Prediction Market: Overview, Types, Examples (2024)

What Is a Prediction Market?

A prediction market is a market where people can trade contracts that pay based on the outcomes of unknown future events. The market prices generated from these contracts can be understood as a kind of collective prediction among market participants. These prices are based on the individual expectations and willingness of investors to put their money on the line for those expectations.

The Iowa Electronic Markets (operated by faculty at the University of Iowa Henry B. Tippie College of Business) are among the better-known prediction markets in operation.

Key Takeaways

  • Prediction markets are markets where contracts that are contingent on the occurrence of events in the future can be traded.
  • These contracts are similar to bets on uncertain events, and prediction markets are also known as betting markets.
  • They are used to bet on a variety of instances and circ*mstances, from the outcome of presidential elections to the results of a sporting event.
  • Prediction markets depend on scale; the more individuals participate in the market, the more data there is, and the more effective they become.
  • The Iowa Electronic Markets and PredictIt are both well-known examples of prediction markets.

Understanding a Prediction Market

Prediction markets are similar to futures markets for commodities or other financial asset prices. In futures markets, traders bid up or down the price of a future contract based on their expectation of what the future price of the underlying asset will be. Prediction markets are just futures markets where the future event being traded upon is something other than the price of an asset at some point in the future. Prediction markets involve a collection of people speculating on a variety of events—exchange averages, election results, quarterly sales results, or even gross movie receipts.

Robin Hanson, a professor at George Mason University, is an advocate of prediction markets. He makes the case for prediction markets by emphasizing the removal of reliance on self-interested punditry by so-called experts. "Instead, let us create betting markets on most controversial questions, and treat the current market odds as our best expert consensus. The real experts (maybeyou), would then be rewarded for their contributions, while clueless pundits would learn to stay away," Hanson says on his web page.

The price in a prediction market is a bet that a particular event will occur. It also represents an estimated value that the person placing the bet assigns to the parameters being considered in the bet. Unlike public markets, where bets are placed indirectly on intangibles, such as government policy or the possible outcomes of an election (via the effects these things are expected to have on asset prices), prediction markets enable users to bet directly on a piece of information that they believe is valuable.

For example, it is impossible for a speculator to bet directly on an election in the U.S. Instead, the trader will have to find stocks that might increase in value if a certain candidate is elected. However, prediction markets allow traders to bet directly on the possibility of actual candidates being elected to office.

The oldest online prediction market is the Iowa Electronic Markets, run by the University of Iowa. Launched in 1988, it has been used to forecast the results of presidential elections with greater accuracy than traditional opinion polls.

Uses of Prediction Markets

Because they represent a wide variety of thoughts and opinions—much like the markets as a whole—prediction markets have proven to be quite effective as a prognostic tool. As a result of their visionary value, prediction markets (sometimes referred to as virtual markets) have been utilized by a number of large companies.

The blending of economics, politics, and more recently, cultural factors, has only made the demand for prediction even greater. Add the benefits of data analytics and artificial intelligence; we're living in the golden age of data and statistical utility.

Over the past 50 years, prediction markets have moved from the private domain to the public. Prediction markets can be thought of as belonging to the more general concept of crowdsourcing. Crowdsourcing is specifically designed to aggregate information on particular topics of interest. The main purpose of prediction markets is eliciting aggregating beliefs over an unknown future outcome. Traders with different beliefs trade on contracts whose payoffs are related to the unknown future outcome; the market prices of the contracts are considered as the aggregated belief.

In theory, by pulling information from every available source, estimation methods should improve and become more accurate and consistent. In reality, as we're currently learning, data manipulation brings a host of new ethical and human biases. As leaders of all varieties help everyday individuals trust and appreciate prediction markets, their use and effectiveness will only improve further.

Types of Prediction Markets

There are several models for prediction markets, depending on the mechanism and frequency of forecasting.

Continuous Double Auction

A continuous double auction is a type of trading mechanism to match buyers to sellers, much like the stock market. In the case of prediction markets, traders can buy or sell their bets on a certain outcome, with the price rising or falling if that outcome appears more or less likely. This requires the operator of the prediction market to maintain a ledger of each trade, delivering the payoff to the final owner of each bet.

Automated Market Makers

An automated market maker is used to provide liquidity for markets where there may not be enough buyers or sellers. In this system, the operator of the prediction market acts as a counterparty to all trades, similar to the "house" in a casino. With each trade, the operator can adjust the payoffs, based on the number of bets placed on each outcome. This system is commonly used in sports betting.

Play Money Markets

While most prediction markets rely on using real money to incentivize accurate forecasts, this can run into trouble in jurisdictions where online gambling is illegal. Some prediction markets allow trades in virtual tokens instead of money, with prizes or other incentives to players that collect the most tokens. This allows markets to operate legally, while providing a low-risk platform for traders.

Blockchain-Based Prediction Markets

Developments in blockchain technology have enabled the creation of decentralized prediction markets that can operate without being controlled by a single party or operator. Typically, these markets use smart contracts to mediate bets between different traders, and a complex voting system to determine the final outcome.

Decentralized prediction markets have attracted controversy, both for ethical reasons and the possibility of manipulation. Augur, one of the first decentralized prediction markets, became infamous after traders began betting on the deaths of political figures, raising the possibility that it might become an "assassination market."

