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A limit distribution of credit portfolio losses with low default probabilities

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  • Shi, Xiaojun
  • Tang, Qihe
  • Yuan, Zhongyi

Abstract

This paper employs a multivariate extreme value theory (EVT) approach to study the limit distribution of the loss of a general credit portfolio with low default probabilities. A latent variable model is employed to quantify the credit portfolio loss, where both heavy tails and tail dependence of the latent variables are realized via a multivariate regular variation (MRV) structure. An approximation formula to implement our main result numerically is obtained. Intensive simulation experiments are conducted, showing that this approximation formula is accurate for relatively small default probabilities, and that our approach is superior to a copula-based approach in reducing model risk.

Suggested Citation

  • Shi, Xiaojun & Tang, Qihe & Yuan, Zhongyi, 2017. "A limit distribution of credit portfolio losses with low default probabilities," Insurance: Mathematics and Economics, Elsevier, vol. 73(C), pages 156-167.
    • Handle: RePEc:eee:insuma:v:73:y:2017:i:c:p:156-167
    DOI: 10.1016/j.insmatheco.2017.02.003
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    Cited by:

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    More about this item

    Keywords

    Credit portfolio loss; Extreme risk; Limit distribution; Loss given default; Model risk; Multivariate regular variation; Tail dependence;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • 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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