Exchange Rate Fundamentals, Forecasting, and Speculation: Bayesian Models in Black Markets

Abstract

SUMMARY Although speculative activity is central to black markets for currency, the out‐of‐sample performance of structural models in those settings is unknown. We substantially update the literature on empirical determinants of black market rates and evaluate the out‐of‐sample performance of linear models and non‐parametric Bayesian treed Gaussian process (BTGP) models against the random walk benchmark. Fundamentals‐based models outperform the benchmark in out‐of‐sample prediction accuracy and trading rule profitability measures given future values of fundamentals. In simulated real‐time trading exercises, however, the BTGP achieves superior realized profitability, accuracy and market timing, while linear models do no better than a random walk. Copyright © 2013 John Wiley & Sons, Ltd.

Timing Foreign Exchange Markets

“…Our strategies, similar to those studied recently in [5,6], fund a long position in a given currency by a short position in the US dollar, if the expected next-month excess return of doing so is positive, and take the opposite positions otherwise. As demonstrated in [7], forecast breakdowns can arise due to the instability of the relationship between exchange rates and fundamentals over time.…”

“…One class of approaches involves using more sophisticated model selection criteria (see e.g., [7,15,16]); others expand the range of exchange rates studied to include smaller country cross rates with the dollar or another major currency ( [17][18][19]). A more detailed discussion of these papers, none of which manages to beat the random walk at the monthly frequency of greatest interest to the literature, can be found in [6]. Earlier work on exchange rate forecasting includes linear models with time-varying features ( [20][21][22]), non-parametric kernel regression models ( [23,24]), and Markov-switching models ( [25,26]).…”

“…As the first study to examine the economic implications of individual exchange rate predictability based on carry and dollar factors, we measure economic value using carry trade timing strategies, e.g., [5,6]. In these papers and our own, the benchmark (random walk) strategy forecasts the log spot exchange rate return to be zero, then invokes CIP to set the expected excess return equal to the forward premium.…”

“…We retain this benchmark, but differ from [5] by including the RWWD, linear, and BTGP models for forming forecasts of log currency returns, as well as paying careful attention to the sources of the economic value derived from forecasts. We differ from [6], which examines speculation in black markets for currency, and employ a set of macroeconomic fundamentals appropriate for that setting, by focusing on large, liquid foreign exchange markets. In this paper, we report results for the cross-section of out-of-sample return time series generated across currencies in a worldwide sample, similar to those studied by [1,2,10,35].…”

“…First, as in [6,19,26,34,43], we report a directional accuracy statistic, which is equal to the percentage of months in which the prediction of the sign of the next-month carry trade return by a given model is correct.…”