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Credit risk optimization using factor models


  • David Saunders


  • Costas Xiouros


  • Stavros Zenios



We study portfolio credit risk management using factor models, with a focus on optimal portfolio selection based on the tradeoff of expected return and credit risk. We begin with a discussion of factor models and their known analytic properties, paying particular attention to the asymptotic limit of a large, finely grained portfolio. We recall prior results on the convergence of risk measures in this “large portfolio approximation” which are important for credit risk optimization. We then show how the results on the large portfolio approximation can be used to reduce significantly the computational effort required for credit risk optimization. For example, when determining the fraction of capital to be assigned to particular ratings classes, it is sufficient to solve the optimization problem for the large portfolio approximation, rather than for the actual portfolio. This dramatically reduces the dimensionality of the problem, and the amount of computation required for its solution. Numerical results illustrating the application of this principle are also presented. Copyright Springer Science+Business Media, LLC 2007

Suggested Citation

  • David Saunders & Costas Xiouros & Stavros Zenios, 2007. "Credit risk optimization using factor models," Annals of Operations Research, Springer, vol. 152(1), pages 49-77, July.
  • Handle: RePEc:spr:annopr:v:152:y:2007:i:1:p:49-77:10.1007/s10479-006-0136-2
    DOI: 10.1007/s10479-006-0136-2

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    References listed on IDEAS

    1. Giesecke, Kay, 2004. "Correlated default with incomplete information," Journal of Banking & Finance, Elsevier, vol. 28(7), pages 1521-1545, July.
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    3. Gordy, Michael B., 2003. "A risk-factor model foundation for ratings-based bank capital rules," Journal of Financial Intermediation, Elsevier, vol. 12(3), pages 199-232, July.
    4. Tasche, Dirk, 2002. "Expected shortfall and beyond," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1519-1533, July.
    5. Lucas, Andre & Klaassen, Pieter & Spreij, Peter & Straetmans, Stefan, 2001. "An analytic approach to credit risk of large corporate bond and loan portfolios," Journal of Banking & Finance, Elsevier, vol. 25(9), pages 1635-1664, September.
    6. Stefan Weber & Kay Giesecke, 2003. "Credit Contagion and Aggregate Losses," Computing in Economics and Finance 2003 246, Society for Computational Economics.
    7. Giesecke, Kay & Weber, Stefan, 2004. "Cyclical correlations, credit contagion, and portfolio losses," Journal of Banking & Finance, Elsevier, vol. 28(12), pages 3009-3036, December.
    8. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
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    Cited by:

    1. Mohamed A. Ayadi & Hatem Ben-Ameur & Nabil Channouf & Quang Khoi Tran, 2019. "NORTA for portfolio credit risk," Annals of Operations Research, Springer, vol. 281(1), pages 99-119, October.
    2. Justin A. Sirignano & Gerry Tsoukalas & Kay Giesecke, 2016. "Large-Scale Loan Portfolio Selection," Operations Research, INFORMS, vol. 64(6), pages 1239-1255, December.
    3. Barro, Diana & Basso, Antonella, 2010. "Credit contagion in a network of firms with spatial interaction," European Journal of Operational Research, Elsevier, vol. 205(2), pages 459-468, September.
    4. Diana Barro & Antonella Basso, 2008. "A network of business relations to model counterparty risk," Working Papers 171, Department of Applied Mathematics, Università Ca' Foscari Venezia.
    5. Rongda Chen & Liu Yang & Weijin Wang & Ling Tang, 2015. "Discovering the impact of systemic and idiosyncratic risk factors on credit spread of corporate bond within the framework of intelligent knowledge management," Annals of Operations Research, Springer, vol. 234(1), pages 3-15, November.
    6. Li, Ping & Han, Yingwei & Xia, Yong, 2016. "Portfolio optimization using asymmetry robust mean absolute deviation model," Finance Research Letters, Elsevier, vol. 18(C), pages 353-362.
    7. Wu, Dexiang & Dash Wu, Desheng, 2019. "An enhanced decision support approach for learning and tracking derivative index," Omega, Elsevier, vol. 88(C), pages 63-76.


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