A Novel Nonlinear Neural Network Ensemble Model for Financial Time Series Forecasting

  • Kin Keung Lai
  • Lean Yu
  • Shouyang Wang
  • Huang Wei
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3991)


In this study, a new nonlinear neural network ensemble model is proposed for financial time series forecasting. In this model, many different neural network models are first generated. Then the principal component analysis technique is used to select the appropriate ensemble members. Finally, the support vector machine regression method is used for neural network ensemble. For further illustration, two real financial time series are used for testing.


Root Mean Square Error Neural Network Model Ensemble Member Ensemble Method Financial Time Series 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Kin Keung Lai
    • 1
    • 2
  • Lean Yu
    • 2
    • 3
  • Shouyang Wang
    • 1
    • 3
  • Huang Wei
    • 4
  1. 1.College of Business AdministrationHunan UniversityChangshaChina
  2. 2.Department of Management SciencesCity University of Hong KongKowloon, Hong Kong
  3. 3.Institute of Systems Science, Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijingChina
  4. 4.School of ManagementHuazhong University of Science and TechnologyWuhanChina

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