Revealing stock market risk from information flow based on transfer entropy: The case of Chinese A-shares

Abstract

According to the efficient-market hypothesis, asset prices can reflect all available information in an efficient stock market. This paper focuses on the transmission of information flow between different equities during a financial crisis to reveal the potential risk spreading in the stock market. The information flow and corresponding time-varying stock networks (i.e., information flow networks and industry networks) are constructed using the transfer entropy with the intra-day data of the Chinese A-Share stock market around the 2008 subprime mortgage crisis. The empirical results show that the information flow can reflect the market condition and the financial crisis stage well. The information flow is more apparent when it falls than when it rises. Similarly, it is more apparent in the crash period than in the downturn period. Furthermore, the evolution of information flow networks, markedly shows that several crucial topological parameters, indicates the crash period. We identify four key stocks, through which the whole stock market tends to exchange market information. Finally, we transform the information flow networks into coarse-grained industry networks, and find that the stock market is more likely to be driven by a master or two industries. Through the core industries, the entire stocks are more like to exchange market information, resulting in the increasing system risk in the crash period. Our work provides an interesting insight for regulators to manage market risks and for market participants to avoid troubles.