Introduction to Prediction Markets

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  • + LuluP LuluP 6 months ago
    Thanks Alex. this has been really useful for me. I am going to attempt to develop a design strategy for a client who runs the first (if not only) prediction market in New Zealand. Been wondering why people haven’t come up with a better experience design. This has really validated my thinking. Will try to catch you through your blog :)
  • + warrickt Warrick Taylor 2 years ago
    v. useful quick summary - needs v.over though!
  • + dmc500hats Dave McClure 3 years ago
    great presentation... very informative.

    thanks alex :)

    - dave mcclure / http://500hats.typepad.com/
  • + castcase1 castcase1 3 years ago
    I guess such market would be the same as 'gambling', right?





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Notes on slide 1

Welcome. I’m assuming that most people have never heard of, or know very little about prediction markets. Right? Today’s goals basic introduction to prediction markets how they are used, who uses them and what for and to tell what I consider to be a fairly interesting story about how these markets have struggled to become more usable

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Introduction to Prediction Markets - Presentation Transcript

  1. An Introduction to Prediction Markets (a.k.a. Idea Futures, Decision Markets, Information Markets, and Event Markets) alex kirtland / UsableMarkets 25 Mar 2007
  2. Simple Definition of Prediction Markets
    • A place where information is aggregated via market (or other) mechanisms for the primary purpose of forecasting events, or the probability that an event will occur
  3. outcome / contract outcome / contract outcome / contract outcome / contract outcome / contract All Others The “who will win the 2008 presidential election” market the market (the event)
  4. Contract Hillary: Hillary Clinton WILL BE our next president $0.00 $1.00 Price 0% 100% Prediction $0.26 26% Hillary Clinton has a 26% chance, at this point in time, of being our next president.
  5. All Others The “who will win the 2008 presidential election” market the market $0.26 $0.20 $0.18 $0.12 $0.24 26% 20% 18% 12% 24% = 100%
  6.  
  7. Basic Elements of a Prediction Market
    • The Market - Markets are generally created around a specific topic or event, and contain the contracts which are traded. Examples : The “Who will win the 2008 Presidential Election” Market
    • The Contract – A specific prediction that the trader can buy or sell Examples : Hillary Clinton Binary contract pays out all (e.g. $1.00) or nothing (e.g. $0.00) Linear contract pays out based on final value
    • Trading Platform – The way that someone interacts with the market Double Auction / Book Order System Automated Market Maker
  8. Basic Elements of a Prediction Market, cont.
    • Traders – the people who come to a market and participate by buying and selling Marginal traders – knowledgeable traders Noise traders – traders who are not knowledgeable, or have some motivation for trading other than what they think the true price should be.
    • Liquidity – the number of trades
    • Currency –real money or fake money.
  9. Simple Definition of Prediction Markets
    • A place where information is aggregated via market (or other) mechanisms for the primary purpose of forecasting events, or the probability that an event will occur
    • Why?
      • Wisdom of the Crowds – “Under the right conditions groups can be remarkably intelligent and possibly smarter than the smartest person.” James Surowiecki
      • Markets provide incentives for information discovery and truthful revelation of beliefs
      • Efficient Market Hypothesis – all available information incorporated into the price
  10. How are prediction markets different than polls?
  11. Who uses these things? ?
  12.  
  13.  
  14.  
  15.  
  16.  
  17. and others ... .
  18.  
  19.  
  20. Gamers Gamblers Sophisticates Employees Your “Average Joe”
  21. Knows how to trade Doesn’t
  22.  
  23. Most of us Knows how to trade Doesn’t
  24.  
  25.  
  26.  
  27.  
  28.  
  29. Where are we now?
    • No perfect site, but lots of experimentation
    • Industry
    • Corporate
    • A growth industry ...?
  30. Q&A
    • Questions I haven’t answered yet ...
  31. Special Thanks To ...
    • Emile Servan-Schreiber (newsFutures)
    • Ed Lenox (TradeSports)
    • Robert Wilburn (RimDex)
    • Adam Siegel (InklingMarkets)
    • Jed Christiansen (Mercury Research & Consulting)
    • Bo Cowgill (Google)
    • David Pennock (Yahoo)
    • Dave Perry (Consensus Point)
    • Midas Oracle / Chris Masse (Blog)
  32. Thank You!

+ Alex KirtlandAlex Kirtland, 3 years ago

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