Prediction Markets, Social Media and Information Efficiency

Vaughan Williams, L. ORCID: 0000-0002-9639-9217 and Reade, J.J., 2016. Prediction Markets, Social Media and Information Efficiency. Kyklos, 69 (3), pp. 518-556. ISSN 0023-5962

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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, Bet- fair. 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.

Item Type:	Journal article
Publication Title:	Kyklos
Creators:	Vaughan Williams, L. and Reade, J.J.
Publisher:	Wiley-Blackwell
Date:	August 2016
Volume:	69
Number:	3
ISSN:	0023-5962
Identifiers:	Number Type 10.1111/kykl.12119 DOI
Divisions:	Schools > Nottingham Business School
Record created by:	Jonathan Gallacher
Date Added:	15 Dec 2016 09:07
Last Modified:	12 Jul 2018 03:00
URI:	https://irep.ntu.ac.uk/id/eprint/29386

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