Short-Run Forecasting of the Euro-Dollar Exchange Rate with Economic Fundamentals

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We propose a fundamentals-based econometric model for the weekly changes in the euro-dollar rate with the distinctive feature of mixing economic variables quoted at different frequencies. The model obtains good in-sample fit and, more importantly, encouraging out-of-sample forecasting results at horizons ranging from one week to one month. Specifically, we obtain statistically significant improvements upon the hard-to-beat random walk model using traditional statistical measures of forecasting error at all horizons. Moreover, our model improves greatly when we use the direction-of-change metric, which has more economic relevance than other loss measures. With this measure, our model performs much better at all forecasting horizons than a naive model that predicts the exchange rate has an equal chance to go up or down, with statistically significant improvements.