Media Content and Stock Returns: The Predictive Power of Press

Multinational Finance Journal, Forthcoming

Midwest Finance Association 2013 Annual Meeting Paper

29 Pages Posted: 18 Jul 2012 Last revised: 23 Nov 2014

See all articles by Nicky J. Ferguson

Nicky J. Ferguson

University of Cambridge - Judge Business School

Dennis Philip

Durham University Business School

Herbert Lam

Renmin University of China - School of Finance

Jie (Michael) Guo

Durham Business School

Multiple version iconThere are 2 versions of this paper

Date Written: November 1, 2014

Abstract

This paper examines whether tone (positive and negative) and volume of firm-specific news media content provide valuable information about future stock returns, using UK news media data from 1981–2010. The results indicate that both tone and volume of news media content significantly predict next period abnormal returns, with the impact of volume more pronounced than tone. Additionally, the predictive power of tone is found to be stronger among lower visibility firms. Further, the paper finds evidence of an attention-grabbing effect for firm-specific news stories with high media coverage, mainly seen among larger firms. A simple news-based trading strategy produces statistically significant risk-adjusted returns of 14.2 to 19 basis points in the period 2003–2010. At the aggregate level, price pressure induced by semantics in news stories is corrected only in part by subsequent reversals. Overall, the findings suggest firm-specific news media content incorporates valuable information that predicts asset returns.

Keywords: news media, stock returns, textual analysis, news-based trading strategy

JEL Classification: G1, G14, G17

Suggested Citation

Ferguson, Nicky J. and Philip, Dennis and Lam, Herbert and Guo, Jie Michael, Media Content and Stock Returns: The Predictive Power of Press (November 1, 2014). Multinational Finance Journal, Forthcoming, Midwest Finance Association 2013 Annual Meeting Paper, Available at SSRN: https://ssrn.com/abstract=2111352 or http://dx.doi.org/10.2139/ssrn.2111352

Nicky J. Ferguson

University of Cambridge - Judge Business School ( email )

Trumpington Street
Cambridge, CB2 1AG
United Kingdom

Dennis Philip (Contact Author)

Durham University Business School ( email )

Mill Hill Lane
Mill Hill Lane
Durham, DH13LB
United Kingdom

Herbert Lam

Renmin University of China - School of Finance ( email )

Ming De Main Building
Renmin University of China
Beijing, Beijing 100872
China

Jie Michael Guo

Durham Business School ( email )

Old Elvet
Mill Hill Lane
Durham, Durham DH1 3HP
United Kingdom

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