Asymmetric Attention and Stock Returns

Peter Cziraki (), Jordi Mondria () and Thomas Wu
Additional contact information
Peter Cziraki: University of Toronto, Toronto, Ontario M5S 3G7, Canada;
Jordi Mondria: University of Toronto, Toronto, Ontario M5S 3G7, Canada;

Management Science, 2021, vol. 67, issue 1, 48-71

Abstract: This paper constructs a new measure of attention allocation by local investors relative to nonlocals using aggregate search volume from Google. We first present a conceptual framework in which local investors optimally choose to focus their attention on local stocks when they receive private news, leading to an asymmetric allocation of attention between local and nonlocal investors. Consistent with the main prediction of this framework, we find that firms attracting abnormally high asymmetric attention from local relative to nonlocal investors earn higher returns. A portfolio that goes long in stocks with high asymmetric attention and short in stocks with low asymmetric attention has an alpha of 32 basis points per month. The results are stronger for stocks with a greater degree of information friction. The new measure of asymmetric attention allows one to infer the arrival of unobservable private information by observing investors’ attention allocation behavior.

Keywords: limited attention; geography; asymmetric information; stock returns (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
https://doi.org/10.1287/mnsc.2019.3460 (application/pdf)

Related works:
Working Paper: Asymmetric Attention and Stock Returns (2011)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:67:y:2021:i:1:p:48-71

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().