Monte Carlo methods. Vol. 1: basics
Monte Carlo methods. Vol. 1: basics
Matrix computations (3rd ed.)
Tutorial on portfolio credit risk management
WSC '04 Proceedings of the 36th conference on Winter simulation
Fast simulation for multifactor portfolio credit risk in the t-copula model
WSC '05 Proceedings of the 37th conference on Winter simulation
Optimization problems in the simulation of multifactor portfolio credit risk
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
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The distribution of possible future losses for a portfolio of credit risky corporate assets, such as bonds or loans, shows strongly asymmetric behavior and a fat tail as the consequence of the limited upside of credit (the promised coupon payment) and substantial downside if the corporation defaults. Because of correlation, it is not possible to fully diversify away this fat tail. Detailed correlation models require Monte Carlo simulation to determine the loss distribution for a credit portfolio. This paper describes an importance sampling method that provides substantial speed up for computing economic capital, the rare event quantile of the loss distribution that must be held in reserve by a lending institution for solvency. The method, based solely on correlation information, provides accuracy in the tail while maintaining suitable performance for statistics related to the center of the distribution. It is also suitable for long/short portfolios.