Multifractal detrended cross-correlations between the Chinese exchange market and stock market

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Measuring correlations between non-stationary series with DCCA coefficient (2013, background): “Introduction Analysis of power-law cross-correlations between various time series has become a popular topic in a broad range of fields – hydrology [4], seismology [21], traffic [31, 27, 32], finance [17, 6, 5, 3], biometrics [23], (hydro)meteorology [24, 8], biology [28], DNA sequences [22], electr”
Detrended cross-correlation analysis approach for assessing asymmetric multifractal detrended cross-correlations and their application to the Chinese financial market (2014, unknown): “MF-DCCA is used widely to detect the cross-correlation between financial markets [9–19].”
Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient (2013, background): “The outstanding advantage of this nonlinear cross-correlation coefficient is that it can investigate the cross-correlations at different time scales [38,39].”
Asymmetric multifractal scaling behavior in the Chinese stock market: Based on asymmetric MF-DFA (2013, methodology): “We employ the following measure [22,47] to quantify the degree of multifractality: ∆H = max(H(q)) − min(H(q)).”