Prediction Markets, Social Media and Information Efficiency

39 Pages Posted: 14 Jul 2016

See all articles by Leighton Vaughan Williams

Leighton Vaughan Williams

Nottingham (Trent) Business School

J. James Reade

University of Reading, Department of Economics

Date Written: August 2016

Abstract

We consider the impact of breaking news on market prices. We measure activity on the micro‐blogging platform Twitter surrounding a unique, newsworthy and identifiable event and investigate subsequent movements of betting prices on the prominent betting exchange, Betfair. The event we use is the Bigotgate scandal, which occurred during the 2010 UK General Election campaign. We use recent developments in time series econometric methods to identify and quantify movements in both Twitter activity and Betfair prices, and compare the timings of the two. We find that the response of market prices appears somewhat sluggish and is indicative of market inefficiency, as Betfair prices adjust with a delay, and there is evidence for post‐news drift. This slow movement may be explained by the need for corroborating evidence via more traditional forms of media. Once important tweeters begin to tweet, including importantly breaking news Twitter feeds from traditional media sources, prices begin to move.

Suggested Citation

Vaughan Williams, Leighton and Reade, J. James, Prediction Markets, Social Media and Information Efficiency (August 2016). Kyklos, Vol. 69, Issue 3, pp. 518-556, 2016. Available at SSRN: https://ssrn.com/abstract=2808783 or http://dx.doi.org/10.1111/kykl.12119

Leighton Vaughan Williams (Contact Author)

Nottingham (Trent) Business School ( email )

Burton Street
NG1 4BU Nottingham
United Kingdom

J. James Reade

University of Reading, Department of Economics ( email )

Whiteknights
Reading, Berkshire RG6 6AH
United Kingdom

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