB/OS areas and potential turning points. Complete list of my indicators:

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**THIS VERSION HAS BEEN STANDARDIZED WITH A Z SCORE CALCULATION AND ALLOWS THE USER TO SELECT WHICH MOVING AVERAGE THEY WOULD LIKE TO UTILIZE FOR THE SIGNAL LINE** Chart shows the Non-Standardized Enhanced Time Segmented Volume (Multi MA) with default settings on top and the Standardized version with default settings on the bottom. Time Segmented Volume was...

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This is an experimental study using z scores of multiple sampling periods to analyze price trends. Z score measures the number of standard deviations price is from its mean. In this study, z scores are calculated over a Fibonacci sequence of sampling periods from 3 to 4181. The scores are then averaged with equal weighting, resulting in a display of long term...

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The following script is an application of the Z-Score (previous script). Z-Scores can be used in place of standard deviation (sigma) in 'Bollinger Bands'. The average of the sample (x-bar) over 21 days (N) 21 average trading days per month, fixed value The average of the population (mu) over 63 days (n) 63 days per quarter, default is set to 63 Z-Score...

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This study calculates the On-Balance Volume (OBV) and displays it in terms of its Z-Score. OBV is a great momentum indicator . As the name suggests, OBV predicts changes in price based on the security's volume flow. Formula: if (Current Price > Previous Price) then Current OBV = Previous OBV + Current Volume if (Current Price < Previous Price) then...

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This is a study to determine if small candle bodies (little difference between open and close), regardless of overall candle length (high/low), can be used to filter choppy markets. The indicator will calculate the selected average "MA Mode" of (close-open). To standardize this result and ensure any filters/thresholds do not need to be recalculated for each...

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Middle quantile/band color is set by confluence of the outer quantiles and not by it's own slope. Optional MTF.

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The z-score is a way of counting the number of standard deviations between a given data value and the mean of the data set. Z-score = (x̄ - μ) / (σ / √ n) x̄ = sample mean (using the array.avg function = array(a,close ), where i = 1 to 21) μ = population mean ( = avg(close, n)) σ = standard deviation of the population ( = stdev(close,n)) n = number of 'close'...

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EXPERIMENTAL: market state, text says it all most of the time at least.

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The Kolmogorov–Smirnov test aims to tell you if the distribution of prices (or log returns) tends to follow a normal distribution or not. You can read about this test on Wikipedia . It seems to be a basic but trusted measure in the quantitative trading world. When KS-t columns are blue, then it's safe to assume normal distribution. When they are red, the normal...

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