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The Role of Speculative Trade in Market Efficiency: Evidence from a Betting Exchange

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  • Alasdair Brown
  • Fuyu Yang

Abstract

Does speculative trade reduce mispricing and help create efficient markets or does it drive prices further from fundamentals? We analyze betting exchange trading on 9,562 UK horse races in 2013 and 2014 to find out. Crucially, as each race is run, the fundamental value of bets is unambiguously revealed. We find that the volume of trade is predictive of fundamentals, suggesting that speculative trade is on average conducive to market efficiency. However, much of this effect is concentrated in the in-running period during races when, even without trade, asset fundamentals would be revealed seconds later.

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  • Alasdair Brown & Fuyu Yang, 2017. "The Role of Speculative Trade in Market Efficiency: Evidence from a Betting Exchange," Review of Finance, European Finance Association, vol. 21(2), pages 583-603.
    • Handle: RePEc:oup:revfin:v:21:y:2017:i:2:p:583-603.
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    Cited by:

    1. Cathy Yi-Hsuan Chen & Christian M. Hafner, 2019. "Sentiment-Induced Bubbles in the Cryptocurrency Market," JRFM, MDPI, vol. 12(2), pages 1-12, April.
    2. Roger, Tristan & Roger, Patrick & Willinger, Marc, 2022. "Number sense, trading decisions and mispricing: An experiment," Journal of Economic Dynamics and Control, Elsevier, vol. 135(C).
    3. Alasdair Brown & Dooruj Rambaccussing & James Reade & Giambattista Rossi, 2016. "Using Social Media to Identify Market Inefficiencies: Evidence from Twitter and Betfair," Economics Discussion Papers em-dp2016-01, Department of Economics, University of Reading.
    4. Alasdair Brown & Fuyu Yang, 2015. "Adverse Selection, Speed Bumps and Asset Market Quality," University of East Anglia Applied and Financial Economics Working Paper Series 070, School of Economics, University of East Anglia, Norwich, UK..
    5. Oliver Merz & Raphael Flepp & Egon Franck, 2019. "Does sentiment harm market efficiency? An empirical analysis using a betting exchange setting," Working Papers 381, University of Zurich, Department of Business Administration (IBW).
    6. Alasdair Brown & Fuyu Yang, 2017. "Have Betting Exchanges Corrupted Horse Racing?," Journal of Sports Economics, , vol. 18(7), pages 673-697, October.
    7. Merz, Oliver & Flepp, Raphael & Franck, Egon, 2021. "Sonic Thunder vs. Brian the Snail: Are people affected by uninformative racehorse names?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 93(C).
    8. Alasdair Brown & Fuyu Yang, 2017. "Salience and the Disposition Effect: Evidence from the Introduction of “Cash‐Outs” in Betting Markets," Southern Economic Journal, John Wiley & Sons, vol. 83(4), pages 1052-1073, April.
    9. Gonçalves, Rui & Ribeiro, Vitor Miguel & Pereira, Fernando Lobo & Rocha, Ana Paula, 2019. "Deep learning in exchange markets," Information Economics and Policy, Elsevier, vol. 47(C), pages 38-51.
    10. Alasdair Brown & Dooruj Rambaccussing & J. James Reade & Giambattista Rossi, 2016. "Using Social Media to Identify Market Ine!ciencies: Evidence from Twitter and Betfair," Working Papers 2016-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    11. Alasdair Brown & Dooruj Rambaccussing & J. James Reade & Giambattista Rossi, 2018. "Forecasting With Social Media: Evidence From Tweets On Soccer Matches," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1748-1763, July.

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    More about this item

    Keywords

    Market efficiency; Trading volume; Asset fundamentals; Betting markets;
    All these keywords.

    JEL classification:

    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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