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Forecasting and Combining Competing Models of Exchange rate Determination

  • Carlo Altavilla
  • Paul De Grauwe

This paper investigates the out-of-sample forecast performance of a set of competing models of exchange rate determination. We compare standard linear models with models that characterize the relationship between exchange rate and its underlying fundamentals by nonlinear dynamics. Linear models tend to outperform at short forecast horizons especially when deviations from long-term equilibrium are small. In contrast, nonlinear models with more elaborate mean-reverting components dominate at longer horizons especially when deviations from long-term equilibrium are large. The results also suggest that combining different forecasting procedures generally produces more accurate forecasts than can be attained from a single model.

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Paper provided by D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy in its series Discussion Papers with number 5_2006.

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Date of creation: 01 Mar 2006
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Handle: RePEc:prt:dpaper:5_2006
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  1. Charles Engel, 1991. "Can the Markov switching model forecast exchange rates?," Research Working Paper 91-04, Federal Reserve Bank of Kansas City.
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  17. Lucio Sarno & Giorgio Valente, 2009. "Exchange Rates and Fundamentals: Footloose or Evolving Relationship?," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 786-830, 06.
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