Publication: Model Uncertainty and Exchange Rate Forecasting
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Issued Date
2017-02-01
Resource Type
ISSN
17566916
00221090
00221090
Other identifier(s)
2-s2.0-85016047990
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Financial and Quantitative Analysis. Vol.52, No.1 (2017), 341-363
Suggested Citation
Roy Kouwenberg, Agnieszka Markiewicz, Ralph Verhoeks, Remco C.J. Zwinkels Model Uncertainty and Exchange Rate Forecasting. Journal of Financial and Quantitative Analysis. Vol.52, No.1 (2017), 341-363. doi:10.1017/S0022109017000011 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/42139
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Title
Model Uncertainty and Exchange Rate Forecasting
Other Contributor(s)
Abstract
© 2017 Michael G. Foster School of Business, University of Washington. 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.