IDEAS home Printed from https://ideas.repec.org/a/iif/iifjrn/v25y2010i290p35-64.html
   My bibliography  Save this article

A comparative analysis of the ARMA and Neural Network Models: A case of Turkish economy

Author

Listed:
  • Aysu İNSEL

    (Marmara Üniversitesi)

  • M. Nedim SUALP

    (Marmara Üniversitesi)

  • Mesut KARAKAŞ

    (Gebze Yüksek Teknoloji Enstitüsü)

Abstract

The aim of this paper is to provide a detailed econometric analysis of the changes in the nominal exchange rate, inflation rate, nominal interest rate and the real gross domestic product in Turkey for the period from January 1987 to December 2007, based on the monthly data. To this end, both ARMA and Neural Network modeling techniques have been employed in order to present a comparative analysis for their estimation and forecast performances. The results indicate that the NN predictions are consistent with those of ARMA models in the sense that the NN models can perform as good as the ARMA models in the estimation process. However, when evaluated for their forecast performances, they differ considerably depending upon the movements in the variables and the length of the sample period.

Suggested Citation

  • Aysu İNSEL & M. Nedim SUALP & Mesut KARAKAŞ, 2010. "A comparative analysis of the ARMA and Neural Network Models: A case of Turkish economy," Iktisat Isletme ve Finans, Bilgesel Yayincilik, vol. 25(290), pages 35-64.
    • Handle: RePEc:iif:iifjrn:v:25:y:2010:i:290:p:35-64
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Keywords

    Inflation rate; Exchange rate; Interest rate; RGDP; AK Party Administration period; Turkey; ARMA; Neural Network Models;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

    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:iif:iifjrn:v:25:y:2010:i:290:p:35-64. 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: Ali Bilge (email available below). General contact details of provider: http://iif.com.tr .

    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.