Prediction Markets: Tapping the Wisdom of Crowds - PowerPoint PPT Presentation

jalia
prediction markets tapping the wisdom of crowds n.
Skip this Video
Loading SlideShow in 5 Seconds..
Prediction Markets: Tapping the Wisdom of Crowds PowerPoint Presentation
Download Presentation
Prediction Markets: Tapping the Wisdom of Crowds

play fullscreen
1 / 61
Download Presentation
Prediction Markets: Tapping the Wisdom of Crowds
156 Views
Download Presentation

Prediction Markets: Tapping the Wisdom of Crowds

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Prediction Markets: Tapping the Wisdom of Crowds Yiling Chen Yahoo! Research February 3, 2008

  2. Outline • Introduction to prediction markets • What is a prediction market? • Functions of markets • Contracts and mechanisms • Prediction market examples • Iowa Electronic Markets • Yahoo! Tech Buzz Game • Looking forward • Decision markets • Combinatorial markets NYU Stern 2/3/2008

  3. Events of Interest • Will Giants win the Super Bowl? • Will Hillary Clinton win the Democratic Primary race? • Will Democratic party win the Presidential election? • Will (Should) Microsoft and Yahoo merge? • Will US economy go into recession during 2008? • Will there be a cure for cancer by 2015? • Will sales value exceed $200k in April? …… NYU Stern 2/3/2008

  4. Info Info I bet $1000 Patriots will win the Super Bowl. Giants will win the Super Bowl. Bet = Credible Opinion • Q: Will Giants win the Super Bowl? • Betting intermediaries • Las Vegas, Wall Street, Betfair, Intrade,... NYU Stern 2/3/2008

  5. Prediction Markets • A prediction market is a financial market that is designed for information aggregation and prediction. • Payoffs of the traded item is associated with outcomes of future events. NYU Stern 2/3/2008

  6. $1 if Clinton Wins $0 Otherwise Prediction Markets • A prediction market is a financial market that is designed for information aggregation and prediction. • Payoffs of the traded item is associated with outcomes of future events. NYU Stern 2/3/2008

  7. $1 if Clinton Wins $0 Otherwise Prediction Markets • A prediction market is a financial market that is designed for information aggregation and prediction. • Payoffs of the traded item is associated with outcomes of future events. $1×Percentage of Vote Share That Clinton Wins NYU Stern 2/3/2008

  8. $1 if Clinton Wins $0 Otherwise $1 if Patriots win $0 Otherwise Prediction Markets • A prediction market is a financial market that is designed for information aggregation and prediction. • Payoffs of the traded item is associated with outcomes of future events. $1×Percentage of Vote Share That Clinton Wins NYU Stern 2/3/2008

  9. $1 if Clinton Wins $0 Otherwise $1 if Patriots win $0 Otherwise Prediction Markets • A prediction market is a financial market that is designed for information aggregation and prediction. • Payoffs of the traded item is associated with outcomes of future events. $1×Percentage of Vote Share That Clinton Wins $f(x) NYU Stern 2/3/2008

  10. $1 if Hillary Clinton wins election $0 otherwise Prediction Market 1, 2, 3 • Turn an uncertain event of interest into a random variable • Hillary Clinton wins election? (Y/N) => 1/0 random variable. • Create a financial contract, payoff = value of the random variable • Open a market in the financial contract and attract traders to wager and speculate NYU Stern 2/3/2008

  11. Terminology • Contract, security, contingent claim, stock, derivatives (futures, options), bet, gamble, wager, lottery • Key aspect: payoff is uncertain • Prediction markets, information markets, virtual stock markets, decision markets, betting markets, contingent claim markets • Historically mixed reputation, but can serve important social roles NYU Stern 2/3/2008

  12. Bird Flu Market http://intrade.com Screen capture 2008/02/02 NYU Stern 2/3/2008

  13. Search Engine Market Shares http://intrade.com Screen capture 2008/02/02 NYU Stern 2/3/2008

  14. Super Bowl Markets NYU Stern 2/3/2008

  15. Function of Markets 1: Get Information • price  expectation of r.v. | all information (in theory, lab experiments, and empirical studies) NYU Stern 2/3/2008

  16. Function of Markets 1: Get Information • price  expectation of r.v. | all information (in theory, lab experiments, and empirical studies) $1 if Patriots win, $0 otherwise NYU Stern 2/3/2008

  17. Function of Markets 1: Get Information • price  expectation of r.v. | all information (in theory, lab experiments, and empirical studies) $1 if Patriots win, $0 otherwise Value of Contract ? NYU Stern 2/3/2008

  18. Function of Markets 1: Get Information • price  expectation of r.v. | all information (in theory, lab experiments, and empirical studies) $1 if Patriots win, $0 otherwise Event Outcome Value of Contract Payoff $1 Patriots win ? $0 Patriots lose NYU Stern 2/3/2008

