This paper considers efficient estimation of
value-at-risk, which is an important problem in risk management.
The value-at-risk is an extreme quantile of the
distribution of the loss in portfolio value during a holding period.
An effective importance sampling technique is described for this
problem. The importance sampling can be further improved by combining
it with stratified sampling. In this setting, an effective stratification variable
is the likelihood ratio itself. The paper examines issues associated
with the allocation of samples to the strata, and compares
the effectiveness of the combination of importance sampling and
stratified sampling to that of stratified sampling alone.
By: Paul Glasserman, Philip Heidelberger, Perwez Shahabuddin
Published in: RC21548 in 1999
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