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Enhanced volatility spillover network prediction of Chinese financial institutions using GCN-LSTM model

Author

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  • Gu, Qinen
  • Li, Shaofang
  • Qin, Jiaying

Abstract

By constructing the volatility spillover network based on LASSO-VAR and generalized variance decomposition method, this study develops the graph convolutional network and long short-term memory (GCN-LSTM) model to predict the volatility spillover network of 31 listed Chinese financial institutions between 2014 and 2022. Our findings confirm the volatility spillover of bank, security and insurance sectors exhibits heterogeneity and during the stock market crash, the volatility spillover network among institutions is enhanced, and the spillover from security to bank and insurance plays a crucial role in accumulating systemic financial risk. The empirical results demonstrate the proposed GCN-LSTM model yields promising predictive performance than models including ARMA, SVM, RF, and LSTM.

Suggested Citation

  • Gu, Qinen & Li, Shaofang & Qin, Jiaying, 2025. "Enhanced volatility spillover network prediction of Chinese financial institutions using GCN-LSTM model," Finance Research Letters, Elsevier, vol. 85(PC).
    • Handle: RePEc:eee:finlet:v:85:y:2025:i:pc:s1544612325012917
    DOI: 10.1016/j.frl.2025.108033
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    References listed on IDEAS

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    1. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
    2. Karim Belcaid & Sara El Aoufi & Mamdouh Abdulaziz Saleh Al-Faryan, 2024. "Dynamics of Contagion Risk Among World Markets in Times of Crises: A Financial Network Perspective," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(4), pages 1007-1033, December.
    3. Nicholson, William B. & Matteson, David S. & Bien, Jacob, 2017. "VARX-L: Structured regularization for large vector autoregressions with exogenous variables," International Journal of Forecasting, Elsevier, vol. 33(3), pages 627-651.
    4. Ouyang, Zisheng & Zhou, Xuewei, 2023. "Multilayer networks in the frequency domain: Measuring extreme risk connectedness of Chinese financial institutions," Research in International Business and Finance, Elsevier, vol. 65(C).
    5. Arash Sioofy Khoojine & Dong Han, 2020. "Stock price network autoregressive model with application to stock market turbulence," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 93(7), pages 1-15, July.
    6. Wu, Xinyu & Jiang, Zhengting, 2023. "Time-varying asymmetric volatility spillovers among China’s carbon markets, new energy market and stock market under the shocks of major events," Energy Economics, Elsevier, vol. 126(C).
    7. Gavronski, Pedro Gerhardt & Ziegelmann, Flavio A., 2021. "Measuring systemic risk via GAS models and extreme value theory: Revisiting the 2007 financial crisis," Finance Research Letters, Elsevier, vol. 38(C).
    8. Sui, Cong & Chen, Nan & Yang, Mo, 2023. "Not all market participants are alike when facing crisis: Evidence from the 2015 Chinese stock market turbulence," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    9. Sylvain Benoit & Jean-Edouard Colliard & Christophe Hurlin & Christophe Pérignon, 2017. "Where the Risks Lie: A Survey on Systemic Risk," Review of Finance, European Finance Association, vol. 21(1), pages 109-152.
    10. Sharma, Prateek & Vipul,, 2016. "Forecasting stock market volatility using Realized GARCH model: International evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 222-230.
    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. Xun Huang & Fanyong Guo, 2021. "A kernel fuzzy twin SVM model for early warning systems of extreme financial risks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1459-1468, January.
    13. Pulikandala Nithish Kumar & Nneka Umeorah & Alex Alochukwu, 2024. "Dynamic graph neural networks for enhanced volatility prediction in financial markets," Papers 2410.16858, arXiv.org.
    14. Ding, Yi & Kambouroudis, Dimos & McMillan, David G., 2021. "Forecasting realised volatility: Does the LASSO approach outperform HAR?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    15. Sylvain Benoit & Jean-Edouard Colliard & Christophe Hurlin & Christophe Pérignon, 2017. "Where the Risks Lie: A Survey on Systemic Risk," Review of Finance, European Finance Association, vol. 21(1), pages 109-152.
    16. Imran Yousaf & Shoaib Ali & Wing-Keung Wong, 2020. "Return and Volatility Transmission between World-Leading and Latin American Stock Markets: Portfolio Implications," JRFM, MDPI, vol. 13(7), pages 1-19, July.
    17. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
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    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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