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arXiv · 2208.05656

Sensitivity of multiperiod optimization problems in adapted Wasserstein distance

Daniel Bartl·Johannes Wiesel
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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.

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BibTeXRIS

Daniel Bartl, Johannes Wiesel. 2022-08-11. Sensitivity of multiperiod optimization problems in adapted Wasserstein distance. https://arxiv.org/abs/2208.05656

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