Unconstrained recursive importance sampling

DOI10.1214/09-AAP650zbMath1207.65007arXiv0807.0762MaRDI QIDQ988764

Gilles Pagès, Vincent Lemaire

Publication date: 18 August 2010

Published in: The Annals of Applied Probability (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0807.0762

zbMATH Keywords

stochastic differential equationconvergenceimportance samplingnumerical experimentsMonte Carlo simulationGaussian distributioncentral limit theoremBlack-Scholes modeldiffusion processesvariance reductionchange of measureGirsanov theoremstochastic algorithmItô processconvergence theoremrecursive proceduresbarrier optionslog-concave probability distributionsRobbins-Monro algorithmbasis in \(L^2\)Escher transformfinite-dimensional settingsinfinite-dimensional settingsNIG distribution

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Diffusion processes (60J60) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30) Stochastic particle methods (65C35)

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