Large deviation principles and Malliavin derivative for mean reflected stochastic differential equations
Probability
2023-03-27 v1
Abstract
In this paper, we consider a class of reflected stochastic differential equations for which the constraint is not on the paths of the solution but on its law. We establish a small noise large deviation principle, a large deviation for short time and the Malliavin derivative. To prove large deviation principles, a sufficient condition for the weak convergence method, which is suitable for Mckean-Vlasov stochastic differential equation, plays an important role.
Cite
@article{arxiv.2303.13834,
title = {Large deviation principles and Malliavin derivative for mean reflected stochastic differential equations},
author = {Ping Chen and Jianliang Zhai},
journal= {arXiv preprint arXiv:2303.13834},
year = {2023}
}