Mathematical Methods of Operations Research

, Volume 90, Issue 2, pp 229–253 | Cite as

Nonconcave robust optimization with discrete strategies under Knightian uncertainty

  • Ariel NeufeldEmail author
  • Mario Šikić
Original Article


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.


Nonconcave robust optimization Robust utility maximization Knightian uncertainty 

Mathematics Subject Classification

93E20 49L20 91B16 



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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Division of Mathematical SciencesNanyang Technological UniversitySingaporeSingapore
  2. 2.Center for Finance and InsuranceUniversity of ZurichZurichSwitzerland

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