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Title: Optimal Importance Sampling Parameter Search for Lévy Processes via Stochastic Approximation
Authors: Kawai, Reiichiro
First Published: 21-Nov-2008
Publisher: Society for Industrial and Applied Mathematics
Citation: SIAM Journal on Numerical Analysis, 2008, 47 (1), pp. 293-307.
Abstract: 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.
DOI Link: 10.1137/070680564
ISSN: 0036-1429
Type: Article
Rights: This is the author's final draft of the paper published as SIAM Journal on Numerical Analysis, 2008, 47 (1), pp. 293-307. The final version is available from Doi: 10.1137/070680564
Appears in Collections:Published Articles, Dept. of Mathematics

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