Abstract
Prediction for the change of stock market has been a hot research subject over the years. This thesis has introduced the definition and arithmetic of BP neural network model and established a stock market index prediction model based on the BP neural network model by taking advantage of the self-learning, self-adapting and nonlinear approximate ability. It is shown through empirical research that BP model not only has a rapid velocity of convergence and a high precision of prediction, but also has a certain application value if it is used for the short-term prediction of stock market index.
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© 2009 Springer-Verlag Berlin Heidelberg
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Fang, B., Ma, S. (2009). Application of BP Neural Network in Stock Market Prediction. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01513-7_119
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DOI: https://doi.org/10.1007/978-3-642-01513-7_119
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01512-0
Online ISBN: 978-3-642-01513-7
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