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LLN-type approximations for large portfolio losses

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  • Liu, Jing

Abstract

We are concerned with the loss from defaults of a large portfolio of defaultable obligors. A static structural model is constructed, in which for each obligor i its default is driven by a latent variable Ui and its loss given default (LGD) is driven by another latent variable Vi through a general loss settlement function G. In this way, the default indicator 1Ui>a, with a denoting a default threshold, and the LGD G(Vi) are not necessarily comonotonic, hence essentially different from the ones used in some recent works. It is further assumed that the two latent variables Ui andVi are correlated in the way that they share a common systematic risk factor but each has its own idiosyncratic risk factor. We employ the law of large numbers (LLN) to derive the exact limit distribution of the portfolio loss as the portfolio size becomes large. As applications, we also derive exact approximations for the TVaR and moments of the portfolio loss.

Suggested Citation

  • Liu, Jing, 2018. "LLN-type approximations for large portfolio losses," Insurance: Mathematics and Economics, Elsevier, vol. 81(C), pages 71-77.
  • Handle: RePEc:eee:insuma:v:81:y:2018:i:c:p:71-77
    DOI: 10.1016/j.insmatheco.2018.05.003
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    References listed on IDEAS

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    1. Denuit, Michel & Kiriliouk, Anna & Segers, Johan, 2015. "Max-factor individual risk models with application to credit portfolios," Insurance: Mathematics and Economics, Elsevier, vol. 62(C), pages 162-172.
    2. Scott, Alexandre & Metzler, Adam, 2015. "A general importance sampling algorithm for estimating portfolio loss probabilities in linear factor models," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 279-293.
    3. Denuit, Michel & Kiriliouk, Anna & Segers, Johan, 2015. "Max-factor individual risk models with application to credit portfolios," LIDAM Reprints ISBA 2015011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Cantia, Catalin & Tunaru, Radu, 2017. "A factor model for joint default probabilities. Pricing of CDS, index swaps and index tranches," Insurance: Mathematics and Economics, Elsevier, vol. 72(C), pages 21-35.
    5. Ballestra, Luca Vincenzo & Pacelli, Graziella, 2014. "Valuing risky debt: A new model combining structural information with the reduced-form approach," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 261-271.
    6. Alexander J. McNeil & Rüdiger Frey & Paul Embrechts, 2015. "Quantitative Risk Management: Concepts, Techniques and Tools Revised edition," Economics Books, Princeton University Press, edition 2, number 10496.
    7. He, Junnan & Tang, Qihe & Zhang, Huan, 2016. "Risk reducers in convex order," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 80-88.
    8. Qihe Tang & Zhongyi Yuan, 2013. "Asymptotic Analysis of the Loss Given Default in the Presence of Multivariate Regular Variation," North American Actuarial Journal, Taylor & Francis Journals, vol. 17(3), pages 253-271.
    9. 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.
    10. Wei, Li & Yuan, Zhongyi, 2016. "The loss given default of a low-default portfolio with weak contagion," Insurance: Mathematics and Economics, Elsevier, vol. 66(C), pages 113-123.
    11. Donnelly, Catherine & Embrechts, Paul, 2010. "The Devil is in the Tails: Actuarial Mathematics and the Subprime Mortgage Crisis," ASTIN Bulletin, Cambridge University Press, vol. 40(1), pages 1-33, May.
    12. 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.
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    More about this item

    Keywords

    Portfolio loss; Default; Law of large numbers; Systematic risk; Loss given default; Inverse;
    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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