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Matt Burgess iPredict Presentation to Treasury Prediction market walkthrough About prediction markets Theory and evidence Public policy analysis [email protected] 12 May 2009 1 iPredict Presentation to Treasury Prediction Markets Definition A prediction market is a speculative marktfket for con trac ts thtildthat yield paymen ts conditional on the outcome of future events [email protected] Example • Contract A pays $1 if the MetService says it ra ins in We lling ton to day. Otherw ise this contract pays $0. $0.45 Price $0.00 $1.00 Likelihood 0% 100% 45% Price = Prediction [email protected] 12 May 2009 2 iPredict Presentation to Treasury Contract Type: Binary • Binary Stock – Pays either $0 or $1 – Price interpretation: percentage likelihood contract will be decided as true •Example: – “This contract pays $1 if Meteira Turei is appointed Greens co-leader,,$ $0 otherwise” – Current price = 85 cents – Interpretation: 85% chance Ms Turei will be Greens co-leader [email protected] Contract Type: Indexed • Indexed Stock – Generally pay s betw een $0 and $1 – Price interpretation: expected value •Example: – “This contract pays $0.01 for each 0.1% of unemployment in September 09 quarter” – Cti66tCurrent price = 66 cents – Interpretation: Forecast unemployment rate in September 2009 quarter is 6.6% [email protected] 12 May 2009 3 iPredict Presentation to Treasury Contract Type: Conditional • Conditional Stock – Pays out on one event but conditional on a second event •Example: – “This contract pays $0.01 for each 0.1% of the [[y]Party X] vote in the Mt Albert electorate conditional on [Candidate Y] being selected. Otherwise this contract pays $0.” – Interpretation: Stay tuned [email protected] Current Predictions • GDP growth to be positive in Sep ‘09 (42%), Dec ‘09 (67%), Mar ‘10 (79%), Jun ‘10 (80%) • OCR: 53% likely to be increased any time before Jul ‘10; 76% likely to go below 2.5% in ’09; 17% likely to go below 2.0% • Unemployment: Jun 09 5.5%; Sep 09 6.6%; Dec 09 7.0% • Mt Albert: Labour 83% likely to win, National 17%, Greens ~0%; Forecast vote L 44%, N 35% • OCR 11 June: NC 79%; 25pt ↓ 18%; 50pt ↓ 2% • NZ Credit Downgrade before July: 19% likely • WHO to raise swine flu alert to phase 6 in 2009: 40% • World temps: 69% likely to be warmer in ’09 than ’08; only 6% likely that 2009 is warmest ever [email protected] Source: iPredict, 3:30pm 11/5/09 12 May 2009 4 iPredict Presentation to Treasury iPredict Walkthrough 12 May 2009 5 iPredict Presentation to Treasury 12 May 2009 6 iPredict Presentation to Treasury 12 May 2009 7 iPredict Presentation to Treasury 12 May 2009 8 iPredict Presentation to Treasury 95% September 9,10 – Owen Glenn Saga 50% PETERS.RESIGN PM: no decision yet 90% 45% Peters testimony 85% 40% 80% 35% Glenn 75% testimony 30% PM. LABOUR 70% 25% 65% 20% Tue Tue Wed Wed Wed Wed Thu Thu Thu Thu Fri 12:00 18:00 00:00 06:00 12:00 18:00 00:00 06:00 12:00 18:00 00:00 9 September Source: ipredict.co.nz Properties of Trade (1/2) Aggregates distributed information and summarises it in a market price 1. Encourages truthful revelation 2. Encourages timely revelation 3. Creates entry bias in favour of the informed 4. Creates incentives for information discovery [email protected] 12 May 2009 9 iPredict Presentation to Treasury Properties of Trade (2/2) 5. Manipulation creates (or magnifies) itifincentives for correc tion 6. Does not require all traders to be rational – a few will do 7. Does not require all traders to be informed – a few will do 8. Markets do not require many traders to be efficient – 7 is enough (Vernon Smith) [email protected] Wisdom of Crowds • Prediction markets • Wikipedia • askagent.com/Mechanical Turk • Digg.com/delicious.com/stumbleupon.com • Open source software • “Ask the audience” [email protected] 12 May 2009 10 iPredict Presentation to Treasury Conditions for Crowd Wisdom 1. Diversity – people have different perspectives about the issue or question at hand 2. Independence – people possess independent information, and are not inter-dependent by way of hierarchy or any other way 3. Decentralization – people are able to specialize and draw on local knowledge 4. Aggregation mechanism – combines all pieces of information into a one coherent entity Source: The Wisdom of Crowds (Surowiecki, 2004) [email protected] About Prediction Markets 12 May 2009 11 iPredict Presentation to Treasury Theory • Hayek (1945), “The Use of Knowledge in Society,” American Economic Review – “The economic problem of society… [is] how to secure the best use