Evaluating the Systemic Importance of China’s Banks via Adjacency Information Entropy

Junzhi Zhang, Lei Chen and Gengxin Sun

Discrete Dynamics in Nature and Society, 2022, vol. 2022, 1-12

Abstract: Information entropy can be utilized to assess the complexity of the Banking System and the uncertainty of association information between banks. Based on information entropy and the balance sheet data of 167 banks from 2011 to 2020, we proposed a centrality indicator based on Adjacency Information Entropy, then applied it to directed weighted and directed unweighted interbank networks to identify banks with systemically important status, and compared the results with those of traditional centrality indicators. The outcomes show that the results of centrality indicator based on Adjacency Information Entropy are more accurate than those of traditional centrality indicators in identifying banks with systemically important status in interbank networks. Six large state-owned commercial banks, nine joint-stock commercial banks, two policy banks, and two urban commercial banks with large assets are identified as systemically important banks based on the proposed centrality indicator, which is highly consistent with the list of systemically important banks published by the Chinese banking regulator. Among the systemically important banks, changes in systemic risk levels of joint-stock commercial banks and urban commercial banks are more susceptible to national policies than those of large state-owned commercial banks. The findings of this paper have certain reference significance for strengthening the supervision of banks with systemically important status in interbank networks and formulating targeted policies for regulating large commercial banks and small- and medium-sized commercial banks.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:6979176

DOI: 10.1155/2022/6979176

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