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Time Series Analysis, Modeling and Applications pp 301–329Cite as

Building a Rough Sets-Based Prediction Model of Tick-Wise Stock Price Fluctuations

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Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 47))

Abstract

Rough sets enable us to mine knowledge in the form of IF-THEN decision rules from a data repository, a database, a web base, and others. Decision rules are used to reason, estimate, evaluate, and forecast. The objective of this paper is to build the rough sets-based model for analysis of time series data with tick-wise price fluctuations where knowledge granules are mined from the data set of tickwise price fluctuations. We show how a method based on rough sets helps acquire the knowledge from time-series data. The method enables us to obtain IF-THEN type rules for forecasting stock prices.

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Author information

Authors and Affiliations

  1. Faculty of Economics, Shimonoseki City University, 2-1-1, Daigaku-cho, Shimonoseki, Yamaguchi, 751-8510, Japan

    Yoshiyuki Matsumoto

  2. Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsu-ku, Kitakyushu, Fukuoka, 808-0135, Japan

    Junzo Watada

Authors
  1. Yoshiyuki Matsumoto
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  2. Junzo Watada
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Corresponding author

Correspondence to Yoshiyuki Matsumoto .

Editor information

Editors and Affiliations

  1. , Electrical & Computer Engineering, University of Alberta, 9107 - 116 Street, 2nd Floor, ECERF, Edmonton, T6G 2V4, Canada

    Witold Pedrycz

  2. , Graduate Institute of Educational Measur, National Taichung University of Educatio, Administration Building A110, Taichung, Taiwan R.O.C.

    Shyi-Ming Chen

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Matsumoto, Y., Watada, J. (2013). Building a Rough Sets-Based Prediction Model of Tick-Wise Stock Price Fluctuations. In: Pedrycz, W., Chen, SM. (eds) Time Series Analysis, Modeling and Applications. Intelligent Systems Reference Library, vol 47. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33439-9_14

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  • DOI: https://doi.org/10.1007/978-3-642-33439-9_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33438-2

  • Online ISBN: 978-3-642-33439-9

  • eBook Packages: EngineeringEngineering (R0)

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