  19. Function of Markets 1: Get Information • price  expectation of r.v. | all information (in theory, lab experiments, and empirical studies) $1 if Patriots win, $0 otherwise Event Outcome Value of Contract Payoff P( Patriots win ) $1 Patriots win ? 1- P( Patriots win ) $0 Patriots lose NYU Stern 2/3/2008

  20. Function of Markets 1: Get Information • price  expectation of r.v. | all information (in theory, lab experiments, and empirical studies) $1 if Patriots win, $0 otherwise Event Outcome Value of Contract Payoff P( Patriots win ) $1 Patriots win $P( Patriots win ) 1- P( Patriots win ) $0 Patriots lose NYU Stern 2/3/2008

  21. Function of Markets 1: Get Information • price  expectation of r.v. | all information (in theory, lab experiments, and empirical studies) $1 if Patriots win, $0 otherwise Event Outcome Value of Contract Payoff P( Patriots win ) $1 Patriots win $P( Patriots win ) 1- P( Patriots win ) $0 Patriots lose Equilibrium Price Value of Contract P( Patriots Win ) Market Efficiency NYU Stern 2/3/2008

  22. Opinion poll Sampling No incentive to be truthful Equally weighted information Hard to be real-time Ask Experts Identifying experts can be hard Incentives Combining opinions can be difficult Prediction Markets Self-selection Monetary incentive and more Money-weighted information Real-time Self-organizing Non-Market Alternatives vs. Markets NYU Stern 2/3/2008

  23. Machine learning/Statistics Historical data Past and future are related Hard to incorporate recent new information Prediction Markets No need for data No assumption on past and future Immediately incorporate new information Non-Market Alternatives vs. Markets NYU Stern 2/3/2008

  24. $1 if $0 otherwise Function of Markets 2: Risk Management • If is terrible to me, I buy a bunch of • If my house is struck by lightening, I am compensated. NYU Stern 2/3/2008

  25. Risk Management Examples • Insurance • I buy car insurance to hedge the risk of accident • Futures • Farmers sell soybean futures to hedge the risk of price drop • Options • Investors buy options to hedge the risk of stock price changes NYU Stern 2/3/2008

  26. Financial Markets vs. Prediction Markets NYU Stern 2/3/2008

  27. Does it work? • Yes, evidence from real markets, laboratory experiments, and theory • Racetrack odds beat track experts [Figlewski 1979] • Orange Juice futures improve weather forecast [Roll 1984] • I.E.M. beat political polls 451/596 [Forsythe 1992, 1999][Oliven 1995][Rietz 1998][Berg 2001][Pennock 2002] • HP market beat sales forecast 6/8 [Plott 2000] • Sports betting markets provide accurate forecasts of game outcomes [Gandar 1998][Thaler 1988][Debnath EC’03][Schmidt 2002] • Market games work [Servan-Schreiber 2004][Pennock 2001] • Laboratory experiments confirm information aggregation[Plott 1982;1988;1997][Forsythe 1990][Chen, EC’01] • Theory: “rational expectations” [Grossman 1981][Lucas 1972] • and more … NYU Stern 2/3/2008

  28. An Incomplete List of Prediction Markets • Real Money • Iowa Electronic Markets (IEM), http://www.biz.uiowa.edu/iem/ • TradeSports, http://www.tradesports.com • InTrade, http://www.intrade.com • Betfair, http://www.betfair.com/ • Gambling markets? sports betting, horse racetrack … • Play Money • Hollywood Stock Exchange (HXS), http://www.hsx.com/ • NewsFutures, http://www.newsfutures.com • Yahoo!/O’REILLY Tech Buzz Game, http://buzz.research.yahoo.com • World Sports Exchange (WSE), http://www.wsex.com/ • Foresight Exchange, http://www.ideosphere.com/ • Inkling Markets http://inklingmarkets.com/ • Internal Prediction Markets • HP, Google, Microsoft, Eli-Lilly, Corning … NYU Stern 2/3/2008

  29. What is being traded?the “good” Define: Random variable Payoff function Payoff output How is it traded?the “mechanism” Call market Continuous double auction Continuous double auction w/ market maker Pari-mutuel market Bookmaker Combinatorial Automated market maker Contracts and Mechanisms NYU Stern 2/3/2008

  30. Contracts • Random variables (Questions to ask) • Binary, Discrete • Tomorrow or • Sales revenue < $100k, $100k - $200k, >$200k • Continuous • interest rate, temperature, vote share … • Clarity • “Clinton wins” • “Saddam out” NYU Stern 2/3/2008

  31. $1 if $1  vote share Contracts • Payoff functions • Winner-takes-all (Arrow-Debreu) • Index, continuous • Dividend, pari-mutuel, option: max[0, s-k], arbitrary function • Payoff output • Real money, play money, prize, lottery NYU Stern 2/3/2008

  32. Call Market and CDA • Call market • Stock market mechanism before 1800 • Orders are collected over a period of time; collected orders are matched at end of period • Price is set such that demand=supply • Continuous double auction (CDA) • Current stock market mechanism • Buy and sell orders continuously come in • As soon as bid  ask, a transaction occurs • IEM, TradeSports, NewsFutures NYU Stern 2/3/2008

