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Exchange Rate Forecasts at Long Horizons: Are Error-Correction Models Superior?

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  • Michael F. Bleaney

Abstract

The out-of-sample forecasting performance of error-correction models of exchange rates is tested on recent monthly data and on annual data from 1900 to 1995. The results for the monthly data set strongly favor the naive model, even when the series are pooled. In the annual data, the best model is usually a regression model of some form, but there is no evidence that a researcher can pick a regression model that outpredicts a naive model more often than not, either by choosing at random or by selecting the model that best fits past data.

Suggested Citation

  • Michael F. Bleaney, 1998. "Exchange Rate Forecasts at Long Horizons: Are Error-Correction Models Superior?," Canadian Journal of Economics, Canadian Economics Association, vol. 31(4), pages 852-864, November.
  • Handle: RePEc:cje:issued:v:31:y:1998:i:4:p:852-864
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    Citations

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    Cited by:

    1. Iqbal, Javed, 2001. "Forecasting methods: a comparative analysis," MPRA Paper 23856, University Library of Munich, Germany, revised 2001.
    2. John Galbraith & Greg Tkacz, 2007. "How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables," Staff Working Papers 07-1, Bank of Canada.

    More about this item

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange

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