IDEAS home Printed from https://ideas.repec.org/a/ecj/econjl/v123y2013i568p491-513.html
   My bibliography  Save this article

Do Prediction Markets Produce Well‐Calibrated Probability Forecasts?-super-

Author

Listed:
  • Lionel Page
  • Robert T. Clemen

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
  • Handle: RePEc:ecj:econjl:v:123:y:2013:i:568:p:491-513
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Jan Hansen & Carsten Schmidt & Martin Strobel, 2004. "Manipulation in political stock markets - preconditions and evidence," Applied Economics Letters, Taylor & Francis Journals, vol. 11(7), pages 459-463.
    2. Manski, Charles F., 2006. "Interpreting the predictions of prediction markets," Economics Letters, Elsevier, vol. 91(3), pages 425-429, June.
    3. Enrico Diecidue & Ulrich Schmidt & Peter P. Wakker, 2004. "The Utility of Gambling Reconsidered," Journal of Risk and Uncertainty, Springer, vol. 29(3), pages 241-259, December.
    4. Russell Sobel & S. Travis Raines, 2003. "An examination of the empirical derivatives of the favourite-longshot bias in racetrack betting," Applied Economics, Taylor & Francis Journals, vol. 35(4), pages 371-385.
    5. Ali, Mukhtar M, 1977. "Probability and Utility Estimates for Racetrack Bettors," Journal of Political Economy, University of Chicago Press, vol. 85(4), pages 803-815, August.
    6. Steffen Andersen & Glenn W. Harrison & Morten I. Lau & E. Elisabet Rutström, 2008. "Eliciting Risk and Time Preferences," Econometrica, Econometric Society, vol. 76(3), pages 583-618, May.
    7. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    8. Robin Hanson & Ryan Oprea, 2009. "A Manipulator Can Aid Prediction Market Accuracy," Economica, London School of Economics and Political Science, vol. 76(302), pages 304-314, April.
    9. Bruno Jullien & Bernard Salanie, 2000. "Estimating Preferences under Risk: The Case of Racetrack Bettors," Journal of Political Economy, University of Chicago Press, vol. 108(3), pages 503-530, June.
    10. Terrell, Dek, 1998. "Biases in Assessments of Probabilities: New Evidence from Greyhound Races," Journal of Risk and Uncertainty, Springer, vol. 17(2), pages 151-166, November.
    11. Joseph Golec & Maurry Tamarkin, 1998. "Bettors Love Skewness, Not Risk, at the Horse Track," Journal of Political Economy, University of Chicago Press, vol. 106(1), pages 205-225, February.
    12. Craig R. Fox & Robert T. Clemen, 2005. "Subjective Probability Assessment in Decision Analysis: Partition Dependence and Bias Toward the Ignorance Prior," Management Science, INFORMS, vol. 51(9), pages 1417-1432, September.
    13. Härdle,Wolfgang, 1992. "Applied Nonparametric Regression," Cambridge Books, Cambridge University Press, number 9780521429504.
    14. Marco Ottaviani & Peter Norman Sørensen, 2009. "Surprised by the Parimutuel Odds?," American Economic Review, American Economic Association, vol. 99(5), pages 2129-2134, December.
    15. Snyder, Wayne W, 1978. "Horse Racing: Testing the Efficient Markets Model," Journal of Finance, American Finance Association, vol. 33(4), pages 1109-1118, September.
    16. Kenneth Oliven & Thomas A. Rietz, 2004. "Suckers Are Born but Markets Are Made: Individual Rationality, Arbitrage, and Market Efficiency on an Electronic Futures Market," Management Science, INFORMS, vol. 50(3), pages 336-351, March.
    17. Michael Cain & David Law & David Peel, 2002. "Is one price enough to value a state-contingent asset correctly? Evidence from a gambling market," Applied Financial Economics, Taylor & Francis Journals, vol. 12(1), pages 33-38.
    18. Hanson, Robin & Oprea, Ryan & Porter, David, 2006. "Information aggregation and manipulation in an experimental market," Journal of Economic Behavior & Organization, Elsevier, vol. 60(4), pages 449-459, August.
    19. Bird, Ron & McCrae, Michael & Beggs, John J, 1987. "Are Gamblers Really Risk Takers?," Australian Economic Papers, Wiley Blackwell, vol. 26(49), pages 237-253, December.
    20. Jed D. Christiansen, 2007. "Prediction Markets: Practical Experiments in Small Markets and Behaviours Observed," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 17-41, February.
    21. Marco Ottaviani & Peter Norman Sørensen, 2007. "Outcome Manipulation in Corporate Prediction Markets," Journal of the European Economic Association, MIT Press, vol. 5(2-3), pages 554-563, 04-05.
    22. Thaler, Richard H & Ziemba, William T, 1988. "Parimutuel Betting Markets: Racetracks and Lotteries," Journal of Economic Perspectives, American Economic Association, vol. 2(2), pages 161-174, Spring.
