News-Based Links and Cross-firm Return Predictability

41 Pages Posted: 14 Sep 2020 Last revised: 31 Dec 2020

See all articles by Ran Tao

Ran Tao

University of Reading - ICMA Centre

Andrew Yim

Cass Business School, City, University of London

Tian Han

University of Reading - Henley Business School

Date Written: July 1, 2020

Abstract

Applying a “co-coverage” concept to the Dow Jones Newswire articles, we propose to identify each firm’s news-based links (NBLs) and thereby construct a newsworthiness economic grouping scheme. The advantage of NBLs is to capture the up-to-date relative importance of different economic links between a base firm and its peers. We show that a base firm's share price responses persistently to the shock transmitted from its industry peers reweighted by the NBLs. Additional empirical tests show that the relative importance of those NBLs is not immediately clear to the investors and therefore is reflected sluggishly in the return shock from NBL peers to the base firms. Taken together, our results suggest that monitoring news co-coverage plays an important role in understanding the cross-firm return predictability documented in the literature.

Keywords: news co-coverage; lead-lag return momentum; investor attention; anomalies

JEL Classification: G12; G14

Suggested Citation

Tao, Ran and Yim, Andrew and Han, Tian, News-Based Links and Cross-firm Return Predictability (July 1, 2020). Available at SSRN: https://ssrn.com/abstract=3687222 or http://dx.doi.org/10.2139/ssrn.3687222

Ran Tao (Contact Author)

University of Reading - ICMA Centre ( email )

Whiteknights Park
P.O. Box 242
Reading RG6 6BA
United Kingdom

Andrew Yim

Cass Business School, City, University of London ( email )

Faculty of Finance
106 Bunhill Row
London, EC1Y 8TZ
United Kingdom

HOME PAGE: http://www.cass.city.ac.uk/faculties-and-research/experts/andrew-yim

Tian Han

University of Reading - Henley Business School ( email )

Greenlands
Reading, Henley on Thames RG6 6AH
United Kingdom

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

Paper statistics

Downloads
200
Abstract Views
805
rank
182,345
PlumX Metrics