Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?
54 Pages Posted: 13 Feb 2014
Date Written: February 12, 2014
This paper shows that economic fundamentals can generate reliable out-of-sample forecasts for exchange rates when prediction is based on a "kitchen-sink" regression that incorporates multiple predictors. The key to establishing predictability is estimating the kitchen-sink regression with the elastic-net shrinkage method, which improves performance by reducing the effect of less informative predictors in out-of-sample forecasting. Using statistical and economic measures of predictability, we show that our approach outperforms alternative models, including the random walk, individual exchange rate models, a kitchen-sink regression estimated with ordinary least squares, standard forecast combinations and popular ad-hoc strategies such as momentum and the 1/N strategy.
Keywords: Exchange Rates, Out-of-Sample Forecasting, Elastic Net, Kitchen-Sink Regression, Combined Forecasts
JEL Classification: F31, F37, G11, G15, G17
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