An Ensemble of Neural Networks for Stock Trading Decision Making

  • Pei-Chann Chang
  • Chen-Hao Liu
  • Chin-Yuan Fan
  • Jun-Lin Lin
  • Chih-Ming Lai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5755)


Stock turning signals detection are very interesting subject arising in numerous financial and economic planning problems. In this paper, Ensemble Neural Network system with Intelligent Piecewise Linear Representation for stock turning points detection is presented. The Intelligent piecewise linear representation method is able to generate numerous stocks turning signals from the historic data base, then Ensemble Neural Network system will be applied to train the pattern and retrieve similar stock price patterns from historic data for training. These turning signals represent short-term and long-term trading signals for selling or buying stocks from the market which are applied to forecast the future turning points from the set of test data. Experimental results demonstrate that the hybrid system can make a significant and constant amount of profit when compared with other approaches using stock data available in the market.


Stock turning signals Ensemble neural network PLR method Financial time series data 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Pei-Chann Chang
    • 1
  • Chen-Hao Liu
    • 2
  • Chin-Yuan Fan
    • 3
  • Jun-Lin Lin
    • 1
  • Chih-Ming Lai
    • 1
  1. 1.Department of Information ManagementYuan Ze UniversityTaoyuanTaiwan
  2. 2.Department of Information ManagementKainan UniversityTaoyuanTaiwan
  3. 3.Department of Business Innovation and DevelopmentMing Dao UniversityChanghuaTaiwan

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