Journal Article10.1111/J.1540-6261.2008.01362.X
More Than Words: Quantifying Language to Measure Firms' Fundamentals
TL;DR: The authors examined whether a simple quantitative measure of language can be used to predict individual firms' accounting earnings and stock returns and found that the fraction of negative words in firm-specific news stories predicts low firm earnings.
read more
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. Language is conceived in sin and science is its redemption
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks
Tim Loughran,Bill McDonald +1 more
TL;DR: In this paper, the authors show that word lists developed for other disciplines misclassify common words in financial text and develop an alternative negative word list, along with five other word lists, that better reflect tone of financial text.
Textual Analysis in Accounting and Finance: A Survey
Tim Loughran,Bill McDonald +1 more
TL;DR: In this paper, the authors describe the nuances of the textual analysis and some of the tripwires in implementation and highlight the contemporary textual analysis literature and highlight areas of future research.
1.6K
Media Coverage and the Cross‐section of Stock Returns
Lily H. Fang,Joel Peress +1 more
TL;DR: The authors investigated the cross-sectional relation between media coverage and expected stock returns and found that stocks with no media coverage earn higher returns than stocks with high media coverage even after controlling for well-known risk factors.
1.5K
Text-Based Network Industries and Endogenous Product Differentiation
Gerard Hoberg,Gordon M. Phillips +1 more
TL;DR: The authors study how firms differ from their competitors using new time-varying measures of product similarity based on text-based analysis of firm 10-K product descriptions and find evidence that firm R&D and advertising are associated with subsequent differentiation from competitors.
Product Market Synergies and Competition in Mergers and Acquisitions: A Text-Based Analysis
Gerard Hoberg,Gordon M. Phillips +1 more
TL;DR: The authors use text-based analysis of 10-K product descriptions to examine whether firms exploit product market synergies through asset complementarities in mergers and acquisitions, and find that transactions are more likely between firms that use similar product market language.
References
Common risk factors in the returns on stocks and bonds
Eugene F. Fama,Kenneth R. French +1 more
TL;DR: In this article, the authors identify five common risk factors in the returns on stocks and bonds, including three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity.
29.7K
A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity
TL;DR: In this article, a parameter covariance matrix estimator which is consistent even when the disturbances of a linear regression model are heteroskedastic is presented, which does not depend on a formal model of the structure of the heteroSkewedness.
28K
A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix
Whitney K. Newey,Kenneth D. West +1 more
TL;DR: In this article, a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction is described.
On Persistence in Mutual Fund Performance
TL;DR: Using a sample free of survivor bias, this paper showed that common factors in stock returns and investment expenses almost completely explain persistence in equity mutual fund's mean and risk-adjusted returns.
Risk, Return, and Equilibrium: Empirical Tests
Eugene F. Fama,James D. MacBeth +1 more
TL;DR: In this article, the relationship between average return and risk for New York Stock Exchange common stocks was tested using a two-parameter portfolio model and models of market equilibrium derived from the two parameter portfolio model.