Does trade clustering reduce trading costs? Evidence from periodicity in algorithmic trading
研究了交易活动中的两种周期性模式（每秒前100毫秒内交易更频繁、整秒时刻交易激增）如何影响流动性和波动性，发现这些周期性导致波动率上升但对流动性影响不显著。
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 ms 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 may provide an example of behavioral biases in trading algorithms.