One model or many? Exchange rates determinants and their predictive capabilities
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In this paper the Dynamic Bayesian Model Averaging (DMA) algorithm is used to establish the key determinants of the nominal exchange rates of 5 currencies: CAD, EUR, GBP, CHF and JPY against the US dollar. My results indicate that the importance of the variables in the exchange rate forecasting can substantially differ in time. Even among the set of developed countries, there are visible differences in the set of key determinants of the exchange rate. However, the lagged value of the exchange rate remains always an important variable indicating significant persistence in the exchange rate time series. Furthermore, the PPP rate, Terms of Trade (TOT) and output per worker are also variables that have high Posterior Inclusion Probabilities among the analyzed countries. My results show that macroeconomic fundamentals are not leading indicators of the exchange rates. As a result, to outperform the random walk (naive) forecast of the exchange rate using the macroeconomic fundamentals, a good quality of the forecast of the explanatory variables is required.
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- KAE Working Papers 
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