Large Deviation for Reflected Backward Stochastic Differential Equations

TL;DR

This paper establishes a large deviation principle for reflected backward stochastic differential equations, extending the Freidlin-Wentzell theory to this class of stochastic processes with boundary constraints.

Contribution

It provides the first large deviation results specifically for BSDEs with one-sided reflection, broadening the understanding of their probabilistic behavior.

Findings

Proved the Freidlin-Wentzell large deviation principle for reflected BSDEs.

Extended large deviation theory to include one-sided reflection boundary conditions.

Enhanced the theoretical framework for analyzing rare events in reflected stochastic systems.

Abstract

In this note, we prove the Freidlin-Wentzell's large deviation principle for BSDEs with one-sided reflection.