A study on investment decision making model: genetic algorithms approach

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 "inves...

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Bibliographic Details
Main Authors: Wen-Shiu Lin, Jiah-Shing Chen, Ping-Chen Lin
Format: Conference Proceeding
Language:English
Subjects:
Decision making
Genetic algorithms
Information management
Investments
Mathematical model
Mathematics
Mutual funds
Portfolios
Quadratic programming
Robustness
Online Access:Request full text
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Summary: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.
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.1999.814238