A New Hybrid Approach for Analysis of Factors Affecting Crude Oil Price

  • Authors:

  • Wei Xu;Jue Wang;Xun Zhang;Wen Zhang;Shouyang Wang

  • Affiliations:

  • School of Management, Graduate University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, 100080, China;Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100080, China;Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100080, China;School of Management, Graduate University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, 100080, China;School of Management, Graduate University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, 100080, China and Institute of Systems Science, Academy of Mathematics and Systems S ...

  • Venue:
  • ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
  • Year:
  • 2007

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Abstract

In this paper, a new hybrid approach is presented to analyze factors affecting crude oil price using rough set and wavelet neural network. Related factors that affect crude oil price are found using text mining technique and Brent oil price is chosen as the decision price because it plays an important role in world crude oil markets. The relevant subsets of the factors are discovered by rough set module and the main factors are got, and then the important degrees of these are measured using wavelet neural network. Based on the novel hybrid approach, the predictability of crude oil price is discussed.