An Economic Evaluation of Empirical Exchange Rate Models

This paper provides a comprehensive evaluation of the short-horizon predictive ability of economic fundamentals and forward premiums on monthly exchange-rate returns in a framework that allows for volatility timing. We implement Bayesian methods for estimation and ranking of a set of empirical exchange rate models, and construct combined forecasts based on Bayesian model averaging. More importantly, we assess the economic value of the in-sample and out-of-sample forecasting power of the empirical models, and find two key results: (1) a risk-averse investor will pay a high performance fee to switch from a dynamic portfolio strategy based on the random walk model to one that conditions on the forward premium with stochastic volatility innovations and (2) strategies based on combined forecasts yield large economic gains over the random walk benchmark. These two results are robust to reasonably high transaction costs.