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math.OC2023
Strategies with minimal norm are optimal for expected utility maximization under high model ambiguity
Laurence Carassus, Johannes Wiesel
We investigate an expected utility maximization problem under model uncertainty in a one-period financial market. We capture model uncertainty by replacing the baseline model $\mat…
math.OC2022★ 1 cited
Sensitivity of multiperiod optimization problems in adapted Wasserstein distance
Daniel Bartl, Johannes Wiesel
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…
math.OC2020★ 24 cited
Sensitivity analysis of Wasserstein distributionally robust optimization problems
Daniel Bartl, Samuel Drapeau, Jan Obloj +1
We consider sensitivity of a generic stochastic optimization problem to model uncertainty. We take a non-parametric approach and capture model uncertainty using Wasserstein balls a…