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Explaining variance in the accuracy of prediction markets

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  • Strijbis, Oliver
  • Arnesen, Sveinung

Abstract

Thus far, the focus in prediction market research has been on establishing its forecast accuracy relative to those of other prediction methods, or on the investigation of a few single sources of forecast error. This article is the first attempt to overcome the narrow focus of the literature by combining observational and experimental analyses of prediction market errors. It investigates the prediction error of a real money prediction market uusing a logarithmic market scoring rule for 65 direct democratic votes in Switzerland. The article distinguishes between prediction market error due to the setup of the market, features of the event to be predicted, and the participants involved, and finds that the prediction market accuracy varies primarily according to the setup of the market, with the features of the event and especially the composition of the participant sample hardly mattering.

Suggested Citation

  • Strijbis, Oliver & Arnesen, Sveinung, 2019. "Explaining variance in the accuracy of prediction markets," International Journal of Forecasting, Elsevier, vol. 35(1), pages 408-419.
    • Handle: RePEc:eee:intfor:v:35:y:2019:i:1:p:408-419
    DOI: 10.1016/j.ijforecast.2018.04.009
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    1. Berg, Joyce & Forsythe, Robert & Nelson, Forrest & Rietz, Thomas, 2008. "Results from a Dozen Years of Election Futures Markets Research," Handbook of Experimental Economics Results, in: Charles R. Plott & Vernon L. Smith (ed.), Handbook of Experimental Economics Results, edition 1, volume 1, chapter 80, pages 742-751, Elsevier.
    2. 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.
    3. Drew Fudenberg & David K. Levine & Zacharias Maniadis, 2012. "On the Robustness of Anchoring Effects in WTP and WTA Experiments," American Economic Journal: Microeconomics, American Economic Association, vol. 4(2), pages 131-145, May.
    4. Andrew Leigh & Justin Wolfers, 2006. "Competing Approaches to Forecasting Elections: Economic Models, Opinion Polling and Prediction Markets," The Economic Record, The Economic Society of Australia, vol. 82(258), pages 325-340, September.
    5. John A. List, 2011. "Does Market Experience Eliminate Market Anomalies? The Case of Exogenous Market Experience," American Economic Review, American Economic Association, vol. 101(3), pages 313-317, May.
    6. Michael S. Haigh & John A. List, 2005. "Do Professional Traders Exhibit Myopic Loss Aversion? An Experimental Analysis," Journal of Finance, American Finance Association, vol. 60(1), pages 523-534, February.
    7. 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.
    8. Kentaro Asai & Seda Ertac & Ali Hortacsu & John List & Howard Nusbaum & Lester Tong & Karen Ye, 2016. "Trading experience modulates anterior insula to reduce the endowment effect," Framed Field Experiments 00717, The Field Experiments Website.
    9. Henry Berg & Todd A. Proebsting, 2009. "Hanson's Automated Market Maker," Journal of Prediction Markets, University of Buckingham Press, vol. 3(1), pages 45-59, April.
    10. Robin Hanson, 2003. "Combinatorial Information Market Design," Information Systems Frontiers, Springer, vol. 5(1), pages 107-119, January.
    11. Yeh, Chia-Hsuan, 2008. "The effects of intelligence on price discovery and market efficiency," Journal of Economic Behavior & Organization, Elsevier, vol. 68(3-4), pages 613-625, December.
    12. John A. List, 2003. "Does Market Experience Eliminate Market Anomalies?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(1), pages 41-71.
    13. Jonathan E. Alevy & Craig E. Landry & John A. List, 2015. "Field Experiments On The Anchoring Of Economic Valuations," Economic Inquiry, Western Economic Association International, vol. 53(3), pages 1522-1538, July.
    14. Miller, Edward M, 1977. "Risk, Uncertainty, and Divergence of Opinion," Journal of Finance, American Finance Association, vol. 32(4), pages 1151-1168, September.
    15. Eric C. Chang & Joseph W. Cheng & Yinghui Yu, 2007. "Short‐Sales Constraints and Price Discovery: Evidence from the Hong Kong Market," Journal of Finance, American Finance Association, vol. 62(5), pages 2097-2121, October.
    16. Viktor Manahov & Mona Soufian & Robert Hudson, 2014. "The Implications Of Trader Cognitive Abilities On Stock Market Properties," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(1), pages 1-18, January.
    17. Patrick McHugh & Aaron Jackson, 2012. "Prediction Market Accuracy: The Impact Of Size, Incentives, Context And Interpretation," Journal of Prediction Markets, University of Buckingham Press, vol. 6(2), pages 22-46.
    18. Robin Hanson, 2007. "Logarithmic Market Scoring Rules for Modular Combinatorial Information Aggregation," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 3-15, February.
    19. Forsythe, Robert & Lundholm, Russell, 1990. "Information Aggregation in an Experimental Market," Econometrica, Econometric Society, vol. 58(2), pages 309-347, March.
    20. Furnham, Adrian & Boo, Hua Chu, 2011. "A literature review of the anchoring effect," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(1), pages 35-42, February.
    21. repec:reg:rpubli:460 is not listed on IDEAS
    22. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    23. 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.
    24. Jaya M. Prosad & Sujata Kapoor & Jhumur Sengupta & Saurav Roychoudhary, 2017. "Overconfidence and Disposition Effect in Indian Equity Market: An Empirical Evidence," Global Business Review, International Management Institute, vol. 19(5), pages 1303-1321, October.
    25. 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.
    26. Boehme, Rodney D. & Danielsen, Bartley R. & Sorescu, Sorin M., 2006. "Short-Sale Constraints, Differences of Opinion, and Overvaluation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 41(2), pages 455-487, June.
    27. Stefan Luckner & Christof Weinhardt, 2007. "How to Pay Traders in Information Markets: Results from a Field Experiment," Journal of Prediction Markets, University of Buckingham Press, vol. 1(2), pages 147-156, July.
    28. Stefan Luckner & Christof Weinhardt, 2007. "How to pay traders in information markets? Results from a field experiment," Artefactual Field Experiments 00107, The Field Experiments Website.
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