Nonconcave Robust Optimization with Discrete Strategies under Knightian Uncertainty
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 9 Nov 2017.
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