Other Crowdsourcing Methods

There are also less formal ways to crowdsource forecasting, such as opinion polls or betting without rewards. These options offer a convenient way to collect crowd forecasts, without a financial incentive for correct forecasting.

Benefits of Prediction Markets

Although they are sometimes controversial, the advantage of prediction markets is that they can benefit from the wisdom of crowds. By collecting and weighing the predictions of a large number of traders, they can provide a market-wide forecast that is generally more reliable and balanced than any single expert opinion. The potential payoffs incentivize traders to reach accurate predictions.

Many real-world securities are traded with the same mechanism as bets in a prediction market. Binary options trades represent a bet on the likelihood of a real-world event, with the price rising or falling as the likelihood of each outcome changes.

Prediction markets raise ethical questions as well as legal ones. One of the latest online markets is the blockchain-based Augur, whose betting pools were described as an "assassination market."

Real-World Example of Prediction Markets

One of the pioneers of online predictions markets is the Iowa Electronic Market (IEM), an experiment in market-based forecasting run by faculty of the University of Iowa's Tippie School of Business. Using real money, speculators on the IEM have been able to forecast the outcome of presidential elections with greater long-run accuracy than traditional opinion polls.

The IEM is not regulated by either the CFTC or the SEC, and regulators have issued two no-action letters stating that they would not attempt to regulate it. This was due to the academic nature of the IEM, and the fact that it is not operated for profit.

What Role Do Prediction Markets Play in Economics?

Prediction markets can be used to create crowd-sourced forecasts, collecting predictions from dozens or hundreds of traders rather than a handful of experts. Traders "vote" by placing bets on what they believe is the most likely outcome, thereby causing the price of that outcome to rise or fall. This market mechanism effectively turns the share price for each outcome into a crowdsourced estimate of that outcome's probability.

What Is a Decentralized Prediction Market?

A decentralized prediction market is a prediction market that can operate without the control or management of any one central operator. Typically, these markets operate through blockchain-based smart contracts that can self-execute in order to distribute payoffs.

Prediction Market: Overview, Types, Examples (2024)

FAQs

Prediction Market: Overview, Types, Examples? ›

There are four types of prediction markets: Continuous Double Auction, Automated Market Makers & Market Scoring Rules, Real Money vs. Play Money, Other Crowdsourced Forecasting Methods. A well-known public prediction market is Predictlt

Predictlt
PredictIt is a New Zealand-based online prediction market that offers exchanges on political and financial events. PredictIt is owned and operated by Victoria University of Wellington with support from Aristotle, Inc.
https://en.wikipedia.org › wiki › PredictIt
.

What is an example of a predictive market? ›

Example #1

Let's say there is a market prediction for the outcome of a presidential election in the U.S. Where the market operates on a binary outcome, meaning that the only two possible outcomes are candidate A winning or candidate B winning. Therefore, this market opens with an initial price for each outcome.

What are the methods of market prediction? ›

Prediction methodologies fall into three broad categories which can (and often do) overlap. They are fundamental analysis, technical analysis (charting) and machine learning.

What is the prediction of the market? ›

A prediction market is a market where people can trade contracts that pay based on the outcomes of unknown future events. The market prices generated from these contracts can be understood as a kind of collective prediction among market participants.

What is a prediction market platform? ›

Prediction markets are financial platforms where participants bet on the outcome of various future events, from elections to commodity prices. Prices in these markets reflect the collective belief about the likelihood of each outcome.

What is predictive segmentation examples? ›

This type of segmentation divides customers based on their past behavior, such as purchase history, website interactions, and engagement with marketing campaigns. For example, an online streaming service can predict user preferences based on viewing habits, content ratings, and time spent on different genres.

What are the four types of prediction? ›

The four basic types are time series, causal methods (like econometric), judgmental forecasting, and qualitative methods (like Delphi and scenario planning).

How do you predict market structure? ›

How Do You Analyze the Market Structure? The most basic form of analysis is to identify higher highs, higher lows, lower highs, and lower lows. Within these four basic structures, you can identify further price patterns like head and shoulders, double tops, triangles, flags, and pennants.

How to predict future markets? ›

Trend analysis, a fundamental aspect of stock market study, empowers investors to predict future market movements based on past data. Whether it's short-term, intermediate-term, or long-term trends, understanding the trajectory of market movements is essential for maximising returns and minimizing risks.

Is it possible to predict the market? ›

Key Takeaways. Predicting the market is challenging because the future is inherently unpredictable. Short-term traders are typically better served by waiting for confirmation that a reversal is at hand, rather than trying to predict a reversal will happen in the future.

Why are prediction markets important? ›

The primary purpose of these markets is to forecast future events, and the contracts are designed to facilitate extracting information used in forecasting.

Can someone predict the market? ›

No one can predict how financial markets will behave with absolute certainty.

What is price prediction model? ›

What is price prediction? Price prediction uses an algorithm to analyze a product or service based on its characteristics, demand, and current market trends. Then the software sets a price at a level it predicts will both attract customers and maximize sales.

Which of the following are examples of predictive analysis? ›

Popular predictive analytics models include classification, clustering, and time series models. Classification models fall under the branch of supervised machine learning models. These models categorize data based on historical data, describing relationships within a given dataset.

What is an example of a predictive survey? ›

For example, if you would like to collect the gender or sex of the respondent, on asking just gender as the question, pre-defined answer responses populate automatically. Another example of predictive survey questions is demographic information questions such as age, race or ethnicity, occupation, etc.

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