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Robust expected utility maximization with medial limits

Daniel Bartl, Patrick Cheridito and Michael Kupper

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Abstract: In this paper we study a robust expected utility maximization problem with random endowment in discrete time. We give conditions under which an optimal strategy exists and derive a dual representation for the optimal utility. Our approach is based on a general representation result for monotone convex functionals, a functional version of Choquet's capacitability theorem and medial limits. The novelty is that it works under nondominated model uncertainty without any assumptions of time-consistency. As applications, we discuss robust utility maximization problems with moment constraints, Wasserstein constraints and Wasserstein penalties.

Date: 2017-12, Revised 2018-11
New Economics Papers: this item is included in nep-mic and nep-upt
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Published in Journal of Mathematical Analysis and Applications, 471(1-2), 752-775, 2019

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