Prediction markets, also known as betting markets, information markets, decision markets, idea futures, or event derivatives, are open markets that enable the prediction of specific outcomes using financial incentives (gambling on real world events). They are exchange-traded markets established for trading bets in the outcome of various events. The market prices can indicate what the crowd thinks the probability of the event is. A typical prediction market contract is set up to trade between 0 and 100%. The most common form of a prediction market is a binary option market, which will expire at the price of 0 or 100%. Prediction markets can be thought of as belonging to the more general concept of crowdsourcing which is specially designed to aggregate beliefs on particular topics of interest. The main purpose of prediction markets are eliciting aggregating beliefs about an unknown future event. Traders with different beliefs trade on contracts whose payoffs are related to the unknown future outcome and the market prices of the contracts are considered as the aggregated belief.

Before the era of scientific polling, early forms of prediction markets often existed in the form of political betting. One such political bet dates back to 1503, in which people bet on who would be the papal successor. Even then, it was already considered "an old practice". According to Paul Rhode and Koleman Strumpf, who have researched the history of prediction markets, there are records of election betting in Wall Street dating back to 1884. Rhode and Strumpf estimate that average betting turnover per US presidential election is equivalent to over 50 percent of the campaign spend.^{[citation needed]}

Economic theory for the ideas behind prediction markets can be credited to Friedrich Hayek in his 1945 article "The Use of Knowledge in Society" and Ludwig von Mises in his "Economic Calculation in the Socialist Commonwealth". Modern economists agree that Mises' argument, combined with Hayek's elaboration of it, is correct. Prediction markets are championed in James Surowiecki's 2004 book The Wisdom of Crowds, Cass Sunstein's 2006 Infotopia, and Douglas Hubbard's How to Measure Anything: Finding the Value of Intangibles in Business.

Prediction markets are based on the theory that individuals with financial stakes in an outcome can collectively predict it more accurately than any single expert. Eric Zitzewitz, an economics professor at Dartmouth, explains "Financial markets are generally pretty efficient, and the evidence suggests that the same is true of prediction markets. There’s no virtue-signaling in an anonymous market when you're betting[. ...W]hat you're seeing with the market is some average of all of those different opinions, weighted by their willingness to put their money where their mouth is."

While prediction markets tend to perform better than polling for the prediction of election outcomes, a study found that belief aggregation of participants who are asked to quantify the strength of their belief can beat prediction markets. When market participants have some intrinsic interest in trying to predict results, even markets with modest incentives or no incentives have been shown to be effective. When the group is more optimistic, they will bet more in aggregate than the pessimists, raising the market price. The movement of the price will reflect more information than a simple average or vote count. Research has suggested that prediction markets' greater accuracy lies largely in superior aggregation methods rather than superior quality or informativeness of responses.

James Surowiecki posits three necessary conditions for collective wisdom: diversity of information, independence of decision, and decentralization of organization. In the case of a predictive market, each participant normally has diversified information from others and makes their decision independently. The market itself has a character of decentralization compared to expert decisions. For these reasons, a predictive market is generally a valuable source to capture collective wisdom and make accurate predictions.^{[citation needed]}

Prediction markets can aggregate information and beliefs of the involved investors and give a good estimate of the mean belief of those investors. The latter have a financial incentive to price in information. This allows prediction markets to incorporate new information quickly and makes them difficult to manipulate.

Numerous researchers have studied the accuracy of prediction markets: