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

Jiahan Li (), Ilias Tsiakas and Wei Wang ()
Additional contact information
Jiahan Li: University of Notre Dame, USA
Wei Wang: Fifth Third Bank, USA

Working Paper series from Rimini Centre for Economic Analysis

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; Combined Forecasts (search for similar items in EconPapers)
JEL-codes: F31 F37 G11 G15 G17 (search for similar items in EconPapers)
Date: 2014-02
New Economics Papers: this item is included in nep-cba, nep-for and nep-mon
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Published in Journal of Financial Econometrics, 13(2):293-341, 2015

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http://www.rcea.org/RePEc/pdf/wp05_14.pdf (application/pdf)

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Journal Article: Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk? (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:rim:rimwps:05_14

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