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Long-Term Prediction Markets

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  • Werner Antweiler

Abstract

Most prediction markets focus on events with a short time horizon such as forthcoming elections. Contracts are typically traded for periods measured in weeks, but rarely exceeding a year. There is great interest in using prediction markets for events with a long time horizon such as climate change outcomes. This paper develops an analytic framework for exploring the time horizon limitations of prediction markets and suggests a simple, practical solution: the market operator must invest cash holdings in a diversified financial portfolio that generates returns that reflect individual traders’ heterogeneous attitudes towards risk and return. The analytic framework identifies how the presence of an opportunity cost for investors reduces market liquidity through a participation constraint and biases the equilibrium price through an inherent money-at-risk asymmetry between long and short positions in a prediction market. This paper explores continuous outcome markets, which are relevant for science-related long-term predictions, along with familiar winner-takes-all markets.

Suggested Citation

  • Werner Antweiler, 2012. "Long-Term Prediction Markets," Journal of Prediction Markets, University of Buckingham Press, vol. 6(3), pages 43-61.
    • Handle: RePEc:buc:jpredm:v:6:y:2012:i:3:p:43-61
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    References listed on IDEAS

    as
    1. Manski, Charles F., 2006. "Interpreting the predictions of prediction markets," Economics Letters, Elsevier, vol. 91(3), pages 425-429, June.
    2. Wolfers, Justin & Zitzewitz, Eric, 2006. "Five Open Questions About Prediction Markets," CEPR Discussion Papers 5562, C.E.P.R. Discussion Papers.
    3. Robert W. Hahn & Paul Tetlock, 2006. "Information Markets: A New Way of Making Decisions," Books, American Enterprise Institute, number 51409, September.
    4. Robin Hanson, 2003. "Combinatorial Information Market Design," Information Systems Frontiers, Springer, vol. 5(1), pages 107-119, January.
    5. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
    6. 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.
    7. 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.
    8. Stefan Luckner & Jan Schröder & Christian Slamka & Markus Franke & Andreas Geyer-Schulz & Bernd Skiera & Martin Spann & Christof Weinhardt, 2012. "Fundamentals of Prediction Markets," Springer Books, in: Prediction Markets, chapter 2, pages 6-10, Springer.
    9. Berg, Joyce E. & Nelson, Forrest D. & Rietz, Thomas A., 2008. "Prediction market accuracy in the long run," International Journal of Forecasting, Elsevier, vol. 24(2), pages 285-300.
    10. Florian Teschner & Maximilian Coblenz & Christof Weinhardt, 2011. "Short-Selling In Prediction Markets," Journal of Prediction Markets, University of Buckingham Press, vol. 5(2), pages 14-31.
    11. Stefan Luckner & Jan Schröder & Christian Slamka & Markus Franke & Andreas Geyer-Schulz & Bernd Skiera & Martin Spann & Christof Weinhardt, 2012. "Applications of Prediction Markets," Springer Books, in: Prediction Markets, chapter 4, pages 48-117, Springer.
    12. Lionel Page & Robert T. Clemen, 2013. "Do Prediction Markets Produce Well‐Calibrated Probability Forecasts?-super-," Economic Journal, Royal Economic Society, vol. 123(568), pages 491-513, May.
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    JEL classification:

    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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