Adaptive Forecasting of Exchange Rates with Panel Data
AbstractThis article investigates the statistical and economic implications of adaptive forecasting of exchange rates with panel data and alternative predictors. The candidate exchange rate predictors are drawn from (i) macroeconomic ‘fundamentals’, (ii) return/volatility of asset markets and (iii) cyclical and confidence indices. Exchange rate forecasts at various horizons are obtained from each of the potential predictors using single market, mean group and pooled estimates by means of rolling window and recursive forecasting schemes. The capabilities of single predictors and of adaptive techniques for combining the generated exchange rate forecasts are subsequently examined by means of statistical and economic performance measures. The forward premium and a predictor based on a Taylor rule yield the most promising forecasting results out of the macro ‘fundamentals’ considered. For recursive forecasting, confidence indices and volatility in-mean yield more accurate forecasts than most of the macro ‘fundamentals’. Adaptive forecast combinations techniques improve forecasting precision and lead to better market timing than most single predictors at higher horizons
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Bibliographic InfoPaper provided by Kiel Institute for the World Economy in its series Kiel Working Papers with number 1656.
Length: 48 pages
Date of creation: Oct 2010
Date of revision:
Exchange rate forecasting; panel data; forecast combinations; market timing;
Find related papers by JEL classification:
- C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
- F31 - International Economics - - International Finance - - - Foreign Exchange
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-11-13 (All new papers)
- NEP-CBA-2010-11-13 (Central Banking)
- NEP-FOR-2010-11-13 (Forecasting)
- NEP-IFN-2010-11-13 (International Finance)
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.:
- Lorenzo Trapani & Giovanni Urga, 2006.
"Optimal forecasting with heterogeneous panels: a Monte Carlo study,"
0616, Department of Economics and Technology Management, University of Bergamo.
- Trapani, Lorenzo & Urga, Giovanni, 2009. "Optimal forecasting with heterogeneous panels: A Monte Carlo study," International Journal of Forecasting, Elsevier, Elsevier, vol. 25(3), pages 567-586, July.
- Turgut Kisinbay, 2007.
"The Use of Encompassing Tests for Forecast Combinations,"
IMF Working Papers
07/264, International Monetary Fund.
- Turgut Kışınbay, 2010. "The use of encompassing tests for forecast combinations," Journal of Forecasting, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 29(8), pages 715-727, December.
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