Behavioral mean-variance portfolio selection

被引:27
|
作者
Bi, Junna [1 ]
Jin, Hanging [2 ]
Meng, Qingbin [3 ]
机构
[1] East China Normal Univ, Sch Stat, Shanghai 200241, Peoples R China
[2] Univ Oxford, Math Inst, Oxford Nie Financial Big Data Lab, Andrew Wiles Bldg,Woodstock Rd, Oxford OX2 6GG, England
[3] Renmin Univ China, Sch Business, Finance Dept, Beijing 100872, Peoples R China
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
Applied probability; Behavioural OR; Mean-variance portfolio selection; Probability distortion; Quantile approach; PROSPECT-THEORY; CONTINUOUS-TIME; RISK; CHOICE; UTILITY;
D O I
10.1016/j.ejor.2018.05.065
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
In this paper, a behavioral mean-variance portfolio selection problem in continuous time is formulated and studied. Unlike in the standard mean-variance portfolio selection problem, the cumulative distribution function of the cash flow is distorted by the probability distortion function used in the behavioral mean-variance portfolio selection problem. With the presence of distortion functions, the convexity of the optimization problem is ruined, and the problem is no longer a conventional linear-quadratic (LQ) problem, and we cannot apply conventional optimization tools like convex optimization and dynamic programming. To address this challenge, we propose and demonstrate a solution scheme by taking the quantile function of the terminal cash flow as the decision variable, and then replace the corresponding optimal terminal cash flow with the optimal quantile function. This allows the efficient frontier and the efficient strategy to be exploited. (C) 2018 Elsevier B.V. All rights reserved.
引用
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页码:644 / 663
页数:20
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