What do we Learn from a Machine Understanding News Content? Stock Market Reaction to News

77 Pages Posted: 31 Oct 2022

See all articles by Marie Briere

Marie Briere

Amundi Asset Management; Paris Dauphine University; Université Libre de Bruxelles

Karen Huynh

Amundi Asset Management

Olav Laudy

Causality Link

Sebastien Pouget

Toulouse School of Economics

Date Written: October 19, 2022

Abstract

Using textual data extracted by Causality Link platform from a large variety of news sources (news stories, call transcripts, broker research, etc.), we build aggregate news signals that take into account the tone, the tense and the prominence of various news statements about a given firm. We test the informational content of these signals and examine how news is incorporated into stock prices. Our sample covers 1,701,789 news-based signals that were built on 4,460 US stocks over the period January 2014 to December 2021. We document large and significant market reactions around the publication of news, with some evidence of return predictability at short horizons. News about the future drives much larger reactions than news about the present or the past. Stock returns also react more to high-coverage news, fresh news and purely financial news. Finally, firms’ size matters: stocks that are not components of the Russell 1000 index experience larger reactions to news compared to those that are Russell 1000 components. Implications of our results for financial analysts and investors are offered and related to the links between news, firms’ market value and investment strategies.

Keywords: Natural Language Processing, Textual Analysis, Efficient Market Hypothesis, ESG

JEL Classification: G11, G14

Suggested Citation

Briere, Marie and Huynh, Karen and Laudy, Olav and Pouget, Sebastien, What do we Learn from a Machine Understanding News Content? Stock Market Reaction to News (October 19, 2022). Available at SSRN: https://ssrn.com/abstract=4252745 or http://dx.doi.org/10.2139/ssrn.4252745

Marie Briere (Contact Author)

Amundi Asset Management ( email )

90 Boulevard Pasteur
Paris, 75015
France

Paris Dauphine University ( email )

Université Libre de Bruxelles ( email )

Brussels
Belgium

Karen Huynh

Amundi Asset Management ( email )

90 Boulevard Pasteur
Paris, 75015
France

Olav Laudy

Causality Link ( email )

UT
United States

Sebastien Pouget

Toulouse School of Economics ( email )

21 allée de Brienne
31015 Toulouse Cedex 6
France

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
152
Abstract Views
592
Rank
306,944
PlumX Metrics