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Fuzzy time-series based on Fibonacci sequence for stock price forecasting

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

Abstract

Time-series models have been utilized to make reasonably accurate predictions in the areas of stock price movements, academic enrollments, weather, etc. For promoting the forecasting performance of fuzzy time-series models, this paper proposes a new model, which incorporates the concept of the Fibonacci sequence, the framework of Song and Chissom's model and the weighted method of Yu's model. This paper employs a 5-year period TSMC (Taiwan Semiconductor Manufacturing Company) stock price data and a 13-year period of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) stock index data as experimental datasets. By comparing our forecasting performances with Chen's (Forecasting enrollments based on fuzzy time-series. Fuzzy Sets Syst. 81 (1996) 311–319), Yu's (Weighted fuzzy time-series models for TAIEX forecasting. Physica A 349 (2004) 609–624) and Huarng's (The application of neural networks to forecast fuzzy time series. Physica A 336 (2006) 481–491) models, we conclude that the proposed model surpasses in accuracy these conventional fuzzy time-series models.

Suggested Citation

  • Chen, Tai-Liang & Cheng, Ching-Hsue & Jong Teoh, Hia, 2007. "Fuzzy time-series based on Fibonacci sequence for stock price forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 377-390.
    • Handle: RePEc:eee:phsmap:v:380:y:2007:i:c:p:377-390
    DOI: 10.1016/j.physa.2007.02.084
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    References listed on IDEAS

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    1. Huarng, Kunhuang & Yu, Tiffany Hui-Kuang, 2006. "The application of neural networks to forecast fuzzy time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 481-491.
    2. Yu, Hui-Kuang, 2005. "A refined fuzzy time-series model for forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 346(3), pages 657-681.
    3. Huarng, Kunhuang & Yu, Hui-Kuang, 2005. "A Type 2 fuzzy time series model for stock index forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 445-462.
    4. Faff, R. W. & Brooks, R. D. & Kee, Ho Yew, 2002. "New evidence on the impact of financial leverage on beta risk: A time-series approach," The North American Journal of Economics and Finance, Elsevier, vol. 13(1), pages 1-20, May.
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    Cited by:

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    2. Chen, Tai-Liang & Cheng, Ching-Hsue & Teoh, Hia-Jong, 2008. "High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 876-888.
    3. Abdallah Abu Abdallah & Mousa Mohammad Abdullah Saleh & Sadam Al-Wadi & Firas Al Rawashdeh, 2019. "Improving the Estimation Accuracy Based on Wavelet Transform," Journal of Social Sciences (COES&RJ-JSS), , vol. 8(4), pages 544-557, October.
    4. Tai-Liang Chen, 2012. "Forecasting the Taiwan Stock Market with a Novel Momentum-based Fuzzy Time-series," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 38-50, February.
    5. MOROSAN Adrian, 2018. "A Mathematical Model That Can Be Used By The Gamblers To Obtain Gains In The Industry Of Sports Betting," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 70(4), pages 68-78, September.
    6. Seung Hwan Jeong & Hee Soo Lee & Hyun Nam & Kyong Joo Oh, 2021. "Using a Genetic Algorithm to Build a Volume Weighted Average Price Model in a Stock Market," Sustainability, MDPI, vol. 13(3), pages 1-16, January.
    7. Jilani, Tahseen Ahmed & Burney, Syed Muhammad Aqil, 2008. "A refined fuzzy time series model for stock market forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2857-2862.
    8. Hunt, Richard A., 2021. "Entrepreneurial orientation and the fate of corporate acquisitions," Journal of Business Research, Elsevier, vol. 122(C), pages 241-255.
    9. Wei, Liang-Ying, 2013. "A hybrid model based on ANFIS and adaptive expectation genetic algorithm to forecast TAIEX," Economic Modelling, Elsevier, vol. 33(C), pages 893-899.
    10. Öztunç Kaymak, Öznur & Kaymak, Yiğit, 2022. "Prediction of crude oil prices in COVID-19 outbreak using real data," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    11. Akbulak, Mehmet & Bozkurt, Durmuş, 2009. "On the order-m generalized Fibonacci k-numbers," Chaos, Solitons & Fractals, Elsevier, vol. 42(3), pages 1347-1355.

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