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Prediction markets are financial markets where participants buy and sell contracts whose value depends on whether a future event occurs. In 2026, prediction markets have evolved from a niche forecasting experiment into a rapidly expanding financial and information market covering elections, economics, weather, sports and other measurable events. Their growth has also created an important regulatory debate in the United States over whether event contracts should be treated primarily as financial derivatives or as gambling.
This article explains how prediction markets work, why their prices can represent collective expectations, how traders make or lose money, and why regulation has become central to their future.
It also examines the historical development of prediction markets, the role of the Commodity Futures Trading Commission, and the risks created by misinformation, manipulation and privileged information. Understanding these markets requires recognising the difference between forecasting an event and wagering on an outcome, because the same contract can have characteristics associated with both financial speculation and gambling.
Key Takeaways
- Prediction markets convert expectations about future events into tradable market prices.
- Event contracts commonly pay a predetermined amount when a specified outcome occurs.
- Market prices can be interpreted as implied probabilities, although they are not guaranteed forecasts.
- Regulation remains contested as US courts consider whether some event contracts constitute financial derivatives or gambling.
- Prediction markets can provide useful information while exposing participants to substantial financial and behavioural risks.
What are prediction markets?
Prediction markets are organised markets in which participants trade contracts linked to future events. Instead of buying shares in a company or a commodity, a trader purchases a contract based on a proposition such as whether a particular candidate will win an election, whether an economic indicator will exceed a specified level, or whether a defined weather condition will occur.
The fundamental idea is remarkably simple. A contract might pay US$1 if a specified event occurs and US$0 if it does not. If traders are willing to pay US$0.65 for that contract, the market price can broadly be interpreted as indicating a 65 percent implied probability of the event occurring. A trader who believes the true probability is substantially higher might buy the contract, while another participant who believes the probability is lower might sell it.
The price is therefore doing more than representing financial value. It is aggregating information, expectations and risk preferences from participants who have different knowledge and opinions.
The US Commodity Futures Trading Commission, or CFTC, describes these products as event contracts and explains that they can be used for forecasting, planning, hedging and speculation. Event contracts are commonly structured as swaps and can derive their value from the outcome of an underlying event rather than the movement of a conventional financial asset.
This structure helps explain why prediction markets occupy an unusual position between finance, economics, statistics, information science and gambling.
How event contracts work
The easiest way to understand an event contract is to imagine a contract asking whether a particular event will happen before a specified deadline.
Suppose a market asks whether a particular city will record a temperature of at least 100 degrees Fahrenheit during a defined period. A contract that pays US$1 if the condition is satisfied might trade at US$0.40. If a trader buys 1,000 contracts at US$0.40, the position costs US$400. If the event occurs, the contracts pay US$1,000, producing a gross gain of US$600 before applicable fees and other costs. If the event does not occur, the contracts expire without that US$1 payout.
The critical feature is that the trader is not necessarily waiting until the event occurs. Contracts can often be bought and sold before settlement. If new information makes the event appear more likely, the market price may rise. A trader who bought at US$0.40 might therefore sell at US$0.70 rather than waiting for final settlement.
The resulting market resembles a continuously updated forecasting mechanism. News, data releases, polling information, weather forecasts, economic indicators and other information can alter participants’ expectations, which can alter prices.
There is an important limitation, however. A market price is not literally a guaranteed probability. Transaction costs, liquidity, trader incentives, risk preferences and market structure can all cause the price to differ from the statistically correct probability.
Why prediction market prices matter
The appeal of prediction markets comes from information aggregation.
A conventional forecast may come from one economist, one polling organisation or one research team. A prediction market can incorporate information from thousands of participants with different expertise, assumptions and sources.
This is closely related to the economic concept commonly called the wisdom of crowds. Participants have financial incentives to identify information that other traders have overlooked. When a trader believes a market is incorrectly priced, the opportunity to profit can motivate that trader to trade against the prevailing consensus.
The Iowa Electronic Markets provide one of the most important historical examples. Established at the University of Iowa in 1988, the market became a real-money research environment for studying whether markets could forecast political outcomes. Research from the Iowa programme found that its election forecasts compared favourably with traditional polling. The University of Iowa has reported that its market’s presidential vote-share forecasts were closer to eventual outcomes than national polls 74 per cent of the time in a historical comparison.
This does not mean prediction markets always outperform polls, economists or professional forecasters. It demonstrates something more specific: market mechanisms can aggregate dispersed information into a continuously changing numerical signal.
That distinction is important. Prediction markets are not crystal balls. They are information-processing systems in which financial incentives influence how participants express their expectations.
