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Trend-Weighted Fuzzy Time-Series Model for TAIEX Forecasting

  • Ching-Hsue Cheng
  • Tai-Liang Chen
  • Chen-Han Chiang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4234)

Abstract

Time-series models have been used to make reasonably accurate predictions in the areas of weather forecasting, academic enrolment and stock price etc... We propose a methodology which incorporates trend-weighting into the fuzzy time-series models advanced by S.M. Chen and Hui-Kuang Yu. By using actual trading data of Taiwan Stock Index (TAIEX) and the enrolment data of the University of Alabama, we evaluate the accuracy of our trend-weighted, fuzzy, time-series model by comparing our forecasts with those derived from Chen’s and Yu’s models. The results indicate that our model surpasses in accuracy those suggested by Chen and Yu.

Keywords

Forecast Error Fuzzy Relationship Reasonable Universe Fuzzy Logical Relationship Stock Index Forecast 
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

  • Ching-Hsue Cheng
    • 1
  • Tai-Liang Chen
    • 1
  • Chen-Han Chiang
    • 1
  1. 1.Department of Information ManagementNational Yunlin University of Science and TechnologyTouliu, YunlinTaiwan,R.O.C.

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