Tag: prediction markets

Prediction Market Monday: More Than One Simple Market

by Simi Awe

Most people think of prediction markets as simple yes-or-no predictions on whether an event will occur. In reality, these markets are far more complex. They include a variety of contract types, market designs, and even different forms of currency. Below, we break down the main types of prediction markets and explain their purposes.

Contract Types

There are three main types of contracts: binary, index, and spread. Binary contracts are the most common and well-known. For these contracts, traders make yes or no trades on their predicted outcome of an event. This contract can help to show the probability of an event occurring based on market expectations. For index contracts, the payout varies continuously based on the value of a numerical outcome. A common example is the percentage of votes Trump receives in the presidential election. Index contracts show the market’s expectation of the value, mean, of the event with investors split into buckets of potential outcomes. Lastly, spread contracts are binary contracts where a person can invest in a specific event outcome both occurring and exceeding a certain threshold and the cutoff. The profit or loss would deviate based on how close the trader got to the actual outcome. An example of this type of contract is that President Trump will win 66% of the popular vote. Spread contracts show the market’s expectation of the median. This contract type rewards the forecasting accuracy of a trader over mere direction.

Market Design

The type of market design used by a prediction market impacts the liquidity, distributions of winnings, and capital choices. Continuous double-action design is similar to the stock market, as it matches buyers and sellers when the bid and asking price align. The market maintains a ledger to catalog the trades to ensure all contracts are correctly paid out. This style of market is conducive to high-activity markets with frequent trading and allows people to move in and out of investment positions based on the current market price. This peer-to-peer style can often be supplemented by automatic market makers, who can act as counterparties to both sides of trades, while making money by arbitraging different market values and taking fees on spreads. This approach helps provide liquidity in markets where there are not enough buyers or sellers at a given time, ensuring that participants can virtually always find a willing buyer or seller at around the then-current market prices. Pari-mutuel payouts occur when all investments are pooled together into one pot and then are divided out amongst the winners in proportion to the size of their investment.

Currency

The most common type of currency used in prediction markets is real currency, defined as actual assets or money. It is typically used because it incentivizes traders to make accurate predictions. More recently, some markets have begun using platform-specific tokens or coins, where payouts or incentives are awarded based on the number of tokens earned. There are advantages to using platform-specific tokens over real currency, as they lower the barrier to entry and can increase participation and liquidity.

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Prediction Market Monday: The History of Prediction Markets

by Simi Awe

Prediction markets in the United States can be traced back to the 1800s, when they were primarily focused on election outcomes. These hedging pools were organized on Wall Street directly outside of the New York Stock Exchange and posted alongside election news. They were seen as the most accurate forecasters.

1988

In 1988, at the University of Iowa, the Iowa Electronic Market (IEM) was launched as a research tool to study the ability of small financial bets to forecast election outcomes. In a 2008 study, IEM data was found to outperform national polls 74% of the time. The next prediction market to launch was InTrade in 2001. It became the most prominent market of its time, correctly predicting Obama’s 2008 victory. Its success was cut short when it was sued by the Commodity Futures Trading Commission (CFTC) for offering commodity options to U.S. customers without proper registration. This case warned other markets about the importance of regulatory compliance.

2010

In 2010, under the Dodd-Frank Act, Congress extended the CFTC’s exclusive jurisdiction over “agreements…and transactions involving swaps.” In 2014, PredictIt filled the gap left by InTrade. Its contracts focused on U.S. politics and operated under the guidance of a no-action letter from the CFTC. This letter allowed it to function, similar to the IEM, as a research tool using real-money trading. Despite the limitations of the no-action letter, PredictIt began to grow. During this period of growth for prediction markets, Augur launched the first blockchain-based prediction market. While there were initial challenges due to low liquidity, it laid out the groundwork for integrating blockchain technology with prediction markets.

2020

In 2020, the CFTC adopted a new regulatory approach to prediction markets, shifting from a primarily research-based framework to full approval under the designation of a contract market (DCM). Kalshi became the first prediction market to receive this approval. As part of this shift away from the research-based model, the CFTC withdrew PredictIt’s no-action letter.

