Portfolio Management: Selection and Allocation across Intelligent Analysis

Xie, Cong (2008) Portfolio Management: Selection and Allocation across Intelligent Analysis. [Dissertation (University of Nottingham only)] (Unpublished)

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During this study, we employed an artificial intelligent technique in order to solve the problem of portfolio optimization. Traditionally, Markowitz Mean-Variance Model is a fundamental method for optimizing portfolio based on risk and return. However, it still remains the assumptions of behaviors among market and investors, which by the way

means they will affect the performances of portfolio optimization. However, Genetic Algorithm as an evolutionary optimization tool can be used in portfolio selection and optimization problems since it would not establish on these assumptions. We compared the performances of the stock portfolio which constructed by Mean-Variance Model and Genetic Algorithm according to investors's expected rate of return in order to minimize the portfolio risk. The empirical study showed that Genetic algorithm provided an alternative solution for a stock portfolio selection and allocation.

Item Type: Dissertation (University of Nottingham only)
Depositing User: EP, Services
Date Deposited: 26 Sep 2008
Last Modified: 12 Jan 2018 10:41
URI: https://eprints.nottingham.ac.uk/id/eprint/22170

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