TITLE

Neural Network Algorithm Based Method for Stock Price Trend Prediction

AUTHOR(S)
Nan Ma; Yun Zhai; Wen-Fa Li; Cui-Hua Li; Shan-shan Wang; Lin Zhou
PUB. DATE
November 2013
SOURCE
Journal of Applied Sciences;2013, Vol. 13 Issue 22, p5384
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Neural network algorithm is very suitable for stock prediction as a model for dealing with complicated relationship. However, the prediction accuracy of neural network algorithm depends largely on the number of hidden nodes and the terminal condition. To follow up the changes in stock prices, a new method is proposed in this study to find out the optimal parameter. The recommended solution is setting fewer hidden nodes and lower holdout percentage. Results show that the proposed method can lessen about 60% of the forecast error such that it can ensure the efficiency and accuracy of the algorithm.
ACCESSION #
91943547

 

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