  33. CDA with Market Maker • Same as CDA, but with a market maker • A market maker is an extremely active, high volume trader (often institutionally affiliated) who is nearly always willing to buy at some price p and sell at some price q ≥ p • Market maker essentially sets prices; others take it or leave it • Market maker bears risk, increases liquidity • HXS, WSE NYU Stern 2/3/2008

  34. A B Pari-Mutuel Market • E.g. horse racetrack style wagering • Two outcomes: A B • Wagers: [Source: Pennock] NYU Stern 2/3/2008

  35. A B Pari-Mutuel Market • E.g. horse racetrack style wagering • Two outcomes: A B • Wagers:  [Source: Pennock] NYU Stern 2/3/2008

  36. A B Pari-Mutuel Market • E.g. horse racetrack style wagering • Two outcomes: A B • Wagers:  [Source: Pennock] NYU Stern 2/3/2008

  37. Bookmaker • Common in sports betting, e.g. Las Vegas • Bookmaker is like a market maker in a CDA • Bookmaker sets “money line”, or the amount you have to risk to win $100 (favorites), or the amount you win by risking $100 (underdogs) • Bookmaker makes adjustments considering amount bet on each side &/or subjective prob’s • Alternative: bookmaker sets “game line”, or number of points the favored team has to win the game by in order for a bet on the favorite to win; line is set such that the bet is roughly a 50/50 proposition NYU Stern 2/3/2008

  38. Outline • Introduction to prediction markets • What is a prediction market? • Functions of markets • Contracts and mechanisms • Prediction market examples • Iowa Electronic Markets • Yahoo! Tech Buzz Game • Looking forward • Decision markets • Combinatorial markets NYU Stern 2/3/2008

  39. Iowa Electronic Markets (IEM) http://www.biz.uiowa.edu/iem 2008 U.S. Presidential Democratic Nomination Markets $1 if Hillary Clinton wins $1 if Barack Obama wins $1 if “other” wins $1 if John Edwards wins [source: http://iemweb.biz.uiowa.edu/graphs/graph_DConv08.cfm, as of 2/2/08] NYU Stern 2/3/2008

  40. IEM Winner Takes All Market 2008 US Presidential Election WTA Market $1 if Democrat votes > Repub $1 if Republican votes > Dem price=E[R]=Pr(R)=0.415 [Source: http://www.biz.uiowa.edu/iem/, as of 2/2/08] NYU Stern 2/3/2008

  41. IEM Vote Share Market 2008 US Presidential Election Vote Share Market $1  vote share of Dem $1  vote share of Repub price=E[VS of Repub]=48.8% [Source: http://www.biz.uiowa.edu/iem/, as of 2/2/08] NYU Stern 2/3/2008

  42. [Source: Berg, DARPA Workshop, 2002] IEM 1992 NYU Stern 2/3/2008

  43. [Source: Berg, DARPA Workshop, 2002] Example: IEM NYU Stern 2/3/2008

  44. [Source: Berg, DARPA Workshop, 2002] Example: IEM NYU Stern 2/3/2008

  45. Tech Buzz Game http://buzz.research.yahoo.com • Yahoo!,O’Reilly launched Buzz Game 3/05 @ETech • Research testbed for investigating prediction markets • Buy “stock” in hundreds of technologies • Earn dividends based on search “buzz” at Yahoo! Search • Mechanism: dynamic pari-mutuel market NYU Stern 2/3/2008

  46. iPod phone Another Apple unveiling 10/12; iPod Video 8/28: buzz gamersbegin biddingup iPod phone 9/7: AppleannouncesRokr 8/29: Appleinvites pressto “secret”unveiling 9/8-9/18: searchesfor iPod phone soar;early buyers profit 9am 10/5 Technology Forecasts price searchbuzz NYU Stern 2/3/2008

  47. Tech Buzz Game Performance Based on data from 9/29/05 to 1/27/06, 175 stocks in 44 markets NYU Stern 2/3/2008

  48. Outline • Introduction to prediction markets • What is a prediction market? • Functions of markets • Contracts and mechanisms • Prediction market examples • Iowa Electronic Markets • Yahoo! Tech Buzz Game • Looking forward • Decision markets • Combinatorial markets NYU Stern 2/3/2008

  49. Predicting the CEO • Will Mr. Smith or Ms. Jones be the CEO of company X? $1 if Mr. Smith becomes CEO Pr(Mr. Smith) $1 Pr(Ms. Jones) $1 if Ms. Jones becomes CEO NYU Stern 2/3/2008

  50. Predicting CEO Outcomes • How will CEO affect stock prices? • Alternatively, $1 if Mr. Smith becomes CEO & stock price goes up $1 if Mr. Smith becomes CEO & stock price goes down $1 if Ms. Jones becomes CEO & stock price goes up $1 if Ms. Jones becomes CEO & stock price goes down 1 share of stock, if Mr. Smith becomes CEO 1 share of stock, if Ms. Jones becomes CEO NYU Stern 2/3/2008