Nonconcave Robust Optimization with Discrete Strategies under Knightian Uncertainty

Ariel Neufeld and Mario Sikic

Papers from arXiv.org

Abstract: We study robust stochastic optimization problems in the quasi-sure setting in discrete-time. The strategies in the multi-period-case are restricted to those taking values in a discrete set. The optimization problems under consideration are not concave. We provide conditions under which a maximizer exists. The class of problems covered by our robust optimization problem includes optimal stopping and semi-static trading under Knightian uncertainty.

Date: 2017-11, Revised 2019-04
New Economics Papers: this item is included in nep-mic
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