The history of prediction markets
Although modern prediction markets are strongly associated with digital platforms, the underlying concept is considerably older.
People have historically placed wagers on elections, political contests, sporting events and other uncertain outcomes. What distinguishes modern prediction markets is the application of market mechanisms, standardised contracts and electronic trading to the forecasting process.
The modern US prediction-market era is generally traced to the creation of the Iowa Presidential Stock Market in 1988. The University of Iowa developed it as an academic experiment rather than a commercial gambling operation. Participants traded contracts connected to presidential election outcomes, allowing researchers to examine whether market prices could aggregate information efficiently.
The regulatory history subsequently became increasingly important. CFTC staff issued a no-action letter concerning the Iowa market in 1992, while regulated US event-contract markets developed further during the following decades. In 2004, the CFTC approved HedgeStreet as a designated contract market offering binary options. The company later became Nadex.
The 2010 Dodd-Frank Act further shaped the regulatory framework by giving the CFTC authority to prohibit certain event contracts and establishing restrictions concerning contracts considered contrary to the public interest.
The technology changed dramatically after the emergence of internet-based trading platforms. Modern prediction markets can now offer contracts to a much broader audience, provide near-real-time prices and create markets around events that would previously have been difficult to trade.
Prediction markets in 2026
The prediction-market industry has entered a substantially different phase in 2026.
Platforms such as Kalshi and Polymarket have brought event-based trading into mainstream financial and political discussion, while other financial companies have introduced or explored event-contract products. Markets can cover elections, economic statistics, interest rates, weather, cryptocurrency prices, sporting events and other objectively measurable outcomes.
The expansion has also intensified scrutiny from regulators and state governments.
The CFTC maintains that event contracts traded on federally regulated designated contract markets fall within its jurisdiction. In February 2026, the agency publicly reaffirmed its position that it has exclusive jurisdiction over US commodity derivatives markets, including event-contract markets commonly referred to as prediction markets.
The issue has become particularly contentious around sports contracts.
In August 2026, the US Ninth Circuit Court of Appeals ruled that Nevada could regulate Kalshi’s sports-related prediction-market activities under state gambling law. The decision conflicts with an earlier Third Circuit ruling that took a different approach to federal regulatory authority, creating a significant legal disagreement between federal appellate courts.
That conflict could ultimately require intervention by the US Supreme Court. The central question extends beyond one company. It concerns how American law should classify a financial contract whose underlying outcome is an event rather than the price of a traditional financial asset.
Prediction markets versus gambling
The distinction between prediction markets and gambling is one of the most consequential issues facing the industry.
A traditional sports bet normally involves a bettor wagering against a sportsbook. The prediction-market model can instead involve standardised financial contracts traded through an exchange structure.
Supporters argue that this distinction matters because event contracts can serve legitimate financial functions. A company exposed to weather-related revenue risk, for example, could potentially use a weather event contract as part of a broader risk-management strategy.
Recent developments illustrate this possibility. In August 2026, a weather-related block trade on Kalshi involved a company taking a position on whether Houston would reach a specified temperature. The transaction was presented as an example of an event contract potentially functioning as a hedge against commercial weather exposure rather than merely a recreational wager.
Critics argue that the structure of a contract does not automatically determine its economic substance. If a consumer is effectively risking money on whether a football team wins, they argue that the transaction resembles sports betting regardless of whether the platform calls the instrument a derivative.
The Ninth Circuit’s August 2026 decision illustrates the force of this argument, finding that Kalshi’s sports contracts constituted sports gambling for purposes of Nevada law.
The resulting legal uncertainty is likely to remain one of the defining issues for prediction markets during the remainder of the decade.
How traders make money
A trader can potentially profit from a prediction market in two principal ways.
The first is holding a contract until settlement and receiving the predetermined payout if the specified event occurs. The second is trading before settlement, attempting to sell a contract at a higher price than the original purchase price.
Consider a contract purchased for US$0.25. If subsequent information causes its price to rise to US$0.60, the trader could potentially sell before the event is resolved. The trader’s profit would come from the difference between the purchase and sale prices, less fees and other transaction costs.
The reverse is equally important. A trader who buys at US$0.70 and sees the contract fall to US$0.30 faces a substantial unrealised loss if the position is closed at that point. If the contract ultimately resolves against the trader, the loss can approach the original amount invested.
The mathematics can therefore appear simple while the underlying forecasting problem is extraordinarily difficult.
A participant who believes an event has an 80 per cent chance of occurring should not automatically buy an event contract trading at US$0.80. Fees, liquidity and the trader’s own uncertainty matter. A contract may need to trade materially below the trader’s estimated probability to provide a sufficiently attractive expected return.