This “open-arms” policy shifted in 2023, when the CFTC sought to restrict Kalshi from offering event contracts based on election outcomes. Kalshi challenged this decision in court and won. With a change in administration in 2025 that was more favorable toward prediction markets, the number of markets increased, and total market volume exceeded $50 billion by the end of the year. While at the federal level, governments were paving the way for prediction markets, the states in 2025 began to send cease-and-desists and sue CFTC-registered companies like Kalshi, claiming the contracts they offered trading on constituted “gambling” under state gaming laws. This began an over-year-long battle in the courts, that is still occurring, over whether event contracts are swaps, thus under exclusive federal jurisdiction, or gambling, allowing for states to have jurisdiction. In an amicus response on February 17, 2026, in the U.S. Circuit of Appeals for the Ninth Circuit, CFTC Chairman Mike Selig came out as saying prediction markets are swaps and thus fall under the exclusive jurisdiction of the CFTC. It remains unclear which way the courts will ultimately rule, and the issue may need to be resolved by the Supreme Court.

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Prediction Market Monday: Offshore vs. Onshore

by Simi Awe

The prediction market landscape is more complex than it appears. Depending on where a platform operates, the rules, protections, and accessibility for users can vary drastically.

There are many differences between offshore and onshore prediction markets, but most of those differences can be tied to the fact that onshore prediction markets are regulated by the Commodity Futures Trading Commission (CFTC) and offshore are not.

Offshore vs Onshore prediction markets comparison across 9 regulatory and operational topics.
Market structure

Offshore vs. Onshore

A side-by-side look at oversight, access, protections, privacy, and participant reach.

Comparing Topic
Market type Offshore
Market type Onshore
U.S. Regulatory Oversight
None
CFTC & DOJ
Issuer Data Reporting
No
Yes
Market Variety
Broad
Limited
Consumer Protection Requirements
Platform discretion
Yes
Limitations on Event Contract Types
No
Yes
Onboarding Process
Faster
Slower, stricter eligibility
Anti-Money Laundering Procedures
Platform discretion
Yes
User Privacy
Higher
Lower
Variety of Participants
Global U.S. largely excluded
U.S. based Primarily domestic
Detailed explainer covering onshore and offshore prediction market structures, regulation, and tradeoffs.
U.S.-regulated
Onshore Markets
CFTC-registered & DCM-licensed

U.S.-based prediction markets must register with the CFTC and obtain a Designated Contract Market (DCM) license to offer event contracts — a high bar with currently only 25 registered DCMs.

Once approved, platforms must comply with 23 Core Principles — including identity verification, fraud monitoring, and market integrity safeguards. The CFTC’s Division of Market Oversight conducts regular Rule Enforcement Reviews (RERs) of each DCM.

The Commodity Exchange Act restricts contract types: events touching war, assassination, terrorism, gaming, or matters deemed against public interest are prohibited.

Regulated platforms must impose stricter user eligibility and collect personal data — reducing anonymity in exchange for stronger protections.
Unregulated
Offshore Markets
No U.S. regulatory oversight

Offshore platforms operate outside U.S. regulatory requirements. Most do not verify identities or collect user data, offering greater privacy and a broader range of contracts to a global user base.

Many run on blockchain-enabled infrastructure — making all trade timing and sizing permanently, publicly recorded via an immutable ledger. Users, not platforms, typically create the markets themselves.

Faster onboarding and fewer compliance barriers make entry easier — but these platforms use geofencing and terms of service to block U.S. users from accessing their markets.

Greater flexibility and privacy come without the consumer protections or regulatory recourse available to onshore participants.
Accessibility & Tradeoffs

Onshore markets are available to U.S. users and deliver stronger consumer protections and regulatory oversight — at the cost of higher compliance burdens and operational constraints. Offshore markets ban U.S. users entirely, offering greater flexibility and accessibility but carrying elevated risk due to the absence of regulatory protections.

