Prediction markets

1. Prediction markets By: Meghan Danielson

2. Introduction • Prediction markets are a tool for collecting group opinion using market principles. • Beginning in 1988, members of the University of Iowa’s Iowa Electronic Market (IEM) project developed the concept of “prediction markets”. According to IEM, the sole purpose of these markets is to provide forecasts of the outcomes of uncertain events. • These markets have proved very successful in presidential elections, Federal Reserve interest rate policy decisions, movie box-office receipts, Nobel prizes, and many more.

3. History • Prediction markets have a long and colorful lineage: • Betting on elections was common in the US until at least the 1940s, with formal markets existing on Wall Street in the months leading up to the race. • Newspapers reported market conditions to give a sense of the closeness of the contest in this period prior to widespread polling. • Markets involved thousands of participants, had millions of dollars in volume in current terms, and had remarkable predictive accuracy.

4. History • Project Xanadu was the first known corporate prediction market in 1990 – employees used it to bet on the cold fusion controversy, among other things. • The U.S. Department of Defense publicized a Policy Analysis Market and speculated additional topics for markets might include terrorist attacks. This program was quickly denounced as a “terrorism futures market” and the Pentegon canceled the program. • In October 2007, companies from the U.S., Ireland, Austria, Germany, and Denmark formed the Prediction Market Industry Association. • Formed to promote awareness, education, and validation for prediction markets

5. Prediction markets in use • Prediction markets are not just for curious academics anymore – there has been an explosion of interest in the last few years. • People are now given the opportunity to predict everything from how much a new movie will gross in its first month to whether or not gasoline prices will rise. • Companies, such as Google have created internal markets, where voters are all employees. • Google executives entice people to participate by giving away t-shirts. • Ask useful questions like “When will a product launch?”, “How many full-time people will accept jobs at Google in the next quarter?”, etc.

6. Prediction markets in use • Many prediction markets are open to the public: • Betfair – world’s biggest prediction exchange • Intrade – for-profit company with a large variety of contracts not including sports • Iowa Electronic Market – academic market examining elections with positions limited to $500 • TradeSports– prediction markets for sporting events • Hollywood Stock Exchange, Inkling, the simExchange, Newsfutures, and more – virtual prediction markets where purchases are made with virtual money • Bet2Give – charity prediction market where real money is traded but winnings are donated to charity of winner’s choice

7. James surowieki • Surowieki was a business columnist with The New Yorker. • Prediction markets are championed in his 2004 book The Wisdom of Crowds. • Surowieki set out only to echo (and contradict) the ideas of Charles Mackey’s work Extraordinary Popular Delusions and the Madness of Crowds. • Surowieki’s book ended up showing that, far more often, the crowd gets it right. • Book is filled with examples of “collective intelligence”

8. Why the term “market” in “prediction market”? • A prediction market is a way to bring together people’s opinions. • These opinions are expressed by buying and selling stocks that represent possible answers to a question being posed. • Example: • Question being asked is “Who will win the Super Bowl?” • For this question there will be Bears stock, Patriots stock, 49ers stock, etc. • Participants are given virtual cash when they sign up, and with this cash, they can buy (and sell) shares in these answers to express individual opinion of what the person thinks will happen. • In prediction markets, the stock price represents the likelihood that the answer is correct. This means if the Bears stock is at $75, we would say “there is a 75% chance the Bears will win the Super Bowl.”

9. So how does it work? • Prediction markets try to “untangle the factors that cause change”. • Example from 2008 election: • The IEM lets participants bet yes or no on simple questions, such as “Will Senator John McCain win the election?” • If the odds are 50-50, you could buy a $0.50 contract and get a $1.00 payout if you win. • Someone on the losing side of the bet is out $0.50 • As bettors change opinions, the odds shift. • At one point, the IEM “winner take all” contract for McCain had fallen to just over $0.15, which was the markets way of saying that he only has 15.5% odds of becoming president.

10. Survey/poll vs prediction market • There are two main differences between surveys/polls and prediction markets. • A survey or a poll is a snapshot in time. Prediction markets, on the other hand, run continuously over a period of days, weeks, and months. People can change their opinion at any time. • Any question asked in a prediction market must have an objective and verifiable outcome. This means that there will never be a simple yes or no question, like “Should we run this promotion?” Instead questions will follow more along the lines of “How much additional web traffic will this promotion generate?”

