Cardinality-constrained distributionally robust portfolio optimization

被引:4
|
作者
Kobayashi, Ken [1 ]
Takano, Yuichi [2 ]
Nakata, Kazuhide [1 ]
机构
[1] Tokyo Inst Technol, Sch Engn, Dept Ind Engn & Econ, 2-12-1 Ookayama,Meguro Ku, Tokyo 1528552, Japan
[2] Univ Tsukuba, Inst Syst & Informat Engn, 1-1-1 Tennodai, Tsukuba, Ibaraki 3058573, Japan
关键词
Portfolio optimization; Mixed-integer semidefinite optimization; Distributionally robust optimization; Cutting-plane algorithm; Matrix completion; VALUE-AT-RISK; EXPLOITING SPARSITY;
D O I
10.1016/j.ejor.2023.01.037
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
This paper studies a distributionally robust portfolio optimization model with a cardinality constraint for limiting the number of invested assets. We formulate this model as a mixed-integer semidefinite optimization (MISDO) problem by means of the moment-based ambiguity set of probability distributions of asset returns. To exactly solve large-scale problems, we propose a specialized cutting-plane algorithm that is based on bilevel optimization reformulation. We prove the finite convergence of the algorithm. We also apply a matrix completion technique to lower-level SDO problems to make their problem sizes much smaller. Numerical experiments demonstrate that our cutting-plane algorithm is significantly faster than the state-of-the-art MISDO solver SCIP-SDP. We also show that our portfolio optimization model can achieve good investment performance compared with the conventional robust optimization model based on the ellipsoidal uncertainty set.(c) 2023 Elsevier B.V. All rights reserved.
引用
收藏
页码:1173 / 1182
页数:10
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