This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Modelling exchange rates: smooth transitions, neural networks, and linear models

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Marcelo Cunha Medeiros () (Department of Economics PUC-Rio)
Álvaro Veiga (Department of Electrical Engineering PUC-Rio)
Carlos Eduardo Pedreira (Department of Electrical Engineering PUC-Rio)

Additional information is available for the following registered author(s):

Abstract

The goal of this paper is to test for and model nonlinearities in several monthly exchange rates time series. We apply two different nonlinear alternatives, namely: the artificial neural network time series model estimated with Bayesian regularization and a flexible smooth transition specifica-tion, called the neuro-coefficient smooth transition autoregression. The linearity test rejects the null hypothesis of linearity in ten out of fourteen series. We compare, using different measures, the fore-casting performance of the nonlinear specifications with the linear autoregression and the random walk models.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. 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.econ.puc-rio.br/pdf/td432.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Department of Economics PUC-Rio (Brazil) in its series Textos para discussão with number 432.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 27 pages
Date of creation: Nov 2000
Date of revision:
Publication status: Published in IEEE Transactions on Neural Networks - Special Issue: Neural Network in Financial Engineering - v. 12, p.755-764
Handle: RePEc:rio:texdis:432

Contact details of provider:
Postal: Rua Marqu�s de S�o Vicente, 225, 22453-900 Rio de Janeiro, RJ
Phone: 021 35271078
Fax: 021 35271084
Web page: http://www.econ.puc-rio.br
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: ().

Related research
Keywords:

Other versions of this item:

This paper has been announced in the following NEP Reports: References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Sarantis, Nicholas, 1999. "Modeling non-linearities in real effective exchange rates," Journal of International Money and Finance, Elsevier, vol. 18(1), pages 27-45, January. [Downloadable!] (restricted)
  2. Chang, P H Kevin & Osler, Carol L, 1999. "Methodical Madness: Technical Analysis and the Irrationality of Exchange-Rate Forecasts," Economic Journal, Royal Economic Society, vol. 109(458), pages 636-61, October. [Downloadable!] (restricted)
  3. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June. [Downloadable!] (restricted)
  4. G. Rech & T. Teräsvirta & R. Tschernig, . "A Simple variable selection technique for nonlinear models," Sonderforschungsbereich 373 1999-26, Humboldt Universitaet Berlin.
    Other versions:
  5. Chung-Ming Kuan & Halbert White, 1994. "Artificial neural networks: an econometric perspective," Econometric Reviews, Taylor and Francis Journals, vol. 13(1), pages 1-91. [Downloadable!] (restricted)
    Other versions:
  6. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
    Other versions:
  7. Medeiros, Marcelo & Veiga, Alvaro, 2000. "A Flexible Coefficient Smooth Transition Time Series Model," Working Paper Series in Economics and Finance 360, Stockholm School of Economics, revised 10 Feb 2000.
  8. Meese, Richard A & Rose, Andrew K, 1991. "An Empirical Assessment of Non-linearities in Models of Exchange Rate Determination," Review of Economic Studies, Blackwell Publishing, vol. 58(3), pages 603-19, May. [Downloadable!] (restricted)
    Other versions:
  9. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September. [Downloadable!] (restricted)
    Other versions:
  10. Gencay, Ramazan, 1999. "Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules," Journal of International Economics, Elsevier, vol. 47(1), pages 91-107, February. [Downloadable!] (restricted)
Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Marie Lebreton & Katia Melnik, 2009. "Voluntary Participation as a Determinant of Social Capital in France : Allowing for Parameter Heterogeneity," Working Papers halshs-00410530_v1, HAL. [Downloadable!]
  2. Khurshid Kiani & Terry Kastens, 2008. "Testing Forecast Accuracy of Foreign Exchange Rates: Predictions from Feed Forward and Various Recurrent Neural Network Architectures," Computational Economics, Springer, vol. 32(4), pages 383-406, November. [Downloadable!] (restricted)
Statistics
Access and download statistics

Did you know? You too can volunteer for RePEc, for example by editing a NEP report.

This page was last updated on 2009-11-17.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.