of resources known to any of the members of society, for ends whose relative importance only these individuals know” – Essential insight: price is a mechanism for communicating information • Efficient market hypothesis [email protected] First implementation • Prediction markets invented 1988 by RbiHRobin Hanson – University of Iowa “Iowa Electronic Markets” (IEM) – Predicted every US election [email protected] 12 May 2009 12 iPredict Presentation to Treasury New Zealand – iPredict • Mid 2005: run a real money prediction marktket on ’05l’05 elec tion • 2005-2008 – legal hurdles – software development • Owned by Victoria University (75%) and Institute for the Study of Competition and Regulation (25%) [email protected] iPredict • Securities Commission authorisation received Aug 2008 – Declared iPredict a futures dealer under Securities Markets Act – Conditions: politics/economics/business/social issues only – $1000/user/6 months – Users must be NZers in NZ • Launched 9 September 2008 [email protected] 12 May 2009 13 iPredict Presentation to Treasury Where don’t prediction markets work? • When information is privately held • When the insider problem is severe [email protected] Prediction Market Research 12 May 2009 14 iPredict Presentation to Treasury Error (SSE) Poll iPredict iPredict Thu 11 Sep 08 Colmar Brunton 0.0077 0.0023 9 Sun 14 Sep 08 Morgan 0.0019 0.0040 Wed 17 Sep 08 Neilsen 0.0061 0.0023 9 vs. Wed 24 Sep 08 Digipoll Herald 0.0056 0.0029 9 Thu 25 Sep 08 TNS TV3 0.0028 0.0026 9 Polls: Thu 2 Oct 08 Colmar Brunton 0.0060 0.0032 9 Sun 5 Oct 08 Morgan 0.0037 0.0029 9 Party Wed 8 Oct 08 TNS TV3 0.0030 0.0025 9 Thu 9 Oct 08 Colmar Brunton 0.0046 0.0036 9 Tue 14 Oct 08 Neilsen 0.0046 0.0021 9 Vote Thu 16 Oct 08 Colmar Brunton 0.0039 0.0020 9 Sun 19 Oct 08 Morgan 0.0031 0.0012 9 Mon 20 Oct 08 TNS TV3 0.0020 0.0022 Comparison uses Sum of Wed 22 Oct 08 Digipoll Herald 0.0051 0.0025 9 Squared Errors (SSE) Thu 23 Oct 08 Colmar Brunton 0.0011 0.0036 SSE = Σ(predicted – actual)2 Sun 2 Nov 08 Neilsen 0.0029 0.0013 9 for each party on that date Sun 2 Nov 08 Morgan 0.0020 0.0013 9 Sun 2 Nov 08 Digipoll Herald 0.0019 0.0013 9 Small SSE = more accurate Thu 6 Nov 08 TNS TV3 0.0008 0.0030 Average 0.0036 0.0025 78.9% Performance: Politics Head to head: Polls vs Market All days from the beginning of the market MOST ACCURATE 1988 1992 1996 2000 2004 All Poll 25 43 21 56 110 255 Market 34 108 136 173 258 709 Market Percentage 58% 72% 87% 76% 70% 74% More than 100 days before election Poll 1203 26692 Market 13 49 30 47 129 268 Market Percentage 93% 71% 91% 96% 66% 74% Last 5 days before election Poll 01481225 Market 6 5 7 17 18 53 Market Percentage 100% 83% 64% 68% 60% 68% Source: "When Markets Beat The Polls" - Scientific American - March 2008, p. 30 [email protected] 12 May 2009 15 iPredict Presentation to Treasury Performance vs Experts • Orange juice futures improve weather forecas t (Ro ll ‘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) [email protected] Obama for President Stock Peak: $0.68 15 Jul Iowa 3 Jan Ohio,RI, NC Texas,Vt 6 May SC 4 Mar 26 Jan D.C., Md,Va 12 Feb Super Tuesday 5 Feb NH 8 Jan Florida 29 Jan 20 Aug 08 Source: intrade.com 12 May 2009 16 iPredict Presentation to Treasury Source: ipredict.co.nz Election Winner 35% 99% 30% 94% National Win 25% 89% 20% 84% 15% 79% Labour Win 10% 74% % Chance Peters Returned 5% 69% 0% 64% 18:00 19:00 20:00 21:00 22:00 23:00 00:00 Election Night Source: ipredict.co.nz 12 May 2009 17 iPredict Presentation to Treasury PowellDole Republican Republican Candidate Candidate vs vs Clinton Re-Election, 1996 Powell Withdraws 8 Nov 95 Google Study • Internal markets asking questions like how many users sign up to Gma il; w hen w ill next office open • Information can be inferred from trading patterns [email protected] 12 May 2009 18 iPredict Presentation to Treasury Conditional Analysis Republican Democrat Vote Share Implied Expected Candidate Vote Against This Probability This Share of Share (Contract Candidate Candidate Wins Popular Vote If Price) (Contract Price) Nomination Nominated A B C = A + B D = A / C John Kerry $0.344 $0.342 68.6% 50.1% John Edwards $0.082 $0.066 14.8% 55.4% Howard Dean $0. 040 $0. 047 87%8.7% 46. 0% Wesley Clark $0.021 $0.025 4.6% 45.7% Other Democrats $0.015 $0.017 3.2% 46.9% Source: Intrade closing contract prices 29 January 2004, Wolfers & Zitzewitz (2004) [email protected] 12 May 2009 19 iPredict Presentation to Treasury Policy Analysis • How to test policy using conditional contracts – E.
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