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Prediction Markets The Millennium Project Futures Research Methodology—V3.0 PREDICTION MARKETS From papers by Justin Wolfers and Eric Zitzewitz1 with notes and additional references by Theodore Gordon I. History of the Method II. Description of the Method III. How to Do It IV. Strengths and Weaknesses of the Method V. Use in Combination with Other Methods VI Frontiers of the Method Appendix: Samples of Applications Bibliography 1 Justin Wolfers is Associate Professor of Business and Public Policy, The Wharton School, University of Pennsylvania; Eric Zitzewitz is Associate Professor of Economics at Dartmouth College. Professors Wolfers and Zitzewitz kindly allowed the Millennium Project to prepare this chapter using their previously published work; the editor arranged the material in the format of this CD ROM, and added several other references and comments along the way. The comments are identified by the parenthetical initials (TG). The final product was reviewed by Professors Wolfers and Zitzewitz. The Millennium Project Futures Research Methodology—V3.0 Acknowledgments This chapter has benefitted from helpful comments and insightful remarks provided by peer reviewers Charles M. Perrottet, Principal, The Futures Strategy Group LLC, USA; Peter Bishop, director, Program for the Study of the Future, University of Houston; Theodore Gordon, Senior Fellow of The Millennium Project; and Jerome Glenn, Director, The Millennium Project. Elizabeth Florescu and Kawthar Nakayima provided excellent project support and John Young proofread. Thanks to all for your contributions. Prediction Markets ii The Millennium Project Futures Research Methodology—V3.0 I. HISTORY OF THE METHOD Prediction Markets, sometimes referred to as ―information markets,‖ ―idea futures‖ or ―event futures‖, are markets where participants trade contracts whose payoffs are tied to a future event, thereby yielding prices that can be interpreted as market aggregated forecasts. For instance, in the Iowa Electronic Market, traders buy and sell contracts that pay $1 if a given candidate wins the election. If a prediction market is efficient, then the prices of these contracts aggregate dispersed information about the probability of each candidate being elected. Markets designed specifically around this information aggregation and revelation motive are the focus of this chapter.2 The most famous prediction markets are the election forecasting markets run by the University of Iowa (Berg, Forsythe, Nelson and Rietz, 2001), but prediction markets have also been used to forecast movie revenues, corporate sales, project completion, economic indicators and Saddam Hussein’s demise. New corporate applications have emerged as firms have looked to markets to predict research and development outcomes, success of new products, and regulatory outcomes. In the public sector, the Pentagon attempted to use markets designed to predict geopolitical risks, although negative publicity stopped the project (Hanson, 2005). An intriguing attempt to apply prediction markets to forecasting influenza outbreaks is detailed in Nelson, Polgreen and Neumann (2006). Rhode and Strumpf (2004) have detailed the existence of large-scale election betting as far back as the election of Washington.3 Not only have prediction markets been used in numerous fields, but the market mechanisms have varied as well; including continuous double auctions (both with and without market-makers), pari-mutuel pools, bookmaker-mediated betting markets, and implementations as market-scoring rules. In July 2003, press reports began to surface of a project within the Defense Advanced Research Projects Agency (DARPA), a research think tank within the Department of Defense, to establish a Policy Analysis Market that would allow trading in various forms of geopolitical risk.4 Proposed contracts were based on indices of economic health, civil stability, military disposition, conflict indicators, and potentially even specific events. For example, contracts might have been based on questions like ―How fast will the non-oil output of Egypt grow next year?‖ or ―Will the U.S. military withdraw from country A in two years or less?