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Credit risk optimization using factor models

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Abstract

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.

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Authors and Affiliations

  1. Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Canada

    David Saunders

  2. Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West Waterloo, West Waterloo, Ontario, Canada, N2L 3

    David Saunders

  3. Marshall School of Business at the University of Southern California, Southern California, USA

    Costas Xiouros

  4. Department of Public and Business Administration, University of Cyprus, Nicosia, Cyprus

    Stavros A. Zenios

  5. Financial Institutions Center, the Wharton School in Philadelphia, Philadelphia, PA, USA

    Stavros A. Zenios

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  1. David Saunders
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  2. Costas Xiouros
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Correspondence to David Saunders.

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JEL Classification G11

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Saunders, D., Xiouros, C. & Zenios, S.A. Credit risk optimization using factor models. Ann Oper Res 152, 49–77 (2007). https://doi.org/10.1007/s10479-006-0136-2

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  • DOI: https://doi.org/10.1007/s10479-006-0136-2

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