Market Efficiency in the Age of Machine Learning

61 Pages Posted: 2 Mar 2021 Last revised: 15 Sep 2021

See all articles by Leonidas G. Barbopoulos

Leonidas G. Barbopoulos

University of Edinburgh

Rui Dai

Wharton Research Data Services (WRDS)

Tālis J. Putniņš

University of Technology Sydney (UTS); Stockholm School of Economics, Riga

Anthony Saunders

New York University - Leonard N. Stern School of Business

Date Written: March 24, 2021

Abstract

As machines replace humans in financial markets, how is informational efficiency impacted? We shed light on this issue by exploiting a unique data-set that allows us to identify when machines access important company information (8-K filings) versus when humans access the same information. We find that increased information access by cloud computing services significantly improves informational efficiency and reduces the price drift following information events. We address identification through exogenous power and cloud outages, a quasi-natural experiment, and instrumental variables. We show that machines are better able to handle linguistically complex filings, less susceptible to bias from negative sentiment and less constrained in attention/processing capacity than humans.

Keywords: Market efficiency; Information acquisition; Machine learning; Informed trading; Algorithmic trading

JEL Classification: G10; G12; G14

Suggested Citation

Barbopoulos, Leonidas G. and Dai, Rui and Putnins, Talis J. and Saunders, Anthony, Market Efficiency in the Age of Machine Learning (March 24, 2021). NYU Stern School of Business Forthcoming, Available at SSRN: https://ssrn.com/abstract=3783221 or http://dx.doi.org/10.2139/ssrn.3783221

Leonidas G. Barbopoulos (Contact Author)

University of Edinburgh ( email )

University of Edinburgh Business School
29 Buccleuch Place
Edinburgh, Scotland EH8 9JS
United Kingdom

Rui Dai

Wharton Research Data Services (WRDS) ( email )

3819 Chestnut St
Suite 300
Philadelphia, PA PA 19104
United States

Talis J. Putnins

University of Technology Sydney (UTS) ( email )

PO Box 123
Broadway
Sydney
Australia
+61 2 9514 3088 (Phone)

Stockholm School of Economics, Riga ( email )

Strelnieku iela 4a
Riga, LV 1010
Latvia
+371 67015841 (Phone)

Anthony Saunders

New York University - Leonard N. Stern School of Business ( email )

44 West 4th Street
9-190, MEC
New York, NY 10012-1126
United States
212-998-0711 (Phone)
212-995-4220 (Fax)

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