The asymptotic error of chaos expansion approximations for stochastic differential equations
Probability
2019-06-05 v1
Abstract
In this paper we present a numerical scheme for stochastic differential equations based upon the Wiener chaos expansion. The approximation of a square integrable stochastic differential equation is obtained by cutting off the infinite chaos expansion in chaos order and in number of basis elements. We derive an explicit upper bound for the approximation error associated with our method. The proofs are based upon an application of Malliavin calculus.
Keywords
Cite
@article{arxiv.1906.01209,
title = {The asymptotic error of chaos expansion approximations for stochastic differential equations},
author = {Tony Huschto and Mark Podolskij and Sebastian Sager},
journal= {arXiv preprint arXiv:1906.01209},
year = {2019}
}
Comments
Published at https://doi.org/10.15559/19-VMSTA133 in the Modern Stochastics: Theory and Applications (https://vmsta.org/) by VTeX (http://www.vtex.lt/)