IDEAS home Printed from https://ideas.repec.org/a/eee/pacfin/v91y2025ics0927538x25000563.html
   My bibliography  Save this article

The performance of industry risk spillover under extreme events: Evidence from the Chinese stock market

Author

Listed:
  • Yao, Haixiang
  • Jiang, Xiaoqing

Abstract

This study examines the characteristics of industry-level risk contagion networks within the Chinese stock market. The research findings indicate that the risk contagion behaviors of most industries exhibit a high degree of consistency under various types of extreme risk events. The upward and downward tail contagion networks constructed based on the ΔCoES indicator reveal that the financial and real estate sectors exhibit the most pronounced performance in the upward tail network. Employing “good” volatility, “bad” volatility, and the Diebold-Yilmaz variance decomposition method, we find that extreme risk events that hit the stock market lead to a significant increase in “good” volatility spillovers between industries. Industry characteristics dictate their roles within contagion networks, categorizing them as risk emitters (industrials, materials, consumer discretionary), risk receivers (financials, energy), systemic risk amplifiers (information technology, communication services), and sectors with low sensitivity to risk (consumer staples, healthcare, utilities). Notably, the healthcare and utilities sectors significantly influence the contagion network during specific periods.

Suggested Citation

  • Yao, Haixiang & Jiang, Xiaoqing, 2025. "The performance of industry risk spillover under extreme events: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 91(C).
  • Handle: RePEc:eee:pacfin:v:91:y:2025:i:c:s0927538x25000563
    DOI: 10.1016/j.pacfin.2025.102719
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927538X25000563
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.pacfin.2025.102719?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.

