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Testing power-law cross-correlations: Rescaled covariance test

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  • Ladislav Kristoufek

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 one with power-law cross-correlations.

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File URL: http://arxiv.org/pdf/1307.4727
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Bibliographic Info

Paper provided by arXiv.org in its series Papers with number 1307.4727.

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Date of creation: Jul 2013
Date of revision: Aug 2013
Publication status: Published in European Physical Journal B 86:418, 2013
Handle: RePEc:arx:papers:1307.4727

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  19. Ladislav Kristoufek, 2012. "Multifractal Height Cross-Correlation Analysis: A New Method for Analyzing Long-Range Cross-Correlations," Papers 1201.3473, arXiv.org, revised Jan 2012.
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Cited by:
  1. Ladislav Kristoufek, 2013. "Measuring correlations between non-stationary series with DCCA coefficient," Papers 1310.3984, arXiv.org.
  2. Ladislav Kristoufek, 2014. "Leverage effect in energy futures," Papers 1403.0064, arXiv.org.

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