# Sensitivity Analysis of Distributionally Robust BSDEs and RBSDEs

arXiv: https://arxiv.org/abs/2511.01828 · HTML: https://mlsanity.com/paper/2511.01828/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Nov 2025.

## Built on by (most cited first, 1 of 1)

- [Policy Gradient Learning for Distributionally Robust Markov Decision Processes under Wasserstein Ambiguity](https://mlsanity.com/paper/2606.27610/) (2026)

## Abstract (arXiv)

We examine the sensitivity properties of backward stochastic differential equations and reflected backward stochastic differential equations, which naturally arise in the context of optimal control and optimal stopping problems. Motivated by issues of sensitivity analysis in distributionally robust optimization (DRO) control and optimal stopping problems, we establish explicit formulas for the corresponding sensitivities under drift reference measure uncertainty. Our work is closely related to citeauthorbartl2023sensitivity citebartl2023sensitivity. In contrast to the existing literature, our analysis is carried out within a general non-Markovian framework.