Minimum Variance Importance Sampling via Population Monte Carlo

Randal Douc, Arnaud Guillin, Jean-Michel Marin and Christian P, Robert
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Randal Douc: Crest
Arnaud Guillin: Crest
Jean-Michel Marin: Crest
Christian P, Robert: Crest

No 2005-09, Working Papers from Center for Research in Economics and Statistics

Abstract: Variance reduction has always been a central issue in Monte Carlo experiments.Population Monte Carlo can be used to this effect, in that a mixture of importancefunctions, called a D-kernel, can be iteratively optimised to achieve the minimumasymptotic variance for a function of interest among all possible mixtures. Theimplementation of this iterative scheme is illustrated for the computation of theprice of a European option in the Cox-Ingersoll-Ross model,

Pages: 24
Date: 2005
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