Spreading Dynamics of Capital Flow Transfer in Complex Financial Networks

Abstract

The financial system, a complex network, operates primarily through the exchange of capital, where the role of information is critical. This study utilizes the transfer entropy method to examine the strength and direction of information flow among different capital flow time series and investigate the community structure within the transfer networks. Moreover, the spreading dynamics of the capital flow transfer networks are observed, and the importance and traveling time of each node are explored. The results imply a dominant role for the food and drink industry within the Chinese market, with increased attention towards the computer industry starting in 2014. The community structure of the capital flow transfer networks significantly differs from those constructed from stock prices, with the main sector predominantly encompassing industry leaders favored by primary funds with robust capital flow connections. The average traveling time from sectors such as food and drink, coal, and utilities to other sectors is the shortest, and the dynamic flow between these sectors displays a significant role. These findings highlight that comprehension of information flow and community structure within the financial system can offer valuable insights into market dynamics and help to identify key sectors and companies.

Research on Risk Contagion in ESG Industries: An Information Entropy-Based Network Approach

“…In financial risk contagion research, information entropy can help quantify the efficiency and strength of network risk contagion [ 38 ]. For instance, transfer entropy [ 32 , 39 , 40 , 41 , 42 ], which has been used to establish a network model, revealed the network structure and potential paths of systemic risk contagion. Ji [ 43 ] employed an entropy-based network method, investigated the risk spillover effects among international real estate markets.…”