    23. Rubinstein, Mark, 1976. "The Strong Case for the Generalized Logarithmic Utility Model as the Premier Model of Financial Markets," Journal of Finance, American Finance Association, vol. 31(2), pages 551-571, May.
    24. Les Coleman, 2004. "New light on the longshot bias," Applied Economics, Taylor & Francis Journals, vol. 36(4), pages 315-326.
    25. Williams, Leighton Vaughan & Paton, David, 1997. "Why Is There a Favourite-Longshot Bias in British Racetrack Betting Markets?," Economic Journal, Royal Economic Society, vol. 107(440), pages 150-158, January.
    26. Paul Rhode & Koleman Strumpf, 2006. "Manipulating political stock markets: A field experiment and a century of observational data," Natural Field Experiments 00325, The Field Experiments Website.
    27. Busche, Kelly & Hall, Christopher D, 1988. "An Exception to the Risk Preference Anomaly," The Journal of Business, University of Chicago Press, vol. 61(3), pages 337-346, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. He, Xue-Zhong & Treich, Nicolas, 2017. "Prediction market prices under risk aversion and heterogeneous beliefs," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 105-114.
    2. Werner Antweiler, 2012. "Long-Term Prediction Markets," Journal of Prediction Markets, University of Buckingham Press, vol. 6(3), pages 43-61.
    3. Romain Gauriot Author e-mail: romain.gauriot@nyu.edu & Lionel Page Author e-mail: lionel.page@uts.edu.au, 2020. "How Market Prices React to Information: Evidence from a Natural Experiment," Working Papers 20200058, New York University Abu Dhabi, Department of Social Science, revised Oct 2020.
    4. Dean Foster & Rakesh Vohra, 2011. "Calibration: Respice, Adspice, Prospice," Discussion Papers 1537, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    5. Marco Ottaviani & Peter Norman Sørensen, 2015. "Price Reaction to Information with Heterogeneous Beliefs and Wealth Effects: Underreaction, Momentum, and Reversal," American Economic Review, American Economic Association, vol. 105(1), pages 1-34, January.
    6. Ruiz-Buforn, Alba & Alfarano, Simone & Camacho-Cuena, Eva & Morone, Andrea, 2020. "Single vs. multiple disclosures in an experimental asset market with information acquisition," MPRA Paper 101035, University Library of Munich, Germany.
    7. 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.
    8. Page, Lionel & Siemroth, Christoph, 2017. "An experimental analysis of information acquisition in prediction markets," Games and Economic Behavior, Elsevier, vol. 101(C), pages 354-378.
    9. Mark Richard & Jan Vecer, 2021. "Efficiency Testing of Prediction Markets: Martingale Approach, Likelihood Ratio and Bayes Factor Analysis," Risks, MDPI, Open Access Journal, vol. 9(2), pages 1-20, February.
    10. Edward Halim & Yohanes E. Riyanto & Nilanjan Roy, 2019. "Costly Information Acquisition, Social Networks, and Asset Prices: Experimental Evidence," Journal of Finance, American Finance Association, vol. 74(4), pages 1975-2010, August.
    11. Michael D. Lee & Megan N. Lee, 2017. "The relationship between crowd majority and accuracy for binary decisions," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 12(4), pages 328-343, July.
    12. Lionel Page & Christoph Siemroth, 2018. "How much information is incorporated in financial asset prices? Experimental Evidence," QuBE Working Papers 054, QUT Business School.
    13. Jason Dana & Pavel Atanasov & Philip Tetlock & Barbara Mellers, 2019. "Are markets more accurate than polls? The surprising informational value of “just askingâ€," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 14(2), pages 135-147, March.
    14. Ahrash Dianat & Christoph Siemroth, 2021. "Improving decisions with market information: an experiment on corporate prediction markets," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 143-176, March.
    15. Ho Cheung Brian Lee & Jan Stallaert & Ming Fan, 2020. "Anomalies in Probability Estimates for Event Forecasting on Prediction Markets," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2077-2095, September.
    16. Schneider, Mark, 2020. "A bias aggregation theorem," Economics Letters, Elsevier, vol. 196(C).
    17. Zhao, Yang & Yu, Min-Teh, 2020. "Predicting catastrophe risk: Evidence from catastrophe bond markets," Journal of Banking & Finance, Elsevier, vol. 121(C).
    18. Giovanni Angelini & Luca De Angelis & Carl Singleton, 2019. "Informational efficiency and behaviour within in-play prediction markets," Economics Discussion Papers em-dp2019-20, Department of Economics, Reading University.

