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Spatial Multivariate GARCH Models and Financial Spillovers

Author

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  • Rosella Giacometti

    (Department of Management, University of Bergamo, Via dei Caniana 2, 24127 Bergamo, Italy)

  • Gabriele Torri

    (Department of Management, University of Bergamo, Via dei Caniana 2, 24127 Bergamo, Italy
    Department of Finance, VŠB-TU Ostrava, Sokolská třída 33, 701 21 Ostrava, Czech Republic)

  • Kamonchai Rujirarangsan

    (Department of Economics, University of Bergamo, Via dei Caniana 2, 24127 Bergamo, Italy)

  • Michela Cameletti

    (Department of Economics, University of Bergamo, Via dei Caniana 2, 24127 Bergamo, Italy)

Abstract

We estimate the risk spillover among European banks from equity log-return data via Conditional Value at Risk (CoVaR). The joint dynamic of returns is modeled with a spatial DCC-GARCH which allows the conditional variance of log-returns of each bank to depend on past volatility shocks to other banks and their past squared returns in a parsimonious way. The backtesting of the resulting risk measures provides evidence that (i) the multivariate GARCH model with Student’s t distribution is more accurate than both the standard multivariate Gaussian model and the Filtered Historical Simulation (FHS), and (ii) the introduction of a spatial component improves the assessment of risk profiles and the market risk spillovers.

Suggested Citation

  • Rosella Giacometti & Gabriele Torri & Kamonchai Rujirarangsan & Michela Cameletti, 2023. "Spatial Multivariate GARCH Models and Financial Spillovers," JRFM, MDPI, vol. 16(9), pages 1-23, September.
    • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:9:p:397-:d:1233944
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    References listed on IDEAS

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    1. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(2), pages 280-310, April.
    2. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    3. Dima Rahman, 2014. "Are banking systems increasingly fragile? Investigating financial institutions' CDS returns extreme co-movements," Quantitative Finance, Taylor & Francis Journals, vol. 14(5), pages 805-830, May.
    4. Jeantheau, Thierry, 1998. "Strong Consistency Of Estimators For Multivariate Arch Models," Econometric Theory, Cambridge University Press, vol. 14(1), pages 70-86, February.
    5. Engle, Robert F. & Ng, Victor K. & Rothschild, Michael, 1990. "Asset pricing with a factor-arch covariance structure : Empirical estimates for treasury bills," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 213-237.
    6. 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.
    7. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    8. 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.
    9. Keiler, Sebastian & Eder, Armin, 2013. "CDS spreads and systemic risk: A spatial econometric approach," Discussion Papers 01/2013, Deutsche Bundesbank.
    10. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    11. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    12. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
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