Antweiler, W., & Frank, M. Z. (2004). Is all that talk just noise? The information content of internet stock message boards. Journal of Finance, 59, 1259–1294.
Audrino, F., Sigrist, F., & Ballinari, D. (2020). The impact of sentiment and attention measures on stock market volatility. International Journal of Forecasting, 36, 334–357.
- Avery, C. N., Chevalier, J. A., & Zeckhauser, R. J. (2015). The “CAPS” prediction system and stock market returns. Review of Finance, 20, 1363–1381.
Paper not yet in RePEc: Add citation now
Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross-section of stock returns. Journal of Finance, 61, 1645–1680.
Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of Economic Perspectives, 21, 129–152.
Ballinari, D., & Behrendt, S. (2020). Structural breaks in online investor sentiment: A note on the nonstationarity of financial chatter. Finance Research Letters, 35, 101479.
- Barber, B. M., & Odean, T. (2007). All that glitters: the effect of attention and news on the buying behavior of individual and institutional investors. Review of Financial Studies, 21, 785–818.
Paper not yet in RePEc: Add citation now
Barber, B. M., Odean, T., & Zhu, N. (2009). Do retail trades move markets? Review of Financial Studies, 22, 151–186.
Barndorff-Nielsen, O. E., Hansen, P. R., Lunde, A., & Shephard, N. (2009). Realized kernels in practice: trades and quotes. Econometrics Journal, 12, C1–C32.
- Bartov, E., Faurel, L., & Mohanram, P. S. (2018). Can Twitter Help Predict Firm-Level Earnings and Stock Returns? Accounting Review, 93, 25–57.
Paper not yet in RePEc: Add citation now
Behrendt, S., & Schmidt, A. (2018). The Twitter myth revisited: Intraday investor sentiment, Twitter activity and individual-level stock return volatility. Journal of Banking and Finance, 96, 355–367.
- Boehmer, E., Jones, C. M., Zhang, X. and Zhang, X. (2020). Tracking retail investor activity, Journal of Finance, Forthcoming.
Paper not yet in RePEc: Add citation now
Carhart, M. M. (1997). On persistence in mutual fund performance. Journal of Finance, 52, 57–82.
Chen, H., De, P., Hu, Y., & Hwang, B.-H. (2014). Wisdom of crowds: the value of stock opinions transmitted through social media. Review of Financial Studies, 27, 1367–1403.
Cookson, J. A., & Niessner, M. (2020). Why don’t we agree? evidence from a social network of investors. Journal of Finance, 75, 173–228.
Da, Z., Engelberg, J., & Gao, P. (2011). In search of attention. Journal of Finance, 66, 1461–1499.
Da, Z., Engelberg, J., & Gao, P. (2015). The sum of all FEARS investor sentiment and asset prices. Review of Financial Studies, 28, 1–32.
Das, S. R. et al. (2014) Text and context: Language analytics in finance, Foundations and Trends® in Finance, 8, 145–261.
Das, S. R., & Chen, M. Y. (2007). Yahoo! for Amazon: Sentiment extraction from small talk on the web. Management Science, 53, 1375–1388.
De Long, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1990). Noise trader risk in financial markets. Journal of Political Economy, 98, 703–738.
- Deriu, J., Lucchi, A., De Luca, V., Severyn, A., Müller, S., Cieliebak, M., Hofmann, T. and Jaggi, M. (2017) Leveraging large amounts of weakly supervised data for multi-language sentiment classification, In Proceedings of the 26th international conference on world wide web, International World Wide Web Conferences Steering Committee, pp. 1045–1052.
Paper not yet in RePEc: Add citation now
Dimpfl, T., & Jank, S. (2016). Can internet search queries help to predict stock market volatility? European Financial Management, 22, 171–192.
Dougal, C., Engelberg, J., GarcÃa, D., & Parsons, C. A. (2012). Journalists and the stock market. Review of Financial Studies, 25, 639–679.
- Engelberg, J. (2008) Costly information processing: evidence from earnings announcements, AFA 2009 San Francisco Meetings Paper.
Paper not yet in RePEc: Add citation now
Engelberg, J. E., Reed, A. V., & Ringgenberg, M. C. (2012). How are shorts informed?: short sellers, news, and information processing. Journal of Financial Economics, 105, 260–278.
- Fama, E. F. (1965). The behavior of stock-market prices. Journal of Business, 38, 34–105.
Paper not yet in RePEc: Add citation now
Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3–56.
Fama, E. F., & MacBeth, J. D. (1973). Risk, return, and equilibrium: empirical tests. Journal of Political Economy, 81, 607–636.
- Felbo, B., Mislove, A., Søgaard, A., Rahwan, I. and Lehmann, S. (2017) Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm, in Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp. 1615–1625.
Paper not yet in RePEc: Add citation now
- Friedman, M. (1953). The case for flexible exchange rates. Essays in Positive Economics, 157, 203.
Paper not yet in RePEc: Add citation now
- García-Medina, A., Sandoval, L., Bañuelos, E. U., & Martínez-Argüello, A. (2018). Correlations and flow of information between the New York Times and stock markets. Physica A: Statistical Mechanics and its Applications, 502, 403–415.
