Robust expected utility maximization with medial limits

JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS

卷:471

Article

Bartl, Daniel^1,2  Cheridito, Patrick³  Kupper, Michael¹ 

[1] Univ Konstanz, Dept Math & Stat, D-78464 Constance, Germany

[2] Univ Vienna, Dept Math, A-1090 Vienna, Austria

[3] Swiss Fed Inst Technol, Dept Math, RiskLab, CH-8092 Zurich, Switzerland

关键词: Robust expected utility maximization;    Convex duality;    Choquet capacitability;    Medial limit;    Moment constraints;    Wasserstein distance;   

DOI  :  10.1016/j.jmaa.2018.11.012

来源: Elsevier

【 摘 要 】

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. (C) 2018 Elsevier Inc. All rights reserved.

【 授权许可】

Free