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Forecasting Stock Price Based on Fuzzy Time-Series with Entropy-Based Discretization Partitioning

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Knowlege-Based and Intelligent Information and Engineering Systems (KES 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6882))

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Abstract

The prediction of stock markets is an important and widely research issue since it could be had significant benefits and impacts. In this paper, we applied entropy-based discretization partitioning to obtain optimized linguistic intervals setting for fuzzy time-series model. In order to evaluate our proposed approach, the dataset collected from Taiwan Stock Exchange (TAIEX). Finally, the experimental results showed that our proposed approach was effective in finding for the better linguistic intervals settings, when the entropy-based discretization partitioning is applied. Furthermore, the performances indicate that the proposed model is superior to the compared models suggested by Chen (1996) and Yu (2005) earlier. It is evident that the entropy partitioning is a good approach to obtain optimized linguistic intervals for fuzzy time-series models.

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Author information

Authors and Affiliations

  1. Department of Information Management, National Taichung Institute of Technology, Taichung, Taiwan (R.O.C.)

    Bo-Tsuen Chen, Mu-Yen Chen & Hsiu-Sen Chiang

  2. Department of Information Management, Tunghai University, Taichung, Taiwan (R.O.C.)

    Chia-Chen Chen

Authors
  1. Bo-Tsuen Chen
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  2. Mu-Yen Chen
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  3. Hsiu-Sen Chiang
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  4. Chia-Chen Chen
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Editor information

Editors and Affiliations

  1. Institute of Integrated Sensor Systems, University of Kaiserslautern, Erwin-Schroedinger-str. 12, 67663, Kaiserslautern, Germany

    Andreas König

  2. Knowledge-Based Systems Group, Department of Computer Science, University of Kaiserslautern, P.O. Box 3049, 67653, Kaiserslautern, Germany

    Andreas Dengel

  3. School of Business, University of Applied Sciences Northwestern Switzerland, Riggenbachstr. 16, 4600, Olten, Switzerland

    Knut Hinkelmann

  4. Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, 599-8531, Sakai,, Osaka, Japan

    Koichi Kise

  5. KES International, P.O. Box 2115, BN43 9AF, Shoreham-by-sea, UK

    Robert J. Howlett

  6. University of South Australia, Adelaide, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2011 Springer-Verlag Berlin Heidelberg

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Chen, BT., Chen, MY., Chiang, HS., Chen, CC. (2011). Forecasting Stock Price Based on Fuzzy Time-Series with Entropy-Based Discretization Partitioning. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowlege-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6882. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23863-5_39

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  • DOI: https://doi.org/10.1007/978-3-642-23863-5_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23862-8

  • Online ISBN: 978-3-642-23863-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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