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Model Uncertainty and Exchange Rate Forecasting

Published online by Cambridge University Press:  20 February 2017

Roy Kouwenberg,
Agnieszka Markiewicz,
Ralph Verhoeks and
Remco C. J. Zwinkels
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Abstract

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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.

Information

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 52 , Issue 1 , February 2017, pp. 341 - 363
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2017 

Footnotes

1 We thank Gurdip Bakshi (associate editor and the referee), Stephen Brown (the editor), André Lucas, Lukas Menkhoff, Maurizio Montone, Andreas Pick, Peter Schotman, Raman Uppal, Vadym Volosovych, and Casper de Vries for their insightful comments, as well as participants of the Forecasting Structure and Time Varying Patterns in Economics and Finance conference at Erasmus University Rotterdam, seminar participants at ISCTE Business School, Maastricht University, VU University Amsterdam, and Katholieke Universiteit Leuven. We especially thank Lucio Sarno for kindly providing us with the real-time data and Arlette Leeflang for excellent research assistance.

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