2013 ExperiencefromHostingaCorporate

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Subject Headings: Prediction Market.

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Abstract

Prediction markets are virtual stock markets used to gain insight and forecast events by leveraging the wisdom of crowds. Popularly applied in the public to cultural questions (election results, box-office returns), they have recently been applied by corporations to leverage employee knowledge and forecast answers to business questions (sales volumes, products and features, release timing). Determining whether to run a prediction market requires practical experience that is rarely described.

Over the last few years, Ford Motor Company obtained practical experience by deploying one of the largest corporate prediction markets known. Business partners in the US, Europe, and South America provided questions on new vehicle features, sales volumes, take rates, pricing, and macroeconomic trends.

We describe our experience, including both the strong and weak correlations found between predictions and real world results. Evaluating this methodology goes beyond prediction accuracy, however, since there are many side benefits. In addition to the predictions, we discuss the value of comments, stock price changes over time, the ability to overcome bureaucratic limits, and flexibly filling holes in corporate knowledge, enabling better decision making. We conclude with advice on running prediction markets, including writing good questions, market duration, motivating traders and protecting confidential information.

References

  • 1. Tom W. Bell, "Private Prediction Markets and the Law," The Journal of Prediction Markets, Vol. 3, No. 1, Pp. 89--110, 2009.
  • 2. Joyce E Berg, Robert Forsythe, Forrest Nelson, and Thomas Rietz, "Results from a Dozen Years of Election Futures Markets Research," in Handbook of Experimental Economic Results, Charles Plott and Vernon Smith, Eds. Amsterdam: Elsevier, 2008, Pp. 742--751.
  • 3. Joyce Berg, Forrest Nelson, and Thomas Rietz, "Prediction Market Accuracy in the Long Run," International Journal of Forecasting, Vol. 24, No. 2, Pp. 285--300, 2008.
  • 4. Bo Cowgill, Justin Wolfers, and Eric Zitzewitz. (2009, January) Using Prediction Markets to Track Information Flows: Evidence from Google. {Online}. http://www.bocowgill.com/GooglePredictionMarketPaper.pdf
  • 5. James Duncan and R. Mark Isaac, "Asset Markets: How They Are Affected by Tournament Incentives for Individuals," American Economic Review, Pp. 995--1004, 2000.
  • 6. Foresight Exchange Partnership. (2012) The Foresight Exchange Prediction Market. {Online}. Www.ideosphere.com
  • 7. Alan Hall. (2011) Ford Prediction Market. {Online}. http://media.ford.com/images/10031/FTL_predmarket.pdf
  • 8. Friedrich Hayek, "The Use of Knowledge in Society," American Economic Review, Vol. XXXV, No. 4, Pp. 519--530, September 1945.
  • 9. Hollywood Stock Exchange, The Entertainment Market. {Online}. Www.hsx.com
  • 10. IEM - Iowa Electronic Markets. {Online}. Tippie.uiowa.edu/iem
  • 11. Infosurv Concept Exchange. {Online}. Www.icepredict.com
  • 12. Christina Ann Lacomb, Janet Arlie Barnett, Qimei Pan, The Imagination Market, Information Systems Frontiers, v.9 n.2-3, p.245-256, July 2007 doi:10.1007/s10796-007-9024-9
  • 13. Steve Lohr, "Betting to Improve Odds," The New York Times, April 2008.
  • 14. Marco Ottaviani and Peter Norman Sørenson, "Outcome Manipulation in Corporate Prediction Markets," Journal of the European Economic Association, Vol. 5, No. 2--3, Pp. 554--563, 2007.
  • 15. L Page and R T Clemen. (2011, September) Do Prediction Markets Produce Well Calibrated Probability Forecasts?. {Online}. http://faculty.fuqua.duke.edu/~clemen/bio/Prediction_Markets.pdf
  • 16. David M Pennock, Steve Lawrence, C. Lee Giles, and Finn Arup Nielsen, "The Real Power of Artificial Markets," Science, Vol. 291, No. 5506, Pp. 987--988, 2001.
  • 17. Prediction Markets - Inkling. {Online}. Inklingmarkets.com
  • 18. Emile Servan-Schreiber, Justin Wolfers, and David M Pennock, "Prediction Markets: Does Money Matter?," Electronic Markets, Vol. 14, No. 3, Pp. 243--251, 2004.
  • 19. Nate Silver, The Signal and the Noise: Why So Many Predictions Fail - But Some Don't. New York: The Penguin Press, 2012, p. 335.
  • 20. B Spears, C LaComb, J Interrante, J Barnett, and D Senturk-Dogonaksoy, "Examining Trader Behavior in Idea Markets: An Implementation of GE's Imagination Markets," The Journal of Prediction Markets, Vol. 3, No. 1, Pp. 17--39, 2009.
  • 21. James Surowiecki, The Wisdom of Crowds: Why the Many Are Smarter Than the Few and how Collective Wisdom Shapes Business, Economies, Societies and Nations. New York: Doubleday, 2004.
  • 22. P C Tetlock, "Liquidity and Prediction Market Efficiency," Columbia Business School, SSRN Working Paper 929916, 2008.
  • 23. Justin Wolfers and Eric Zitzewitz, Prediction Markets, April 19, 2004.

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2013 ExperiencefromHostingaCorporateThomas A. Montgomery
Paul M. Stieg
Michael J. Cavaretta
Paul E. Moraal
Experience from Hosting a Corporate Prediction Market: Benefits Beyond the Forecasts10.1145/2487575.24882122013