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Keywords = Giacomini-White statistic

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23 pages, 337 KiB  
Article
Timing Foreign Exchange Markets
by Samuel W. Malone, Robert B. Gramacy and Enrique Ter Horst
Econometrics 2016, 4(1), 15; https://doi.org/10.3390/econometrics4010015 - 11 Mar 2016
Cited by 3 | Viewed by 8201
Abstract
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 [...] Read more.
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 a model 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. Full article
(This article belongs to the Special Issue Computational Complexity in Bayesian Econometric Analysis)
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