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An EPC Forecasting Method for Stock Index Based on Integrating Empirical Mode Decomposition, SVM and Cuckoo Search Algorithm

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Listed:
  • Li Xiangfei

    (School of Management, Tianjin Polytechnic University, Tianjin300387, China)

  • Zhang Zaisheng

    (College of Management and Economics, Tianjin University, Tianjin300072, China)

  • Huang Chao

    (School of Accountancy, Shanghai University of Finance and Economics, Shanghai200433, China)

Abstract

In order to improve the forecasting accuracy, a hybrid error-correction approach by integrating support vector machine (SVM), empirical mode decomposition (EMD) and the improved cuckoo search algorithm (ICS) was introduced in this study. By using two indexes as examples, the empirical study shows our proposed approach by means of synchronously predict the prediction error which used to correct the preliminary predicted values has better prediction precision than other five competing approaches, furthermore, the improved strategies for cuckoo search algorithm has better performance than other three evolutionary algorithms in parameters selection.

Suggested Citation

  • Li Xiangfei & Zhang Zaisheng & Huang Chao, 2014. "An EPC Forecasting Method for Stock Index Based on Integrating Empirical Mode Decomposition, SVM and Cuckoo Search Algorithm," Journal of Systems Science and Information, De Gruyter, vol. 2(6), pages 481-504, December.
    • Handle: RePEc:bpj:jossai:v:2:y:2014:i:6:p:481-504:n:1
    DOI: 10.1515/JSSI-2014-0481
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    References listed on IDEAS

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    Cited by:

    1. Wang, Jue & Wang, Zhen & Li, Xiang & Zhou, Hao, 2022. "Artificial bee colony-based combination approach to forecasting agricultural commodity prices," International Journal of Forecasting, Elsevier, vol. 38(1), pages 21-34.

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