In the context of U.S. users and federal oversight, only onshore markets are currently available — and those markets operate under a strict regulatory regime.

If you have any questions, please reach out to policy@digitalchamber.org. 

Prediction Market Monday: Common Misconceptions

by Simi Awe

Prediction markets are more than they appear, and the misconceptions surrounding them are holding back a powerful financial innovation. From unfair comparisons to casino gambling to assumptions of zero oversight, the narrative around prediction markets is often wrong.

The reality is that these markets are peer-to-peer exchanges regulated by the CFTC, and they offer real value to businesses, policymakers, and individuals alike.

Full explainer on prediction markets covering three myths and three supporting facts, with footnote citation.
Prediction Markets — Common Misconceptions
Myth 1
Prediction Markets Are Gambling

Prediction Markets are simply marketplaces that connect buyers with sellers on contracts based on the outcomes of future events. These events span a wide range of topics, including election results, economic indicators, and sports outcomes.

While they may resemble casino-style gambling at first glance, prediction markets have key differences, which is why they so clearly should be regulated by the CFTC. Prediction markets are driven by purely supply/demand dynamics and there is no “house” to win if a consumer loses.

Just like other financial markets, profits or losses are based solely on how accurate the individual’s investment thesis is, and there is no central “book” that sets odds in ways to ensure the “book” always wins. These are marketplaces that simply bring together willing buyers with willing sellers.

Because participants trade peer-to-peer contracts on exchanges based on the underlying outcome of future events, these instruments are better classified as swaps rather than gambling.

Myth 2
Prediction Markets Are Unregulated

Prediction markets in the United States are not unregulated. The Commodity Futures Trading Commission (CFTC) oversees event contracts under the Commodity Exchange Act, as it does with other derivatives, and the Department of Justice (DOJ) has the power to bring criminal charges for perpetrators of insider trading or fraud on these markets.

This regulatory framework imposes requirements for platform registration including AML/KYC checks, customer protections, and safeguards against fraud and market manipulation. Platforms must comply with these standards to operate legally in the United States.

Myth 3
Prediction Markets Have No Benefits

Prediction markets serve as powerful forecasting tools. By aggregating the beliefs of many participants, they generate probability estimates for future outcomes that are often more accurate than traditional methods.

Unlike expert-driven forecasts, prediction markets do not privilege credentials or authority. Instead, they rely on incentives; participants earn rewards for accurate predictions, which encourages honest and information-driven participation.

These markets can complement traditional polling by filling gaps and providing additional data. Their applications extend beyond politics to areas such as economic forecasting, offering valuable insights to companies, policymakers, and analysts alike and the ability to financially hedge against future events by individuals and entities financially effected by the potential outcome of those events.

Setting the Record Straight
Overview

As interest in prediction markets has increased, so too have misconceptions surrounding them. Lawmakers, news outlets, financial experts, and citizens frequently discuss three common myths: that prediction markets are casino-style gambling, that they are unregulated, and that they have no benefit. Each of these claims is misleading and contributes to an overly negative and inaccurate perception of prediction markets.

First
01

Prediction markets are not simply gambling or sports betting. A prediction market is an online platform where users buy and sell contracts based on the outcomes of future events. Unlike traditional gambling, which typically involves betting against a “house,” prediction markets operate as peer-to-peer exchanges where participants trade with one another. Participants can also trade in and out of their positions in real time based on new information.

In addition, event contracts in prediction markets are swaps or other derivatives depending on their structure. Like other swaps, these contracts include cash settlements based on the occurrence of an underlying event. This classification has important legal implications, as regulators and courts increasingly analyze event contracts under the Commodity Exchange Act’s framework for derivatives. Recently, in Kalshi v Flaherty, the U.S. Court of Appeals for the Third Circuit stated that event contracts satisfy the CEA’s definition of a swap.

