Order Anticipation in Large Order Executions

Abstract

This paper studies the presence of order anticipation strategies by examining predictable patterns in large order executions. I construct four simple signals based on child-order execution patterns that may potentially leak order flow information to algorithmic traders and find empirical evidence that stronger signals are correlated with higher execution costs. This effect is more pronounced for stocks with higher algorithmic trading activity consistent with the order anticipation hypothesis. Higher price impact due to predictable signals can be transitory and permanent suggesting that algorithmic traders may exploit both the liquidity needs and private information of the investors.