Combining forecasts: some results on exchange and interest rates
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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Volume (Year): 6 (2000)
Issue (Month): 2 ()
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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.:
- 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.
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- Diebold, Francis X. & Pauly, Peter, 1990.
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Elsevier, vol. 6(4), pages 503-508, December.
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- Carlo Carraro & Domenico Sartore, 1987. "Square Root Iterative Filter: Theory and Applications to Econometric Models," Annals of Economics and Statistics, GENES, issue 6-7, pages 435-459. Full references (including those not matched with items on IDEAS)