More than Words: Quantifying Language to Measure Firms' Fundamentals
Paul C. Tetlock
Columbia Business School - Finance and Economics
University of Texas at Austin
Fetch Technologies, Inc
9th Annual Texas Finance Festival
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 in stock prices.
Number of Pages in PDF File: 48
Keywords: Market Efficiency, Underreaction, News Media, Qualitative Information, Language
JEL Classification: G12, G14, M41working papers series
Date posted: August 13, 2006
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