Does Trade Clustering Reduce Trading Costs? Evidence from Periodicity in Algorithmic Trading

Abstract

We use quasi-exogenous variation in trading activity at the sub-second frequency to show that higher trade and quote intensities cause higher volatility but perhaps surprisingly have no significant effect on stock liquidity. This result has significant implications for the theories of strategic trading. We use the fact that many more trades and quote updates arrive within the first 100 milliseconds than during the rest of a second. These periodicities originate from algorithms that trade predictably by repeating instructions in loops with round start times and time increments. This seemingly irrational behavior serves as a synchronization mechanism for other investors. We also show that HFTs are much less prone to this bias.

Keywords: trading seasonality, liquidity, informed trading, behavioral algorithmic trading