IDEAS home Printed from https://ideas.repec.org/a/ayb/jrnael/20.html
   My bibliography  Save this article

Systemic Risk in China's Financial Industry Due to the COVID-19 Pandemic

Author

Listed:
  • Cheng Lan
  • Ziyi Huang
  • Wenli Huang

    (China Academy of Financial Research, Zhejiang University of Finance and Economics, China)

Abstract

In this paper, the dynamic CoVaR method is used to measure changes in systemic risk in the financial industry during the COVID-19 pandemic. We find that, first, after the outbreak of the COVID-19 pandemic, the systemic risk of the financial industry increased significantly. Second, the impact of the COVID-19 pandemic on the systemic risk of the securities industry was greater than that of the banking and insurance industries.

Suggested Citation

  • Cheng Lan & Ziyi Huang & Wenli Huang, 2021. "Systemic Risk in China's Financial Industry Due to the COVID-19 Pandemic," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 1(3), pages 1-5.
    • Handle: RePEc:ayb:jrnael:20
    DOI: 2021/08/10
    as

    Download full text from publisher

    File URL: https://a-e-l.scholasticahq.com/api/v1/articles/18070-systemic-risk-in-china-s-financial-industry-due-to-the-covid-19-pandemic.pdf
    Download Restriction: no
    File URL: https://libkey.io/2021/08/10?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
    ---><---

    References listed on IDEAS

    as
    1. Tobias Adrian & Markus K. Brunnermeier, 2016. "CoVaR," American Economic Review, American Economic Association, vol. 106(7), pages 1705-1741, July.
      • Tobias Adrian & Markus K. Brunnermeier, 2008. "CoVaR," Staff Reports 348, Federal Reserve Bank of New York.
      • Tobias Adrian & Markus K. Brunnermeier, 2011. "CoVaR," NBER Working Papers 17454, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chang, Carolyn W. & Li, Xiaodan & Lin, Edward M.H. & Yu, Min-Teh, 2018. "Systemic risk, interconnectedness, and non-core activities in Taiwan insurance industry," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 273-284.
    2. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
    3. Roland Füss & Daniel Ruf, 2018. "Office Market Interconnectedness and Systemic Risk Exposure," Working Papers on Finance 1830, University of St. Gallen, School of Finance.
    4. Lovcha, Yuliya & Perez-Laborda, Alejandro, 2020. "Dynamic frequency connectedness between oil and natural gas volatilities," Economic Modelling, Elsevier, vol. 84(C), pages 181-189.
    5. Dissem, Sonia & Lobez, Frederic, 2020. "Correlation between the 2014 EU-wide stress tests and the market-based measures of systemic risk," Research in International Business and Finance, Elsevier, vol. 51(C).
    6. Algieri, Bernardina & Leccadito, Arturo, 2017. "Assessing contagion risk from energy and non-energy commodity markets," Energy Economics, Elsevier, vol. 62(C), pages 312-322.
    7. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 958-969.
    8. Kabundi, Alain & De Simone, Francisco Nadal, 2020. "Monetary policy and systemic risk-taking in the euro area banking sector," Economic Modelling, Elsevier, vol. 91(C), pages 736-758.
    9. Yuya Sasaki & Yulong Wang, 2022. "Fixed-k Inference for Conditional Extremal Quantiles," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(2), pages 829-837, April.
    10. Alin Marius Andrieş & Simona Nistor, 2018. "Systemic Risk and Foreign Currency Positions of Banks: Evidence from Emerging Europe," Eastern European Economics, Taylor & Francis Journals, vol. 56(5), pages 382-421, September.
    11. Warshaw, Evan, 2019. "Extreme dependence and risk spillovers across north american equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 237-251.
    12. Ellington, Michael, 2022. "Fat tails, serial dependence, and implied volatility index connections," European Journal of Operational Research, Elsevier, vol. 299(2), pages 768-779.
    13. Ahelegbey, Daniel Felix & Giudici, Paolo & Hashem, Shatha Qamhieh, 2021. "Network VAR models to measure financial contagion," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    14. Gong, Chen & Tang, Pan & Wang, Yutong, 2019. "Measuring the network connectedness of global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    15. Laurentiu Dumitru ANDREI & Petre BREZEANU & Sorin-Marius DINU & Tiberiu DIACONESCU & Constantin ANGHELACHE, 2019. "Correlations and Turbulence of the European Markets," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 88-100, March.
    16. Xu, Qiuhua & Zhang, Yixuan & Zhang, Ziyang, 2021. "Tail-risk spillovers in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 38(C).
    17. Ebrahimi Kahou, Mahdi & Lehar, Alfred, 2017. "Macroprudential policy: A review," Journal of Financial Stability, Elsevier, vol. 29(C), pages 92-105.
    18. Caporin, Massimiliano & Pelizzon, Loriana & Ravazzolo, Francesco & Rigobon, Roberto, 2018. "Measuring sovereign contagion in Europe," Journal of Financial Stability, Elsevier, vol. 34(C), pages 150-181.
    19. Bruno Ferreira Frascaroli & Wellington Charles Lacerda Nobrega, 2019. "Inflation Targeting and Inflation Risk in Latin America," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(11), pages 2389-2408, September.
    20. Robert F. Engle & Emil N. Siriwardane, 2018. "Structural GARCH: The Volatility-Leverage Connection," The Review of Financial Studies, Society for Financial Studies, vol. 31(2), pages 449-492.

    More about this item

    Keywords

    systemic financial risk; dynamic covar; covid-19;
    All these keywords.

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • I1 - Health, Education, and Welfare - - Health

    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:ayb:jrnael:20. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Asia-Pacific Applied Economics Association (email available below). General contact details of provider: https://edirc.repec.org/data/apaeaea.html .

    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.