Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: http://hdl.handle.net/10419/171868
Autoren: 
Malone, Samuel W.
Gramacy, Robert B.
ter Horst, Enrique
Datum: 
2016
Quellenangabe: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 4 [Year:] 2016 [Issue:] 1 [Pages:] 1-23
Zusammenfassung: 
To improve short-horizon exchange rate forecasts, we employ foreign exchange market risk factors as fundamentals, and Bayesian treed Gaussian process (BTGP) models to handle non-linear, time-varying relationships between these fundamentals and exchange rates. Forecasts from the BTGP model conditional on the carry and dollar factors dominate random walk forecasts on accuracy and economic criteria in the Meese-Rogoff setting. Superior market timing ability for large moves, more than directional accuracy, drives the BTGP's success. We explain how, through amodel averaging Monte Carlo scheme, the BTGP is able to simultaneously exploit smoothness and rough breaks in between-variable dynamics. Either feature in isolation is unable to consistently outperform benchmarks throughout the full span of time in our forecasting exercises. Trading strategies based on ex ante BTGP forecasts deliver the highest out-of-sample risk-adjusted returns for the median currency, as well as for both predictable, traded risk factors.
Schlagwörter: 
foreign exchange
speculation
Bayesian treed Gaussian process
Anatolyev-Gerko statistic
Giacomini-White statistic
JEL: 
F31
G15
G17
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
http://creativecommons.org/licenses/by/4.0/
Dokumentart: 
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