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Measuring Systemic Risk Contagion Effect of the Banking Industry in China: A Directed Network Approach

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  • Zi-Sheng Ouyang
  • Ying Huang
  • Yun Jia
  • Chang-Qing Luo

Abstract

To capture the impact of investor sentiment on risk contagion of financial institutions and potential tail risks caused by financial network structure, this paper uses a directed network approach to measure systemic risk contagion effect of Chinese banking industry. We use linear quantile lasso regression and local polynomial method to estimate TENET model, and construct a weighted directed network. Moreover, we study directed network from different perspectives, analyze financial risk contagion effect and the influence of investor sentiment on financial risk contagion, and identify systemically important financial institutions. We find that: (1) As crisis spreads, financial system becomes more closely related, and total network connectivity continues to rise until it reaches a maximum value. (2) Total network connectivity and systemic risk have the same upward or downward trend, but systemic risk lags behind total network connectivity. (3) Current bank has characteristics of “too big to fail” and “too contact to fail”.

Suggested Citation

  • Zi-Sheng Ouyang & Ying Huang & Yun Jia & Chang-Qing Luo, 2020. "Measuring Systemic Risk Contagion Effect of the Banking Industry in China: A Directed Network Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(6), pages 1312-1335, May.
    • Handle: RePEc:mes:emfitr:v:56:y:2020:i:6:p:1312-1335
    DOI: 10.1080/1540496X.2019.1711368
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    Cited by:

    1. Ouyang, Zisheng & Zhou, Xuewei, 2023. "Interconnected networks: Measuring extreme risk connectedness between China’s financial sector and real estate sector," International Review of Financial Analysis, Elsevier, vol. 90(C).
    2. Ouyang, Zisheng & Zhou, Xuewei & Lu, Min & Liu, Ke, 2024. "Imported financial risk in global stock markets: Evidence from the interconnected network," Research in International Business and Finance, Elsevier, vol. 69(C).
    3. Addi, Abdelhamid & Bouoiyour, Jamal, 2023. "Interconnectedness and extreme risk: Evidence from dual banking systems," Economic Modelling, Elsevier, vol. 120(C).
    4. Tian, Sihua & Li, Shaofang & Gu, Qinen, 2023. "Measurement and contagion modelling of systemic risk in China's financial sectors: Evidence for functional data analysis and complex network," International Review of Financial Analysis, Elsevier, vol. 90(C).
    5. Ouyang, Zisheng & Chen, Shili & Lai, Yongzeng & Yang, Xite, 2022. "The correlations among COVID-19, the effect of public opinion, and the systemic risks of China’s financial industries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).

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