A Computing Procedure Combining Fuzzy Clustering with Fuzzy Inference System for Financial Index Forecasting

  • Bui Cong Cuong
  • Pham Van ChienEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 341)


In this paper, a computing procedure for stock value and financial index forecasting based on fuzzy clustering and fuzzy inference system is presented. Firstly, we present a data processing method based on percentage variation rate. Then we construct a fuzzy inference system with fuzzy rules obtained by the fuzzy clustering process. We determine weight of each rule and construct a defuzzification method. Finally, we apply the proposed computing procedure to some financial forecasting problems such as Vietnam’s stock value and foreign exchange. The experimental results show that our computing procedure gives better forecasting results in some case than several conventional models such as Autoregressive Model (AR), Adaptive neuro fuzzy inference system (ANFIS).


Fuzzy system Fuzzy clustering Fuzzy rule generation Forecasting 


  1. 1.
    Anari, T., Kumar, M., Shukla, A., Dhar, J., Tiwari, R.: Sequential combination of statistics, econometrics and adaptive neural-fuzzy interface for stock market prediction. Expert Syst. Appl. 37, 5116–5125 (2010)CrossRefGoogle Scholar
  2. 2.
    Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York (1981)CrossRefzbMATHGoogle Scholar
  3. 3.
    Bezdek, J.C., Ehrlich, R., William Full, F.C.M.: The fuzzy C-means clustering algorithm. Comput. Geosci. 10(2–3), 191–203 (1984)CrossRefGoogle Scholar
  4. 4.
    Chen, S.-M., Chang, Y.-C.: Multi-variable fuzzy forecasting based on fuzzy clustering and fuzzy rule interpolation techniques. Inf. Sci. 180, 4772–4783 (2010)CrossRefMathSciNetGoogle Scholar
  5. 5.
    Cuong, B.C., Van Chien, P.: An experiment result based on Adaptive Neuro-Fuzzy Inference System for stock price prediction. J. Comput. Sci. Cybern. 1, 51–60 (2011)Google Scholar
  6. 6.
    Kimoto, T., Asakawa, K., Yoda, M., Takeoka, M.: Stock market prediction with modular neural networks. In: Proceedings of the International Joint Conference on Neural Networks (IJCNN), vol. I, pp. 1–6, San Diego (1990)Google Scholar
  7. 7.
    Tambi, T.B.: Forecasting exchange rate a uni-variate out of sample approach (Box-Jenkin Methodology), 0506005 International Finance-Economics Working Paper Archive (2005)Google Scholar
  8. 8.
    White, H.: Economic prediction using neural networks: the case of IBM daily stock returns. In: The Proceedings of the Second IEEE Annual Conference on Neural networks, II, 451–458 (1988)Google Scholar
  9. 9.
    Chiang,W., Urban,T.L., Baldridge, G.W.: A neural network approach to mutual fund net asset value forecasting. Int. J. Manag. Sci. 24(2), 205–215 (1996)Google Scholar
  10. 10.
    Trafalis, T.B.: Artificial neural networks applied to financial forecasting. Proceedings of the artificial neural networks in engineering conference (ANNIE’99) (pp. 1049–1054). New York. ASME Press (1999)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Institute of MathematicsVietnam Academy of Science and TechnologyHanoiVietnam
  2. 2.Hanoi University of Science and TechnologyHanoiVietnam

Personalised recommendations