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Abstract
The normal inverse Gaussian process has been used to model both
stock returns and interest rate processes. Although several numerical
methods are available to compute, for instance, VaR and derivatives val-
ues, these are in a relatively undeveloped state compared to the techniques
available in the Gaussian case.
This paper shows how a Monte Carlo valuation method may be used
with the NIG process, incorporating stratified sampling together with an
inverse Gaussian bridge.
The method is illustrated by pricing average rate options. We find the
method is up to around 200 times faster than plain Monte Carlo. These
e ciency gains are similar to those found in a related paper, Ribeiro and
Webber (02) [20], which develops an analogous method for the variance-
gamma process.
难度比较大,对数学基础要求比较高
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