Advanced Search
MyIDEAS: Login to save this article or follow this journal

Estimating structural exchange rate models by artificial neural networks

Contents:

Author Info

  • Joseph Plasmans
  • William Verkooijen
  • Hennie Daniels
Registered author(s):

    Abstract

    No theory of structural exchange rate determination has yet been found that performs well in prediction experiments. Only very seldom has the simple random walk model been significantly outperformed. Referring to three, sometimes highly nonlinear, monetary and nonmonetary structural exchange rate models, a feedforward artificial neural network specification is investigated to determine whether it improves the prediction performance of structural and random walk exchange rate models. A new test for univariate nonlinear cointegration is also derived. Important nonlinearities are not detected for monthly data of US dollar rates in Deutsche marks, Dutch guilders, British pounds and Japanese yens.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://www.tandfonline.com/doi/abs/10.1080/096031098332844
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Applied Financial Economics.

    Volume (Year): 8 (1998)
    Issue (Month): 5 ()
    Pages: 541-551

    as in new window
    Handle: RePEc:taf:apfiec:v:8:y:1998:i:5:p:541-551

    Contact details of provider:
    Web page: http://www.tandfonline.com/RAFE20

    Order Information:
    Web: http://www.tandfonline.com/pricing/journal/RAFE20

    Related research

    Keywords:

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as in new window

    Cited by:
    1. Poghosyan, K., 2012. "Structural and reduced-form modeling and forecasting with application to Armenia," Open Access publications from Tilburg University urn:nbn:nl:ui:12-5590845, Tilburg University.
    2. Jane Binner & Rakesh Bissoondeeal & Thomas Elger & Alicia Gazely & Andrew Mullineux, 2005. "A comparison of linear forecasting models and neural networks: an application to Euro inflation and Euro Divisia," Applied Economics, Taylor & Francis Journals, vol. 37(6), pages 665-680.
    3. Malhotra, Rashmi & Malhotra, D. K., 2003. "Evaluating consumer loans using neural networks," Omega, Elsevier, vol. 31(2), pages 83-96, April.
    4. Poghosyan, K. & Boldea, O., 2011. "Structural versus Matching Estimation: Transmission Mechanisms in Armenia," Discussion Paper 2011-104, Tilburg University, Center for Economic Research.
    5. Boldea, O. & Engwerda, J.C. & Michalak, T. & Plasmans, J.E.J. & Salmah, S., 2011. "A Simulation Study of an ASEAN Monetary Union (Replaces CentER DP 2010-100)," Discussion Paper 2011-098, Tilburg University, Center for Economic Research.
    6. Engwerda, J. & Boldea, O. & Michalak, T. & Plasmans, J. & Salmah,, 2012. "A simulation study of an ASEAN monetary union," Economic Modelling, Elsevier, vol. 29(5), pages 1870-1890.
    7. Tseng, Chih-Hsiung & Cheng, Sheng-Tzong & Wang, Yi-Hsien & Peng, Jin-Tang, 2008. "Artificial neural network model of the hybrid EGARCH volatility of the Taiwan stock index option prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3192-3200.
    8. Stavros Degiannakis & Evdokia Xekalaki, 2007. "Assessing the performance of a prediction error criterion model selection algorithm in the context of ARCH models," Applied Financial Economics, Taylor & Francis Journals, vol. 17(2), pages 149-171.
    9. Panda, Chakradhara & Narasimhan, V., 2007. "Forecasting exchange rate better with artificial neural network," Journal of Policy Modeling, Elsevier, vol. 29(2), pages 227-236.
    10. Chun-Teck Lye & Tze-Haw Chan & Chee-Wooi Hooy, 2012. "Nonlinear Analysis Of Chinese And Malaysian Exchange Rates Predictability With Monetary Fundamentals," Journal of Global Business and Economics, Global Research Agency, vol. 5(1), pages 38-49, July.
    11. Cem Kadilar & Muammer Simsek & Cagdas Hakan Aladag, 2009. "Forecasting The Exchange Rate Series With Ann: The Case Of Turkey," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 9(1), pages 17-29, May.
    12. Jo-Hui Chen & Yen-Po Fang, 2011. "A study on the modified components of Asian Currency Unit: an application of the Artificial Neural Network," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(2), pages 329-347, February.
    13. Stelios Bekiros, 2007. "A neurofuzzy model for stock market trading," Applied Economics Letters, Taylor & Francis Journals, vol. 14(1), pages 53-57.
    14. Ahmad Zubaidi Baharumshah & Liew Khim Sen & Lim Kian Ping, 2003. "Exchange Rates Forecasting Model: An Alternative Estimation Procedure," International Finance 0307005, EconWPA.
    15. Chun-Teck Lye & Tze-Haw Chan & Chee-Wooi Hooy, 2011. "Nonlinear prediction of Malaysian exchange rate with monetary fundamentals," Economics Bulletin, AccessEcon, vol. 31(3), pages 1960-1967.

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:taf:apfiec:v:8:y:1998:i:5:p:541-551. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 profile, as there may be some citations waiting for confirmation.

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