Dynamics of Chinese stock market from a complex network perspective

In this paper, we investigate the dynamics of Chinese stock market from a complex network perspective, based on daily fluctuations of all stocks during 1906 working day period from 2005 to 2012. In the network being constructed, each node is a stock, and each edge indicates the time correlation coefficient of two stocks over a window of T days. The network evolves chronologically as the window slides in forward time at a ΔT-days interval. By examining the variation of the network parameters as time elapses, we show that 1) Different from the scale-free property observed in US stock markets, the degree distributions of Chinese stock market networks cannot follow the power-law at some periods; 2) When the Chinese stock market experiences a bear market, the average degree is exceedingly large and the ratio of edges existing at two sequential networks is high. Moreover, we select a few largest-degree stocks for inclusion in a stock index, and find that it fits in with the HS300 Index well at some periods, but far exceeds after the Four Trillion Program implemented by Chinese government.