Adaptive importance sampling in least-squares Monte Carlo algorithms for backward stochastic differential equations

DOI10.1016/j.spa.2016.07.011zbMath1361.93067OpenAlexW2512458358MaRDI QIDQ516010

Emmanuel Gobet, Plamen Turkedjiev

Publication date: 20 March 2017

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://kclpure.kcl.ac.uk/portal/en/publications/adaptive-importance-sampling-in-leastsquares-monte-carlo-algorithms-for-backward-stochastic-differential-equations(4a66140a-33da-4da5-b762-a43f3be0ce3c).html

zbMATH Keywords

importance samplingbackward stochastic differential equationsempirical regressions

Mathematics Subject Classification ID

General nonlinear regression (62J02) Dynamic programming in optimal control and differential games (49L20) Least squares and related methods for stochastic control systems (93E24) Sampled-data control/observation systems (93C57) Optimal stochastic control (93E20) Stochastic calculus of variations and the Malliavin calculus (60H07) Numerical solutions to stochastic differential and integral equations (65C30)

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