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Time Variation in the News–Returns Relationship

Published online by Cambridge University Press:  15 November 2023

Paul Glasserman ,
Fulin Li  and
Harry Mamaysky Open the ORCID record for Harry Mamaysky [Opens in a new window]
Paul Glasserman
Affiliation:
Columbia University Business School pg20@columbia.edu
Fulin Li
Affiliation:
Texas A&M University Business School fli3@mays.tamu.edu
Harry Mamaysky*
Affiliation:
Columbia University Business School
*
hm2646@columbia.edu (corresponding author)
Rights & Permissions [Opens in a new window]

Abstract

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The speed of stock price reaction to news exhibits substantial time variation. Higher risk-bearing capacity of financial intermediaries, lower passive ownership of stocks, and more informative news increase price responses to contemporaneous news; surprisingly, these interaction variables also increase price responses to lagged news (underreaction). A simple model with limited attention and three investor types (institutional, noninstitutional, and passive) predicts the observed variation in news responses. A long–short trading strategy based on news sentiment earns high returns, which increase when conditioning on the interaction variables. The interactions we document are robust to the choice of news source.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , First View , pp. 1 - 37
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

Footnotes

We thank an anonymous referee, Hendrik Bessembinder (the editor), Zhiguo He, John Heaton, Ralph Koijen, Lubos Pastor, and seminar participants at Baruch College, Chicago Booth, Columbia University, Cornerstone Research, De Nederlandsche Bank, the Society of Quantitative Analysts, the University of Maryland, and Yale University for helpful comments and suggestions. We thank Patrick Wu for valuable research assistance and the Financial Times for providing their news archive for this study.

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