Twitter and the US stock market: The influence of micro-bloggers on share prices

• Authors: Karl Shutes , Karen McGrath , Piotr Lis , Robert Riegler
• Languages of publication: EN

Abstracts

EN

With the increased interest in social media over recent years, the role of information disseminated through avenues such as Twitter has become more widely perceived. This paper examines the mention of stocks on the US markets (NYSE and NASDAQ) by a number of financial micro-bloggers to establish whether their posts are reflected in price movements. The Twitter feeds are selected from syndicated and non-syndicated authors. A substantial number of tweets were linked to the price movements of the mentioned assets and an event study methodology was used to ascertain whether these mentions carry any significant information or whether they are merely noise.

Keywords

EN

Twitter; social network; social media; financial markets; event studies; information

• Publisher: Uniwersytet Ekonomiczny w Poznaniu
• Journal: Economics and Business Review
• Year: 2016
• Volume: 2(16)
• Issue: 3
• Pages: 57-77

Dates

published

2016-09-30

Contributors

author

Karl Shutes

• School of Economics, Finance & Accounting, Coventry University, Priory Street, Coventry, CV1 5FB, UK

author

Karen McGrath

• Mays Business School, Texas A&M University, College Station, Texas, USA

author

Piotr Lis

• School of Economics, Finance & Accounting, Coventry University, Priory Street, Coventry, CV1 5FB, UK

author

Robert Riegler

• School of Economics, Finance & Accounting, Coventry University, Priory Street, Coventry, CV1 5FB, UK

References

• Aizenman, J., Jinjarak, Y., Lee, M. and Park, D., 2016, Developing countries’ financial vulnerability to the eurozone crisis: an event study of equity and bond markets, Journal of Economic Policy Reform, vol. 19, no. 1: 1-19.
• Będowska-Sójka, B., 2014, Intraday stealth trading: Evidence from the Warsaw Stock Exchange, Poznań University of Economics Review, vol. 14, no. 1: 5-19.
• Bollen, J., Mao, H., and Zeng, X., 2011, Twitter mood predicts the stock market, Journal of Computational Science, vol. 2, no. 1: 1-8.
• Campbell, J. Y., Lo, A. W., and Mackinlay, A. C., 1997, The econometrics of financial markets, Princeton University Press.
• Choi, H. and Varian, H., 2012, Predicting the present with Google Trends, Economic Record, vol. 88, no. 1: 2-9.
• Das, S. R. and Chen, M. Y., 2007, Yahoo! for Amazon: Sentiment extraction from small talk on the Web, Management Science, vol. 53, no. 9: 1375-1388.
• Folfas, P., 2016, Co-movements of NAFTA stock markets: Granger-causality analysis, Economics and Business Review, vol. 2(16) no. 1: 53-65.
• Gruhl, D., Guha, R., Kumar, R., Novak, J., and Tomkins, A. (eds.), 2005, The predictive power of online chatter, Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery in Data Mining: ACM.
• Java, A., Song, X., Finin, T. and Tseng, B., 2007, Why we Twitter: Understanding microblogging usage and communities, Joint 9th WEBKDD & 1st SNA-KDD Workshop ’07.
• Liu, Y., Huang, X., An, A., and Yu, X. (eds.), 2007, A sentiment-aware model for predicting sales performance using blogs, Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, ARSA.
• Mei, Q., Ling, X., Wondra, M., Su, H., and Zhai, C. (eds.), 2007, Topic sentiment mixture: Modeling facets and opinions in weblogs, Proceedings of the 16th International Conference on World Wide Web: ACM.
• Milstein, S and Lorica, B., 2008, Twitter and the micro messaging revolution, communication, connections and immediacy - 140 characters at a time, O’Reilly Media, United States.
• Mishne, G. and Glance, N. (eds.), 2006, Predicting movie sales from blogger sentiment, AAAI 2006 Spring Symposium on Computational Approaches to Analysing Weblogs.
• Nardo, M., Petracco‐Giudici, M. and Naltsidis, M., 2015, Walking Down Wall Street With A Tablet: A Survey of Stock Market Predictions Using The Web, Journal of Economic Surveys, vol. 30, no. 2: 356-369.
• O’Connor, B., Balasubramanyan, R., Routledge, B. R., and Smith, N. A. (eds.), 2010, From tweets to polls: Linking text sentiment to public opinion time series, Proceedings of the International AAAI Conference on Weblogs and Social Media.
• Porshnev, A., Redkin, I., & Shevchenko, A., 2013, Improving prediction of stock market indices by analyzing the psychological states of Twitter users, National Research University Higher School of Economics, No. WP BRP 22/FE/2013.
• Preis, T., Moat, H. S., and Stanley, H. E., 2013, Quantifying Trading Behavior in Financial Markets using Google Trends, Scientific Reports 3.
• Ranco, G., Aleksovski, D., Caldarelli, G., Grčar, M. and Mozetič, I., 2015, The effects of Twitter sentiment on stock price returns, PloS one, vol. 10, no. 9.
• Rani, N., Yadav, N.I.I. and Jain, P.K., 2015, Impact of cross-border acquisitions' announcements on shareholders' wealth: evidence from India, Global Business and Economics Review, vol. 17, no. 4:360-382.
• Santos, H.S., Laender, A.H. and Pereira, A.C., 2015, A Twitter View of the Brazilian Stock Exchange Market, E-Commerce and Web Technologies, vol. 239: 112-123.
• Si, J., Mukherjee, A., Liu, B., Li, Q., Li, H., Deng, X., 2013, Exploiting topic based Twitter sentiment for stock prediction, Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics.
• Sprenger, T. O., Tumasjan, A., Sandner, P. G., & Welpe, I. M., 2013, Tweets and trades: The information content of stock microblogs, European Financial Management, vol. 20, no. 5.
• Sul, H.K., Dennis, A.R. and Yuan, L.I., 2014, Trading on Twitter: The financial information content of emotion in social media. System Sciences (HICSS), 2014 47th Hawaii International Conference: IEEE.
• Tumarkin, R. and Whitelaw, R. F., 2001, News or noise? Internet postings and stock prices, Financial Analysts Journal, vol. 57, no. 3:41-51.
• Tumasjan, A., Sprenger, T. O., Sandner, P. G., and Welpe, I. M., 2010, Predicting elections with Twitter: What 140 characters reveal about political sentiment, ICWSM 10: 178-185.
• Wang, H., Can, D., Kazemzadeh, A., Bar, F., and Narayanan, S. (eds.), 2012, A system for real-time Twitter sentiment analysis of 2012 US Presidential Election cycle, Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, Jeju, Korea.
• Wysocki, P., 1998, Cheap talk on the web: The determinants of postings on stock message boards, University of Michigan Business School Working Paper, 98025.
• Yang, H., Zheng, Y. and Zaheer, A., 2015a, Asymmetric learning capabilities and stock market returns, Academy of Management Journal, vol. 58, no. 2: 356-374.
• Yang, S.Y., Mo, S.Y.K. and Liu, A., 2015b, Twitter financial community sentiment and its predictive relationship to stock market movement, Quantitative Finance, vol. 15, no. 10:1637-1656.
• Zhang, X., Fuehres, H., and Gloor, P. A., 2011, Predicting stock market indicators through Twitter “I Hope it is Not as Bad as I Fear”, Procedia-Social and Behavioral Sciences, vol. 26: 55-62

Identifiers

DOI

10.18559/ebr.2016.3.5