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:: year 9, Issue 27 (Spring 2016) ::
JMBR 2016, 9(27): 131-170 Back to browse issues page
Comparison of Forecasting the Index Price Movement in Financial Institutions using Artificial Intelligence
Mehdi Salehi, Kiana Hamidehpour 1, Hamid Khadem
Abstract:   (1739 Views)

This study predicts the movements in the stock price index of Tehran Stock Exchange by using neural networks. The source of this paper is the information from banks and financial institutions listed on the Tehran Stock Exchange during the years 1385 to 1391 are used. The results show that the ANFIS algorithm has the best performance between FA, RBF, MLP and ICA algorithms. Results indicate that the proposed algorithms overall have high ability to predict the stock price index movement of Tehran Stock Exchange. Output of MATLAB shows that correlation coefficient of ANFIS algorithm about 0.9985.

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Type of Study: Methodological Article | Subject: Prices, Business Fluctuations, and Cycles (E3)
Received: 2016/05/13 | Accepted: 2017/01/4 | Published: 2017/05/22
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
year 9, Issue 27 (Spring 2016) Back to browse issues page
فصلنامه پژوهش‌های پولی-بانکی Journal of Monetary & Banking Research
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