Constructing Risk Measures from Uncertainty Sets
成果类型：
Article
署名作者：
Natarajan, Karthik; Pachamanova, Dessislava; Sim, Melvyn
署名单位：
National University of Singapore; National University of Singapore; Babson College; National University of Singapore
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.1080.0683
发表日期：
2009
页码：
1129-1141
关键词：
摘要：
We illustrate the correspondence between uncertainty sets in robust optimization and some popular risk measures in finance and show how robust optimization can be used to generalize the concepts of these risk measures. We also show that by using properly defined uncertainty sets in robust optimization models, one can construct coherent risk measures and address the issue of the computational tractability of the resulting formulations. Our results have implications for efficient portfolio optimization under different measures of risk.