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Testing power-law cross-correlations: rescaled covariance test

  • Ladislav KristoufekEmail author
Regular Article

Abstract

We introduce a new test for detection of power-law cross-correlations among a pair of time series – the rescaled covariance test. The test is based on a power-law divergence of the covariance of the partial sums of the long-range cross-correlated processes. Utilizing a heteroskedasticity and auto-correlation robust estimator of the long-term covariance, we develop a test with desirable statistical properties which is well able to distinguish between short- and long-range cross-correlations. Such test should be used as a starting point in the analysis of long-range cross-correlations prior to an estimation of bivariate long-term memory parameters. As an application, we show that the relationship between volatility and traded volume, and volatility and returns in the financial markets can be labeled as the power-law cross-correlated one.

Keywords

Statistical and Nonlinear Physics 

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Copyright information

© EDP Sciences, SIF, Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Institute of Information Theory and Automation, Academy of Sciences of the Czech RepublicPragueCzech Republic
  2. 2.Institute of Economic Studies, Faculty of Social Sciences, Charles University in PraguePragueCzech Republic

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