Nonconcave robust optimization with discrete strategies under Knightian uncertainty

被引：0
|
作者：
Ariel Neufeld
Mario Šikić
机构：
[1] Nanyang Technological University,Division of Mathematical Sciences
[2] University of Zurich,Center for Finance and Insurance
来源：
Mathematical Methods of Operations Research | 2019年 / 90卷
关键词：
Nonconcave robust optimization; Robust utility maximization; Knightian uncertainty; 93E20; 49L20; 91B16;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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页码：229 / 253
页数：24
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