‖ Moreover, the exchange would have offered combinations of contracts, perhaps combining an economic event and a political event. The concept was to discover whether trading in such contracts could help to predict future events and how connections between events were perceived. However, a political uproar 2 The material in this section is from: Justin Wolfers and Eric Zitzewitz, ―Prediction Markets in Theory and Practice, NBER Working Paper No. 12083, March 2006 3 In fact Rhode and Strumpf (2004) provide references to historical accounts of early uses of betting (prediction markets) in elections as dating back to the Italian City States in the 1500-1700’s and in the anticipation of the succession of Catholic popes. In Great Britain, it can be traced back to the 18th century. (TG) 4 This material from Wolfers, Justin and Eric Zitzewitz, Prediction Markets, Journal of Economic Perspectives— Volume 18, Number 2—Spring 2004—Pages 107–126 Prediction Markets 1 The Millennium Project Futures Research Methodology—V3.0 followed. Critics savaged DARPA for proposing ―terrorism futures,‖ and rather than spend political capital defending a tiny program, the proposal was dropped.5 Ironically, the aftermath of the DARPA controversy provided a vivid illustration of the power of markets to provide information about probabilities of future events. An offshore betting exchange, Tradesports.com, listed a new security that would pay $100 if the head of DARPA, Admiral John Poindexter, was ousted by the end of August 2003. Early trading suggested a likelihood of resignation by the end of August of 40 percent, and price fluctuations reflected ongoing news developments. Around lunchtime on July 31, reports started citing credible Pentagon insiders who claimed knowledge of an impending resignation. Within minutes of this news first surfacing (and hours before it became widely known), the price spiked to around 80. These reports left the date of Poindexter’s proposed departure uncertain, which explains the remaining risk. As August dragged on, the price slowly fell back toward 50. On August 12, Poindexter then issued a letter of resignation suggesting that he would resign on August 29. On the 12th, the market rose sharply, closing at a price of 96. This anecdote illustrates a market where participants trade in contracts whose payoff depends on unknown future events. II. DESCRIPTION OF THE METHOD Much of the enthusiasm for prediction markets derives from the efficient markets hypothesis. In a truly efficient prediction market, the market price will be the best predictor of the event, and no combination of available polls or other information can be used to improve on the market- generated forecasts. This statement does not require that all individuals in a market be rational, as long as the marginal trade in the market is motivated by rational traders. Of course, it is unlikely that prediction markets are literally efficient, but a number of successes in these markets, both with regard to public events like presidential elections and within firms, have generated substantial interest. Although markets designed specifically for information aggregation and revelation are the focus of this chapter, the line between these kinds of prediction markets and the full range of contingent commodities—from owning stock in your employer’s company to betting on the Super Bowl—can become blurry. Most contingent commodity markets involve some mix of risk sharing, fun, and information transmission, so these distinctions are not impermeable. The design of how the payoff is linked to the future event can elicit the market’s expectations of a range of different parameters. Practitioners speak as though the market is itself a representative ―person‖ with a set of expectations. However, the reader should be warned that there are important but subtle differences between, say, the market’s median expectation and the median expectation of market participants. 5 Looney (2003) provides a useful summary of both the relevant proposal and its aftermath. Further, Robin Hanson has maintained a useful archive of related news stories and government documents at http://hanson.gmu.edu/policyanalysismarket.html. Prediction Markets 2 The Millennium Project Futures Research Methodology—V3.0 Table 1 below summarizes some of the on-line prediction markets, and in the aggregate describes the range of applications being made today: Table 1. Prediction Markets Typical Turnover on an Market Focus Event Small-scale election markets. A Iowa Electronic Markets Tens of thousands of dollars similar market is run by http://www.biz.uiowa.edu/iem/ (Traders limited to $500 UBC (Canada) Run by University of Iowa positions.) http://esm.ubc.ca/CA08/ Trade in a rich set of political InTrade futures, financial contracts, Hundreds of thousands www.intrade.com current events, sports and of dollars For-profit company entertainment. Economic Derivatives Large-scale financial market www.economicderivatives.com trading in the likely outcome Hundreds of millions Run by Goldman Sachs and of future economic data Deutsche Bank releases Virtual currency redeemable Political, finance, current for monthly prizes (such as a NewsFutures events and sports markets. television set). Also player www.newsfutures.com Also can use real money and For-profit company technology and pharmaceutical designate winnings to go to a futures for
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