Robust expected utility maximization with medial limits
Patrick Cheridito and
Papers from arXiv.org
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 of the optimal utility. Our approach is based on medial limits, a functional version of Choquet's capacitability theorem and a general representation result for monotone convex functionals. The novelty is that it works in cases where robustness is described by a general family of probability measures that do not have to be dominated or time-consistent.
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