@misc{tetlock2007,
	title = {More Than Words: Quantifying Language to Measure Firms ' Fundamentals},
	author = { Tetlock},
	journal = {Journal of Finance},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/2f02e88b673ad086ca43d83a16fa1bcb9/utahell},
	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;for a brief period of time, firms ' stock prices underreact to the information embedded in negative words;the earnings and return predictability from negative words is largest for the stories that focus on firms ' 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},
	date = {forthcoming.(2)(3)}, tech = {and},
	keywords = {finance news sentiment text }
}