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Forecasting nominal exchange rates using a dynamic model averaging framework.

Martin Časta^1,2

¹Prague University of Economics and Business, Prague, Czech Republic.

|December 6, 2024

Summary

This study introduces dynamic model averaging for exchange rate forecasting, demonstrating significant predictability across major currencies. The approach accounts for model uncertainty, offering insights into medium, long, and even short-term forecasting.

Keywords:

Exchange rates Forecast evaluation Forecasting

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Area of Science:

Economics
Econometrics
Financial Forecasting

Background:

Exchange rate forecasting is crucial for international finance.
Existing models often struggle with parameter and model uncertainty.
A unified framework is needed to encompass various forecasting approaches.

Purpose of the Study:

To present a dynamic model averaging (DMA) approach for nominal exchange rate forecasting.
To analyze parameter and model uncertainty within exchange rate prediction.
To assess the predictability of major currency pairs.

Main Methods:

Developed a dynamic model averaging (DMA) framework.
Applied the DMA approach to nine major currency pairs (AUD/USD, CAD/USD, CHF/USD, EUR/USD, GBP/USD, NOK/USD, NZD/USD, SEK/USD, JPY/USD).
Utilized approximately two decades of historical data for empirical analysis.

Main Results:

Empirically demonstrated statistically and economically significant exchange rate predictability.
Found predictability in the medium and long run for major currency pairs.
Identified evidence of predictability even in the short run.

Conclusions:

The dynamic model averaging approach effectively forecasts nominal exchange rates.
The study confirms the existence of significant exchange rate predictability.
Theoretical explanations for observed predictability are provided.