Second
02

Prediction markets are not an unregulated “Wild West,” as some assume. Because many prediction market contracts fall within the category of derivatives, the CFTC oversees them under the Commodity Exchange Act. The CFTC has exclusive jurisdiction over swaps. The CFTC imposes strict regulations under 17 CFR 40.11 over what events can’t be used as a basis for a contract.

It also requires platforms to create rules to protect participants from fraud and market manipulation. Prediction markets can face serious consequences from the CFTC if they violate any of their regulations.

Third
03

Prediction markets can serve as valuable tools for society. One of their primary strengths is their ability to aggregate information from a wide range of participants. Unlike traditional polling, which may rely on limited samples or emphasize expert opinion★, prediction markets incorporate diverse viewpoints and incentivize accuracy through financial stakes. In some cases, prediction markets have matched or exceeded the accuracy of traditional polling.

This aggregation of information extends beyond politics. Businesses can use prediction markets to forecast demand or assess regulatory risk. As understanding of these platforms grows, their potential to contribute to more informed and efficient decision-making is likely to expand.

★

Diercks, Anthony M., Jared Dean Katz, and Jonathan H. Wright (2026). “Kalshi and the Rise of Macro Markets,” Finance and Economics Discussion Series 2026-010. Washington: Board of Governors of the Federal Reserve System. https://doi.org/10.17016/FEDS.2026.010

If you have any questions, please reach out to policy@digitalchamber.org. 

Insider Trading and Prediction Markets; Blockchain Transparency Drives Enforcement  

by Megan Thorpe

Recently, insider trading allegations related to prediction markets have been dominating headlines. One of the recent headline grabbers includes allegations a U.S. military official committed fraud and misuse of classified information. The soldier allegedly used classified intelligence related to U.S. military action in Venezuela to place a series of trades on Polymarket’s offshore platform, generating over $400,000 in personal profit. He has been charged with multiple criminal offenses, and the CFTC has also filed a lawsuit against him for civil damages. 

According to the criminal indictment, to bypass the offshore platform’s restrictions against use by U.S. individuals, it is alleged the individual accessed the platform through foreign accounts and attempted to conceal his activity by moving funds through offshore accounts. However, the activity was quickly discovered despite alleged attempts to conceal because the trades at issue were executed through public and immutable blockchain technologies. The suspicious timing and size of the trades were rapidly spotted by the public and quickly uncovered in media reports, leading to a federal investigation and the resulting criminal and civil charges. Since everyone could see the suspicious trading activity, accountability was as transparent as the blockchain ledger. 

As the call for prediction markets regulation bubbles at the state and federal level, this example illuminates a number of key policy discussion points: 

• Transparency: Blockchain-based technologies and platform monitoring appear to have contributed to identifying unusual trading patterns, which were later investigated by authorities.  

• Existing rules: This case represents one of the first major criminal prosecutions and civil enforcement actions for insider trading involving prediction markets. The case suggests that existing fraud, commodities, and misuse-of-information statutes can be applied to conduct on prediction markets.   

• Jurisdictional complexity: U.S. law prohibits certain event contracts, such as those involving war, which is why the individual allegedly had to use workarounds to trade on offshore markets. This highlights that U.S. regulations prohibiting event contracts on things like war and terrorism are still in full force, but the borderless nature of prediction markets and digital assets complicate who and how bad actors are brought to justice.  

• Regulatory scrutiny of prediction markets: The case and similar recent civil enforcement actions are heating up policy discussions around how prediction markets and insider trading with sensitive information on those markets should be regulated. Even though the trades happened on an offshore platform, U.S. authorities can still enforce the law. If someone in the U.S. tries to bypass restrictions to access those markets, they can be held accountable if they break U.S. law.  

Though existing laws already prohibit the insider trading alleged in this matter, clearly tying those existing rules to emerging technology like prediction markets in cases like this is necessary to ensure law enforcement can fairly police online trading activity. As with so many emerging technology products, there is a clear need for consistent regulatory frameworks that address misuse without stifling innovation. 


If you have any questions, please reach out to policy@digitalchamber.org.