Paper not yet in RePEc: Add citation now
Garcia, D. (2013). Sentiment during recessions. Journal of Finance, 68, 1267–1300.
Giannini, R., Irvine, P., & Shu, T. (2019). The convergence and divergence of investors’ opinions around earnings news: Evidence from a social network. Journal of Financial Markets, 42, 94–120.
- Guégan, D. and Renault, T. (2020). Does investor sentiment on social media provide robust information for bitcoin returns predictability?, Finance Research Letters (Forthcoming).
Paper not yet in RePEc: Add citation now
Hanley, K. W., & Hoberg, G. (2010). The information content of IPO prospectuses. Review of Financial Studies, 23, 2821–2864.
- Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer.
Paper not yet in RePEc: Add citation now
- Hernandez-Suarez, A., Sanchez-Perez, G., Toscano-Medina, K., Martinez-Hernandez, V., Sanchez, V. and Pérez-Meana, H. (2018) A web scraping methodology for bypassing Twitter API restrictions, Working Paper.
Paper not yet in RePEc: Add citation now
Hillert, A., Jacobs, H., & Müller, S. (2014). Media makes momentum. Review of Financial Studies, 27, 3467–3501.
- Hutto, C. J. and Gilbert, E. (2014) VADER: A parsimonious rule-based model for sentiment analysis of social media text, in Eighth International AAAI Conference on Weblogs and Social Media.
Paper not yet in RePEc: Add citation now
Joseph, K., Wintoki, M. B., & Zhang, Z. (2011). Forecasting abnormal stock returns and trading volume using investor sentiment: evidence from online search. International Journal of Forecasting, 27, 1116–1127.
Kearney, C., & Liu, S. (2014). Textual sentiment in finance: A survey of methods and models. International Review of Financial Analysis, 33, 171–185.
Kumar, A., & Lee, C. M. C. (2006). Retail investor sentiment and return comovements. Journal of Finance, 61, 2451–2486.
Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica, 53, 1315–1335.
Lehrer, S., Xie, T., & Zeng, T. (2019). Does high-frequency social media data improve forecasts of low-frequency consumer confidence measures? Journal of Financial Econometrics, 1–24.
Leung, H., & Ton, T. (2015). The impact of internet stock message boards on cross-sectional returns of small-capitalization stocks. Journal of Banking and Finance, 55, 37–55.
Liu, B., & McConnell, J. J. (2013). The role of the media in corporate governance: Do the media influence managers capital allocation decisions? Journal of Financial Economics, 110, 1–17.
Loughran, T., & McDonald, B. (2011). When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks. Journal of Finance, 66, 35–65.
Loughran, T., & McDonald, B. (2016). Textual analysis in accounting and finance: a survey. Journal of Accounting Research, 54, 1187–1230.
- Mahmoudi, N., Docherty, P., & Moscato, P. (2018). Deep neural networks understand investors better. Decision Support Systems, 112, 23–34.
Paper not yet in RePEc: Add citation now
Nardo, M., Petracco-Giudici, M., & Naltsidis, M. (2016). Walking down Wall Street with a tablet: a survey of stock market predictions using the web. Journal of Economic Surveys, 30, 356–369.
Newey, W. K., & West, K. D. (1987). Hypothesis testing with efficient method of moments estimation. International Economic Review, 28, 777–787.
Nofer, M., & Hinz, O. (2015). Using twitter to predict the stock market, business and information. Systems Engineering, 57, 229–242.
- Rao, T. and Srivastava, S. (2014) Twitter sentiment analysis: how to hedge your bets in the stock markets, in State of the Art Applications of Social Network Analysis, Springer International Publishing, pp. 227–247.
Paper not yet in RePEc: Add citation now
Renault, T. (2017). Intraday online investor sentiment and return patterns in the U.S. stock market. Journal of Banking and Finance, 84, 25–40.
- Renault, T. (2019). Sentiment analysis and machine learning in finance: a comparison of methods and models on one million messages. Digital Finance, 1–13.
Paper not yet in RePEc: Add citation now
Shleifer, A., & Vishny, R. W. (1997). The limits of arbitrage. Journal of Finance, 52, 35–55.
Sprenger, T. O., Sandner, P. G., Tumasjan, A., & Welpe, I. M. (2014). News or noise? Using Twitter to identify and understand company-specific news flows. Journal of Business Finance and Accounting, 41, 791–830.
Sprenger, T. O., Sandner, P. G., Tumasjan, A., & Welpe, I. M. (2014). Tweets and trades: the information content of stock microblogs. European Financial Management, 20, 926–957.
Tetlock, P. C. (2007). Giving content to investor sentiment: the role of media in the stock market. Journal of Finance, 62, 1139–1168.
Tetlock, P. C., Saar-Tsechansky, M., & Macskassy, S. (2008). More than words: Quantifying language to measure firms fundamentals. Journal of Finance, 63, 1437–1467.
Yang, S., Mo, S., & Liu, A. (2015). Twitter financial community sentiment and its predictive relationship to stock market movement. Quantitative Finance, 15, 1637–1656.