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Combining forecasts: some results on exchange and interest rates

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Author Info

  • Monica Billio
  • Domenico Sartore
  • Carlo Toffano

Abstract

The aim of this work is to investigate whether the combination of forecasts plays an important role in the improvement of forecast accuracy Particular attention is paid to: (a) the methods of forecasting (the methods compared are neural networks, fuzzy logic, GARCH models, switching regime and chaotic dynamics); (b) combining the forecasts provided by the different methods. This work has also the aim of revising a short-term econometric forecast using a longer-term forecast. The revision process usually runs the opposite way (revision is made on a longer-term forecast using a short-term one to reflect the current available information, but it is not excluded that it is possible to proceed as described above. Daily data from the financial market is used. Some empirical applications on exchange and interest rates are given.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal The European Journal of Finance.

Volume (Year): 6 (2000)
Issue (Month): 2 ()
Pages: 126-145

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Handle: RePEc:taf:eurjfi:v:6:y:2000:i:2:p:126-145

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Related research

Keywords: Forecast Combination Composite Forecasts Forecast Comparison Exchange Rates Interest Rates;

References

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  1. Diebold, Francis X. & Pauly, Peter, 1990. "The use of prior information in forecast combination," International Journal of Forecasting, Elsevier, vol. 6(4), pages 503-508, December.
  2. Clemon, Robert T & Winkler, Robert L, 1986. "Combining Economic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 39-46, January.
  3. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
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Cited by:
  1. Piotr Wdowinski & Aneta Zglinska-Pietrzak, 2005. "The Warsaw Stock Exchange Index WIG: Modelling and Forecasting," CESifo Working Paper Series 1570, CESifo Group Munich.
  2. Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco & van Dijk, Herman K., 2013. "Time-varying combinations of predictive densities using nonlinear filtering," Journal of Econometrics, Elsevier, vol. 177(2), pages 213-232.

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