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

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

No em-dp2016-01, Economics & Management Discussion Papers from Henley Business School, Reading University

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)
New Economics Papers: this item is included in nep-mst
Date: 2016-04-10
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http://www.reading.ac.uk/web/FILES/economics/emdp2016118.pdf

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Working Paper: Using Social Media to Identify Market Inefficiencies: Evidence from Twitter and Betfair (2016) Downloads
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