期刊
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
卷 161, 期 1, 页码 103-121出版社
SPRINGER/PLENUM PUBLISHERS
DOI: 10.1007/s10957-013-0329-1
关键词
Mean-variance model; Robust portfolio; Worst-case optimization; Uncertainty sets
资金
- Basic Science Research Program through the National Research Foundation of Korea (NRF)
- Ministry of Education, Science, and Technology [NRF-2012R1A1A1011157]
- National Research Foundation of Korea [2012R1A1A1011157] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Robust models have a major role in portfolio optimization for resolving the sensitivity issue of the classical mean-variance model. In this paper, we survey developments of worst-case optimization while focusing on approaches for constructing robust portfolios. In addition to the robust formulations for the Markowitz model, we review work on deriving robust counterparts for value-at-risk and conditional value-at-risk problems as well as methods for combining uncertainty in factor models. Recent findings on properties of robust portfolios are introduced, and we conclude by presenting our thoughts on future research directions.
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