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Frequency-Weighted Fuzzy Time-Series Based on Fibonacci Sequence for TAIEX Forecasting

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Part of the book series:Lecture Notes in Computer Science ((LNAI,volume 4819))

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Abstract

This paper proposes a new fuzzy time-series model for promoting the stock price forecasting, which provides two refined approaches, a frequency-weighted method, and the concept of Fibonacci sequence in forecasting processes. In empirical analysis, two different types of financial datasets, TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) stock index and HSI (Hong Kong Heng Seng Index) stock index are used as model verification. By comparing the forecasting results with those derived from Chen’s, Yu’s, and Hurang’s models, the authors conclude that the research goal has been reached.

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Author information

Authors and Affiliations

  1. Department of Information Management, National Yunlin University of Science and Technology, 123, section 3, University Road, Touliu, Yunlin 640, Taiwan, R.O.C.

    Hia Jong Teoh, Tai-Liang Chen & Ching-Hsue Cheng

  2. Department of Accounting Information, Ling Tung University, 1, Ling Tung Road, Nantun, Taichung 408, Taiwan, R.O.C.

    Hia Jong Teoh

Authors
  1. Hia Jong Teoh
  2. Tai-Liang Chen
  3. Ching-Hsue Cheng

Editor information

Takashi Washio Zhi-Hua Zhou Joshua Zhexue Huang Xiaohua Hu Jinyan Li Chao Xie Jieyue He Deqing Zou Kuan-Ching Li Mário M. Freire

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© 2007 Springer-Verlag Berlin Heidelberg

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Teoh, H.J., Chen, TL., Cheng, CH. (2007). Frequency-Weighted Fuzzy Time-Series Based on Fibonacci Sequence for TAIEX Forecasting. In: Washio, T.,et al. Emerging Technologies in Knowledge Discovery and Data Mining. PAKDD 2007. Lecture Notes in Computer Science(), vol 4819. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77018-3_4

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