    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. Stefan Winter & Martin Kukuk, 2008. "Do horses like vodka and sponging? - On market manipulation and the favourite-longshot bias," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 75-87.
    2. Martin Kukuk & Stefan Winter, 2008. "An Alternative Explanation of the Favorite-Longshot Bias," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 2(2), pages 79-96, September.
    3. Erik Snowberg & Justin Wolfers, 2010. "Explaining the Favorite-Longshot Bias: Is it Risk-Love or Misperceptions?," CESifo Working Paper Series 3029, CESifo.
    4. Maschke Mario & Schmidt Ulrich, 2011. "Das Wettmonopol in Deutschland: Status quo und Reformansätze," Zeitschrift für Wirtschaftspolitik, De Gruyter, vol. 60(1), pages 110-124, April.
    5. 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.
    6. Philip W. S. Newall & Dominic Cortis, 2021. "Are Sports Bettors Biased toward Longshots, Favorites, or Both? A Literature Review," Risks, MDPI, Open Access Journal, vol. 9(1), pages 1-9, January.
    7. Jinook Jeong & Jee Young Kim & Yoon Jae Ro, 2019. "On the efficiency of racetrack betting market: a new test for the favourite-longshot bias," Applied Economics, Taylor & Francis Journals, vol. 51(54), pages 5817-5828, November.
    8. Alistair C. Bruce & Johnnie E. V. Johnson & John D. Peirson & Jiejun Yu, 2009. "An Examination of the Determinants of Biased Behaviour in a Market for State Contingent Claims," Economica, London School of Economics and Political Science, vol. 76(302), pages 282-303, April.
    9. Lionel Page, 2012. "‘It ain’t over till it's over.’ Yogi Berra bias on prediction markets," Applied Economics, Taylor & Francis Journals, vol. 44(1), pages 81-92, January.
    10. 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.
    11. Bo Cowgill & Eric Zitzewitz, 2015. "Corporate Prediction Markets: Evidence from Google, Ford, and Firm X," Review of Economic Studies, Oxford University Press, vol. 82(4), pages 1309-1341.
    12. John Peirson, 2008. "Expert Analysis and Insider Information in Horse Race Betting: Regulating Informed Market Behaviour," Studies in Economics 0819, School of Economics, University of Kent.
    13. Les Coleman, 2004. "New light on the longshot bias," Applied Economics, Taylor & Francis Journals, vol. 36(4), pages 315-326.
    14. N. Bhattacharya & T. A. Garrett, 2008. "Why people choose negative expected return assets - an empirical examination of a utility theoretic explanation," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 27-34.
    15. Russell Sobel & S. Travis Raines, 2003. "An examination of the empirical derivatives of the favourite-longshot bias in racetrack betting," Applied Economics, Taylor & Francis Journals, vol. 35(4), pages 371-385.
    16. Marco Ottaviani & Peter Norman Sorensen, 2010. "Noise, Information, and the Favorite-Longshot Bias in Parimutuel Predictions," American Economic Journal: Microeconomics, American Economic Association, vol. 2(1), pages 58-85, February.
    17. Leighton Vaughan Williams & Ming‐Chien Sung & Peter A. F. Fraser‐Mackenzie & John Peirson & Johnnie E. V. Johnson, 2018. "Towards an Understanding of the Origins of the Favourite–Longshot Bias: Evidence from Online Poker Markets, a Real‐money Natural Laboratory," Economica, London School of Economics and Political Science, vol. 85(338), pages 360-382, April.
    18. Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico & Johnson, Johnnie E.V., 2018. "It takes all sorts: A heterogeneous agent explanation for prediction market mispricing," European Journal of Operational Research, Elsevier, vol. 270(2), pages 556-569.
    19. David Paton & Leighton Vaughan Williams, 2001. "Monopoly Rents and Price Fixing in Betting Markets," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 19(3), pages 265-278, November.
    20. John Peirson & Michael A. Smith, 2010. "Symposium Expert Analysis and Insider Information in Horse Race Betting: Regulating Informed Market Behavior," Southern Economic Journal, Southern Economic Association, vol. 76(4), pages 976-992, April.

    More about this item

    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:ecj:econjl:v:123:y:2013:i:568:p:491-513. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). General contact details of provider: https://edirc.repec.org/data/resssea.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.