Prediction Markets: What They Are and How They Work

Prediction markets let participants estimate the probability of future events through market mechanisms. Rather than relying on dozens of forecasts about elections, central bank interest rates, the price of Bitcoin, or the outcome of a sporting event, users can see how the market prices a specific outcome. These platforms are often referred to as information markets because market prices reflect the collective expectations of participants and adjust continuously as new information emerges.

The concept isn’t new. Iowa Electronic Markets (IEM), an academic election forecasting platform launched by the University of Iowa’s Tippie College of Business in 1988, is widely regarded as the world’s oldest prediction market. Regulated event contract markets have existed for more than 2 decades, but interest in the model accelerated with the rise of decentralized platforms. These platforms use blockchain technology to record transactions, determine outcomes, and settle contracts without relying on a centralized operator.

What Is a Prediction Market

Most prediction markets use binary contracts with 2 possible outcomes: Yes or No. If the event occurs, the winning contract settles at a fixed value, typically $1, while the losing contract becomes worthless. If the event doesn’t occur, the opposite happens.

The model consists of 4 core elements:

1. Event. A question with a predefined resolution date or condition.
2. Outcomes. The possible results to which probabilities are assigned.
3. Contracts. The instruments participants buy and sell.
4. Settlement. The determination of the final outcome based on a predefined resolution source.

What sets prediction markets apart from traditional betting is that they’re built around tradable contracts. Participants don’t have to hold a position until the event is resolved. They can sell a contract before settlement to lock in profits or limit potential losses. Contract prices fluctuate throughout trading and simultaneously reflect the market’s current estimate of an outcome’s probability. For example, if a Yes contract trades at $0.65, the market is effectively assigning a 65% probability to that event.

How Prediction Markets Work

The platform defines an event, sets the settlement rules, and opens trading. Participants then place orders. As new information emerges, whether it’s a poll, a macroeconomic report, a regulator’s statement, an athlete’s injury, or a move in the underlying asset, contract prices adjust accordingly.

The main use cases include:

• Politics: elections, appointments, and voting outcomes.
• Economics: central bank decisions, GDP, inflation, and unemployment data.
• Cryptocurrencies: price targets, exchange listings, and network upgrades.
• Sports and entertainment: matches, tournaments, awards, and box office performance.
• Corporate forecasting: product launch timelines, sales, the achievement of internal targets, and more.

Modern prediction markets generally fall into 2 categories: centralized and decentralized. In decentralized markets, smart contracts and blockchain oracles handle contract issuance, trading, and settlement, while a distributed ledger records every transaction. This makes the platforms more transparent. Among centralized platforms, Kalshi is the largest. Among decentralized platforms, Polymarket leads the market.

According to the Pew Research Center, combined monthly trading volume across Kalshi and Polymarket increased from less than $5 billion in September 2025 to approximately $24 billion in April 2026. Meanwhile, data from Dune and Keyrock covering decentralized platforms only, excluding Kalshi, showed more than $13 billion in notional trading volume, 43 million transactions, and over 600,000 active users in November 2025. As of July 9, 2026, DeFi Rate reported $15.3 billion in notional trading volume over the most recent full week across Kalshi, Polymarket, and Polymarket US, with open interest totaling $1.5 billion.

Contract Prices and Implied Probability

A contract’s price reflects the current balance of supply and demand rather than the objective probability of an event occurring. If market participants believe the likelihood of an event is higher than the current price implies, they buy the contract. If they believe it’s overpriced, they sell. As a result, the market continuously incorporates new information into pricing.

Three key factors influence contract prices:

• The quality and timeliness of information
• Liquidity, meaning a sufficient number of buyers and sellers
• Confidence in the settlement rules and the source used to determine the outcome

In this context, the wording of a contract is critical. For example, the question “Will Bitcoin go up?” isn’t suitable because it can’t be settled objectively. By contrast, “Will BTC trade above $150,000 on Coinbase at 11:59 p.m. UTC on December 31?” can be verified unambiguously. The more precise the contract terms, the lower the risk of disputes after the market closes.

