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Combinatorial Prediction Markets

Combinatorial Prediction Markets. Robin Hanson Economics, George Mason University Chief Scientist, Consensus Point. “Pays $1 if Obama wins”. Will price rise or fall?. sell. E[ price change | ?? ]. buy. price. sell. Lots of ?? get tried, price includes all!. buy.

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Combinatorial Prediction Markets

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  1. Combinatorial Prediction Markets Robin Hanson Economics, George Mason University Chief Scientist, Consensus Point

  2. “Pays $1 if Obama wins” Will price rise or fall? sell E[ price change | ?? ] buy price sell Lots of ?? get tried, price includes all! buy Buy Low, Sell High

  3. Beats Alternatives • Vs. Public Opinion • I.E.M. beat presidential election polls 709/964 (Berg et al ‘08) • Re NFL, beat ave., rank 7 vs. 39 of 1947 (Pennock et al ’04) • Vs. Public Experts • Racetrack odds beat weighed track experts (Figlewski ‘79) • If anything, track odds weigh experts too much! • OJ futures improve weather forecast (Roll ‘84) • Stocks beat Challenger panel (Maloney & Mulherin ‘03) • Gas demand markets beat experts (Spencer ‘04) • Econ stat markets beat experts 2/3 (Wolfers & Zitzewitz ‘04) • Vs. Private Experts • HP market beat official forecast 6/8 (Plott ‘00) • Eli Lily markets beat official 6/9 (Servan-Schreiber ’05) • Microsoft project markets beat managers (Proebsting ’05) • XPree beat corp error, 3.5 vs 6.6%

  4. Advantages Incentives Self-Selection Correct Biases • Numerically precise • Consistent across many issues • Frequently updated • Hard to manipulate • Need not say who how expert when • Issue is not experts vs. amateurs • At least as accurate as alternatives

  5. “Prediction Markets” Market Search Spot Speculative Matching Future Currency Bet Stock Bond Insurance Hedging Decision Gambling Context Direct

  6. To Evaluate Institutions Institution A Institution B When They Use Similar Inputs Compare Quality Of Outputs

  7. Collective Forecasting Forecasts On Requested Topics User Contributions User Scores Engagement

  8. Issues Input: Contributions Output: Forecasts, Scores What questions can ask? How account for value? Use or validate system? Should adjust outputs? Who let see outputs? Sabotage & manipulation Legal, P.R. risks? • What info can express? • How account for costs? • Who let in where? • Enough Incentives • T-shirts enough? • Zero-sum scoring? • Limit Costs • Awkward Interface • Wait for offer accept • Retribution

  9. Collective Forecasting Questions Consensus What exactly is my influence? What exactly are my incentives? My Forecast My Score How exactly do I express my opinion? Truth

  10. Editing Interface Is Transparent If my edit increases the consensus chance of true state, I win. If decreases, I lose. I directly change the consensus Consensus My Edits My Score Truth

  11. Issues Input: Contributions Output: Forecasts, Scores What questions can ask? How account for value? Use or validate system? Should adjust outputs? Who let see outputs? Sabotage & manipulation Legal, P.R. risks? • What info can express? • How account for costs? • Who let in where? • Enough Incentives • T-shirts enough? • Zero-sum scoring? • Limit Costs • Awkward Interface • Wait for offer accept • Retribution

  12. Factors Might Influence Sales E[Sales|Factor] P[Factor] • Economy recovers fast? • Competitors introduce new version? • We do big promotion? • We lower prices? They lower prices? • We add distribution channel? • We add feature F? They add feature F? • Our defect rate very low?

  13. Win Place Show All outcomes Yoopick Facebook Application Combo Betting Show Win Place Not Not Not

  14. Sport Finals Tickets Ticket if Greece in Finals Greece v. Croatia

  15. Politimetrics.com US President Decision Markets

  16. Return to Focus ? Trade IQcs4 IQcs4 < 85 85 03 03 SAum3 105-125 03 Update Payoffs: If & Ave. pay Select New Price 65% Max Up 95.13% +$34.74 -$85.18 -$19.72 Buy 10% Up 68.72% +$2.74 -$3.28 -$1.07 You Pick 65 % +1.43 -2.04 +0.34 Saudi Arabian Economic Health No Trade 62.47% $0.00 $0.00 $0.00 125 30 15 10% Dn 56.79% -$2.61 +$2.74 -$1.12 65 70 Sell Exit Issue 48.54% -$15.34 +$26.02 -$6.31 35 40 100 94 100 Max Dn 22.98% -$120.74 +$96.61 -$22.22 < 85 25 35 35 30 10 10 75 1 2 3 4 1 2 > 03 03 03 03 04 04 ? Return to Form Execute a Trade If US military involvement in Saudi Arabia in 3rd Quarter 2003 is not between 105 and 125, this trade is null and void. Otherwise, if Iraq civil stability in 4th Quarter 2003 is below 85, then I will receive $1.43, but if it is not below 85, I will pay $2.04. Abort trade if price has changed? Execute PAM Scenario

