Distributionally robust expectation inequalities for structured distributions

• 成果类型: Article
• 署名作者: Van Parys, Bart P. G.; Goulart, Paul J.; Morari, Manfred
• 署名单位: Massachusetts Institute of Technology (MIT); University of Oxford; University of Pennsylvania
• 刊物名称: MATHEMATICAL PROGRAMMING
• ISSN/ISSBN: 0025-5610
• DOI: 10.1007/s10107-017-1220-x
• 发表日期: 2019
• 页码: 251-280
• 关键词: Bounds; optimization; uncertainty; OPTION; prices

摘要

Quantifying the risk of unfortunate events occurring, despite limited distributional information, is a basic problem underlying many practical questions. Indeed, quantifying constraint violation probabilities in distributionally robust programming or judging the risk of financial positions can both be seen to involve risk quantification under distributional ambiguity. In this work we discuss worst-case probability and conditional value-at-risk problems, where the distributional information is limited to second-order moment information in conjunction with structural information such as unimodality and monotonicity of the distributions involved. We indicate how exact and tractable convex reformulations can be obtained using standard tools from Choquet and duality theory. We make our theoretical results concrete with a stock portfolio pricing problem and an insurance risk aggregation example.