IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v29y2019icp303-307.html
   My bibliography  Save this article

The temporal evolution of mispricing in prediction markets

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612318303349
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2018.08.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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," The 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)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Siemroth, Christoph, 2014. "Why prediction markets work : The role of information acquisition and endogenous weighting," Working Papers 14-02, University of Mannheim, Department of Economics.
    2. Tai, Chung-Ching & Lin, Hung-Wen & Chie, Bin-Tzong & Tung, Chen-Yuan, 2019. "Predicting the failures of prediction markets: A procedure of decision making using classification models," International Journal of Forecasting, Elsevier, vol. 35(1), pages 297-312.
    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico, 2019. "Statistical properties of volume and calendar effects in prediction markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1150-1160.
    5. Sung, Ming-Chien & McDonald, David C.J. & Johnson, Johnnie E.V. & Tai, Chung-Ching & Cheah, Eng-Tuck, 2019. "Improving prediction market forecasts by detecting and correcting possible over-reaction to price movements," European Journal of Operational Research, Elsevier, vol. 272(1), pages 389-405.
    6. Strijbis, Oliver & Arnesen, Sveinung, 2019. "Explaining variance in the accuracy of prediction markets," International Journal of Forecasting, Elsevier, vol. 35(1), pages 408-419.
    7. Berg, Joyce E. & Rietz, Thomas A., 2019. "Longshots, overconfidence and efficiency on the Iowa Electronic Market," International Journal of Forecasting, Elsevier, vol. 35(1), pages 271-287.
    8. Yue Zhao & Difang Wan, 2018. "Institutional high frequency trading and price discovery: Evidence from an emerging commodity futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 243-270, February.
    9. Guillaume Plantin & Jean Tirole, 2018. "Marking to Market versus Taking to Market," American Economic Review, American Economic Association, vol. 108(8), pages 2246-2276, August.
    10. Romain Gauriot Author e-mail: romain.gauriot@nyu.edu & Lionel Page Author e-mail: lionel.page@uts.edu.au, 2021. "How Market Prices React to Information: Evidence from Binary Options Markets," Working Papers 20200058, New York University Abu Dhabi, Department of Social Science, revised Oct 2021.
    11. Barge-Gil, Andrés & García-Hiernaux, Alfredo, 2019. "Staking plans in sports betting under unknown true probabilities of the event," MPRA Paper 92196, University Library of Munich, Germany.
    12. Michelle B Graczyk & Sílvio M Duarte Queirós, 2017. "Intraday seasonalities and nonstationarity of trading volume in financial markets: Collective features," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-23, July.
    13. Isaac Ehrlich & Jong Kook Shin & Yong Yin, 2011. "Private Information, Human Capital, and Optimal "Home Bias" in Financial Markets," Journal of Human Capital, University of Chicago Press, vol. 5(3), pages 255-301.
    14. Zhong, Meirui & Zhang, Rui & Ren, Xiaohang, 2023. "The time-varying effects of liquidity and market efficiency of the European Union carbon market: Evidence from the TVP-SVAR-SV approach," Energy Economics, Elsevier, vol. 123(C).
    15. Isaac Ehrlich & Jong Kook Shin & Yong Yin, 2010. "Human Capital, Endogenous Information Acquisition,and Home Bias in Financial Markets," Working Papers 202010, Hong Kong Institute for Monetary Research.
    16. A. Corcos & J-P Eckmann & A. Malaspinas & Y. Malevergne & D. Sornette, 2002. "Imitation and contrarian behaviour: hyperbolic bubbles, crashes and chaos," Quantitative Finance, Taylor & Francis Journals, vol. 2(4), pages 264-281.
    17. Guglielmo Caporale & Luis Gil-Alana & Alex Plastun & Inna Makarenko, 2016. "Intraday Anomalies and Market Efficiency: A Trading Robot Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 47(2), pages 275-295, February.
    18. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, June.
    19. J. Doyne Farmer, 2002. "Market force, ecology and evolution," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 11(5), pages 895-953, November.
    20. Legge, Stefan & Schmid, Lukas, 2016. "Media attention and betting markets," European Economic Review, Elsevier, vol. 87(C), pages 304-333.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:29:y:2019:i:c:p:303-307. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.