The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
More Than Words: Quantifying Language to Measure Firms' Fundamentals
Open accessAbstract
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.
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Cites
Common risk factors in the returns on stocks and bonds
Fama, E. F., & French, K. R. (1993) · Journal of Financial Economics · doi:10.1016/0304-405x(93)90023-5 · Cited by 25,754
On Persistence in Mutual Fund Performance
Carhart, M. M. (1997) · The Journal of Finance · doi:10.1111/j.1540-6261.1997.tb03808.x · Cited by 17,283
Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency
JEGADEESH, N., & TITMAN, S. (1993) · The Journal of Finance · doi:10.1111/j.1540-6261.1993.tb04702.x · Cited by 11,584
Biases in dynamic models with fixed effects
Nickell, S. (1981) · Econometrica · doi:10.2307/1911408 · Cited by 8,735
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Giving content to investor sentiment: The role of media in the stock market
TETLOCK, P. C. (2007) · The Journal of Finance · doi:10.1111/j.1540-6261.2007.01232.x · Cited by 4,827
Self-citationNegativity Bias, Negativity Dominance, and Contagion
Rozin, P., & Royzman, E. B. (2001) · Personality and Social Psychology Review · doi:10.1207/s15327957pspr0504_2 · Cited by 4,342
On the impossibility of informationally efficient markets
Stiglitz, J. E., & Grossman, S. J. (1980) · Columbia University · doi:10.7916/d8765r99 · Cited by 3,645
Cited by
When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks
LOUGHRAN, T., & MCDONALD, B. (2011) · The Journal of Finance · doi:10.1111/j.1540-6261.2010.01625.x · Cited by 6,015
The Sum of All FEARS Investor Sentiment and Asset Prices
Da, Z., Engelberg, J., & Gao, P. (2015) · Review of Financial Studies · doi:10.1093/rfs/hhu072 · Cited by 1,379
Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media
Chen, H., De, P., Hu, Y. (., & Hwang, B.-H. (2014) · Review of Financial Studies · doi:10.1093/rfs/hhu001 · Cited by 1,251
The Causal Impact of Media in Financial Markets
ENGELBERG, J. E., & PARSONS, C. A. (2011) · The Journal of Finance · doi:10.1111/j.1540-6261.2010.01626.x · Cited by 1,121
What can big data and text analytics tell us about hotel guest experience and satisfaction?
Xiang, Z., Schwartz, Z., Gerdes, J. H., & Uysal, M. (2015) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2014.10.013 · Cited by 953
Metadata
- Authors
- TETLOCK, P. C., SAAR‐TSECHANSKY, M., & MACSKASSY, S.
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 2008-05-09
- Volume
- 63
- Issue
- 3
- Pages
- 1437-1467
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W3122563224
- Cited by
- 2,304
- References
- 8
- FWCI
- 95.65
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
