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Timing Foreign Exchange Markets

Author

Listed:
  • Samuel W. Malone

    (Moody’s Analytics, 121 N Walnut St., West Chester, PA 19380, USA)

  • 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)

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.

Suggested Citation

  • Samuel W. Malone & Robert B. Gramacy & Enrique Ter Horst, 2016. "Timing Foreign Exchange Markets," Econometrics, MDPI, vol. 4(1), pages 1-23, March.
  • Handle: RePEc:gam:jecnmx:v:4:y:2016:i:1:p:15-:d:65565
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    References listed on IDEAS

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    Cited by:

    1. Xin Yang & Shigang Wen & Zhifeng Liu & Cai Li & Chuangxia Huang, 2019. "Dynamic Properties of Foreign Exchange Complex Network," Mathematics, MDPI, vol. 7(9), pages 1-19, September.

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