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Neural network analysis of varying trends in real exchange rates

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  • Kaashoek, J.F.
  • van Dijk, H.K.

Abstract

In this paper neural networks are fitted to the real exchange rates of seven industrialized countries. The size and topology of the used networks is found by reducing the size of the network through the use of multiple correlation coefficients, principal component analysis of residuals and graphical analysis of network output per hidden layer cell and input layer cell.

Suggested Citation

  • Kaashoek, J.F. & van Dijk, H.K., 1999. "Neural network analysis of varying trends in real exchange rates," Econometric Institute Research Papers EI 9915-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1569
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    References listed on IDEAS

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    1. Schotman, Peter C & van Dijk, Herman K, 1991. "On Bayesian Routes to Unit Roots," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 387-401, Oct.-Dec..
    2. Johan F. Kaashoek & Herman K. van Dijk, 1997. "A Simple Strategy to prune Neural Networks with an Application to Economic Time Series," Tinbergen Institute Discussion Papers 97-123/4, Tinbergen Institute.
    3. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207.
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    Cited by:

    1. Nikola Gradojevic & Jing Yang, 2000. "The Application of Artificial Neural Networks to Exchange Rate Forecasting: The Role of Market Microstructure Variables," Staff Working Papers 00-23, Bank of Canada.

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