An investigation of customer order flow in the foreign exchange market

Abstract

This paper examines the effect that heterogeneous customer orders flows have on exchange rates by using a new, and the largest, proprietary dataset of weekly net order flow segmented by customer type across nine of the most liquid currency pairs. We make several contributions. Firstly, we investigate the extent to which customer order flow can help to explain exchange rate movements over and above the influence of macroeconomic variables. Secondly, we address the issue of whether order flows contain (private) information which explain exchange rates changes. Thirdly, we look at the usefulness of order flow in forecasting exchange rate movements at longer horizons than those generally considered in the microstructure literature. Finally we address the question of whether the out-of-sample exchange rate forecasts generated by order flows can be employed profitably in the foreign exchange markets.

Microstructure order flow: statistical and economic evaluation of nonlinear forecasts

“…We have used this data set to assess the in sample predictive power of the three models introduced above. Results were not di¤erent to what is already reported in Cerrato et al (2009) and therefore are not reported in this study to save space 3 . Linearity tests against STAR nonlinearity for the order ‡ow are reported in Table 3 These results are available upon request.…”

“…The …rst data set is the customer order ‡ow data set used in Cerrato et al (2009). The data set consists of customer (weekly frequency) order ‡ows from UBS and covers the period November, 02 2001 -November, 23 2007 for nine of the most liquid currencies.…”

“…Conversly, a decline in this rate represents a strengthening of the foreign currency relative to the US dollar. Descriptive statistics for this data set are reported in Cerrato et al (2009). Since exchange rates are found to be I(1), we employ log di¤erenced rates.…”

“…In this section, following Evans and Lyons (2005b), Sager and Taylor (2008) and Cerrato et al (2009), we test whether the predictive performance of the order ‡ow model can be improved using disaggregate customer data.…”

“…This result is consistent with the empirical evidence of Engel and West (2005), which have found some support for the link between fundamentals and exchange rate in the other direction: exchange rates can help forecast the fundamentals. More recently, Cerrato et al (2009) uses weekly customer order ‡ow for nine of the most liquid currencies and investigates the in-sample and out-of-sample forecasting power of the order ‡ow models. While empirical results using aggregate data are in line with Sager and Taylor (2008) 1 , using disaggregate data seems to increase the in-sample and out-of-sample forecasting power of the order ‡ow model.…”