Sensitivity of multiperiod optimization problems in adapted Wasserstein distance
Optimization and Control
2023-06-19 v2 Probability
Mathematical Finance
Abstract
We analyze the effect of small changes in the underlying probabilistic model on the value of multi-period stochastic optimization problems and optimal stopping problems. We work in finite discrete time and measure these changes with the adapted Wasserstein distance. We prove explicit first-order approximations for both problems. Expected utility maximization is discussed as a special case.
Keywords
Cite
@article{arxiv.2208.05656,
title = {Sensitivity of multiperiod optimization problems in adapted Wasserstein distance},
author = {Daniel Bartl and Johannes Wiesel},
journal= {arXiv preprint arXiv:2208.05656},
year = {2023}
}
Comments
final version, accepted for publication in SIAM J. Financial Math