Wolfers.fm Page 37 Monday, June 8, 2009 3:12 PM Prediction Markets: The Collective Knowledge of Market Participants Justin Wolfers Associate Professor of Business and Public Policy Wharton School, University of Pennsylvania Philadelphia Prediction markets provide an information-aggregation technology applicable to a variety of topics, including political and financial risk. Because of the human idiosyncrasies identified by behavioral finance, prediction markets can fail, but historical data show them to be as accurate as traditional polling methodologies and far less expensive to establish and maintain. n this discussion, I will make three substantive Sports Prediction Markets. Interestingly, I claims about prediction markets. First, if mar- sports betting markets manifest many of the charac- kets really are efficient, as the efficient market teristics expected of an efficient market, and they hypothesis asserts, then the prices that come out of now allow participants to trade stock during the any market contain valuable information. To make game on the likelihood of a particular team winning. the case for this claim, I will use data from sports For example, Figure 1 shows real-time betting dur- betting markets. Second, prediction markets can be ing Game 6 of the 2003 National League Champion- used to track political risk, which can be a key factor ship Series (NLCS). This prediction market from driving investment performance. Third, prediction Intrade pays $1 if and only if the Chicago Cubs win markets can fail, so I will conclude my discussion this particular game. At the beginning of the game, by describing why prediction markets work and it looks as if the Cubs have about a 75 percent chance what causes them to fail. of winning. In the top of the eighth inning, the Cubs go ahead of the Florida Marlins 3–0, and the chance Prediction Markets and the of the Cubs winning the game and going to the World Series reaches 95 percent. Unfortunately, in Efficient Market Hypothesis the bottom of that same inning, one of the great The efficient market hypothesis asserts that market collapses in sporting history occurred. A fan reaches prices fully reflect available information. But the out from the stands and prevents a catch by Cubs degree to which information is available determines outfielder Moises Alou. The Marlins proceed to the form in which the hypothesis reveals itself. In its score eight runs in that inning, and the market strong form, prices reflect all information; in its responds immediately to this new information. In a semi-strong form, prices reflect all publicly avail- matter of minutes, the market price declines from 95 able information; in its weak form, prices reflect cents to about 5 cents. only past data. In any one of these forms, however, The question more important than whether pre- prices can reflect, summarize, and aggregate a huge diction markets respond quickly to news, though, is amount of information, but the unfortunate impli- whether these market prices are accurate. To answer cation of the hypothesis is that excess returns are that question, I have charted data from all 21,885 unpredictable. Thus, prices can be said to follow a major league baseball games played from 1991 random walk. through 2000, and the data show that the predic- tions are quite close to the actual outcomes. For This presentation comes from the 2008 CFA Institute Annual Confer- instance, if the market says a team has a 33 percent ence held in Vancouver, British Columbia, Canada, on 11–14 May 2008. chance of winning, it actually wins 31 percent of the ©2009 CFA Institute cfapubs.org JUNE 2009 37 Wolfers.fm Page 38 Monday, June 8, 2009 3:12 PM CFA Institute Conference Proceedings Quarterly Figure 1. Real-Time Betting on the Chicago Cubs: 2003 NLCS, Game 6 Price ($) 1.00 Fan Spoils Alou’s Catch 0.80 Top of the 8th Inning 0.60 0.40 0.20 0 8:05 p.m. 9:00 p.m. 10:00 p.m. 11:00 p.m. Note: Time is given in central (Chicago) time. Source: Based on data from Intrade. time. When the market says a team has a 67 percent ing take, which are, again, quite accurate. Therefore, chance of winning, it wins 65 percent of the time, an analyst covering the movie industry may find and when the market says a team has a 90 percent these forecasts quite useful, which means that such chance of winning, it wins 88 percent of the time. an exchange moves us toward the realm of socially The difference is how Las Vegas makes money. But useful prediction markets. the real point is that if a person wants accurate For instance, Deutsche Bank and Goldman information on the likely outcomes of baseball Sachs briefly started a new market (now folded, games, the betting odds do an excellent job of pro- unfortunately) that they called the “economic viding that information. derivatives market.” It allowed investors to trade The same point holds true for other sports. For on the future outcomes of particular economic indi- example, based on market expectations and game outcomes for the National Football League from cators, such as retail sales and business confidence. 