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

39 Pages Posted: 22 Sep 2014 Last revised: 9 Aug 2016

See all articles by Dmitriy Muravyev

Dmitriy Muravyev

Michigan State University - Department of Finance

Joerg Picard

Grand Valley State University

Date Written: July 24, 2016

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

Suggested Citation

Muravyev, Dmitriy and Picard, Joerg, Does Trade Clustering Reduce Trading Costs? Evidence from Periodicity in Algorithmic Trading (July 24, 2016). Available at SSRN: https://ssrn.com/abstract=2496669 or http://dx.doi.org/10.2139/ssrn.2496669

Dmitriy Muravyev

Michigan State University - Department of Finance ( email )

315 Eppley Center
East Lansing, MI 48824-1122
United States

Joerg Picard (Contact Author)

Grand Valley State University ( email )

Seidman School of Business
1 Campus Drive
Allendale, MI 49401
United States
+1-616-331-7404 (Phone)

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