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Forecasting Systemic Risk in the European Banking Industry: A Machine Learning Approach

Author

Listed:
  • Zeinab Srour

    (Department of Financial Studies, College of Business Administration, Rafik Hariri University, Block G, Room G101-C, P.O. Box 10, Damour-Chouf 2010, Lebanon)

  • Jamil Hammoud

    (Department of Financial Studies, College of Business Administration, Rafik Hariri University, Block G, Room G101-C, P.O. Box 10, Damour-Chouf 2010, Lebanon)

  • Mohamed Tarabay

    (Department of Financial Studies, College of Business Administration, Rafik Hariri University, Block G, Room G101-C, P.O. Box 10, Damour-Chouf 2010, Lebanon)

Abstract

The aim of this article is to forecast the systemic risk contribution and exposure measured by the delta conditional value at risk (ΔCoVaR) and the marginal expected shortfall (MES), respectively. We first estimate the ΔCoVaR and MES for banks in 16 European countries for the 2002–2016 period. We then predict systemic risk measures using machine learning techniques, such as artificial neural network (ANN) and support vector machine (SVM), and we use AR-GARCH specification. Finally, we compare the methods’ forecasting values and the actual values. Our results show that two hidden layers of artificial neural networks perform efficiently in forecasting systemic risk.

Suggested Citation

  • Zeinab Srour & Jamil Hammoud & Mohamed Tarabay, 2025. "Forecasting Systemic Risk in the European Banking Industry: A Machine Learning Approach," JRFM, MDPI, vol. 18(6), pages 1-20, June.
    • Handle: RePEc:gam:jjrfmx:v:18:y:2025:i:6:p:335-:d:1682304
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    References listed on IDEAS

    as
    1. 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.
    2. Saktinil Roy, 2023. "Do Changes in Risk Perception Predict Systemic Banking Crises?," JRFM, MDPI, vol. 16(11), pages 1-15, October.
    3. Girardi, Giulio & Tolga Ergün, A., 2013. "Systemic risk measurement: Multivariate GARCH estimation of CoVaR," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3169-3180.
    4. Gabriele Galati & Richhild Moessner, 2013. "Macroprudential Policy – A Literature Review," Journal of Economic Surveys, Wiley Blackwell, vol. 27(5), pages 846-878, December.
    5. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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