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Clustering Based Stocks Recognition

  • Yaoyuan Shi
  • Zhongke Shi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4223)

Abstract

A new stocks analysis method based on clustering is presented in this paper, in which, six-dimension feature space is constructed according to the data structure of stock chief-index, and the constructed feature space is analyzed with a new fuzzy kern clustering algorithm. We use the Shanghai and Shenzhen’s stock index since 1997 to test our presented method. The results show that the method could intelligently recognizes some rules of essence trends of the stock markets and forecasts essence direction of the stock markets not only in short-term but also in long-term.

Keywords

Stock Market Feature Space Stock Index Time Series Forecast Stock Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yaoyuan Shi
    • 1
    • 2
  • Zhongke Shi
    • 1
  1. 1.The Northwestern Polytechnical UniversityXi’anChina
  2. 2.Xidian UniversityXi’anChina

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