IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v680y2025ics0378437125007101.html

Extreme volatility risk dynamic diffusion in financial market based on a new VEBN framework

Author

Listed:
  • Li, Jiang-Cheng
  • Tao, Chen
  • Xu, Yi-Zhen
  • Zhong, Guang-Yan

Abstract

Understanding how volatility risk spreads during financial crises is vital for market stability and effective risk management. We introduce the Volatility Entropy-based Network (VEBN), a new framework that quantifies volatility risk diffusion using weighted network statistics. Applying this method to the Chinese stock market, we reveal the asymmetry of risk diffusion across industries and explore the changes of risky industries under different types of extreme events. Notably, internal industry linkages drive risk transmission more strongly than external shocks, and extreme events intensify this effect while promoting inter-industry cooperation. These findings suggest that risk managers and regulators should focus on monitoring industry interconnections and adapt risk controls dynamically during periods of heightened volatility. Robustness checks with stochastic volatility and GARCH models confirm our results. Our work offers a novel quantitative tool for analyzing and mitigating systemic risk in complex financial networks.

Suggested Citation

  • Li, Jiang-Cheng & Tao, Chen & Xu, Yi-Zhen & Zhong, Guang-Yan, 2025. "Extreme volatility risk dynamic diffusion in financial market based on a new VEBN framework," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 680(C).
  • Handle: RePEc:eee:phsmap:v:680:y:2025:i:c:s0378437125007101
    DOI: 10.1016/j.physa.2025.131058
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437125007101
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2025.131058?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. Jaroonchokanan, Nawee & Termsaithong, Teerasit & Suwanna, Sujin, 2022. "Dynamics of hierarchical clustering in stocks market during financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    2. M. Raddant & T. Di Matteo, 2023. "A look at financial dependencies by means of econophysics and financial economics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(4), pages 701-734, October.
    3. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
    4. Li, Zhong-fei & Zhou, Qi & Chen, Ming & Liu, Qian, 2021. "The impact of COVID-19 on industry-related characteristics and risk contagion," Finance Research Letters, Elsevier, vol. 39(C).
    5. Huang, Wei-Qiang & Wang, Dan, 2018. "A return spillover network perspective analysis of Chinese financial institutions’ systemic importance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 405-421.
    6. Zhang, Dayong & Hu, Min & Ji, Qiang, 2020. "Financial markets under the global pandemic of COVID-19," Finance Research Letters, Elsevier, vol. 36(C).
    7. Uzonwanne, Godfrey, 2021. "Volatility and return spillovers between stock markets and cryptocurrencies," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 30-36.
    8. Jiang, Wei & Ruan, Qingsong & Li, Jianfeng & Li, Ye, 2018. "Modeling returns volatility: Realized GARCH incorporating realized risk measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 249-258.
    9. Fama, Eugene F, 1981. "Stock Returns, Real Activity, Inflation, and Money," American Economic Review, American Economic Association, vol. 71(4), pages 545-565, September.
    10. Greenwood-Nimmo, Matthew & Nguyen, Viet Hoang & Rafferty, Barry, 2016. "Risk and return spillovers among the G10 currencies," Journal of Financial Markets, Elsevier, vol. 31(C), pages 43-62.
    11. 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.
    12. 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.
    13. Tao, Chen & Zhong, Guang-Yan & Li, Jiang-Cheng, 2023. "Dynamic correlation and risk resonance among industries of Chinese stock market: New evidence from time–frequency domain and complex network perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 614(C).
    14. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Hussain Shahzad, Syed Jawad & Výrost, Tomáš, 2022. "Measuring systemic risk in the global banking sector: A cross-quantilogram network approach," Economic Modelling, Elsevier, vol. 109(C).
    15. Ahnert, Toni & Georg, Co-Pierre, 2018. "Information contagion and systemic risk," Journal of Financial Stability, Elsevier, vol. 35(C), pages 159-171.
    16. Yu, Miao & Hu, Xiaolu & Zhong, Angel, 2024. "Network centrality, information diffusion and asset pricing," International Review of Financial Analysis, Elsevier, vol. 93(C).
    17. Joshua C. C. Chan & Eric Eisenstat, 2018. "Bayesian model comparison for time‐varying parameter VARs with stochastic volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(4), pages 509-532, June.
    18. Syed Jawad Hussain Shahzad & Elie Bouri & Ladislav Kristoufek & Tareq Saeed, 2021. "Impact of the COVID-19 outbreak on the US equity sectors: Evidence from quantile return spillovers," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-23, December.
    19. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    20. Espinosa-Paredes, G. & Rodriguez, E. & Alvarez-Ramirez, J., 2022. "A singular value decomposition entropy approach to assess the impact of Covid-19 on the informational efficiency of the WTI crude oil market," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    21. Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015. "Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes," Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
