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.
The definitive version of this article is available at Wiley Interscience.
Tetlock, Paul, Maytal Saar-Tsechansky, and Sofus Macskassy. "More Than Words: Quantifying Language to Measure Firms' Fundamentals." Journal of Finance 63 (June 2008): 1437-1467.
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