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Endogenous Hidden Markov Regimes in Operational Loss Data: Application to the Recent Financial Crisis

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  • Georges Dionne
  • Amir Saissi Hassani

Abstract

We determine whether there is an endogenous Hidden Markov Regime (HMR) in the operational loss data of banks from 2001 to 2010. A high level regime is marked by very high loss values during the recent financial crisis. There is therefore temporal heterogeneity in the data. If this heterogeneity is not considered in risk management models, capital estimations will be biased. Levels of reserve capital will be overestimated in periods of normal losses, corresponding to the low level of the regime, and underestimated in periods of a high regime. Variation in capital can go up to 30% during this period of analysis when regimes are not considered.

Suggested Citation

  • Georges Dionne & Amir Saissi Hassani, 2015. "Endogenous Hidden Markov Regimes in Operational Loss Data: Application to the Recent Financial Crisis," Cahiers de recherche 1516, CIRPEE.
  • Handle: RePEc:lvl:lacicr:1516
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    References listed on IDEAS

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    1. 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.).
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    4. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    5. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    6. Chun, Olfa Maalaoui & Dionne, Georges & François, Pascal, 2014. "Detecting Regime Shifts in Credit Spreads," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(5-6), pages 1339-1364, December.
    7. Dahen, Hela & Dionne, Georges, 2010. "Scaling models for the severity and frequency of external operational loss data," Journal of Banking & Finance, Elsevier, vol. 34(7), pages 1484-1496, July.
    8. Visser, Ingmar & Speekenbrink, Maarten, 2010. "depmixS4: An R Package for Hidden Markov Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i07).
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    11. Psaradakis, Zacharias & Sola, Martin, 1998. "Finite-sample properties of the maximum likelihood estimator in autoregressive models with Markov switching," Journal of Econometrics, Elsevier, vol. 86(2), pages 369-386, June.
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    More about this item

    Keywords

    Hidden Markov regime; operational risk; 2007-2009 financial crisis; Skew t type 4 distribution; bank’s regulatory capital; Basel regulation;

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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