Multifractal detrended cross-correlation analysis for two nonstationary signals.

By Wei‐Xing Zhou. Physical review. E, Statistical, nonlinear, and soft matter physics, 2008

670 citations recorded by the source corpus.

We propose a method called multifractal detrended cross-correlation analysis to investigate the multifractal behaviors in the power-law cross-correlations between two time series or higher-dimensional quantities recorded simultaneously, which can be applied to diverse complex systems such as turbulence, finance, ecology, physiology, geophysics, and so on. The method is validated with cross-correlated one- and two-dimensional binomial measures and multifractal random walks. As an example, we illustrate the method by analyzing two financial time series.

Subfields: Economics and Econometrics, Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/4448dfcb436cde799297bada3d4e835e4e8db81c

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Citations in the corpus

Multifractal detrended cross-correlations between the Chinese exchange market and stock market (2012, methodology): “Zhou observed that for two time series constructed by a binomial measure from the p-model, the following relationship exists [27]:”
Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient (2013, neutral): “Then determine the detrended covariance [29,42–44]”
A new approach to quantify power-law cross-correlation and its application to commodity markets (2011, methodology): “To unveil multifractal features of two cross-correlated nonstationary signals, Zhou proposes Multifractal Detrended Cross-Correlation Analysis (MF-DCCA) to combine Multifractal Detrended Fluctuation Analysis (MF-DFA) and DCCA approaches [26], while the latter can be also regarded as a generalization”
Measuring correlations between non-stationary series with DCCA coefficient (2013, methodology): “For an estimation of parameters λ and Hxy, several estimators have been proposed—(multifractal) detrended crosscorrelation analysis (DCCAandMF-DXA, also referred to asMF-X-DFA) [19,20], detrendingmoving-average cross-correlation analysis (DMCA) [8], their combination of multifractal detrending movin”
Nonlinear bivariate dependency of price–volume relationships in agricultural commodity futures markets: A perspective from Multifractal Detrended Cross-Correlation Analysis (2011, methodology): “To unveil multifractal features of two cross-correlated nonstationary signals, Zhou proposed Multifractal Detrended Cross-Correlation Analysis (MF-DCCA) by combining Multifractal Detrended Fluctuation Analysis (MF-DFA) and DCCA approaches [18].”
Correlation structure and dynamics of international real estate securities markets: A network perspective (2015, methodology): “correlation structure among financial assets, such as random matrix theory [23,24], detrended cross-correlation analysis (DCCA) method [25], and multifractal DCCA method [26].”
Multifractal Detrended Fluctuation Analysis of the Chinese Stock Index Futures Market (2013, background): “Scholars have also studied the cross-correlations between two non-stationary time series [10-13] by generalising DFA and MF-DFA analyses with an emphasis on detrended covariance.”