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Smarter Markets: Bringing Intelligence into the Exchange Example: Smarter Prediction Markets

Smarter Markets: Bringing Intelligence into the Exchange Example: Smarter Prediction Markets. David Pennock Microsoft Research. NYSE 1926. http:// online.wsj.com /article/SB10001424052748704858404576134372454343538. html. NYSE 1987.

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Smarter Markets: Bringing Intelligence into the Exchange Example: Smarter Prediction Markets

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  1. Smarter Markets: Bringing Intelligence into the ExchangeExample: Smarter Prediction Markets David PennockMicrosoft Research

  2. NYSE 1926 http://online.wsj.com/article/SB10001424052748704858404576134372454343538.html

  3. NYSE 1987 http://online.wsj.com/article/SB10001424052748704858404576134372454343538.html

  4. NYSE 2006-2011 • 2011 Deutsche BörseAG • 2007 Euronext • 2006 Archipelago, ipo

  5. NYSE 7pm Sep 10, 2012

  6. New Markets – Same CDA

  7. 2012 September107:23p.m. ET

  8. 2012 September107:23p.m. ET Between 3.0% and 3.7% chance

  9. http://www.predictwise.com/maps/2012president

  10. Goals for trade Efficiency (gains) Inidiv. rationality Budget balance Revenue Comp. complexity Equilibrium General, Nash, ... Design for Prediction

  11. Goals for trade Efficiency (gains) Inidiv. rationality Budget balance Revenue Comp. complexity Equilibrium General, Nash, ... Goals for prediction Info aggregation 1. Liquidity 2. Expressiveness Bounded budget Indiv. rationality Comp. complexity Equilibrium Rational expectations Design for Prediction Competes with:experts, scoring rules, opinion pools, ML/stats, polls, Delphi

  12. Goals for trade Efficiency (gains) Inidiv. rationality Budget balance Revenue Comp. complexity Equilibrium General, Nash, ... Goals for prediction Info aggregation 1. Liquidity 2. Expressiveness Bounded budget Indiv. rationality Comp. complexity Equilibrium Rational expectations Design for Prediction Competes with:experts, scoring rules, opinion pools, ML/stats, polls, Delphi

  13. Why Liquidity?

  14. Why Liquidity? Low liquidity takes the prediction out of marketshttp://blog.oddhead.com/2010/07/08/why-automated-market-makers/ Between 0.2% and 99.8% chance

  15. Why Expressiveness?

  16. Why Expressiveness?

  17. Why Expressiveness?

  18. Why Expressiveness? • Call option and put options are redundant • Range bets require four trades(“butterfly spread”) • Bid to buy call option @strike 15 can’t match with ask to sell @strike 10 • Can’t set own strike • Bottom line: Lacks expressiveness

  19. Why Expressiveness? • Dem Pres, Dem Senate, Dem HouseDem Pres, Dem Senate, GOP HouseDem Pres, GOP Senate, Dem HouseDem Pres, GOP Senate, GOP House... • Dem PresDem HouseDem wins >=270 electoral votesDem wins >=280 electoral votes...

  20. Industry Standard • Ignore relationships:Treat them as independent markets • Las Vegas sports bettingKentucky horseracingWall Street stock optionsHigh Street spread betting

  21. A Better Way(Or,... Bringing trading into digital age) • Expressiveness • Linear programming • Bossaerts, Fine, Ledyard: Combined Value Trading • http://bit.ly/multipm • Expressiveness + Liquidity • Automated market maker • Always quote a price on anything • Downside: requires subsidy/risk

  22. Example: Liquidityand Expressiveness

  23. Getting Greedy • Design a marketfor information on exponentially many things • “Combinatorial prediction market”

  24. Combinatorial securities:More information, more fun • Payoff is function of common variables,e.g. 50 states elect Dem or Rep

  25. Combinatorial securities:More information, more fun • Dem will win California

  26. Combinatorial securities:More information, more fun • Dem will lose FL but win election • Dem will win >8 of 10 Northeastern states • Same party will win OH & PA PA OH

  27. Combinatorial securities:More information, more fun • There will be a path of blue from Canada to Mexico WA OR

  28. Some Counting 54 “states”: 48 + DC + Maine (2), Nebraska (3) 254= 18 quadrillion possible outcomes 2254 1018008915383333500distinct predictionsMore than a googol, less than a googolplex NOT independent

  29. A tractable combinatorial market maker using constraint generationACM EC 2012 MIROSLAV DUDÍK,SEBASTIEN LAHAIE,DAVID M. PENNOCK Thanks: David Rothschild, Dan Osherson, Arvid Wang, Jake Abernethy, Rafael Frongillo, Rob Schapire

  30. http://PredictWise.com/fantasy

  31. Predictalot alpha

  32. Combo Prediction Markets:More Info Gory detailsWhat is (and what good is) a combinatorial prediction market? http://bit.ly/combopm More accessibleGuest post on Freakonomics http://bit.ly/combopmfreak

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