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

Alasdair Brown, Dooruj Rambaccussing, James J. Reade, Giambattista Rossi

    Research output: Contribution to conferencePaperpeer-review


    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.
    Original languageEnglish
    Number of pages33
    Publication statusPublished - 25 Aug 2016
    EventEEA-ESEM 2016 Conference: 31th annual congress of the European Economic Association & 69th European meeting of the Econometric Society - University of Geneva, Geneva, Switzerland
    Duration: 22 Aug 201626 Aug 2016


    ConferenceEEA-ESEM 2016 Conference


    • social media
    • prediction markets
    • fundamentals
    • sentiment
    • mispricing

    ASJC Scopus subject areas

    • Economics, Econometrics and Finance(all)
    • Economics and Econometrics
    • Finance


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