    References listed on IDEAS

    as
    1. Marco Bardoscia & Stefano Battiston & Fabio Caccioli & Guido Caldarelli, 2016. "Pathways towards instability in financial networks," Papers 1602.05883, arXiv.org, revised Feb 2017.
    2. Segal, Gill & Shaliastovich, Ivan & Yaron, Amir, 2015. "Good and bad uncertainty: Macroeconomic and financial market implications," Journal of Financial Economics, Elsevier, vol. 117(2), pages 369-397.
    3. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    4. 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.
    5. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    6. Matthew Elliott & Benjamin Golub & Matthew O. Jackson, 2014. "Financial Networks and Contagion," American Economic Review, American Economic Association, vol. 104(10), pages 3115-3153, October.
    7. Battiston, Stefano & Delli Gatti, Domenico & Gallegati, Mauro & Greenwald, Bruce & Stiglitz, Joseph E., 2012. "Liaisons dangereuses: Increasing connectivity, risk sharing, and systemic risk," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1121-1141.
    8. Bouri, Elie & Harb, Etienne, 2022. "The size of good and bad volatility shocks does matter for spillovers," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    9. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers," Journal of Financial Markets, Elsevier, vol. 27(C), pages 55-78.
    10. Robert J. Barro, 2006. "Rare Disasters and Asset Markets in the Twentieth Century," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(3), pages 823-866.
    11. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    12. Xie, Yiwei & Jiao, Feng & Li, Shihan & Liu, Qingfu & Tse, Yiuman, 2022. "Systemic risk in financial institutions: A multiplex network approach," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    13. Ellis, Scott & Sharma, Satish & Brzeszczyński, Janusz, 2022. "Systemic risk measures and regulatory challenges," Journal of Financial Stability, Elsevier, vol. 61(C).
    14. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    15. Chen, Wei & Hou, Xiaoli & Jiang, Manrui & Jiang, Cheng, 2022. "Identifying systemically important financial institutions in complex network: A case study of Chinese stock market," Emerging Markets Review, Elsevier, vol. 50(C).
    16. Christian Brownlees & Robert F. Engle, 2017. "SRISK: A Conditional Capital Shortfall Measure of Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 48-79.
    17. Wang, Hu & Liu, Xin, 2024. "Volatility spillover features in financial industries and identification of systemically important financial institutions: A new perspective," Pacific-Basin Finance Journal, Elsevier, vol. 83(C).
    18. Nartea, Gilbert V. & Kong, Dongmin & Wu, Ji, 2017. "Do extreme returns matter in emerging markets? Evidence from the Chinese stock market," Journal of Banking & Finance, Elsevier, vol. 76(C), pages 189-197.
    19. Yangguang Zhu & Feng Yang & Wuyi Ye, 2018. "Financial contagion behavior analysis based on complex network approach," Annals of Operations Research, Springer, vol. 268(1), pages 93-111, September.
    20. Marco Bardoscia & Stefano Battiston & Fabio Caccioli & Guido Caldarelli, 2017. "Pathways towards instability in financial networks," Nature Communications, Nature, vol. 8(1), pages 1-7, April.
    21. Gong, Xiao-Li & Liu, Jian-Min & Xiong, Xiong & Zhang, Wei, 2022. "Research on stock volatility risk and investor sentiment contagion from the perspective of multi-layer dynamic network," International Review of Financial Analysis, Elsevier, vol. 84(C).
    22. Zheng, Yingfei & Shen, Anran & Li, Ruihai & Yang, Yuhong & Wang, Shengjin & Cheng, Lee-Young, 2023. "Spillover effects between internet financial industry and traditional financial industry: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    23. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    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. Ahelegbey, Daniel Felix & Giudici, Paolo & Mojtahedi, Fatemeh, 2021. "Tail risk measurement in crypto-asset markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    2. Wang, Gang-Jin & Xie, Chi & Zhao, Longfeng & Jiang, Zhi-Qiang, 2018. "Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 205-230.
    3. Cao, Yufei & Zou, Yueming, 2025. "How robust are financial connectedness networks? A network attack assessment," Research in International Business and Finance, Elsevier, vol. 76(C).
    4. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    5. Xiaoyu Liu & Xiaoli Chen, 2021. "Can “Concerted” Macroprudential Policies Mitigate Cross‐border Contagion of Financial Risks? Evidence from China and Its Financially Connected Economies," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 29(3), pages 26-54, May.
    6. Jozef Barunik & Mattia Bevilacqua & Radu Tunaru, 2022. "Asymmetric Network Connectedness of Fears," The Review of Economics and Statistics, MIT Press, vol. 104(6), pages 1304-1316, November.
    7. Nong, Huifu & Yu, Ziliang & Li, Yang, 2024. "Financial shock transmission in China's banking and housing sectors: A network analysis," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 701-723.
    8. Foglia, Matteo & Addi, Abdelhamid & Angelini, Eliana, 2022. "The Eurozone banking sector in the time of COVID-19: Measuring volatility connectedness," Global Finance Journal, Elsevier, vol. 51(C).
    9. Chen, Huayi & Shi, Huai-Long & Zhou, Wei-Xing, 2024. "Carbon volatility connectedness and the role of external uncertainties: Evidence from China," Journal of Commodity Markets, Elsevier, vol. 33(C).
    10. Egger, Peter H. & Li, Jie & Zhu, Jiaqing, 2023. "The network and own effects of global-systemically-important-bank designations," Journal of International Money and Finance, Elsevier, vol. 136(C).
    11. Fengler, Matthias R. & Gisler, Katja I.M., 2015. "A variance spillover analysis without covariances: What do we miss?," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 174-195.
    12. Chen, Chuanglian & Zhou, Lichao & Sun, Chuanwang & Lin, Yuting, 2024. "Does oil future increase the network systemic risk of financial institutions in China?," Applied Energy, Elsevier, vol. 364(C).
    13. Li, Yanshuang & Zhuang, Xintian & Wang, Jian, 2021. "Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    14. Buse, Rebekka & Schienle, Melanie, 2019. "Measuring connectedness of euro area sovereign risk," International Journal of Forecasting, Elsevier, vol. 35(1), pages 25-44.
    15. Shafiullah, Muhammad & Senthilkumar, Arunachalam & Lucey, Brian M. & Naeem, Muhammad Abubakr, 2024. "Deciphering asymmetric spillovers in US industries: Insights from higher-order moments," Research in International Business and Finance, Elsevier, vol. 70(PA).
    16. Wiesen, Thomas F.P. & Adekoya, Oluwasegun Babatunde & Oliyide, Johnson & Afatsao, Richard, 2024. "Does high volatility increase connectedness? A study of Asian equity markets," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    17. Mr. Jorge A Chan-Lau, 2017. "Variance Decomposition Networks: Potential Pitfalls and a Simple Solution," IMF Working Papers 2017/107, International Monetary Fund.
    18. Caporin, Massimiliano & Naeem, Muhammad Abubakr & Arif, Muhammad & Hasan, Mudassar & Vo, Xuan Vinh & Hussain Shahzad, Syed Jawad, 2021. "Asymmetric and time-frequency spillovers among commodities using high-frequency data," Resources Policy, Elsevier, vol. 70(C).
    19. Jules Clement Mba, 2024. "Assessing portfolio vulnerability to systemic risk: a vine copula and APARCH-DCC approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-36, December.
    20. Hsu, Chih-Hsiang & Lee, Hsiu-Chuan & Lien, Donald, 2020. "Stock market uncertainty, volatility connectedness of financial institutions, and stock-bond return correlations," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 600-621.

    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:eee:pacfin:v:91:y:2025:i:c:s0927538x25000563. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/pacfin .

    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.