Algorithmic Trading in Turbulent Markets

Posted: 20 May 2019

See all articles by Hao Zhou

Hao Zhou

University of South Australia

Petko S. Kalev

La Trobe Business School

Guanghua Lian

University of South Australia - School of Commerce

Date Written: October 27, 2016

Abstract

We investigate the role algorithmic trading (AT) on days when the absolute value of the market return is more than two percent. We find that the abnormal return of a stock is related to the stock's AT intensity, that high AT intensity stocks experience less price drops (surges) on days when the market declines (increases) for more than two percent. This result is consistent with the view that AT minimizes price pressures and mitigates transitory pricing errors. Further analyses confirm that AT order imbalances have a smaller price impact compared to non-AT order imbalances and algorithmic traders reduce their price pressure by executing their trades according to the volume-weighted average prices.

Keywords: Algorithmic trading, Order imbalance, Turbulent markets, Volume-weighted average price, Price fluctuation

JEL Classification: G12, G14, G19

Suggested Citation

Zhou, Hao and Kalev, Petko S. and Lian, Guanghua, Algorithmic Trading in Turbulent Markets (October 27, 2016). https://doi.org/10.3905/jot.2008.3.4.7. Available at SSRN: https://ssrn.com/abstract=2316040 or http://dx.doi.org/10.2139/ssrn.2316040

Hao Zhou (Contact Author)

University of South Australia ( email )

37-44 North Terrace, City West Campus
Adelaide, South Australia 5001
Australia

Petko S. Kalev

La Trobe Business School ( email )

Department of Economics and Finance
Donald Whitehead Building: Level 3, DWB313
Bundoora, Victoria 3086
Australia
+613 9479 6285 (Phone)
+613 9479 1654 (Fax)

HOME PAGE: http://www.latrobe.edu.au/business/about/staff/profile?uname=PKalev

Guanghua Lian

University of South Australia - School of Commerce ( email )

37-44 North Terrace
Adelaide SA 5000, South Australia 5001
Australia

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