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Behavioral mean-variance portfolio selection

Abstract:
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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.ejor.2018.05.065

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Oxford college:
St Peter's College
Role:
Author


More from this funder
Funding agency for:
Jin, H
Grant:
71720107001


Publisher:
Elsevier
Journal:
European Journal of Operational Research More from this journal
Volume:
271
Issue:
2
Pages:
644-663
Publication date:
2018-06-01
Acceptance date:
2018-05-23
DOI:
EISSN:
1872-6860
ISSN:
0377-2217


Language:
English
Keywords:
Pubs id:
pubs:865181
UUID:
uuid:c6e8d8a1-5fde-40a3-9a7e-6f00a7ce4837
Local pid:
pubs:865181
Source identifiers:
865181
Deposit date:
2018-10-23
ARK identifier:

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