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Meta-model of a large credit risk portfolio in the Gaussian copula model

Author

Listed:
  • Florian Bourgey

    (CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique - X - École polytechnique - CNRS - Centre National de la Recherche Scientifique)

  • Emmanuel Gobet

    (CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique - X - École polytechnique - CNRS - Centre National de la Recherche Scientifique)

  • Clément Rey

    (CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique - X - École polytechnique - CNRS - Centre National de la Recherche Scientifique)

Abstract

We design a meta-model for the loss distribution of a large credit portfolio in the Gaussian copula model. Using both the Wiener chaos expansion on the systemic economic factor and a Gaussian approximation on the associated truncated loss, we significantly reduce the computational time needed for sampling the loss and therefore estimating risk measures on the loss distribution. The accuracy of our method is confirmed by many numerical examples.

Suggested Citation

  • Florian Bourgey & Emmanuel Gobet & Clément Rey, 2019. "Meta-model of a large credit risk portfolio in the Gaussian copula model," Working Papers hal-02291548, HAL.
    • Handle: RePEc:hal:wpaper:hal-02291548
    Note: View the original document on HAL open archive server: https://hal.science/hal-02291548v2
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    References listed on IDEAS

    as
    1. Paul Glasserman & Jingyi Li, 2005. "Importance Sampling for Portfolio Credit Risk," Management Science, INFORMS, vol. 51(11), pages 1643-1656, November.
    2. 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.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Monte Carlo simulation; portfolio credit risk; polynomial chaos expansion; meta-model;
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