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Neural Network Method to Predict Stock Price Movement Based on Stock Information Entropy

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3973))

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Abstract

In this paper, the neural network is employed to learn the complicated association of the stock information stream with stock price movement. In general, the positive stream of stock information is assumed to stimulate buying and increase the stock prices, and the negative stream of stock information is assumed to result in selling and decrease the stock prices. Based on the stock information entropy, the intensity for stock information stream is measured and applied to associating with the stock price movement with the aid of neural networks. Experiments illustrate the associations statistically. The results are helpful in probing the microstructure of the stock markets from a new angle.

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Author information

Authors and Affiliations

  1. Institute of Computer Science and Technology, Peking University, Beijing, 100871, China

    Xun Liang

  2. Department of Economics and Operations Research, Stanford University, Palo Alto, CA, 94305, USA

    Xun Liang

Authors
  1. Xun Liang
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd, 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Liang, X. (2006). Neural Network Method to Predict Stock Price Movement Based on Stock Information Entropy. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_65

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  • DOI: https://doi.org/10.1007/11760191_65

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34482-7

  • Online ISBN: 978-3-540-34483-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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