In stochastic processes, chaos theory and time series analysis, detrended fluctuation analysis (DFA) is a method for determining the statistical self-affinity of a signal. It is useful for analyzing time series that appear to be long-memory processes and noise. █ OVERVIEW We have introduced the concept of Hurst Exponent in our previous open indicator Hurst...

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In Finance, people usually assume the price follows a random walk or more precisely geometric Brownian motion. In 1988, Lo and MacKinlay came up with the variance ratio test to refute the random walk hypothesis and efficient market hypothesis. The variance ratio test is a simple test for market efficiency, autocorrelation, and whether price follows a random walk....

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In statistics, the Durbin–Watson statistic is a test statistic used to detect the presence of autocorrelation at lag 1 (AR(1) process) in the residuals (prediction errors) from a regression analysis. With the new array function tradingview implemented, we are able to do our calculations on the residuals. The residual is given by subtracting the actual value (in...

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Autocorrelation, also known as serial correlation, is the correlation of a signal with a delayed copy of itself as a function of delay. This indicator displays autocorrelation based on lag number. The autocorrelation is not displayed based on time on the x-axis. It's based on the lag number which is from 1 to 50. The calculations can be done with "Log...

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The AutoCorrelation Indicator was created by John Ehlers (Cycle Analytics pgs 94-98) and this can be viewed as both a momentum indicator and a trend indicator. This was his basis for several other indicators that he created which I will be publishing soon but essentially as this indicator goes up then the stock is in an uptrend and also has upward momentum. You...

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Ehlers Correlation Trend Indicator CTI by Cryptorhythms 📜Intro In his article “Correlation As A Trend Indicator” in issue May 2020 of TASC, author John Ehlers introduces a new trend indicator that is based on the correlation between a security’s price history and the ideal trend: a straight line. He describes methods for using the indicator to not only...

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Level: 2 Background @pips_v1 has proposed an interesting idea that is it possible to code an "Adaptive Jon Andersen R-Squared Indicator" where the length is determined by DCPeriod as calculated in Ehlers Sine Wave Indicator? I agree with him and starting to construct this indicator. After a study, I found "(blackcat) L2 Ehlers Autocorrelation Periodogram"...

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Experimental: The Gramian Angular Field is usually used in machine learning for machine vision, it allows the encoding of data as a visual queue / matrix.

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Experimental: finds and displays the wavelength index's of the autocorrelation wavelengths..

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Fast estimation of an autocorrelogram, more commonly called autocorrelation function (ACF). The script sets the maximum lag as 10*log10(N)-1 and sets the autocorrelation at lag 0 to 1. Length controls the number of past observations of Src to use as input, while Differentiate Src perform first order differencing to Src before calculating the...

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A tool to plot auto correlation of time series, this is useful in identifying periodicity in a time series or signal. Due to the limits of Pine Script you'll need to add it multiple times if you want autocorrelation beyond 55 periods. I have added it 4 times here for 220 periods. For more information on Autocorrelation see:...

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experimental: shows the distribution for each shift in a autocorrelation.

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Level: 2 Background John F. Ehlers introduced Autocorrelation Periodogram in his "Cycle Analytics for Traders" chapter 8 on 2013. Function Construction of the autocorrelation periodogram starts with the autocorrelation function using the minimum three bars of averaging. The cyclic information is extracted using a discrete Fourier transform (DFT) of the...

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Autocorrelation, also known as serial correlation, is the correlation of a signal with a delayed copy of itself as a function of delay. Informally, it is the similarity between observations as a function of the time lag between them. The analysis of autocorrelation is a mathematical tool for finding repeating patterns, such as the presence of a periodic signal...

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Level: 2 Background John F. Ehlers introduced Autocorrelation Indicator in his "Cycle Analytics for Traders" chapter 8 on 2013. Function If we correlate a waveform composed of perfectly random numbers by itself, the correlation will be perfect. However, if we lag one of the data streams by just one bar, the correlation will be dramatically reduced. In a long...

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This indicator shows the Pearson correlation coefficient between different periods of one financial instrument. Two dates are set, which are the starting points of two series, between which the correlation coefficient is calculated. The correlation period is taken from the difference of the current date from the second reference point. The indicator is designed to...

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Level: 2 Background John F. Ehlers introduced Autocorrelation Reversals in his "Cycle Analytics for Traders" chapter 8 on 2013. Function One of the distinctive characteristics of autocorrelation is that the autocorrelation shifts from yelow to red or from red to yellow at all values of lag at the cyclic reversals of the price. Therefore, all we need do to...

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Warning! Frequently hits the execution time limit for scripts. Especially on initially adding to your chart. Often requires toggling show/hide indicator to get it to complete script execution within the time limit. YMMV! From TASC Sept 2016 this is Ehler's Autocorrelation periodogram. A means of determining the dominant cycle ("ideal" indicator length /...

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