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A New Measurement of Systemic Risk in China's Banking System

Received: 20 April 2021     Accepted: 4 June 2021     Published: 10 June 2021
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Abstract

At present, the measurement of systemic risk is still a worldwide challenge. The complex network theory provides a new perspective for the study of this problem. Based on the correlation coefficient between the banks calculated using their default probabilities, this paper builds China's banking networks for the periods of 2008-2019, and analyzes systematically the topological structure of the networks, and determine the size of the systemic risk from the perspective of network topology by using the corresponding characteristics of complex network with the feature of systemic financial risk. It is found that the systemic risk of China's banking industry has a declined tendency before 2018, and the main cause is due to the eigenvector centrality and clustering coefficient declined rapidly. However, after 2018, systemic risk showed a litter upward trend, and the increase of clustering coefficient and eigenvector centrality was the main reason for that upward trend. Before 2018, risk transmission was mainly taken place from local banks and joint-equity commercial banks to state-owned banks, which were the main risk bearers. After 2018, risk contagion mainly occurred among local banks, and some local banks role as systemically important ones. Therefore, dissolving the systemic financial risk in China should strengthen the regulation of local banks. In particular, the high-risk leverage operations and excessively innovative business should be strictly supervised so as to prevent the expansion and spread of the negative effects stemmed from maturity mismatch, maturity transformation and credit transformation.

Published in Journal of Finance and Accounting (Volume 9, Issue 3)
DOI 10.11648/j.jfa.20210903.14
Page(s) 87-92
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Banking Network, Probability of Default, Contagion Risk, Systemic Risk

References
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[5] Larry, E., and T. Noe, Systemic Risk in Financial System, Management Science. 2011, 47 (2): 236-49.
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[7] Ouyang Hong-bing. Liu Xiao-dong, An Analysis of the Systemic Importance and Systemic Risk Contagion Mechanism of China’s Financial Institution on Network Analysis, Chinese Journal of Management Science, 2015, 23 (10): 30-37.
[8] Acharya, V., and A. Bisin, Counterparty Risk Externality: Centralized versus Over-the-counter Markets, Journal of Economic Theory, 2014, Vol. 149. 153-182.
[9] Liu Zhi-yang. The Risk Analysis of Chinese Inter-bank Debt Default Contagion Under Network Structure – A Two-dimensional Data Perspective of Inter-bank Debt and Financial Market, Modern Economic Science. 2020, 42 (03).
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[11] Zhang Wei-ping, Zhuang Xin-tian, Li Yan-shuang. Stock Market Network Topology and Systematic Risk Contribution: Based on VaR Network Model, Engineering Management. 2020 (04).
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Cite This Article
  • APA Style

    Yong Li, Hulin Zhao. (2021). A New Measurement of Systemic Risk in China's Banking System. Journal of Finance and Accounting, 9(3), 87-92. https://doi.org/10.11648/j.jfa.20210903.14

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    ACS Style

    Yong Li; Hulin Zhao. A New Measurement of Systemic Risk in China's Banking System. J. Finance Account. 2021, 9(3), 87-92. doi: 10.11648/j.jfa.20210903.14

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    AMA Style

    Yong Li, Hulin Zhao. A New Measurement of Systemic Risk in China's Banking System. J Finance Account. 2021;9(3):87-92. doi: 10.11648/j.jfa.20210903.14

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  • @article{10.11648/j.jfa.20210903.14,
      author = {Yong Li and Hulin Zhao},
      title = {A New Measurement of Systemic Risk in China's Banking System},
      journal = {Journal of Finance and Accounting},
      volume = {9},
      number = {3},
      pages = {87-92},
      doi = {10.11648/j.jfa.20210903.14},
      url = {https://doi.org/10.11648/j.jfa.20210903.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jfa.20210903.14},
      abstract = {At present, the measurement of systemic risk is still a worldwide challenge. The complex network theory provides a new perspective for the study of this problem. Based on the correlation coefficient between the banks calculated using their default probabilities, this paper builds China's banking networks for the periods of 2008-2019, and analyzes systematically the topological structure of the networks, and determine the size of the systemic risk from the perspective of network topology by using the corresponding characteristics of complex network with the feature of systemic financial risk. It is found that the systemic risk of China's banking industry has a declined tendency before 2018, and the main cause is due to the eigenvector centrality and clustering coefficient declined rapidly. However, after 2018, systemic risk showed a litter upward trend, and the increase of clustering coefficient and eigenvector centrality was the main reason for that upward trend. Before 2018, risk transmission was mainly taken place from local banks and joint-equity commercial banks to state-owned banks, which were the main risk bearers. After 2018, risk contagion mainly occurred among local banks, and some local banks role as systemically important ones. Therefore, dissolving the systemic financial risk in China should strengthen the regulation of local banks. In particular, the high-risk leverage operations and excessively innovative business should be strictly supervised so as to prevent the expansion and spread of the negative effects stemmed from maturity mismatch, maturity transformation and credit transformation.},
     year = {2021}
    }
    

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  • TY  - JOUR
    T1  - A New Measurement of Systemic Risk in China's Banking System
    AU  - Yong Li
    AU  - Hulin Zhao
    Y1  - 2021/06/10
    PY  - 2021
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    DO  - 10.11648/j.jfa.20210903.14
    T2  - Journal of Finance and Accounting
    JF  - Journal of Finance and Accounting
    JO  - Journal of Finance and Accounting
    SP  - 87
    EP  - 92
    PB  - Science Publishing Group
    SN  - 2330-7323
    UR  - https://doi.org/10.11648/j.jfa.20210903.14
    AB  - At present, the measurement of systemic risk is still a worldwide challenge. The complex network theory provides a new perspective for the study of this problem. Based on the correlation coefficient between the banks calculated using their default probabilities, this paper builds China's banking networks for the periods of 2008-2019, and analyzes systematically the topological structure of the networks, and determine the size of the systemic risk from the perspective of network topology by using the corresponding characteristics of complex network with the feature of systemic financial risk. It is found that the systemic risk of China's banking industry has a declined tendency before 2018, and the main cause is due to the eigenvector centrality and clustering coefficient declined rapidly. However, after 2018, systemic risk showed a litter upward trend, and the increase of clustering coefficient and eigenvector centrality was the main reason for that upward trend. Before 2018, risk transmission was mainly taken place from local banks and joint-equity commercial banks to state-owned banks, which were the main risk bearers. After 2018, risk contagion mainly occurred among local banks, and some local banks role as systemically important ones. Therefore, dissolving the systemic financial risk in China should strengthen the regulation of local banks. In particular, the high-risk leverage operations and excessively innovative business should be strictly supervised so as to prevent the expansion and spread of the negative effects stemmed from maturity mismatch, maturity transformation and credit transformation.
    VL  - 9
    IS  - 3
    ER  - 

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Author Information
  • Business School, China University of Political Science and Law, Beijing, China

  • Business School, Gansu University of Political Science and Law, Lanzhou, China

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