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A study on investment decision making model: genetic algorithms approach

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3 Author(s)
Wen-Shiu Lin ; Dept. of Inf. Manage., Nat. Central Univ., Chung-Li, Taiwan ; Jiah-Shing Chen ; Ping-Chen Lin

Genetic algorithms (GAs) are becoming a paramount research method because of their robustness due to mimicking the natural evolution mechanism. Genetic algorithms can easily learn to adapt to complex environments. The paper studies the application of genetic algorithms on a user-oriented “investment decision-making model”. The portfolio selection considers users' preferences in addition to the common return and risk factors. Preliminary results show that the portfolios generated by GAs outperform some of the better mutual funds and the index

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Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on  (Volume:1 )

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