Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?

54 Pages Posted: 13 Feb 2014

See all articles by Jiahan Li

Jiahan Li

University of Notre Dame

Ilias Tsiakas

University of Guelph

Wei Wang

Fifth Third Bank

Date Written: February 12, 2014

Abstract

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

Suggested Citation

Li, Jiahan and Tsiakas, Ilias and Wang, Wei, Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk? (February 12, 2014). Available at SSRN: https://ssrn.com/abstract=2394798 or http://dx.doi.org/10.2139/ssrn.2394798

Jiahan Li

University of Notre Dame ( email )

156 Hurley Hall
Notre Dame, IN 46556-5646
United States

Ilias Tsiakas (Contact Author)

University of Guelph ( email )

Department of Economics and Finance
University of Guelph
Guelph, Ontario N1G 2W1
Canada
5198244120 ext 53054 (Phone)
5197638497 (Fax)

HOME PAGE: http://www.uoguelph.ca/~itsiakas

Wei Wang

Fifth Third Bank ( email )

38 Fountain Square Plaza
Cincinnati, OH 45263
United States

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