An importance sampling algorithm for estimating extremes of perpetuity sequences

Abstract

In a wide class of problems in insurance and financial mathematics, it is of interest to study the extremal events of a perpetuity sequence. This paper addresses the problem of numerically evaluating these rare event probabilities. Specifically, an importance sampling algorithm is described which is efficient in the sense that it exhibits bounded relative error, and which is optimal in an appropriate asymptotic sense. The main idea of the algorithm is to use a "dual" change of measure, which is employed to an associated Markov chain over a randomly-stopped time interval. The algorithm also makes use of the so-called forward sequences generated to the given stochastic recursion, together with elements of Markov chain theory.

Original languageEnglish
Title of host publicationAIP Conference Proceedings
Number of pages4
Volume1479
PublisherAmerican Institute of Physics
Publication date2012
Pages1966-1969
ISBN (Print)8-0-7354-1091-6
DOIs
Publication statusPublished - 2012

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