Cross-correlation |
| Written by Mikhail Kopytine | |
| Monday, 21 April 2008 08:17 | |
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In our usage cross-correlation is a generalization of autocorrelation to a pair of time series: C(T)=E[x(t),y(t+T)]|over all available t where T is the time lag. We will also use the more context-specific term intermarket correlation for certain cross-correlations. Just like significant autocorrelation at non-zero time lags lets one predict (in the statistical sense) the process on the basis of its own past history ("auto-" means "self-"), significant cross-correlation at non-zero time lags lets one predict X on the basis of Y (in the same sense with the same caveates) or Y on the basis of X, depending on the sign of T where the signal occurs. For example if you notice that XXX/YYY lags begind UUU/VVV, and you know that UUU/VVV just went up, you can go long on XXX/YYY and have a better than average chance of ending up with a winning trade. Feel free to browse our collection of cross-correlation data for the forex markets -- some of them are highly non-trivial. Bookmark with:
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| Last Updated ( Saturday, 25 October 2008 17:05 ) |
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ROOT -- An Object-Oriented Data Analysis Framework
