Portfolio selection with parameter uncertainty under α maxmin mean-variance criterion

被引:4
|
作者
Yu, Xingying [1 ]
Shen, Yang [2 ]
Li, Xiang [3 ]
Fan, Kun [4 ]
机构
[1] London Sch Econ & Polit Sci, Dept Math, London WC2A 2AE, England
[2] Univ New South Wales, Sch Risk & Actuarial Studies, Sydney, NSW 2052, Australia
[3] York Univ, Dept Math & Stat, Toronto, ON M3P 1P3, Canada
[4] East China Normal Univ, Sch Stat, Key Lab Adv Theory & Applicat Stat & Data Sci MOE, Shanghai 200241, Peoples R China
基金
中国国家自然科学基金; 澳大利亚研究理事会;
关键词
Portfolio selection; Uncertainty; Ambiguity seeking; Ambiguity aversion; Quasi-efficient frontier; EXPECTED UTILITY; AMBIGUITY;
D O I
10.1016/j.orl.2020.08.008
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
We consider a mean-variance portfolio selection problem with uncertain model parameters. We formulate the mean-variance problem under the alpha maxmin criterion, in which the investor has mixed ambiguity aversion and ambiguity seeking attitudes and solves a convex combination of max-min and max-max optimization problems. By the Lagrangian method, we obtain the efficient portfolio and quasi-efficient frontier in closed form. We provide comparative statics of the quasi-efficient frontier to various parameters. (c) 2020 Elsevier B.V. All rights reserved.
引用
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页码:720 / 724
页数:5
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