Portfolio Optimization Using Evolutionary Algorithms

Portfolio Optimization Using Evolutionary Algorithms

Lean Yu (Chinese Academy of Sciences, China & City University of Hong Kong, Hong Kong), Shouyang Wang (Chinese Academy of Sciences, China) and Kin Keung Lai (City University of Hong Kong, Hong Kong)
DOI: 10.4018/978-1-59904-627-3.ch014
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Abstract

In this study, a double-stage evolutionary algorithm is proposed for portfolio optimization. In the first stage, a genetic algorithm is used to identify good-quality assets in terms of asset ranking. In the second stage, investment allocation in the selected good-quality assets is optimized using another genetic algorithm based on Markowitz’s theory. Through the two-stage genetic optimization process, an optimal portfolio can be determined. Experimental results obtained reveal that the proposed double-stage evolutionary algorithm for portfolio optimization provides a very useful tool to assist the investors in planning their investment strategy and constructing their portfolio.

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