A duality approach for the weak approximation of stochastic differential equations
Probability
2016-08-16 v1
Abstract
In this article we develop a new methodology to prove weak approximation results for general stochastic differential equations. Instead of using a partial differential equation approach as is usually done for diffusions, the approach considered here uses the properties of the linear equation satisfied by the error process. This methodology seems to apply to a large class of processes and we present as an example the weak approximation of stochastic delay equations.
Cite
@article{arxiv.math/0610178,
title = {A duality approach for the weak approximation of stochastic differential equations},
author = {Emmanuelle Clément and Arturo Kohatsu-Higa and Damien Lamberton},
journal= {arXiv preprint arXiv:math/0610178},
year = {2016}
}
Comments
Published at http://dx.doi.org/10.1214/105051606000000060 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)