Exchange rate models with uncertain and incomplete information predict that investors focus on a small set of fundamentals that changes frequently over time. We design a model selection rule that captures the current set of fundamentals that best predicts the exchange rate. Out-of-sample tests show that the forecasts made by this rule significantly beat a random walk for 5 out of 10 currencies. Furthermore, the currency forecasts generate meaningful investment profits. We demonstrate that the strong performance of the model selection rule is driven by time-varying weights attached to a small set of fundamentals, in line with theory.

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Journal Journal of Financial and Quantitative Analysis
Kouwenberg, R.R.P, Markiewicz, A, Verhoeks, R. (Ralph), & Zwinkels, R.C.J. (2017). Model Uncertainty and Exchange Rate Forecasting. Journal of Financial and Quantitative Analysis (Vol. 52, pp. 341–363). doi:10.1017/S0022109017000011