A Composite Risk Measure Framework for Decision Making Under Uncertainty
作者机构：Graduate School of BusinessColumbia UniversityNew YorkNY 10027USA Department of Industrial and Systems EngineeringUniversity of MinnesotaMinneapolisMN 55455USA Beijing International Center forMathematical ResearchPekingUniversityBeijing 100871China
出 版 物：《Journal of the Operations Research Society of China》 (中国运筹学会会刊（英文）)
年 卷 期：2019年第7卷第1期
页 面：43-68页
核心收录：
学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：Risk management Stochastic programming Portfolio management
摘 要：In this paper,we present a unified framework for decision making under *** framework is based on the composite of two risk measures,where the inner risk measure accounts for the risk of decision if the exact distribution of uncertain model parameters were given,and the outer risk measure quantifies the risk that occurs when estimating the parameters of *** show that the model is tractable under mild *** framework is a generalization of several existing models,including stochastic programming,robust optimization,distributionally robust *** this framework,we study a few new models which imply probabilistic guarantees for solutions and yield less conservative results compared to traditional *** experiments are performed on portfolio selection problems to demonstrate the strength of our models.
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