Abstract
In this study, we utilize the genetic algorithm (GA) to select high quality stocks with investment value. Given the fundamental financial and price information of stocks trading, we attempt to use GA to identify stocks that are likely to outperform the market by having excess returns. To evaluate the efficiency of the GA for stock selection, the return of equally weighted portfolio formed by the stocks selected by GA is used as evaluation criterion. Experiment results reveal that the proposed GA for stock selection provides a very flexible and useful tool to assist the investors in selecting valuable stocks.
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© 2006 Springer-Verlag Berlin Heidelberg
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Zhou, C., Yu, L., Huang, T., Wang, S., Lai, K.K. (2006). Selecting Valuable Stock Using Genetic Algorithm. In: Wang, TD., et al. Simulated Evolution and Learning. SEAL 2006. Lecture Notes in Computer Science, vol 4247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11903697_87
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DOI: https://doi.org/10.1007/11903697_87
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-47331-2
Online ISBN: 978-3-540-47332-9
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