Nonconcave robust optimization with discrete strategies under Knightian uncertainty

Ariel Neufeld () and Mario Šikić ()
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Ariel Neufeld: Nanyang Technological University
Mario Šikić: University of Zurich

Mathematical Methods of Operations Research, 2019, vol. 90, issue 2, No 4, 229-253

Abstract: 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.

Keywords: Nonconcave robust optimization; Robust utility maximization; Knightian uncertainty; 93E20; 49L20; 91B16 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s00186-019-00669-7

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