Identifying states of global financial market based on information flow network motifs

Abstract

Stock markets exhibit different states due to internal and external shocks. It is of great significance to identify the status of global financial markets. Based on 48 global stock indices from 1996 to 2018, we constructed a global stock index transfer entropy network, which represents the information flow between stock markets in different economies. By analyzing the triadic motifs in the transfer entropy network, we divided the global stock market into different market states based on the distribution of motifs. The characteristic structure of information flow was observed in different market states. We found that the information flow in the global stock market increases significantly during major financial events, indicating that the global stock index has a mutual influence and a close relationship with each other. In addition, stock indices in the Asia-Pacific, Middle East, and Africa are the main sinks of information, while stock indices in the Americas and Europe are the primary sources of information.