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Efficient Importance Sampling Estimation for Joint Default Probability:The First Passage Time Problem
Book chapter   Peer reviewed

Efficient Importance Sampling Estimation for Joint Default Probability:The First Passage Time Problem

Chuan-Hsiang Han
Progress in Probability, Vol.65, pp.347-359
2011

Abstract

efficient importance large deviation theory probability of joint default sampling Structural-form model Statistics and Probability Mathematics (miscellaneous) Mathematical Physics Applied Mathematics
Motivated from credit risk modeling, this paper extends the twodimensional first passage time problem studied by Zhou (2001) to any finite dimension by means of Monte Carlo simulation. We provide an importance sampling method to estimate the joint default probability, and apply the large deviation principle to prove that the proposed importance sampling is asymptotically optimal. Our result is an alternative to the interacting particle systems proposed by Carmona, Fouque, and Vestal (2009).

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