Credit risk optimization using factor models |
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| Authors: | David Saunders Costas Xiouros Stavros A Zenios |
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| Institution: | 1.Department of Statistics and Actuarial Science,University of Waterloo,Waterloo,Canada;2.Department of Statistics and Actuarial Science,University of Waterloo,West Waterloo,Canada;3.Marshall School of Business at the University of Southern California,Southern California,USA;4.Department of Public and Business Administration,University of Cyprus,Nicosia,Cyprus;5.Financial Institutions Center,the Wharton School in Philadelphia,Philadelphia,USA |
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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.
JEL Classification G11 |
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| Keywords: | Credit risk Portfolio optimization Large portfolio approximation |
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