An enhanced artificial neural network for stock price predications
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Predicting stock price of a particular stock is a difficult non-linear problem. Artificial Neural Network (ANN) is a tool to solve this kind of problem and has received much attentions in the field of financial modeling in recent years. This paper proposes an enhanced ANN for predicting stock prices with a novel Max-Min normalization method as well as an iterative approach. Our experimental results confirm that the predication accuracy outperforms other existing ANN predication mechanisms.
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How to Cite
Ma, J., Huang, S., & Kwok, S. H.. (2016). An enhanced artificial neural network for stock price predications. International Journal of Business and Economic Development, Volume 04 Issue 3.
Citation Context
APA
Ma, J., Huang, S., & Kwok, S. H.. (2016). An enhanced artificial neural network for stock price predications. International Journal of Business and Economic Development, Volume 04 Issue 3.
MLA
Ma, Jiaxin, et al.. "An enhanced artificial neural network for stock price predications." International Journal of Business and Economic Development, Volume 04 Issue 3, 2016.
Chicago
Jiaxin Ma, Silin Huang, and S. H. Kwok. "An enhanced artificial neural network for stock price predications." International Journal of Business and Economic Development Volume 04 Issue 3 (17 Dec 2016).
Harvard
Ma, J., Huang, S., & Kwok, S. H. (2016) An enhanced artificial neural network for stock price predications. International Journal of Business and Economic Development, Volume 04 Issue 3
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