Using Social Media to Identify Market Ine!ciencies: Evidence from Twitter and Betfair

Alasdair Brown (), Dooruj Rambaccussing, J Reade and Giambattista Rossi ()
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Alasdair Brown: University of East Anglia

No 2016-002, Working Papers from The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting

Abstract: 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.

Keywords: social media; prediction markets; fundamentals; sentiment; mispricing (search for similar items in EconPapers)
JEL-codes: G14 G17 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2016-02
New Economics Papers: this item is included in nep-mst and nep-pke
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:gwc:wpaper:2016-002

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