A prediction market is a market for a contract that yields payments based on the outcome of a partially uncertain future event, such as an election. A contract pays $100 only if candidate X wins the election, and $0 otherwise. When the market price of an X contract is $60, the prediction market believes that candidate X has a 60% chance of winning the election. The price of this event derivative represents the imputed perceived likelihood of the partially uncertain event (i.e., its aggregated expected probability). A 60% probability means that, in a series of events each with a 60% probability, the favored outcome is expected to occur 60 times out of 100, and the unfavored outcome is expected to occur 40 times out of 100.
Each prediction exchange organizes its own set of real-money and/or play-money markets, using either a CDA or a MSR mechanism ---with or without an automated market maker.
Prediction markets enable us to attain collective intelligence. Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events by aggregating disparate pieces of information that the traders bring when they agree on prices. The event derivative traders are informed by the primary indicators (i.e., the primary sources of information), like the polls, for instance. These informed speculators then execute their transactions based on their anticipations about the future ---anticipations that will be either confirmed or infirmed.
The value of a set of prediction markets consists in the added accuracy that these prediction markets provide relative to the other forecasting mechanisms, times the value of accuracy in improved decisions, minus the cost of maintaining these prediction markets, relative to the cost of the other forecasting mechanisms. According to Robin Hanson, a highly accurate prediction market has little value if some other forecasting mechanism(s) can provide similar accuracy at a lower cost, or if very few substantial decisions are influenced by accurate forecasts on its topic.
2. The Best Midas Oracle Explainers On Prediction Markets
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Prediction markets produce dynamic, objective probabilistic predictions on the outcomes of future events by aggregating disparate pieces of information that traders bring when they agree on prices. Prediction markets are meta forecasting tools that feed on the advanced indicators (i.e., the primary sources of information). Garbage in, garbage out… Intelligence in, intelligence out…
A prediction market is a market for a contract that yields payments based on the outcome of a partially uncertain future event, such as an election. A contract pays $100 only if candidate X wins the election, and $0 otherwise. When the market price of an X contract is $60, the prediction market believes that candidate X has a 60% chance of winning the election. The price of this event derivative can be interpreted as the objective probability of the future outcome (i.e., its most statistically accurate forecast). A 60% probability means that, in a series of events each with a 60% probability, then 6 times out of 10, the favored outcome will occur; and 4 times out of 10, the unfavored outcome will occur.
Each prediction exchange organizes its own set of real-money and/or play-money markets, using either a CDA or a MSR mechanism.
- Regulation Looms for Prediction Markets. - The Commodity Futures Trading Commission is likely to become involved in regulating event futures—and it just may boost these markets. - by BusinessWeek’s Ricky McRoskey - 2008-07-07
- Mob wisdom means business - So-called ‘crowdsourcing’ lets companies create massive focus groups, garner fresh ideas, and even predict the future. - by InfoWorld’s Lena West - 2007-12-10
- Ask The Market - Companies are leading the way in the use of prediction markets. The public sector may soon follow. - (PDF) - by Region Focus’ Vanessa Sumo - 2007-07-20
Prediction markets: the future of decision-making - Companies are now making business decisions based on information employees provide via internal trading systems. - The Tines of London - 2008-09-04
“We use them ["them" = the enterprise prediction markets] as another point in the decision-making process, alongside asking experts and other business leaders,” said Christina LaComb, a computer scientist in the R&D lab at GE.
