Efficient Monte Carlo methods for convex risk measures in portfolio credit risk models

Authors:
Jörn Dunkel;Stefan Weber
Affiliations:
Universität Augsburg, Augsburg, Germany;Cornell University, Ithaca, N.Y.
Venue:
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Year:
2007

Citing 3
Cited 1

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New simulation methodology for risk analysis: importance sampling for a mixed Poisson model of portfolio credit risk

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Stochastic Root Finding and Efficient Estimation of Convex Risk Measures

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Abstract

We discuss efficient Monte Carlo (MC) methods for the estimation of convex risk measures within the portfolio credit risk model CreditMetrics. Our focus lies on the Utility-based Shortfall Risk (SR) measures, as these avoid several deficiencies of the current industry standard Value-at-Risk (VaR). It is demonstrated that the importance sampling method exponential twisting provides computationally efficient SR estimators. Numerical simulations of test portfolios illustrate the good performance of the proposed algorithms.