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Performance Evaluation of ANFIS and GA-ANFIS for Predicting Stock Market Indices

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  • Farnaz Ghashami
  • Kamyar Kamyar

Abstract

A model of Adaptive Neuro-Fuzzy Inference System (ANFIS) trained with an evolutionary algorithm, namely Genetic Algorithm (GA) is presented in this paper. Further, the model is tested on the NASDAQ stock market indices which is among the most widely followed indices in the United States. Empirical results show that by determining the parameters of ANFIS (premise and consequent parameters) using GA, we can improve performance in terms of Mean Squared Error (MSE), Root Mean Squared Error (RMSE), coefficient of determination (R-Squared) in comparison with using solely ANFIS.

Suggested Citation

  • Farnaz Ghashami & Kamyar Kamyar, 2021. "Performance Evaluation of ANFIS and GA-ANFIS for Predicting Stock Market Indices," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 13(7), pages 1-1, June.
    • Handle: RePEc:ibn:ijefaa:v:13:y:2021:i:7:p:1
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    Citations

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    Cited by:

    1. Lam, H.Y. & Ho, G.T.S. & Mo, Daniel Y. & Tang, Valerie, 2023. "Responsive pick face replenishment strategy for stock allocation to fulfil e-commerce order," International Journal of Production Economics, Elsevier, vol. 264(C).
    2. Sina E. Charandabi & Farnaz Ghashami & Kamyar Kamyar, 2021. "US-China Tariff War: A Gravity Approach," Business and Economic Research, Macrothink Institute, vol. 11(3), pages 69-77, December.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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