The Ehlers Autocorrelation study is a technical indicator used in the calculation of John F. Ehlers’s Autocorrelation Periodogram. Its main purpose is to eliminate noise from the price data, reduce effects of the “spectral dilation” phenomenon, and reveal dominant cycle periods. The spectral dilation has been discussed in several studies by John F. Ehlers; for more information on this, refer to sources in the "Further Reading" section.
As the first step, Autocorrelation uses Mr. Ehlers’s previous installment, Ehlers Roofing Filter, in order to enhance the signal-to-noise ratio and neutralize the spectral dilation. This filter is based on aerospace analog filters and when applied to market data, it attempts to only pass spectral components whose periods are between 10 and 48 bars.
Autocorrelation is then applied to the filtered data: as its name implies, this function correlates the data with itself a certain period back. As with other correlation techniques, the value of +1 would signify the perfect correlation and -1, the perfect anti-correlation.
Using values of Autocorrelation in Thermo Mode may help you reveal the cycle periods within which the data is best correlated (or anti-correlated) with itself. Those periods are displayed in the extreme colors (red and green) while areas of intermediate colors mark periods of less useful cycles.
||Defines the lookback period for prior data to calculate the correlation with.|
Defines the correlation period. If set to 0, the
||The Ehlers Autocorrelation plot.|
||The zero level.|
1. "Measuring Market Cycles" by John F. Ehlers. Technical Analysis of Stocks & Commodities, September 2016.
2. "Whiter is Brighter" by John Ehlers, PhD. Technical Analysis of Stocks & Commodities, January 2015.
3. "Predictive Indicators for Effective Trading Strategies" by John F. Ehlers. Technical Analysis of Stocks & Commodities, January 2014.
*For illustrative purposes only. Not a recommendation of a specific security or investment strategy.