Recent studies of correlations in Chinese stock market have mainly focused on the static correlations in financial time series, and then we pay great attention to investigate their dynamic evolution of correlations. Our paper reports on topology of 41 AH-shares companies traded on Shanghai and Hong Kong Stock Exchange in Chinese stock market. We apply the concept of minimum spanning tree (MST) and hierarchical tree (HT) to analyze and reveal the dynamic evolution of correlations between different market sectors for the period 2008-2014. From these trees, we can detect that significantly industry clustering effects are in the stock network. We measure the linkage of different companies geared to different industrial sectors. We observe the evolution of AH-shares companies in the stock network based on the moving window technique and investigate the correlations by calculating the correlation coefficient distribution, mean correlation coefficient and mean distance of these companies with time. Therefore, through our analysis, we find that companies working in the same branch of production tend to make up cluster. The results present the difference and similarity between different industry sectors in different time periods.
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