TESTING FOR INDEPENDENCE BETWEEN 2 COVARIANCE STATIONARY TIME-SERIES

A one-sided asymptotically normal test for independence between two st ationary time series is proposed by first prewhitening the two time se ries and then basing the test on the residual cross-correlation functi on. The test statistic is a properly standardised version of the sum o f weighted squares of residual cross-correlations, with weights depend ing on a kernel function. Haugh's (1976) test can be viewed as a speci al case of our approach in the sense that it corresponds to the use of the truncated kernel. Many kernels deliver better power than Haugh's test. A simulation study shows that the new test has good power agains t short and long cross-correlations.