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Comparison results for exchangeable credit risk portfolios

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  • Cousin, Areski
  • Laurent, Jean-Paul

Abstract

This paper is dedicated to risk analysis of credit portfolios. Assuming that default indicators form an exchangeable sequence of Bernoulli random variables and as a consequence of de Finetti's theorem, default indicators are Binomial mixtures. We can characterize the supermodular order between two exchangeable Bernoulli random vectors in terms of the convex ordering of their corresponding mixture distributions. Thus we can proceed to some comparisons between stop-loss premiums, CDO tranche premiums and convex risk measures on aggregate losses. This methodology provides a unified analysis of dependence for a number of CDO pricing models based on factor copulas, multivariate Poisson and structural approaches.

Suggested Citation

  • Cousin, Areski & Laurent, Jean-Paul, 2008. "Comparison results for exchangeable credit risk portfolios," Insurance: Mathematics and Economics, Elsevier, vol. 42(3), pages 1118-1127, June.
    • Handle: RePEc:eee:insuma:v:42:y:2008:i:3:p:1118-1127
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    References listed on IDEAS

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    Cited by:

    1. Giuseppe Genovese & Ashkan Nikeghbali & Nicola Serra & Gabriele Visentin, 2022. "Universal approximation of credit portfolio losses using Restricted Boltzmann Machines," Papers 2202.11060, arXiv.org, revised Apr 2023.
    2. Areski Cousin & Stéphane Crépey & Yu Kan, 2012. "Delta-hedging correlation risk?," Review of Derivatives Research, Springer, vol. 15(1), pages 25-56, April.
    3. Margaret Meyer & Bruno Strulovici, 2013. "The Supermodular Stochastic Ordering," Discussion Papers 1563, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    4. Margaret Meyer & Bruno Strulovici, 2013. "Beyond Correlation: Measuring Interdependence Through Complementarities," Economics Series Working Papers 655, University of Oxford, Department of Economics.
    5. Dorinel Bastide & St'ephane Cr'epey, 2024. "Provisions and Economic Capital for Credit Losses," Papers 2401.07728, arXiv.org, revised Dec 2024.

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