1984 to 2000 (i.e., for 3,791 games), a regression The economic derivatives market provided fore- analysis shows a slope of almost 1.0 (0.997 to be casts for nonfarm payrolls, initial unemployment exact). Thus, when the market says that a team is claims, retail sales, and business confidence, and likely to win and gives a margin of a prespecified based on data that Refet Gürkaynak and I gathered, number of points (the “point spread”), that team, on these forecasts were more accurate than an average average, wins by the point spread. or consensus forecast of 35 economists. Do not, however, think of these findings as mere My conclusion, therefore, is that rather than conversation topics. Rather, think of prediction averaging the forecasts of 35 economists, those same markets as a technology that can be used to aggre- economists should be put in a room and told to bet gate opinions about anything of importance. or trade against each other. Taking the market- Socially Useful Prediction Markets. Consider aggregated price from this trading would provide a the firm called the Hollywood Stock Exchange. It more efficient way of aggregating forecasts. The runs prediction markets on the opening weekend task, then, is to harness this technology to more box office take of various movies. Essentially, it challenging issues. One such issue is politics. In fact, allows people to trade, or bet, on how well each prediction markets have been used quite exten- movie will perform. Data from that market can sively to predict political risk, which is a key factor show the aggregated forecast and the actual open- driving investment performance. 38 JUNE 2009 ©2009 CFA Institute cfapubs.org Wolfers.fm Page 39 Monday, June 8, 2009 3:12 PM Prediction Markets Prediction Markets and Political therefore, represent a valuable gain in accuracy and a significant reduction in costs. Risk ■ Results from recent cycles. In the 2004 U.S. In 2003, a recall election was held to remove Califor- election cycle, investors could trade not only which nia Governor Gray Davis from office and replace candidate would become president but also who him with one of several contenders, one of whom would win the Electoral College votes of each state. was Arnold Schwarzenegger. Prediction markets Based on data from Intrade, the prediction market allowed people to trade on the question of whether price accurately predicted every state that went for Schwarzenegger would win the governorship. A George W. Bush and every state that went against contract paying $100 if Schwarzenegger won could him. For the 2004 U.S. Senate races, the Intrade price be traded on two exchanges—Intrade, which is was correct for every state but Alaska. In the 2006 based in Ireland, or the World Sports Exchange, election cycle, most knowledgeable observers and which is based in the Caribbean. Attempts to recall many Republicans did not expect the Democrats to other governors had occurred in California, but win enough seats to gain the majority in the Senate. none had been successful. Nevertheless, I set my But every single Senate race went exactly the way computer to look for arbitrage opportunities the election-eve prediction market said it would. between Intrade and the World Sports Exchange. ■ History of political prediction markets. Such Every four hours, my computer checked these two prediction markets seem like a marvelous new tech- websites and searched for potential profits. By the nology for forecasting election results, but as it turns end of the exercise, I had made no money, but I had out, betting on politics is as old as politics itself. Two learned an important research lesson. When I fol- enterprising economic historians—Rhode and lowed the chart of the two exchange prices, the bid Strumpf—have gathered data on the amount of bet- price in one market was never above the asking ting that has occurred on U.S. presidential elections price in the other, which means that the two markets from 1884 through 1928. Opinion polling did not are closely linked. The price pattern that we are so exist in any systematic or nationwide manner at the familiar with in other financial markets appears to time, but betting on elections occurred regularly on hold true for political prediction markets. the curb where the American Stock Exchange now stands. In fact, large sums of money were traded. Accuracy of Political Prediction Markets. For the 1884–1928 period, an average of $37 million These markets have a tremendous historical record.