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.

What is autocorrelation used for?

Autocorrelation measures the relationship between a variable's current value and its past values. An autocorrelation of +1 represents a perfect positive correlation, while an autocorrelation of negative 1 represents a perfect negative correlation.

When should you test for autocorrelation?

It is necessary to test for autocorrelation when analyzing a set of historical data. For example, in the equity market, the stock prices in one day can be highly correlated to the prices in another day.