Next Article in Journal / Special Issue
The Evolving Transmission of Uncertainty Shocks in the United Kingdom
Previous Article in Journal / Special Issue
Return and Risk of Pairs Trading Using a Simulation-Based Bayesian Procedure for Predicting Stable Ratios of Stock Prices
Article Menu

Export Article

Open AccessArticle
Econometrics 2016, 4(1), 15; doi:10.3390/econometrics4010015

Timing Foreign Exchange Markets

1
Moody’s Analytics, 121 N Walnut St., West Chester, PA 19380, USA
2
Booth School of Business, The University of Chicago, 5807 S, Woodlawn Ave, Chicago, IL 60637, USA
3
Colegio de Estudios Superiores de Administración, Bogotá, Colombia and Instituto de Estudios Superiores de Administración, Caracas 1010, Venezuela
*
Author to whom correspondence should be addressed.
Academic Editors: Herman K. van Dijk, Francesco Ravazzolo, Nalan Basturk and Roberto Casarin
Received: 2 July 2015 / Revised: 14 December 2015 / Accepted: 28 January 2016 / Published: 11 March 2016
(This article belongs to the Special Issue Computational Complexity in Bayesian Econometric Analysis)
View Full-Text   |   Download PDF [337 KB, uploaded 11 March 2016]

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. View Full-Text
Keywords: foreign exchange; speculation; Bayesian treed Gaussian process; Anatolyev-Gerko statistic; Giacomini-White statistic foreign exchange; speculation; Bayesian treed Gaussian process; Anatolyev-Gerko statistic; Giacomini-White statistic
JEL: F31; G15; G17
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Malone, S.W.; Gramacy, R.B.; ter Horst, E. Timing Foreign Exchange Markets. Econometrics 2016, 4, 15.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Econometrics EISSN 2225-1146 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top