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Evaluation of Credit Risk Under Correlated Defaults: The Cross-Entropy Simulation Approach

Author

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  • Loretta Mastroeni
  • Giuseppe D'Acquisto
  • Maurizio Naldi

Abstract

Credit risk, associated to borrowers defaulting on their debts, is an ever growing source of concern for lenders. The presence of correlation among defaults may be described by the t-copula model. However, the typically large number of variables involved calls for a simulation approach. A simulation method, based on the use of the Cross-Entropy (CE) technique, is here proposed as an alternative to non-adaptive Importance Sampling (IS) techniques so far presented in the literature, the main advantage of CE being that it allows to deal easily with a wider range of probability models than ad hoc IS. The method is validated through a comparison of its results with the crude MonteCarlo and the Exponential Twist approaches. The proposed Cross-Entropy technique is shown to provide accurate results even when the sample size is several orders of magnitude smaller than the inverse of the probability to be estimated.

Suggested Citation

  • Loretta Mastroeni & Giuseppe D'Acquisto & Maurizio Naldi, 2014. "Evaluation of Credit Risk Under Correlated Defaults: The Cross-Entropy Simulation Approach," Departmental Working Papers of Economics - University 'Roma Tre' 0193, Department of Economics - University Roma Tre.
    • Handle: RePEc:rtr:wpaper:0193
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    References listed on IDEAS

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    1. Michel Dietsch, 2004. "Should SME exposures be treated as retail or corporate exposures: a comparative analysis of probabilities of default and assets correlations in French and German SMEs," ULB Institutional Repository 2013/14164, ULB -- Universite Libre de Bruxelles.
    2. Dietsch, Michel & Petey, Joel, 2004. "Should SME exposures be treated as retail or corporate exposures? A comparative analysis of default probabilities and asset correlations in French and German SMEs," Journal of Banking & Finance, Elsevier, vol. 28(4), pages 773-788, April.
    3. P. T. de Boer & D. P. Kroese & R. Y. Rubinstein, 2004. "A Fast Cross-Entropy Method for Estimating Buffer Overflows in Queueing Networks," Management Science, INFORMS, vol. 50(7), pages 883-895, July.
    4. Joshua Chan & Dirk Kroese, 2011. "Rare-event probability estimation with conditional Monte Carlo," Annals of Operations Research, Springer, vol. 189(1), pages 43-61, September.
    5. Achal Bassamboo & Sandeep Juneja & Assaf Zeevi, 2008. "Portfolio Credit Risk with Extremal Dependence: Asymptotic Analysis and Efficient Simulation," Operations Research, INFORMS, vol. 56(3), pages 593-606, June.
    6. Crouhy, Michel & Galai, Dan & Mark, Robert, 2000. "A comparative analysis of current credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 59-117, January.
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    More about this item

    Keywords

    Credit risk; Cross-Entropy; Copula models;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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