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Conditional graphical models for systemic risk measurement

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  • Paola Cerchiello

    () (Department of Economics and Management, University of Pavia)

  • Paolo Giudici

    () (Department of Economics and Management, University of Pavia)

Abstract

Financial network models are a useful tool to model interconnectedness and systemic risks in financial systems. They are essentially descriptive, and based on highly correlated networks. In this paper we embed them in a stochastic framework, aimed at a more parsimonious and more realistic representation. First we introduce Gaussian graphical models in the field of systemic risk modelling, thus estimating the adjacency matrix of a network in a robust and coherent way. Second, we propose a conditional graphical model that can usefully decompose correlations between financial institutions into correlations between countries and correlations between institutions, within countries. While the former may be further explained by macroeconomic variables, the latter may be further explained by idiosyncratic balance sheet indicators. We have applied our proposed methods to the largest European banks, with the aim of identifying central in situations, more subject to contagion or, conversely, whose failure could result in further distress or breakdowns in the whole system. Our results show that, in the transmission of the perceived default risk, there is a strong country effect, that reflects the weakness and the strength of the underlying economies. In addition, each country reveals specific idiosyncratic factors, with communalities among similar countries

Suggested Citation

  • Paola Cerchiello & Paolo Giudici, 2014. "Conditional graphical models for systemic risk measurement," DEM Working Papers Series 087, University of Pavia, Department of Economics and Management.
  • Handle: RePEc:pav:demwpp:087
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    File URL: http://dem-web.unipv.it/web/docs/dipeco/quad/ps/RePEc/pav/demwpp/DEMWP0087.pdf
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    References listed on IDEAS

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    1. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Can Macroeconomists Forecast Risk? Event-Based Evidence from the Euro-Area SPF," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 1-46, December.
    2. Sinkey, Joseph F, Jr, 1975. "A Multivariate Statistical Analysis of the Characteristics of Problem Banks," Journal of Finance, American Finance Association, vol. 30(1), pages 21-36, March.
    3. Mare, Davide Salvatore, 2015. "Contribution of macroeconomic factors to the prediction of small bank failures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 25-39.
    4. Idier, Julien & Lamé, Gildas & Mésonnier, Jean-Stéphane, 2014. "How useful is the Marginal Expected Shortfall for the measurement of systemic exposure? A practical assessment," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 134-146.
    5. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    6. Matteo Barigozzi & Christian Brownlees, 2019. "NETS: Network estimation for time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 347-364, April.
    7. Hua Chen & J. David Cummins & Krupa S. Viswanathan & Mary A. Weiss, 2014. "Systemic Risk and the Interconnectedness Between Banks and Insurers: An Econometric Analysis," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 81(3), pages 623-652, September.
    8. Riccardo Lisa & Stefano Zedda & Francesco Vallascas & Francesca Campolongo & Massimo Marchesi, 2011. "Modelling Deposit Insurance Scheme Losses in a Basel 2 Framework," Journal of Financial Services Research, Springer;Western Finance Association, vol. 40(3), pages 123-141, December.
    9. Davis, E. Philip & Karim, Dilruba, 2008. "Comparing early warning systems for banking crises," Journal of Financial Stability, Elsevier, vol. 4(2), pages 89-120, June.
    10. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    11. Klomp, Jeroen & Haan, Jakob de, 2012. "Banking risk and regulation: Does one size fit all?," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3197-3212.
    12. Arena, Marco, 2008. "Bank failures and bank fundamentals: A comparative analysis of Latin America and East Asia during the nineties using bank-level data," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 299-310, February.
    13. Koopman, Siem Jan & Lucas, André & Schwaab, Bernd, 2011. "Modeling frailty-correlated defaults using many macroeconomic covariates," Journal of Econometrics, Elsevier, vol. 162(2), pages 312-325, June.
    14. Hałaj, Grzegorz, 2013. "Optimal asset structure of a bank - bank reactions to stressful market conditions," Working Paper Series 1533, European Central Bank.
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    Cited by:

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    Keywords

    Conditional independence; network models; financial risk management;
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