We build statistical models to describe how market participants choose the direction, price, and volume of orders. Our dataset, which spans sixteen weeks for four shares traded in Euronext Amsterdam, contains all messages sent to the exchange and includes algorithm identification and member identification. We obtain reliable out-of-sample predictions and report the top features that predict direction, price, and volume of orders sent to the exchange. The coefficients from the fitted models are used to cluster trading behaviour and we give novel stylized representations of different patterns of algorithmic behaviour in these markets.

Bio: Samuel Cohen received his doctorate from the University of Adelaide in 2011, under the supervision of Robert Elliott and Charles Pearce. Since then he has been based in the Mathematical Institute in Oxford. His work has covered a broad range of topics in stochastic calculus, optimal control theory, and the use of statistical methods in quantitative finance.