Monte Carlo simulation is widely used to measure the credit risk in portfolios of loans,
corporate bonds, and other instruments subject to possible default. The accurate measurement
of credit risk is often a rare-event simulation problem because default probabilities
are low for highly rated obligors and because risk management is particularly concerned
with rare but significant losses resulting from a large number of defaults. This makes importance
sampling (IS) potentially attractive. But the application of IS is complicated by
the mechanisms used to model dependence between obligors; and capturing this dependence
is essential to a portfolio view of credit risk. This paper provides an IS procedure for the
widely used normal copula model of portfolio credit risk. The procedure has two parts:
one applies IS conditional on a set of common factors affecting multiple obligors, the other
applies IS to the factors themselves. The relative importance of the two parts of the procedu

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credit risk　importance sampling　dependence　default　Monte Carlo　
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VaR Uses——Credit Risk