11. The future dividend by the crowd • Every year, Michael J. Mauboussin, an adjunct professor at Columbia Business School asks students to vote on winners in 12 Academy Awards categories (including obscure ones like best film editing and art direction). • In 2006, the pick that received the most votes – the consensus pick – was right in 9 out of the 12 categories. • Of the 47 participating students, only 1 correctly matched the accuracy of the consensus – average number of correct answers per ballot was 4.1. • Illustrates the power of prediction markets – although they are not perfect, they are certainly more accurate than individual experts of polls. “All of us walk around with a little information and a substantial error term. And when we aggregate our results, the errors tend to cancel each other out and what is distilled is pure information.” -Michael J. Mauboussin

12. Group intelligence • The idea of scenario forecasts using group intelligence was created by Robert Hanson of George Mason University. • He said that humans have access to imperfect information and we follow the group think of our peers. • We often disagree with other groups, so we band together with our own group and often end up agreeing too much. • No single leader can overcome such biases and data gaps to predict with certainty whether an action will succeed or fail. Hanson, however, suggests that markets can bridge this gap.

13. legality • Online gambling is outlawed in the United States through federal laws, as well as many state laws. • Because of this, most prediction markets that target U.S. users operate with “play money” rather than “real money” – this means that the markets are free to play, participants are given virtual cash to spend, and the best traders are usually offered prizes as an incentive to play.

14. legality • Exceptions: • Intrade and TradeSports escape U.S. legal restrictions because they are operated from Dublin, Ireland, where gambling is legal and regulated, and are therefore out of the jurisdiction of the U.S. • The Iowa Electronic Markets operates from the University of Iowa, under the cover of a no-action letter from the Commodity Futures Trading Commission and allows bets up to $500. • Controversial: • Some prediction markets are not as wholesome. For example, a market predicting the death of a world leader might be useful to people whose activities are related to the leader’s policies. • This type of market is controversial, however, because it could end up turning into an assassination market.

15. accuracy • When groups of people bet on something, the combined intelligence is remarkably accurate. • British scientist Francis Galton noticed this in 1906: He observed 787 people at a county fair try to guess weight of an ox after it was slaughtered. The average of all guesses was 1,197, only one pound less than the correct answer. • The Iowa Electronic Market (IEM), one of the most famous prediction markets, is set up to foretell U.S. Presidential elections. This market has accurately foretold each election result since 1988 with only 1.33% error rate in voter totals.

16. Stock price and probability accuracy • This graph plots the “perfect” line, with 5% of the events actually occurring 5% of the time, 15% occurring 15% of the time etc. • This is compared to Inkling’s participant data for how often 5%, 15%, and so on of the events will occur.

17. Numerical outcome prediction accuracy • This type of prediction is based on the answer to a question like: What will the population of Philadelphia be in 2011? • Hundreds of answers to market questions such as this are plotted as data points. • The “perfect” line tracks if you said there would be 100 people and there were 100 people, etc. • The red line is a line of best fit through the data.

18. Future of prediction markets • If markets are watched carefully, they reveal a knowledge based on many pieces of individual data. • This data is collected from information that each person provides as he or she makes a best guess about the future. • Working towards idea of “consumer prediction markets” to improve accuracy of buyer’s forecasts. • Opinion capturing website feature • Real-time polling with an automatic smartphone prompt for opinion entry per interest profile

19. Future of prediction markets • One big problem facing prediction markets is getting enough people to use them and to continue trading now that the novelty has begun to wear off. • Many companies use gaming-style leader boards to encourage internal rivalry or offer modest prizes to the most successful traders. • Employees also struggle to see how results of prediction markets are used, so they begin to lose interest. • To counteract this, some companies have been running internal markets in areas where the managers could do something with their findings. This act helps to make staff feel that trading is worthwhile.

20. Why believe in prediction markets? • If prediction markets were unable to predict the recent financial crisis, how are we supposed to believe they can accurately predict anything else? • The major difference between a prediction market that is run within a company, and the financial market as a whole, is that the company has access to all of its own data. • They can see if or when bubbles are forming and can better understand why someone may behave the specific way that they do. • Companies can also see any outliers to the questions being asked. • All of this transparency means that the company can see if there are signals that are being missed by the broader participant-base and react accordingly.

21. Works Cited • en.wikipedia.org/wiki/Prediction_market • http://www.google.com/search?q=history+of+prediction+markets#q=history+of+prediction+markets&hl=en&prmd=iv&tbs=tl:1&tbo=u&ei=iibXTM-uNcLflgfFkcWACQ&sa=X&oi=timeline_result&ct=title&resnum=11&ved=0CEoQ5wIwCg&fp=c7e82246a09ed920 • http://inklingmarkets.com/homes/frequently_asked_questions • http://www.businessweek.com/technology/content/oct2008/tc20081013_033687.htm • “The Future Dividend by the Crowd” by Joe Nocera • “The Wisdom of Crowds” by James Surowiecki • http://www.economist.com/node/13184829?story_id=13184829