Abstract
In this paper, we investigate the correlation and cross-correlation behaviors in Shanghai stock market by combining the traditional detrended fluctuation analysis (DFA) and detrended cross-correlation analysis (DCCA) method with moving fitting windows, respectively. The new method can not only show detailed scale exponent properties of non-stationary time series in small and large scale simultaneously, but also provide a more faithful and more interpretable description of series under investigation. Using the moving fitting windows, we find that the correlation in Shanghai B-share is stronger than Shanghai A-share on the whole, and we also show the dynamic long–range cross-correlations behaviors between Shanghai A-share and B-share index series.
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