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The behaviour of betting and currency markets on the night of the EU referendum

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  • Tom Auld
  • Oliver Linton

Abstract

We study the behaviour of the Betfair betting market and the sterling/dollar exchange rate (futures price) during 24 June 2016, the night of the EU referendum. We investigate how the two markets responded to the announcement of the voting results. We employ a Bayesian updating methodology to update prior opinion about the likelihood of the final outcome of the vote. We then relate the voting model to the real time evolution of the market determined prices as results are announced. We find that although both markets appear to be inefficient in absorbing the new information contained in vote outcomes, the betting market is apparently less inefficient than the FX market. The different rates of convergence to fundamental value between the two markets leads to highly profitable arbitrage opportunities.

Suggested Citation

  • Tom Auld & Oliver Linton, 2018. "The behaviour of betting and currency markets on the night of the EU referendum," Monash Econometrics and Business Statistics Working Papers 10/18, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:2018-10
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    Cited by:

    1. Wiśniowski, Arkadiusz & Bijak, Jakub & Forster, Jonathan J. & Smith, Peter W.F., 2019. "Hierarchical model for forecasting the outcomes of binary referenda," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 90-103.
    2. Manamba Epaphra & Khatibu Kazungu, 2021. "Efficiency of Tanzania's foreign exchange market," African Development Review, African Development Bank, vol. 33(2), pages 368-381, June.
    3. Erdinc Akyildirim & Oguzhan Cepni & Shaen Corbet & Gazi Salah Uddin, 2023. "Forecasting mid-price movement of Bitcoin futures using machine learning," Annals of Operations Research, Springer, vol. 330(1), pages 553-584, November.
    4. Wael Bousselmi & Patrick Sentis & Marc Willinger, 2018. "Impact of the Brexit vote announcement on long-run market performance," CEE-M Working Papers hal-01954920, CEE-M, Universtiy of Montpellier, CNRS, INRA, Montpellier SupAgro.
    5. Facundo Albornoz & Jake Bradley & Silvia Sonderegger, 2020. "The Brexit referendum and the rise in hate crime; conforming to the new norm," Discussion Papers 2020-06, Nottingham Interdisciplinary Centre for Economic and Political Research (NICEP).
    6. Auld, T., 2022. "Betting and financial markets are cointegrated on election night," Cambridge Working Papers in Economics 2263, Faculty of Economics, University of Cambridge.
    7. Facundo Albornoz & Jake Bradley & Silvia Sonderegger, 2022. "Updating the Social Norm: the Case of Hate Crime after the Brexit Referendum," Working Papers 203, Red Nacional de Investigadores en Economía (RedNIE).
    8. Paolo Manasse & Graziano Moramarco & Giulio Trigilia, 2024. "Exchange rates and political uncertainty: the Brexit case," Economica, London School of Economics and Political Science, vol. 91(362), pages 621-652, April.

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    Keywords

    EU referendum; prediction markets; machine learning; efficient markets hypothesis; pairs trading; cointegration; Bayesian methods; exchange rates.;
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