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http://dx.doi.org/10.7465/jkdi.2014.25.1.107

Using cluster analysis and genetic algorithm to develop portfolio investment strategy based on investor information  

Cheong, Donghyun (Department of Information and Industrial Engineering, Yonsei University)
Oh, Kyong Joo (Department of Information and Industrial Engineering, Yonsei University)
Publication Information
Journal of the Korean Data and Information Science Society / v.25, no.1, 2014 , pp. 107-117 More about this Journal
Abstract
The main purpose of this study is to propose a portfolio investment strategy based on investor types information. For improvement of investment performance, artificial intelligence techniques are used to construct a portfolio. Among many artificial intelligence techniques, cluster analysis is applied to select securities and genetic algorithm is applied to assign the respective weight within the portfolio. Empirical experiments in the Korean stock market show that proposed portfolio investment strategy is practicable and superior strategy. This result implies that analysis of investor's trading behavior may assist investors to make an investment decision and to get superior performance.
Keywords
Cluster analysis; genetic algorithm; investor types; portfolio investment;
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Times Cited By KSCI : 2  (Citation Analysis)
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