Regression-based variance reduction approach for strong approximation schemes

DOI10.1007/978-3-319-65313-6_7zbMath1386.65035arXiv1612.03407OpenAlexW2563163175MaRDI QIDQ1703895

Stefan Häfner, Denis Belomestny, Mikhail A. Urusov

Publication date: 8 March 2018

Full work available at URL: https://arxiv.org/abs/1612.03407

zbMATH Keywords

stochastic differential equationsMonte Carlo methodscontrol variatesregression methodsstrong schemes

Mathematics Subject Classification ID

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

Related Items (1)

Truncated control variates for weak approximation schemes

This page was built for publication: Regression-based variance reduction approach for strong approximation schemes