IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this paper

Using Social Media to Identify Market Inefficiencies: Evidence from Twitter and Betfair

Listed author(s):
  • Alasdair Brown

    ()

    (School of Economics, University of East Anglia)

  • Dooruj Rambaccussing

    ()

    (Economic Studies, University of Dundee)

  • James Reade

    ()

    (Department of Economics, University of Reading)

  • Giambattista Rossi

    ()

    (Department of Management, Birkbeck, University of London)

Information extracted from social media has been used by academics, and increasingly by practitioners, to predict stock returns. But to what extent does social media output predict asset fundamentals, and not simply short-term returns? In this paper we analyse 13.8m posts on Twitter, and high-frequency betting data from Betfair, concerning English Premier League soccer matches in 2013/14. Crucially, asset fundamentals are revealed at the end of play. We find that the tweets of certain journalists, and the tone of all tweets, contain fundamental information not revealed in betting prices. In particular, tweets aid in the interpretation of news during matches.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.reading.ac.uk/web/FILES/economics/emdp2016118.pdf
Download Restriction: no

Paper provided by Henley Business School, Reading University in its series Economics & Management Discussion Papers with number em-dp2016-01.

as
in new window

Length: 35 pages
Date of creation: 10 Apr 2016
Handle: RePEc:rdg:emxxdp:em-dp2016-01
Contact details of provider: Postal:
PO Box 218, Whiteknights, Reading, Berks, RG6 6AA

Phone: +44 (0) 118 378 8226
Fax: +44 (0) 118 975 0236
Web page: http://www.henley.reading.ac.uk/

More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as
in new window


  1. Erik Snowberg & Justin Wolfers, 2010. "Explaining the Favorite-Long Shot Bias: Is it Risk-Love or Misperceptions?," Journal of Political Economy, University of Chicago Press, vol. 118(4), pages 723-746, 08.
  2. Alasdair Brown & Fuyu Yang, 2014. "The Role of Speculative Trade in Market Efficiency: Evidence from a Betting Exchange," University of East Anglia Applied and Financial Economics Working Paper Series 068, School of Economics, University of East Anglia, Norwich, UK..
  3. Leighton Vaughan Williams & J. James Reade, 2016. "Forecasting Elections," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(4), pages 308-328, 07.
  4. Avery, Christopher & Chevalier, Judith & Zeckhauser, Richard, 2009. "The "CAPS" Prediction System and Stock Market Returns," Working Paper Series rwp09-011, Harvard University, John F. Kennedy School of Government.
  5. Karen Croxson & J. James Reade, 2014. "Information and Efficiency: Goal Arrival in Soccer Betting," Economic Journal, Royal Economic Society, vol. 124(575), pages 62-91, 03.
  6. Paul C. Tetlock, 2011. "All the News That's Fit to Reprint: Do Investors React to Stale Information?," Review of Financial Studies, Society for Financial Studies, vol. 24(5), pages 1481-1512.
  7. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
  8. Williams, Leighton Vaughan & Paton, David, 1997. "Why Is There a Favourite-Longshot Bias in British Racetrack Betting Markets?," Economic Journal, Royal Economic Society, vol. 107(440), pages 150-158, January.
  9. Alex Edmans & Diego García & Øyvind Norli, 2007. "Sports Sentiment and Stock Returns," Journal of Finance, American Finance Association, vol. 62(4), pages 1967-1998, 08.
  10. Ali, Mukhtar M, 1977. "Probability and Utility Estimates for Racetrack Bettors," Journal of Political Economy, University of Chicago Press, vol. 85(4), pages 803-815, August.
  11. Leighton Vaughan Williams & James Reade, 2014. "Prediction Markets, Twitter and Bigotgate," Economics & Management Discussion Papers em-dp2014-09, Henley Business School, Reading University.
  12. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, 06.
  13. Snyder, Wayne W, 1978. "Horse Racing: Testing the Efficient Markets Model," Journal of Finance, American Finance Association, vol. 33(4), pages 1109-1118, September.
  14. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
  15. Eric K. Kelley & Paul C. Tetlock, 2013. "How Wise Are Crowds? Insights from Retail Orders and Stock Returns," Journal of Finance, American Finance Association, vol. 68(3), pages 1229-1265, 06.
  16. Martin Spann & Bernd Skiera, 2009. "Sports forecasting: a comparison of the forecast accuracy of prediction markets, betting odds and tipsters," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 55-72.
  17. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, 02.
  18. Hailiang Chen & Prabuddha De & Yu (Jeffrey) Hu & Byoung-Hyoun Hwang, 2014. "Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media," Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1367-1403.
  19. Paul W. Rhode & Koleman S. Strumpf, 2004. "Historical Presidential Betting Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 127-141, Spring.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:rdg:emxxdp:em-dp2016-01. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marie Pearson)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.