When Machines Read the Web: Market Efficiency and Costly Information Acquisition at the Intraday Level

37 Pages Posted: 4 Jun 2018

See all articles by Roland L. Gillet

Roland L. Gillet

Université Paris I Panthéon-Sorbonne

Thomas Renault

Université Paris I Panthéon-Sorbonne - Laboratoire PRISM; Catholic University of Lille - IESEG School of Management

Date Written: May 24, 2018

Abstract

We investigate the efficient market hypothesis at the intraday level by analyzing market reactions to negative tweets and reports published on the Internet by an activist short-seller. Conducting event-studies, we find that fast-moving traders can generate small, but albeit significant, abnormal profit by trading on public information published on social media. The market reaction to tweets is stronger when a company is mentioned for the first time on Twitter, showing that investors are able to disentangle new information from noise in real time. We also find that traders who manage to identify the information on the short-seller's website before the dissemination of the same news on Twitter can generate much greater abnormal returns. As acquiring information on a website is more costly and difficult than acquiring the same information on Twitter, our findings provide empirical evidence supporting the Grossman-Stiglitz paradox at the intraday level. Very short-lived market anomalies do exist in the stock market to compensate investors who spent time and money setting up bots and algorithms to trade on new information before the crowd.

Keywords: Market Efficiency, Intraday Analysis, Costly Information Acquisition, Event-Study, Twitter, Short-Seller

JEL Classification: G12, G14

Suggested Citation

Gillet, Roland L. and Renault, Thomas, When Machines Read the Web: Market Efficiency and Costly Information Acquisition at the Intraday Level (May 24, 2018). Available at SSRN: https://ssrn.com/abstract=3189991 or http://dx.doi.org/10.2139/ssrn.3189991

Roland L. Gillet

Université Paris I Panthéon-Sorbonne ( email )

12, place du Panthéon
Paris, IL
France

Thomas Renault (Contact Author)

Université Paris I Panthéon-Sorbonne - Laboratoire PRISM ( email )

17 rue de la Sorbonne
Paris, 75005
France

Catholic University of Lille - IESEG School of Management ( email )

Socle de la Grande Arche
1 Parvis de la Defense
Puteaux, Paris 92800
France

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