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The temporal evolution of mispricing in prediction markets

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  • Restocchi, Valerio
  • McGroarty, Frank
  • Gerding, Enrico

Abstract

We analyze mispricing in prediction markets, a powerful forecasting tool that harnesses the wisdom of the crowd. We show that prediction market prices exhibit mispricing, and we quantify its temporal evolution. Our results suggest that level of the FLB, averaged over the entire time period, decreases with market duration, but this changes when considering only the last trading days. In that case, we find FLB to be positively correlated with duration. We argue that this type of temporal dynamics of mispricing we observe is consistent with herding behavior.

Suggested Citation

  • Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico, 2019. "The temporal evolution of mispricing in prediction markets," Finance Research Letters, Elsevier, vol. 29(C), pages 303-307.
    • Handle: RePEc:eee:finlet:v:29:y:2019:i:c:p:303-307
    DOI: 10.1016/j.frl.2018.08.003
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    References listed on IDEAS

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    1. Erik Snowberg & Justin Wolfers, 2010. "Explaining the Favorite-Long Shot Bias: Is it Risk-Love or Misperceptions?," Journal of Political Economy, University of Chicago Press, vol. 118(4), pages 723-746, August.
    2. Ottaviani, Marco & Sørensen, Peter Norman, 2003. "Late Informed Betting and the Favourite-Longshot Bias," CEPR Discussion Papers 4092, C.E.P.R. Discussion Papers.
    3. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    4. Karen Croxson & J. James Reade, 2014. "Information and Efficiency: Goal Arrival in Soccer Betting," Economic Journal, Royal Economic Society, vol. 124(575), pages 62-91, March.
    5. Justin Wolfers & Eric Zitzewitz, 2006. "Prediction Markets in Theory and Practice," NBER Working Papers 12083, National Bureau of Economic Research, Inc.
    6. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    7. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    8. R. David Mclean & Jeffrey Pontiff, 2016. "Does Academic Research Destroy Stock Return Predictability?," Journal of Finance, American Finance Association, vol. 71(1), pages 5-32, February.
    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.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Mispricing; Prediction markets; Asset pricing; Favorite-longshot bias;
    All these keywords.

    JEL classification:

    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • G1 - Financial Economics - - General Financial Markets

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