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References (29)
-
Fama Fama, French French (1993)
Common risk factors in the returns of stocks and bondsJournal of Financial Economics, 33
-
Newey Newey, West West (1987)
A simple positive semi‐definite, heteroskedasticity and autocorrelation consistent covariance matrix estimatorEconometrica, 55
-
Antweiler (2004)
Is all that talk just noise? The information content of Internet stock message boardsJournal of Finance, 59
-
Tetlock Tetlock (2007)
Giving content to investor sentiment: The role of media in the stock marketJournal of Finance, 62
-
Fama Fama, French French (1992)
The cross‐section of expected stock returnsJournal of Finance, 47
-
Campbell Campbell, Shiller Shiller (1987)
Cointegration and tests of present value modelsJournal of Political Economy, 95
-
Shiller Shiller (1981)
Do stock prices move too much to be justified by subsequent changes in dividendsAmerican Economic Review, 71
-
Fama Fama (1998)
Market efficiency, long‐term returns, and behavioral financeJournal of Financial Economics, 49
-
Froot Froot (1989)
Consistent covariance matrix estimation with cross‐sectional dependence and heteroskedasticity in financial dataJournal of Financial and Quantitative Analysis, 24
-
Grossman Grossman, Stiglitz Stiglitz (1980)
On the impossibility of informationally efficient marketsAmerican Economic Review, 70
-
Abarbanell (1992)
Tests of analysts' overreaction/underreaction to earnings information as an explanation for anomalous stock price behaviorJournal of Finance, 47
-
Chan Chan (2003)
Stock price reaction to news and no‐news: Drift and reversal after headlinesJournal of Financial Economics, 70
-
De Bondt De Bondt, Thaler Thaler (1990)
Do security analysts overreactAmerican Economic Review, 80
-
Easterwood Easterwood, Nutt Nutt (1999)
Inefficiency in analysts' earnings forecasts: Systematic misreaction or systematic optimismJournal of Finance, 54
-
Cutler Cutler, Poterba Poterba, Summers Summers (1989)
What moves stock pricesJournal of Portfolio Management, 15
-
Chan Chan, Jegadeesh Jegadeesh, Lakonishok Lakonishok (1996)
Momentum strategiesJournal of Finance, 51
-
Daniel Daniel, Grinblatt Grinblatt, Titman Titman, Wermers Wermers (1997)
Measuring mutual fund performance with characteristic‐based benchmarksJournal of Finance, 52
-
Ball Ball, Brown Brown (1968)
An empirical examination of accounting numbersJournal of Accounting Research, 6
-
Carhart Carhart (1997)
On the persistence of mutual fund performanceJournal of Finance, 52
-
Jegadeesh Jegadeesh, Titman Titman (1993)
Returns to buying winners and selling losers: Implications for stock market efficiencyJournal of Finance, 48
-
Shleifer Shleifer (1986)
Do demand curves for stocks slope downJournal of Finance, 41
-
Roll Roll (1988)
R‐squaredJournal of Finance, 43
-
Pritamani Pritamani, Singal Singal (2001)
Return predictability following large price changes and information releasesJournal of Banking and Finance, 25
-
Rozin Rozin, Royzman Royzman (2001)
Negativity bias, negativity dominance, and contagionPersonality and Social Psychology Review, 5
-
Baumeister Baumeister, Bratslavsky Bratslavsky, Finkenauer Finkenauer, Vohs Vohs (2001)
Bad is stronger than goodReview of General Psychology, 5
-
Bernard Bernard, Thomas Thomas (1989)
Post‐earnings‐announcement drift: Delayed price response or risk premiumJournal of Accounting Research, 27
-
Nickell Nickell (1981)
Biases in dynamic models with fixed effectsEconometrica, 49
-
White White (1980)
A heteroskedasticity‐consistent covariance matrix and a direct test for heteroskedasticityEconometrica, 48
-
Fama Fama, MacBeth MacBeth (1973)
Risk and return: Some empirical testsJournal of Political Economy, 81
- Publisher
- Wiley
- Copyright
- © American Finance Association
- ISSN
- 0022-1082
- eISSN
- 1540-6261
- DOI
- 10.1111/j.1540-6261.2008.01362.x
- Publisher site
- See Article on Publisher Site
Abstract
ABSTRACT We examine whether a simple quantitative measure of language can be used to predict individual firms' accounting earnings and stock returns. Our three main findings are: (1) the fraction of negative words in firm‐specific news stories forecasts low firm earnings; (2) firms' stock prices briefly underreact to the information embedded in negative words; and (3) the earnings and return predictability from negative words is largest for the stories that focus on fundamentals. Together these findings suggest that linguistic media content captures otherwise hard‐to‐quantify aspects of firms' fundamentals, which investors quickly incorporate into stock prices.
Journal
The Journal of Finance – Wiley
Published: Jun 1, 2008