    22. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
    23. Peng Yue & Yaodong Fan & Jonathan A. Batten & Wei-Xing Zhou, 2020. "Information transfer between stock market sectors: A comparison between the USA and China," Papers 2004.07612, arXiv.org.
    24. Shahzad, Syed Jawad Hussain & Naeem, Muhammad Abubakr & Peng, Zhe & Bouri, Elie, 2021. "Asymmetric volatility spillover among Chinese sectors during COVID-19," International Review of Financial Analysis, Elsevier, vol. 75(C).
    25. Goodell, John W., 2020. "COVID-19 and finance: Agendas for future research," Finance Research Letters, Elsevier, vol. 35(C).
    26. repec:iae:iaewps:wp2016n4 is not listed on IDEAS
    27. Kim, Jungmu & Park, Yuen Jung & Ryu, Doojin, 2017. "Stochastic volatility of the futures prices of emission allowances: A Bayesian approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 714-724.
    28. Zhang, Jixiang & Zeng, Qing & Bouri, Elie & Gozgor, Giray, 2025. "Newly-constructed Chinese geopolitical risk index and trade stock returns," Research in International Business and Finance, Elsevier, vol. 74(C).
    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. Abubakr Naeem, Muhammad & Iqbal, Najaf & Lucey, Brian M. & Karim, Sitara, 2022. "Good versus bad information transmission in the cryptocurrency market: Evidence from high-frequency data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    2. Cheng, Tingting & Liu, Fei & Liu, Junli & Yao, Wenying, 2024. "Tail connectedness: Measuring the volatility connectedness network of equity markets during crises," Pacific-Basin Finance Journal, Elsevier, vol. 87(C).
    3. Fei Su & Feifan Wang & Yahua Xu, 2025. "Economic Policy Uncertainty and Volatility Spillovers Among International Stock Market Indices During the COVID-19 Outbreak," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 32(1), pages 237-266, March.
    4. Shahzad, Syed Jawad Hussain & Naeem, Muhammad Abubakr & Peng, Zhe & Bouri, Elie, 2021. "Asymmetric volatility spillover among Chinese sectors during COVID-19," International Review of Financial Analysis, Elsevier, vol. 75(C).
    5. Costa, Antonio & Matos, Paulo & da Silva, Cristiano, 2022. "Sectoral connectedness: New evidence from US stock market during COVID-19 pandemics," Finance Research Letters, Elsevier, vol. 45(C).
    6. 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).
    7. Ahelegbey, Daniel Felix & Cerchiello, Paola & Scaramozzino, Roberta, 2022. "Network based evidence of the financial impact of Covid-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 81(C).
    8. Finta, Marinela Adriana & Aboura, Sofiane, 2020. "Risk premium spillovers among stock markets: Evidence from higher-order moments," Journal of Financial Markets, Elsevier, vol. 49(C).
    9. Corradi, Valentina & Distaso, Walter & Mele, Antonio, 2013. "Macroeconomic determinants of stock volatility and volatility premiums," Journal of Monetary Economics, Elsevier, vol. 60(2), pages 203-220.
    10. Finta, Marinela Adriana, 2025. "Risk premia-return spillovers among commodity-U.S. equity markets," International Review of Economics & Finance, Elsevier, vol. 102(C).
    11. Zhou, Dong-hai & Liu, Xiao-xing & Tang, Chun & Yang, Guang-yi, 2023. "Time-varying risk spillovers in Chinese stock market – New evidence from high-frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    12. Wang, Dong & Li, Ping & Huang, Lixin, 2022. "Time-frequency volatility spillovers between major international financial markets during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 46(PA).
    13. Christian Urom & Gideon Ndubuisi & Jude Ozor, 2021. "Economic activity, and financial and commodity markets’ shocks: An analysis of implied volatility indexes," International Economics, CEPII research center, issue 165, pages 51-66.
    14. Syed Moudud-Ul-Huq & Md. Shahriar Rahman, 2025. "Stock Market Efficiency of the BRICS Countries Pre-, During, and Post Covid-19 Pandemic: A Multifractal Detrended Fluctuation Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 65(3), pages 1643-1705, March.
    15. Tim Bollerslev & Benjamin Hood & John Huss & Lasse Heje Pedersen, 2018. "Risk Everywhere: Modeling and Managing Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2729-2773.
    16. Cao, Guangxi & Xie, Wenhao, 2022. "Asymmetric dynamic spillover effect between cryptocurrency and China's financial market: Evidence from TVP-VAR based connectedness approach," Finance Research Letters, Elsevier, vol. 49(C).
    17. František Pollák & Kristián Kalamen & Roman Vavrek & Mónica García-Melón, 2026. "Understanding sectoral co-movement and investor behaviour during black swan events: a study of tech and pharma stocks during the global pandemic," Digital Finance, Springer, vol. 8(2), pages 1-23, June.
    18. Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Doğan, Buhari & Adekoya, Oluwasegun B. & Wohar, Mark, 2024. "Asymmetric spillover effects in energy markets," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 470-502.
    19. Ouyang, Minhua & Xiao, Hailian, 2024. "Tail risk spillovers among Chinese stock market sectors," Finance Research Letters, Elsevier, vol. 62(PB).
    20. Naeem, Muhammad Abubakr & Yousaf, Imran & Karim, Sitara & Yarovaya, Larisa & Ali, Shoaib, 2023. "Tail-event driven NETwork dependence in emerging markets," Emerging Markets Review, Elsevier, vol. 55(C).

    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:phsmap:v:680:y:2025:i:c:s0378437125007101. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.