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

Abstract

We study how trading activity affects liquidity and volatility by introducing two periodicities in trading activity. First, trades and quote updates are much more frequent within the first 100 milliseconds of a second than during its remainder. Second, trading activity often spikes at intervals of exactly one second. For these two periodicities, higher trade and quote intensities lead to higher volatility, but they do not significantly affect stock liquidity. These periodicities are likely caused by algorithms that trade predictably by repeating instructions in loops with round start times and time increments. Such predictable behavior is exploitable and may provide an example of behavioral biases in trading algorithms.

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