Timing Foreign Exchange Markets

Samuel Malone, Robert B. Gramacy and Enrique Ter Horst
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Robert B. Gramacy: Booth School of Business, The University of Chicago, 5807 S, Woodlawn Ave, Chicago, IL 60637, USA
Enrique Ter Horst: Colegio de Estudios Superiores de Administración, Bogotá, Colombia and Instituto de Estudios Superiores de Administración, Caracas 1010, Venezuela

Econometrics, 2016, vol. 4, issue 1, 1-23

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 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.

Keywords: foreign exchange; speculation; Bayesian treed Gaussian process; Anatolyev-Gerko statistic; Giacomini-White statistic (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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