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Short-run forecasting of the euro-dollar exchange rate with economic fundamentals

Author

Listed:
  • Marcos dal Bianco

    (BBVA Research)

  • Maximo Camacho

    (Universidad de Murcia)

  • Gabriel Perez-Quiros

    (Banco de España)

Abstract
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 outof-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.

Suggested Citation

  • Marcos dal Bianco & Maximo Camacho & Gabriel Perez-Quiros, 2012. "Short-run forecasting of the euro-dollar exchange rate with economic fundamentals," Working Papers 1203, Banco de España.
    • Handle: RePEc:bde:wpaper:1203
    as

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    References listed on IDEAS

    as
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    More about this item

    Keywords

    euro-dollar rate; exchange rate forecasting; State-space model; mixed frequencies;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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