Proceedings of the 3rd International Conference on Mechatronics, Robotics and Automation

Portfolio analysis based on multi-objective optimization algorithm

Authors
Juan Chen, Mengla Ji
Corresponding Author
Juan Chen
Available Online April 2015.
DOI
https://doi.org/10.2991/icmra-15.2015.157How to use a DOI?
Keywords
Portfolio; multi-objective optimization; NSGA-II
Abstract
Evolutionary algorithm in risk minimization and the expected return maximization of bi-objective for portfolio optimization applications has received widespread attention. Although the problem is a quadratic programming (QP) problem, the practical investment problems tend to make variables discontinuous and introduce other complexities. Under this circumstance, a normal QP solution is not always capable of finding a feasible solution. In this paper the NSGA-II algorithm is used to deal with the situation for classical QP unconventional methods. Results demonstrate that the evolutionary algorithm NSGA-II can find out the front of the conflict optimization problem which is difficult to achieve through other methods.
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Proceedings
3rd International Conference on Mechatronics, Robotics and Automation
Part of series
Advances in Computer Science Research
Publication Date
April 2015
ISBN
978-94-62520-76-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmra-15.2015.157How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Juan Chen
AU  - Mengla Ji
PY  - 2015/04
DA  - 2015/04
TI  - Portfolio analysis based on multi-objective optimization algorithm
BT  - 3rd International Conference on Mechatronics, Robotics and Automation
PB  - Atlantis Press
SP  - 809
EP  - 812
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmra-15.2015.157
DO  - https://doi.org/10.2991/icmra-15.2015.157
ID  - Chen2015/04
ER  -