IDEAS home Printed from https://ideas.repec.org/a/vls/finstu/v20y2016i1p54-68.html
   My bibliography  Save this article

Forecasting The Total Index Of Tehran Stock Exchange

Author

Listed:
  • EMAMVERDI, Ghodratollah

    (Islamic Azad University, Central Tehran Branch)

  • KARIMI, Mohammad Sharif

    (Department of Economics, Faculty of Social Sciences, Razi University, Kermanshah, Iran)

  • KHAKIE, Sima

    (Islamic Azad University, Central Tehran Branch)

  • KARIMI, Mojtaba

    (Islamic Azad University, Central Tehran Branch)

Abstract

Development of financial markets and financial instruments is one of the pillars of economic growth and capital accumulation in any countries especially in the developing ones. Capital market works as a substantial tool for development and financing which attracts many investors for purchasing and selling capital. Hence they are seeking for forecasting events and situations of future till can invest with a lower uncertainty. On the other hand total index of stock exchanges accounted for a precursor one in economics which we expect following improvement in index of capital market, the economic growth will improve and we face condition of recession after its decrease. Thus the importance of exact prediction of this index is redoubled. In this paper we forecast the index by applying ARIMA and Neural Network and then we achieve the minimum and maximum of total index by using FARIMA. Indeed the main aim of this research is to imply this point that these three methods are complementary to each other in decision making of investors and economic policy makers.

Suggested Citation

  • EMAMVERDI, Ghodratollah & KARIMI, Mohammad Sharif & KHAKIE, Sima & KARIMI, Mojtaba, 2016. "Forecasting The Total Index Of Tehran Stock Exchange," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 20(1), pages 54-68.
    • Handle: RePEc:vls:finstu:v:20:y:2016:i:1:p:54-68
    as

    Download full text from publisher

    File URL: http://www.icfm.ro/RePEc/vls/vls_pdf/vol20i1p54-68.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Forecasting; Stock price index; Tehran Stock Exchange; Fuzzy ARIMA; Neural Network;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:vls:finstu:v:20:y:2016:i:1:p:54-68. 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: Daniel Mateescu (email available below). General contact details of provider: https://edirc.repec.org/data/cfiarro.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.