AutocorrelogramFast 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 autoccorelations.
The ACF can return a lot of information, for technical analysis, the ACF can be used to determine whether the market is trending or ranging. Without prior processing, we expect trending prices to have a slowly decaying ACF with significant autocorrelation at each lag, while ranging prices will have an ACF that decay faster toward 0.
I won't post a lot on this profile, I'll post most of my future work on the LuxAlgo profile instead, link in the signature.
Autocorrelation
Ehler's Autocorrelation Periodogram - RSI/MFIWarning! 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 / dynamic length).
As an example it's applied here to RSI or MFI. Lower indicator segment displays the autocorrelation spectrum and the computed dominant cycle. Upper segment is RSI/MFI.
Autocorrelation PlotA 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: en.wikipedia.org
Note: There are 1 bar gaps every 55 because I wanted the labels to remain every 5, but you don't have to have gaps....
Ehlers Correlation Trend Indicator CTI by Cryptorhythms [CR]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 identify the onset of new trends but to identify trend failures as well. He presents what looks like a simple and elegant idea for a trend-detection and mode-switching indicator.
📋Comments
Careful market selection may be the key to a correct application of the indicator. Even such barebone rules could shine with stocks like AAPL that tend to develop prolonged trends. But for others like CAT, which can keep oscillating in ranges for years, results will be much less impressive. They require a different approach. For example, you would want to buy when Correlation Trend falls significantly below zero and sell when it reaches positive values.
Therefore, it would be an interesting problem to research Correlation Trend’s ability to identify the switch to a cycle mode. That might help develop countertrend systems and
trade pullbacks. Another possible application might be to act as a system filter of change from trending mode to mean-reversion mode.
Extras
As usual when porting indicators to the library here on tradingview, I like to add some extra flare!
💠Customizable Overbought and Oversold Zones for Alert Creation
💠Bar coloration based on trade state for easy visual at a glance chart checking
💠Some basic example Entry and Exit conditions and a simple Trade State Engine to get you going creating your own strategy
Enjoy!
👍 We hope you enjoyed this indicator and find it useful! We post free crypto analysis, strategies and indicators regularly. This is our 81st script on Tradingview!
Multistep AutocorrelationAutocorrelation, 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 obscured by noise, or identifying the missing fundamental frequency in a signal implied by its harmonic frequencies. It is often used in signal processing for analyzing functions or series of values, such as time domain signals.
This multistep autocorrelation function calculates the correlation of roc (rate of change) between an asset at t and t-1 as well as the correlation of the same asset at t and t-4. The output is an average of the two.
If both outputs show a positive correlation, the color will be green.
If only one shows a positive correlation, the color will be yellow.
If neither show a positive correlation, the color will be red.
This indicator can be useful as a filter for strategy entry logic (only enter on strong correlation and the strategy entry condition), or as standalone confirmation of strength in a specific direction. It can also be used to filter chop.
Another potential usecase would be as a variable in regression applications.
Enjoy!
