Order anticipation around predictable trades

I study the presence of order anticipation strategies by examining predictable patterns in large order trades. I construct three simple signals based on child-order execution patterns and find empirical evidence that stronger signals are correlated with higher execution costs. I use the SEC's (Securities and Exchange Commission's) ban on unfiltered access and increase in noise trading as shocks to order anticipatory activities of algorithmic traders and find that the price impact of predictability is smaller when order anticipation becomes difficult. The empirical findings are mostly consistent with the back-running theory that predicts delayed price impact as strategic traders learn about large orders gradually.