Why Prediction Markets Can Be Accurate

Prediction markets derive their strength from combining collective judgment with financial incentives. Participants put their own money at risk, so they’re motivated not just to express an opinion, but to identify probabilities the market has mispriced. When many people analyze different sources of information and trade against inaccurate pricing, the resulting market signal can be more informative than any individual forecast.

Prediction markets also have a speed advantage. Contract prices respond almost immediately to new information, while surveys capture opinions at a single point in time and official reports are released with a delay. As a result, prediction markets can serve as a valuable complement to traditional analytical tools.

That said, prediction markets don’t guarantee accurate forecasts. When liquidity is low, prices may reflect the views of only a handful of active participants. In niche markets, there may not be enough informed traders to produce reliable pricing. In addition, contract wording and the potential for market manipulation can undermine accuracy, particularly when the underlying event is controversial.

Prediction Markets vs. Betting

Prediction markets share several similarities with sports betting. In both cases, participants take on financial risk tied to the outcome of a future event. The underlying mechanics, however, are fundamentally different. On betting platforms, odds are typically set by the operator. In prediction markets, prices are determined through trading and continue to fluctuate until settlement.

It’s worth noting that sports betting also features live odds, also known as in-play odds, which are continuously updated as an event unfolds. Even so, those odds remain under the control of the bookmaker or platform operator.

Despite their similarities, the 2 models are often subject to different regulatory frameworks. In some jurisdictions, event contracts are treated as financial derivatives. In others, they may fall under gambling regulations. For example, in 2026, the U.S. Commodity Futures Trading Commission (CFTC) requested public comment on the regulation of prediction markets, including permissible contract types and broader public interest considerations.

Risks and Limitations of Prediction Markets

Prediction markets provide valuable insights only when their signals are interpreted correctly. Their main limitations include:

1. Low liquidity. When trading volume is limited, even relatively large orders can have a significant impact on contract prices, reducing their value as an indicator of market expectations.
2. Market manipulation. Individual participants may attempt to influence prices deliberately, creating a distorted perception of an event’s probability.
3. Information asymmetry. Participants with access to material nonpublic information may gain an advantage over the rest of the market.
4. Ambiguous settlement terms. Poorly defined contract wording or unclear settlement rules can lead to disputes once contracts are settled.
5. Regulatory uncertainty. The legal status of prediction markets varies significantly across jurisdictions and depends on the nature of the underlying event.
6. Limited representativeness. Market prices reflect the expectations of participants on a particular platform rather than the views of the broader public or the professional community.

The regulatory risks became particularly clear in February 2026, when the CFTC issued guidance for prediction market participants following 2 investigations into the misuse of material nonpublic information and fraud involving event contracts. The regulator emphasized that prediction markets are fully subject to laws prohibiting market manipulation, fraud, and insider trading.

Putting Prediction Markets Into Perspective

To interpret the signals generated by prediction markets correctly, it’s important to keep several key principles in mind:

1. Prediction markets can’t forecast the future with certainty. Market prices reflect only the current collective estimate of an event’s probability, and that estimate can change as new information becomes available.
2. A high probability isn’t a guarantee. Even if the market assigns an 80% probability to an event, there’s still a chance it won’t happen.
3. Prediction markets work best when outcomes can be verified objectively. The more precisely a contract defines its terms and settlement source, the more useful the market’s pricing becomes.
4. Prediction markets are most valuable when used alongside other sources of information. Their signals should be considered together with research, statistical data, expert analysis, and fundamental factors rather than in isolation.

By 2026, prediction markets had become a meaningful part of the information and financial ecosystem because they offered a simple way to answer a fundamental question: What is the probability of a given event right now? Their value lies in their ability to aggregate market expectations quickly and translate new information into a quantitative signal.

At the same time, the sector’s future development will depend on regulation, the reliability of event resolution, and market liquidity. If platforms continue to improve transparency and meet regulatory requirements, prediction markets are likely to establish themselves not only as speculative instruments but also as a mainstream tool for forecasting and decision-making.