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Optimal Importance Sampling Parameter Search for Lévy Processes via Stochastic Approximation

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journal contribution
posted on 2009-09-16, 13:44 authored by Reiichiro Kawai
The author proposes stochastic approximation methods of finding the optimal measure change by the exponential tilting for Lévy processes in Monte Carlo importance sampling variance reduction. In accordance with the structure of the underlying Lévy measure, either a constrained or unconstrained algorithm of the stochastic approximation is chosen. For both cases, the almost sure convergence to a unique stationary point is proved. Numerical examples are presented to illustrate the effectiveness of our method.

History

Citation

SIAM Journal on Numerical Analysis, 2008, 47 (1), pp. 293-307.

Published in

SIAM Journal on Numerical Analysis

Publisher

Society for Industrial and Applied Mathematics

issn

0036-1429

Copyright date

2008

Available date

2009-09-16

Publisher version

http://epubs.siam.org/doi/abs/10.1137/070680564

Language

en

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