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Using Market Prices to Predict Election Results: The 1993 UBC Election Stock Market

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  • Robert Forsythe
  • Murray Frank
  • V. Krishnamurthy
  • Thomas W. Ross

Abstract

Economists believe that markets are exceptionally efficient aggregators of information. This research tests this theory by asking whether markets can successfully predict uncertain outcomes. Specifically, the UBC Election Stock Market (UBC-ESM) was created to see if market prices could be accurate predictors of the outcome of the 1993 Canadian federal election. This paper presents the results of this experiment in which over 250 traders from across Canada and the United States participated, investing over $30,000. The structure and workings of the market are explained in some detail and the performance of the market is reviewed. The market predicted the popular vote shares of the major parties very well, but did less well at predicting the split of seats between the Liberal and Conservative parties. Coauthors are Murray Frank, Vasu Krishnamurthy, and Thomas W. Ross.

Suggested Citation

  • Robert Forsythe & Murray Frank & V. Krishnamurthy & Thomas W. Ross, 1995. "Using Market Prices to Predict Election Results: The 1993 UBC Election Stock Market," Canadian Journal of Economics, Canadian Economics Association, vol. 28(4a), pages 770-793, November.
  • Handle: RePEc:cje:issued:v:28:y:1995:i:4a:p:770-93
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    Citations

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    Cited by:

    1. Forsythe, Robert & Rietz, Thomas A. & Ross, Thomas W., 1999. "Wishes, expectations and actions: a survey on price formation in election stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 39(1), pages 83-110, May.
    2. Werner Antweiler, 2012. "Long-Term Prediction Markets," Journal of Prediction Markets, University of Buckingham Press, vol. 6(3), pages 43-61.
    3. Robert Hudson & Kevin Keasey & Mike Dempsey, 1998. "Share prices under Tory and Labour governments in the UK since 1945," Applied Financial Economics, Taylor & Francis Journals, vol. 8(4), pages 389-400.
    4. Jay Simon & Donald Saari & Donald Saari, 2020. "Interdependent Altruistic Preference Models," Decision Analysis, INFORMS, vol. 17(3), pages 189-207, September.
    5. Mongrain, Philippe & Nadeau, Richard & Jérôme, Bruno, 2021. "Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model," International Journal of Forecasting, Elsevier, vol. 37(1), pages 289-301.
    6. Berlemann, Michael, 2001. "Forecasting inflation via electronic markets: Results from a prototype market," Dresden Discussion Paper Series in Economics 06/01, Technische Universität Dresden, Faculty of Business and Economics, Department of Economics.
    7. Auld, T., 2022. "Betting and financial markets are cointegrated on election night," Cambridge Working Papers in Economics 2263, Faculty of Economics, University of Cambridge.
    8. Auld, T., 2022. "Political markets as equity price factors," Cambridge Working Papers in Economics 2264, Faculty of Economics, University of Cambridge.
    9. Berlemann, Michael & Schmidt, Carsten, 2001. "Predictive accuracy of political stock markets: Empirical evidence from an European perspective," Dresden Discussion Paper Series in Economics 05/01, Technische Universität Dresden, Faculty of Business and Economics, Department of Economics.

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