Analysis of the risk spillover network of G20 stock markets based on transfer entropy and complex network approaches

Abstract

This study investigates the risk spillover network among major stock market indices of G20 countries from 2003 to 2024. Transfer entropy is employed to measure the asymmetric and nonlinear information flow between stock markets. Based on this key metric, a directed and weighted risk spillover network among stock markets is constructed using the threshold method during periods of extreme events. Utilizing complex network theories, such as PageRank and betweenness centrality, the study analyzes the macro-topological characteristics of the risk spillover network and identifies key nodes. The findings not only demonstrate strong information interaction among G20 stock markets but also show that European and North American markets exhibit regional clustering characteristics, while emerging markets serve as bridging nodes in the risk spillover network. These results offer theoretical and practical insights for portfolio management, risk monitoring, and cross-border financial regulation and crisis management.