The importance of market liquidity
Liquidity is fundamental to prediction markets.
A market with substantial trading activity generally allows participants to enter and exit positions more easily. A thin market can produce wider spreads, greater price volatility and prices that may be more sensitive to individual trades.
This creates a critical distinction between a market price and a reliable forecast.
A contract trading at US$0.72 in a deep and liquid market with many independent participants may contain a different information signal from a contract trading at US$0.72 because one participant placed a large order in an otherwise inactive market.
Professional analysis therefore considers trading volume, bid-ask spreads, open interest, market depth, settlement methodology and the identity and incentives of participants.
The quality of the underlying event definition is equally important. A prediction market must establish precisely what constitutes a successful outcome and which authoritative source determines settlement. Ambiguous wording can create disputes even when the underlying event itself is not controversial.
The insider information problem
Prediction markets face a particularly important problem when participants can influence the events on which they are trading.
A person who can directly affect an outcome possesses an informational and potentially operational advantage over ordinary participants. That creates an obvious market-integrity concern.
The CFTC issued a prediction-markets enforcement advisory in February 2026 following cases involving misuse of non-public information and improper trading.
The issue became especially prominent in August 2026 when the CFTC ordered former White House teleprompter operator Gabriel Perez to repay more than US$100,000 in alleged illicit profits and pay a civil penalty after trading event contracts based on privileged knowledge concerning presidential speeches. The CFTC’s settlement imposed a three-year trading ban.
Former Congressman George Santos was also permanently banned by Kalshi in August 2026 after the company concluded that he had improperly traded contracts connected to his own attendance at President Donald Trump’s State of the Union address. Kalshi imposed a US$71,356 fine, while the CFTC had separately taken enforcement action.
These cases demonstrate why prediction markets cannot depend solely on mathematical market design. They also require surveillance, disclosure rules, position controls and enforcement mechanisms capable of identifying manipulation and conflicts of interest.
The financial risks of prediction markets
Prediction markets can be intellectually fascinating and financially dangerous.
The apparent simplicity of a yes-or-no contract can conceal substantial risk. A participant may become overconfident because the contract appears easier to understand than a conventional financial security. The binary outcome can encourage excessive trading, particularly when the subject is politically or emotionally important to the trader.
Market prices can also change rapidly as new information appears. A trader who believes an event is highly likely can still lose money because unlikely events happen.
There is also a fundamental difference between being correct and being profitable. A trader can correctly predict an event but lose money if the contract was purchased at an excessively high price. Conversely, a trader can make money from a position even when an event ultimately fails to occur by selling the contract before settlement after its price has risen.
This makes prediction markets a form of financial speculation rather than a reliable method of generating income.
The future of prediction markets
The long-term significance of prediction markets may extend beyond politics and sports.
Their potential value lies in turning uncertainty into a continuously updated price signal. Businesses could use event contracts to manage certain forms of event-driven exposure. Researchers could use market prices as supplementary forecasting information. Journalists could monitor markets as one indicator of changing expectations. Economists could study how participants respond to new information.
Yet the industry’s development will depend heavily on regulation.
The CFTC has pursued litigation against several states in 2026 to defend what it describes as federal authority over event contracts. In April, for example, the agency sued Wisconsin after the state brought actions against several prediction-market operators. In June, it filed a similar case involving New Mexico.
At the same time, courts have increasingly been asked to determine whether sports-related contracts fall within state gambling regimes. The conflicting appellate decisions of 2026 mean that the regulatory framework remains unsettled.
The eventual legal outcome will influence which markets can operate, where consumers can access them, how contracts are classified and what protections participants receive.
Why prediction markets matter
Prediction markets matter because they transform uncertainty into something that can be measured, traded and continuously reassessed.
Their greatest contribution may not be their ability to predict the future with perfect accuracy. No market can eliminate uncertainty. Their importance comes from creating a mechanism through which people with different information and expectations can express those views and respond financially when they believe the prevailing market price is wrong.
The concept has travelled a remarkable distance from the University of Iowa’s small academic experiment in 1988 to a major contemporary debate involving financial regulation, technology, sports, politics, economics and market structure.
In 2026, prediction markets are no longer merely an academic curiosity. They have become part of a broader transformation in how society measures expectations about uncertain events. Their future will depend on whether regulators, courts and market operators can establish rules that preserve information discovery and legitimate risk management while preventing manipulation, insider trading and products that cross legally defined boundaries.
For the individual participant, the essential principle remains straightforward. A prediction-market contract is not a guaranteed forecast, a conventional investment or a risk-free way to make money. It is a financial position whose value depends on a future outcome.
Understanding that distinction is the foundation for understanding prediction markets themselves.
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