Adaptive Monte Carlo Variance Reduction with Two-time-scale Stochastic Approximation

DOI10.1515/mcma.2007.010zbMath1128.65002OpenAlexW1964659851MaRDI QIDQ5421636

Reiichiro Kawai

Publication date: 24 October 2007

Published in: Monte Carlo Methods and Applications (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2381/4695

zbMATH Keywords

algorithmconvergenceimportance samplingBrownian motionlaw of large numberscentral limit theoremnumerical experimentfinancial engineeringcontrol variatesadaptive Monte Carlo variance reductiontwo-time-scale stochastic approximation algorithm

Mathematics Subject Classification ID

Gaussian processes (60G15) Numerical methods (including Monte Carlo methods) (91G60) Monte Carlo methods (65C05) Stochastic approximation (62L20) Stochastic learning and adaptive control (93E35) Stochastic particle methods (65C35)

Related Items (8)

On Monte Carlo and Quasi-Monte Carlo Methods for Series Representation of Infinitely Divisible Laws ⋮ Optimizing Adaptive Importance Sampling by Stochastic Approximation ⋮ Acceleration on Adaptive Importance Sampling with Sample Average Approximation ⋮ Batching Adaptive Variance Reduction ⋮ Adaptive Monte Carlo variance reduction for Lévy processes with two-time-scale stochastic approximation ⋮ On adaptive stratification ⋮ Adaptive importance sampling Monte Carlo simulation for general multivariate probability laws ⋮ Adaptive importance sampling and control variates

Cites Work

• Stochastic approximation with two time scales
• Asymptotically Optimal Importance Sampling and Stratification for Pricing Path-Dependent Options
• General results on the convergence of stochastic algorithms
• Adaptative Monte Carlo Method, A Variance Reduction Technique

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