Comparison of Forecasting the Index Price Movement in Financial Institutions using Artificial Intelligence (in Persian)

Mehdi Salehi (), Kiana Hamidehpour () and Hamid Khadem ()
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Mehdi Salehi: Iran
Kiana Hamidehpour: Iran
Hamid Khadem: Iran

Journal of Monetary and Banking Research (فصلنامه پژوهش‌های پولی-بانکی), 2016, vol. 9, issue 27, 131-170

Abstract: 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.

JEL-codes: C15 C45 M31 (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:mbr:jmbres:v:9:y:2016:i:27:p:131-170

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