Applications of Genetic Algorithm to Portfolio Optimization with Practical Transaction Constraints

DOI

10.2991/jcis.2006.273How to use a DOI?

Keywords

portfolio, mean-variance model, genetic algorithms

Abstract

The portfolio optimization model, initially proposed by Markowitz in 1952 and known as mean-variance model (MV model), is applied to find the optimized allocation among assets to get higher investment return and lower investment risk. However, the MV model did not consider some practical limitations of financial market, including: (1) transaction cost and (2) minimal transaction lots. While these constraints are not considered in the model, the practicability of the model will be restrained. But when they are included in the model, the model will become an NP hard problem, which cannot obtain global optimal solution by traditional mathematics programming techniques. In this research, besides proposing various models to include afore-mentioned consideration in the MV model, genetic algorithms are applied to solve these models. Empirical tests in the Taiwan stock market are provided to prove the applicability of the techniques.

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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TY  - CONF
AU  - Chieh-Yow ChiangLin
PY  - 2006/10
DA  - 2006/10
TI  - Applications of Genetic Algorithm to Portfolio Optimization with Practical Transaction Constraints
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.2006.273
DO  - 10.2991/jcis.2006.273
ID  - ChiangLin2006/10
ER  -