Nonconcave Robust Optimization with Discrete Strategies under Knightian Uncertainty
Optimization and Control
2019-04-25 v3 Probability
Mathematical Finance
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
Cite
@article{arxiv.1711.03875,
title = {Nonconcave Robust Optimization with Discrete Strategies under Knightian Uncertainty},
author = {Ariel Neufeld and Mario Sikic},
journal= {arXiv preprint arXiv:1711.03875},
year = {2019}
}
Comments
arXiv admin note: text overlap with arXiv:1610.09230