  17. Imagine A Dashboard Ave. Worth: $12,459

  18. Ask For Detail Ave.Worth: $12,459 Them B Ship Date 2009 2010 J F M A M J J A S O N D

  19. Make An Edit Ave. Worth: $12,459 If We Have Autozoop, you gain $53 But if We Don’t Have It You lose $78. OK?

  20. Make an Assumption Scenario: 15% Ave. Worth: $10,724

  21. Add 2nd Assumption Scenario: 2.3% Ave. Worth: $10,982

  22. Edit As Before Scenario: 2.3% Ave. Worth: $10,724 If we have Autozoop, you gain $53 But if we don’t have it You lose $78. OK?

  23. Combo Market Maker Best of 5 Mechs 3 subjects, 7 prices, 5 minutes 6 subjects, 256 prices, 5 minutes

  24. KL(prices,group) 1- KL(uniform,group) MSR Info vs. Time – 7 Prices 1 % Info Agg. = 0 0 5 10 15 Minutes -1

  25. KL(prices,group) 1- KL(uniform,group) MSR Info vs. Time – 255 prices 1 % Info Agg. = 0 0 5 10 15 Minutes -1

  26. Issues Input: Contributions Output: Forecasts, Scores What questions can ask? How account for value? Use or validate system? Should adjust outputs? Sabotage & manipulation Can keep results secret? Legal, P.R. risks? • What info can express? • How account for costs? • Who let in where? • Enough Incentives • T-shirts enough? • Zero-sum scoring? • Limit Costs • Awkward Interface • Wait for offer accept • Retribution

  27. B A f1>1 f2<1 Prices + q1 $1 if A&B - q2 $1 if B User Assets A Simple Implementation States + - LISP: http://hanson.gmu.edu/mktscore-prototype.html

  28. A&B A&B A Simple Implementation States Prices User Assets

  29. Environments: Goals, Training (Actually: X Z Y ) Case A B C 1 1 - 1 2 1 - 0 3 1 - 0 4 1 - 0 5 1 - 0 6 1 - 1 7 1 - 1 8 1 - 0 9 1 - 0 10 0 - 0 Sum: 9 - 3 Same A B C A -- -- 4 B -- -- -- C -- -- -- • Want in Environment: • Many variables, few directly related • Few people, each not see all variables • Can compute rational group estimates • Explainable, fast, neutral • Training Environment: • 3 binary variables X,Y,Z, 23 = 8 combos • P(X=0) = .3, P(X=Y) = .2, P(Z=1)= .5 • 3 people, see 10 cases of: AB, BC, AC • Random map XYZ to ABC

  30. Experiment Environment (Really: W V X S U Z Y T ) Case A B C D E F G H 1 0 1 0 1 - - - - 2 1 0 0 1 - - - - 3 0 0 1 1 - - - - 4 1 0 1 1 - - - - 5 0 1 1 1 - - - - 6 1 0 0 1 - - - - 7 0 1 1 1 - - - - 8 1 0 0 1 - - - - 9 1 0 0 1 - - - - 10 1 0 0 1 - - - - Sum 6 3 4 10 - - - - Same A B C D E F G H A -- 1 2 6 -- -- -- -- B -- -- 7 3 -- -- -- -- C -- -- -- 4 -- -- -- -- D -- -- -- -- -- -- -- -- … • 8 binary vars: STUVWXYZ • 28 = 256 combinations • 20% = P(S=0) = P(S=T) = P(T=U) = P(U=V) = … = P(X=Y) = P(Y=Z) • 6 people, each see 10 cases: ABCD, EFGH, ABEF, CDGH, ACEG, BDFH • random map STUVWXYZ to ABCDEFGH

  31. $ Revenue if Switch $1 $1 if Switch P(S) E(R | S) E(R) Compare! $ Revenue E(R | not S) $ Revenue if not Switch $1 if not Switch Ad Agency Decision Markets

  32. Corporate Applications E[ Revenue | Switch ad agency? ] E[ Revenue | Raise price 10%? ] E[ Project done date | Drop feature? ] E[ Project done date | Add personnel? ] E[ Stock price | Fire CEO? ] E[ Stock price | Acquire firm X? ]

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