Institute of Information Theory and Automation

Publication details

Measuring correlations between non-stationary series with DCCA coefficient

Journal Article

Krištoufek Ladislav


serial: Physica. A : Statistical Mechanics and its Applications vol.402, 1 (2014), p. 291-298

project(s): GAP402/11/0948, GA ČR, GP14-11402P, GA ČR

keywords: power-law cross-correlations, long-term memory, econophysics

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abstract (eng):

In this short report, we investigate the ability of the DCCA coefficient to measure correlation level between non-stationary series. Based on a wide Monte Carlo simulation study, we show that the DCCA coefficient can estimate the correlation coefficient accurately regardless the strength of non-stationarity (measured by the fractional differencing parameter d). For a comparison, we also report the results for the standard Pearson correlation coefficient. The DCCA coefficient dominates the Pearson coefficient for non- stationary series.

RIV: AH

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Last modification: 21.12.2012
Institute of Information Theory and Automation