Forex Automaton > Forex Research > Key concepts > Pearson correlation coefficient

Pearson correlation coefficient
Written by Mikhail Kopytine   
Thursday, 29 May 2008 12:42

Pearson correlation coefficient (or Pearson coefficient) between x and y is defined by:

Cov[x,y]/(Var[x]Var[y])1/2

where Cov(x,y) is covariance and Var(x) is variance.

For the forex time series we analyze, the mean is typically at least two orders of magnitude smaller than the RMS. For this reason we often neglect the mean. Then, Cov[x,y] is simply the amplitude of the zero-lag bin of the cross-correlation function and Var[x] is the amplitude of the zero-lag bin of the autocorrelation function. Pearson coefficient of two price series is therefore a zero time-lag property of the correlation functions. For prediction purposes, properties associated with non-zero time lags are much more interesting.

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Last Updated ( Saturday, 25 October 2008 17:01 )
 

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