IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v66y2025i6d10.1007_s10614-025-10870-y.html
   My bibliography  Save this article

Tail Risk Spillovers Between the Financial Sector and Real Economy: Network Analysis of China’s Industries

Author

Listed:
  • Chao Li

    (Shandong University of Finance and Economics, School of Insurance)

  • Zhuoer Zhang

    (Cornell University, Department of Operations Research and Information Engineering)

  • Han Cang

    (Soochow University, Finance Department, Business School)

Abstract

In this paper, applying dynamic CoVaR models and the Tail-event driven network (TENET) approach, we measure tail-risk interdependence among 11 industries in China over the period between October 2006 to December 2023. The TENET approach extends the bivariate CoVaR model to an ultra-high dimensional analysis framework. Backtesting analysis illustrates the outperformance of TENET approaches in capturing the tail-risk spread during crisis period. Our analysis reveals that the real estate, energy, and telecommunication industries are more susceptible to the tail risk of the financial sector, while the financial, energy, and materials sectors emerge as the largest risk receivers. This interconnectedness intensifies during crises, driven largely by the fatter tails of the financial sector’s return distributions. Our findings highlight the significant role of “derealization to virtuality” measure by the financialization of firms as a primary channel through which financial risks are transmitted to the real economy. The connectedness between the financial and real sectors forms a two-way link, with risks originating from the financial sector flowing between the two sectors. This risk transmission gradually weakens over time, resulting in incoming links exhibiting lower volatility compared to outgoing ones.

Suggested Citation

  • Chao Li & Zhuoer Zhang & Han Cang, 2025. "Tail Risk Spillovers Between the Financial Sector and Real Economy: Network Analysis of China’s Industries," Computational Economics, Springer;Society for Computational Economics, vol. 66(6), pages 5055-5081, December.
    • Handle: RePEc:kap:compec:v:66:y:2025:i:6:d:10.1007_s10614-025-10870-y
    DOI: 10.1007/s10614-025-10870-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-025-10870-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10614-025-10870-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:66:y:2025:i:6:d:10.1007_s10614-025-10870-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.