Abstract

This paper investigates the empirical relation between order flow and macroeconomic information in the foreign exchange market, and the ability of microstructure models based on order flow to outperform a naive random walk benchmark. If order flow reflects heterogeneous beliefs about macroeconomic fundamentals, and currency markets learn about the state of the economy gradually, then order flow can have both explanatory and forecasting power for exchange rates. Using one year of high frequency data for three major exchange rates, we demonstrate that order flow is intimately related to a broad set of current and expected macroeconomic fundamentals. More importantly, we find that order flow is a powerful predictor of daily movements in exchange rates in an out-of-sample exercise. The Sharpe ratio obtained from allocating funds using forecasts generated by an order flow model is generally above unity and substantially higher than the Sharpe ratios obtained from alternative models, including the random walk model.