Timing Foreign Exchange Markets

Abstract

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.

The Share of Systematic Variation in Bilateral Exchange Rates

“…The carry and dollar factors also beat the random walk benchmark easily in the pseudopredictability exercise of Meese and Rogoff (). Building on this paper, Malone, Gramacy, and ter Horst () reproduce the above pseudopredictability results and find actual predictability for bilateral rates by forecasting the carry and dollar factors.…”

Dynamic Properties of Foreign Exchange Complex Network

“…It identifies the exchange rates of global trade and also determines the relative wealth of a country [4][5][6]. The volatility of the FX market is affected by many factors, and its occurrence, formation and evolution show the typical feature of complex system [7][8][9]. To date, networks and dynamics modeling have attracted great attention in natural, social science and engineering technology [10][11][12][13][14][15][16][17][18][19][20][21][22].…”