Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)

Incorporating Value-at-Risk in Portfolio Selection: An Evolutionary Approach

Authors
Chueh-Yung Tsao1, Chao-Kung Liu
1Department of Business Administration, Chang Gung University
Corresponding Author
Chueh-Yung Tsao
Available Online October 2006.
DOI
10.2991/jcis.2006.321How to use a DOI?
Keywords
NSGA-II, mean-variance efficient frontier, mean-VaR efficient frontier, portfolio selection.
Abstract

The mean-variance framework for portfolio selection should be revised when investor’s concern is the downside risk. This is especially true when the asset returns are not normal. In this paper, we incorporate value-at-risk (VaR) in portfolio selection and the mean-VaR framework is proposed. Due to the two-objective optimization problem faced by the mean-VaR framework, an evolutionary multi-objective approach is applied to construct the mean-VaR efficient frontier. In particular, the NSGA-II is considered here. From the empirical analysis it is found that the risk-averse investor might inefficiently allocate his wealth if his decision is based on the mean-variance framework.

Copyright
© 2006, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
Series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
10.2991/jcis.2006.321
ISSN
1951-6851
DOI
10.2991/jcis.2006.321How to use a DOI?
Copyright
© 2006, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Chueh-Yung Tsao
AU  - Chao-Kung Liu
PY  - 2006/10
DA  - 2006/10
TI  - Incorporating Value-at-Risk in Portfolio Selection: An Evolutionary Approach
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.321
DO  - 10.2991/jcis.2006.321
ID  - Tsao2006/10
ER  -