Trader Lead-Lag Networks and Order Flow Prediction
21 Pages Posted: 18 Sep 2016
Date Written: September 15, 2016
Using trader-resolved data, we document lead-lag relationships between groups of investors in the foreign exchange market. Because these relationships are systematic and persistent, order flow is predictable from trader-resolved order flow. We thus propose a generic method to exploit trader lead-lag and predict the sign of the total order imbalance over a given time horizon. It first consists in an unsupervised clustering of investors according to their buy/sell/inactivity synchronization. The collective actions of these groups and their lagged values are given as inputs to machine learning methods. When groups of traders and when their lead-lag relationships are sufficiently persistent, highly successful out-of-sample order flow sign predictions are obtained.
Keywords: order flow, lead-lag, machine learning, prediction, networks
JEL Classification: G02, G11, G23
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