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Calibrating the CreditRisk + Model at Different Time Scales and in Presence of Temporal Autocorrelation †

Author

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  • Jacopo Giacomelli

    (SACE S.p.A., Piazza Poli 42, 00187 Rome, Italy
    Department of Statistics, Sapienza University of Rome, Viale Regina Elena 295, 00161 Rome, Italy
    The views and opinions expressed in this article are those of the author and do not necessarily reflect the official policy or position of SACE S.p.A.)

  • Luca Passalacqua

    (Department of Statistics, Sapienza University of Rome, Viale Regina Elena 295, 00161 Rome, Italy)

Abstract

The CreditRisk + model is one of the industry standards for the valuation of default risk in credit loans portfolios. The calibration of CreditRisk + requires, inter alia, the specification of the parameters describing the structure of dependence among default events. This work addresses the calibration of these parameters. In particular, we study the dependence of the calibration procedure on the sampling period of the default rate time series, that might be different from the time horizon onto which the model is used for forecasting, as it is often the case in real life applications. The case of autocorrelated time series and the role of the statistical error as a function of the time series period are also discussed. The findings of the proposed calibration technique are illustrated with the support of an application to real data.

Suggested Citation

  • Jacopo Giacomelli & Luca Passalacqua, 2021. "Calibrating the CreditRisk + Model at Different Time Scales and in Presence of Temporal Autocorrelation †," Mathematics, MDPI, vol. 9(14), pages 1-30, July.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:14:p:1679-:d:596003
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    References listed on IDEAS

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    1. Paul Glasserman & Jingyi Li, 2005. "Importance Sampling for Portfolio Credit Risk," Management Science, INFORMS, vol. 51(11), pages 1643-1656, November.
    2. Vandendorpe, Antoine & Ho, Ngoc-Diep & Vanduffel, Steven & Van Dooren, Paul, 2008. "On the parameterization of the CreditRisk + model for estimating credit portfolio risk," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 736-745, April.
    3. A. Mathal & P. Moschopoulos, 1992. "A form of multivariate gamma distribution," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 44(1), pages 97-106, March.
    4. 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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