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Exploring Systemic Risk Dynamics in the Chinese Stock Market: A Network Analysis with Risk Transmission Index

Author

Listed:
  • Xiaowei Zeng

    (School of Management, Fudan University, Shanghai 200433, China)

  • Yifan Hu

    (School of Data Science, Fudan University, Shanghai 200433, China)

  • Chengjun Pan

    (School of Data Science, Fudan University, Shanghai 200433, China)

  • Yanxi Hou

    (School of Data Science, Fudan University, Shanghai 200433, China)

Abstract

Systemic risk refers to the potential for a disruption in one part of a financial system to trigger a cascade of adverse effects, impacting the functioning of the system. Despite the progress on novel systemic risk measures, research on dynamics of systemic risk network structure and its community effect is still in its initial state. In this study, we utilize price data from 107 representative Chinese stocks spanning the period from 2017 to 2022. A systemic risk network is derived from the Risk Transmission Index based on TENET and the QR–Lasso model. By utilizing DBSCAN, HITS and community detection algorithms on the network, we aim to propose a more suitable definition of systemically important companies, explore the interrelationships between companies, and discuss its plausible reasons for dynamics structural changes. The empirical findings demonstrate a substantial involvement of insurance companies in both contributing to and receiving systemic risk within the analyzed context. We identify prominent risk output and input centers, and emphasize the profound impact of the COVID-19 pandemic on the dynamics of systemic risk.

Suggested Citation

  • Xiaowei Zeng & Yifan Hu & Chengjun Pan & Yanxi Hou, 2024. "Exploring Systemic Risk Dynamics in the Chinese Stock Market: A Network Analysis with Risk Transmission Index," Risks, MDPI, vol. 12(3), pages 1-24, March.
    • Handle: RePEc:gam:jrisks:v:12:y:2024:i:3:p:56-:d:1360214
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    References listed on IDEAS

    as
    1. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    2. Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
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