Disagreement after News: Gradual Information Diffusion or Differences of Opinion?

46 Pages Posted: 7 Aug 2016 Last revised: 21 Oct 2018

See all articles by Anastassia Fedyk

Anastassia Fedyk

University of California, Berkeley - Haas School of Business

Date Written: September 5, 2017

Abstract

This paper explores the long-standing empirical fact of increased trading volume around news releases through the lens of canonical models of gradual information diffusion and differences of opinion. I use a unique dataset of clicks on news by key finance professionals to distinguish between trading among investors who see the news at different times and trading among investors who see the same news but disagree regarding its interpretation. Consistent with gradual information diffusion, dispersion in the timing of investors' attention is strongly predictive of daily volume around earnings announcements and volume within minutes of individual news articles. Furthermore, delayed attention is predictive of minute-level return continuation, daily-level post-earnings-announcement drift, and monthly-level return momentum. Differences of opinion, measured as heterogeneity in the investors clicking on the news, is generally weaker in explaining trading volume around news, but plays a larger role when the news is more textually ambiguous.

Keywords: information diffusion, disagreement, price formation, trading volume

JEL Classification: G12, G14, G02

Suggested Citation

Fedyk, Anastassia, Disagreement after News: Gradual Information Diffusion or Differences of Opinion? (September 5, 2017). Available at SSRN: https://ssrn.com/abstract=2817087 or http://dx.doi.org/10.2139/ssrn.2817087

Anastassia Fedyk (Contact Author)

University of California, Berkeley - Haas School of Business ( email )

545 Student Services Building, #1900
2220 Piedmont Avenue
Berkeley, CA 94720
United States

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