Ranking Systemically Important Financial Institutions of the Chinese Financial System : Evidence from the Higher-Order Temporal Network

Based on the daily data of 45 listed financial institutions from 2015 to 2022 in Chinese financial market, we construct higher-order temporal causal networks via the variable-lag Granger-causality test and higher-order temporal network model, and rank the systemic important financial institutions using the higher-order PageRank algorithm. The higher-order temporal causal networks provide evidence that financial institutions become more interrelated during crisis periods, and capture the higher-order dynamic characteristics of interconnectedness among institutions. The ranking results show that not only the largest financial institutions but also the smaller but highly interconnected institutions are systemically important and need to be regulated