IDEAS home Printed from https://ideas.repec.org/a/mbr/jmbres/v9y2016i27p131-170.html
   My bibliography  Save this article

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

Author

Listed:
  • Salehi, Mehdi

    (Iran)

  • Hamidehpour, Kiana

    (Iran)

  • Khadem, Hamid

    (Iran)

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.

Suggested Citation

  • Salehi, Mehdi & Hamidehpour, Kiana & Khadem, Hamid, 2016. "Comparison of Forecasting the Index Price Movement in Financial Institutions using Artificial Intelligence (in Persian)," Journal of Monetary and Banking Research (فصلنامه پژوهش‌های پولی-بانکی), Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 9(27), pages 131-170, April.
    • Handle: RePEc:mbr:jmbres:v:9:y:2016:i:27:p:131-170
    as

    Download full text from publisher

    File URL: http://jmbr.mbri.ac.ir/article-1-472-en.pdf
    Download Restriction: no
    File URL: http://jmbr.mbri.ac.ir/article-1-472-en.html
    Download Restriction: no
    File URL: http://jmbr.mbri.ac.ir/article-1-472-fa.html
    Download Restriction: no
    ---><---

    More about this item

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mbr:jmbres:v:9:y:2016:i:27:p:131-170. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: M. E. (email available below). General contact details of provider: https://edirc.repec.org/data/mbcbiir.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.