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Optimization Problems in the Simulation of Multifactor Portfolio Credit Risk

  • Wanmo Kang
  • Kyungsik Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3982)

Abstract

We consider some optimization problems arising in an efficient simulation method for the measurement of the tail of portfolio credit risk. When we apply an importance sampling (IS) technique, it is necessary to characterize the important regions. In this paper, we consider the computation of directions for the IS, which becomes hard in multifactor case. We show this problem is NP-hard. To overcome this difficulty, we transform the original problem to subset sum and quadratic optimization problems. We support numerically that these re-formulation is computationally tractable.

Keywords

Knapsack Problem Importance Sampling Gaussian Copula Quadratic Optimization Problem Portfolio Credit Risk 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wanmo Kang
    • 1
  • Kyungsik Lee
    • 2
  1. 1.Columbia UniversityNew YorkUSA
  2. 2.Hankuk University of Foreign StudiesYonginKorea

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