Insider Trading on Prediction Markets: Next up for DOJ

Prediction markets have changed quickly. What began as small, academic experiments now move billions of dollars in aggregate trading volume.

During major election cycles, regulatory announcements, and geopolitical events, individual markets routinely attract hundreds of millions of dollars in bets. Across platforms, annual volume now reaches into the multi-billion-dollar range.

These markets shape narratives. Prices are quoted in news coverage. Analysts treat these markets as real-time signals of probability and sentiment.

As the money has grown, so will the legal scrutiny. And with real money comes real legal risk.

The core question is simple: does trading on nonpublic information in prediction markets expose participants to insider-trading or fraud liability? The answer is, “Yes.” But building and proving such a case will be difficult for law enforcement.

What Are Prediction Markets?

Prediction markets allow users to trade contracts tied to future events. A contract usually pays a fixed amount if an event happens, and nothing if it does not. The price reflects the market’s view of probability.

That simplicity is part of the appeal. It is also part of the risk.

Common Prediction Market Events

Prediction markets often focus on:

  • Federal and state elections

  • Regulatory approvals and enforcement actions

  • Economic data releases

  • Court decisions and litigation outcomes

  • Corporate and business milestones

  • Geopolitical developments

Each market resolves at a specific moment. That timing matters.

How Prediction Markets Work — A Simple Example

Prediction markets let people trade on the outcome of future events. The mechanics are straightforward. The appeal is obvious once you see how the pricing works. Here is a simple example.

A Basic Prediction Market Question

Imagine a prediction market that asks:

“Will the Federal Reserve raise interest rates at its next meeting?”

The market offers two contracts:

  • YES — pays $1 if the Fed raises rates

  • NO — pays $1 if the Fed does not raise rates

Each contract trades for a price between $0 and $1.

What the Price Means

Suppose the market prices look like this:

  • YES: $0.65

  • NO: $0.35

The market is saying there is roughly a 65% chance the Fed will raise rates.

Prices move constantly as new information becomes public. Economic data. Fed speeches. Market rumors. News headlines.

How Someone Makes Money

Prediction markets reward people who believe the market price is wrong. Not completely wrong. Just a little wrong.

Example: Buying an Undervalued Outcome

Assume a trader believes the Fed is very likely to raise rates. Closer to 80%, based on public information like inflation data and recent Fed statements.

That trader might:

  • Buy 100 YES contracts at $0.65

  • Total cost: $65

If the Fed raises rates:

  • Each contract pays $1

  • Total payout: $100

  • Profit: $35

If the Fed does not raise rates, the contracts expire worthless and the trader loses the $65.

It’s About Probability, Not Certainty

This is the key point. Prediction markets are not about being certain. They are about believing the true probability is higher or lower than the current price suggests. You can be wrong about the outcome and still have made a rational trade. Over time, traders who price probability better than the crowd tend to profit.

Why These Markets Attract So Much Money

Prediction markets have grown quickly for a few reasons:

  • The questions are simple

  • The payouts are clear

  • Prices update in real time

  • Outcomes resolve on a fixed date

For many participants, prediction markets feel like a stripped-down version of financial markets. No balance sheets. No earnings calls. Just probabilities.

At their core, prediction markets are markets for beliefs. If you think the crowd is underestimating an outcome, you buy it. If you think the crowd is overestimating it, you trade the other side.

How Are Prediction Markets Regulated?

From a legal standpoint, prediction markets do not fit neatly into one box. Depending on structure, they may be treated as:

  • Commodity derivatives under the Commodity Exchange Act

  • Event contracts overseen or exempted by the CFTC

  • Swaps or futures if improperly designed

  • In narrow cases, unlawful gaming instruments

Many U.S.-facing platforms operate under CFTC oversight or limited exemptions.

What matters most, however, is this: the absence of a traditional security does not eliminate insider-trading or fraud risk.

Kalshi and Polymarket: Platform Models and Market Activity

Prediction markets are not all the same. Kalshi and Polymarket illustrate how different these platforms can be in structure, scope, and liquidity.

Kalshi Prediction Market Overview

Kalshi operates a U.S.-based platform offering standardized event contracts. Each contract is tied to an objectively verifiable outcome. The exchange is centralized, with fixed settlement rules.

Kalshi markets tend to focus on:

  • Inflation data and interest rate decisions

  • Regulatory and administrative outcomes

  • Weather and climate events

  • Elections and public policy milestones

Trading occurs in U.S. dollars. Contracts typically have capped payouts, which limits notional exposure.

Volume has grown steadily. Activity spikes around elections, major economic releases, and high-profile policy announcements. Participation increasingly includes professional traders and institutional participants. Kalshi’s success is in the numbers. It recently raised a boatload of money.

Polymarket Prediction Market Overview

Polymarket operates a blockchain-based prediction market. Trades settle on public ledgers. Markets are often narrower, more numerous, and more granular.

Common Polymarket markets include:

  • National and international elections

  • Geopolitical events

  • Corporate actions and litigation milestones

  • Media, technology, and cultural events

Polymarket is known for scale. During election cycles, individual markets have drawn tens or hundreds of millions of dollars in trading volume. Global participation and rapid market creation drive liquidity.

Prices move quickly. News, rumors, and narrative shifts are reflected almost instantly. Polymarket is moving quickly to enter the US market to counter Kalshi’s moves.

Why Insider Trading Law Applies to Prediction Markets

Classic insider-trading law developed around securities. Prediction markets are not securities. But that fact does not end the analysis.

Regulators and prosecutors rely on broader tools to investigate and charge insider-trading schemes, including:

Prediction markets can make these cases easier in some respects. Profits are tied to discrete outcomes. Timing is clear. Access is often limited. But as noted below, law enforcement will have headaches putting these cases together.

The Misappropriation Theory and Prediction Markets

Under the misappropriation theory, liability arises when someone misuses material nonpublic information obtained through a duty of trust or confidence.

Prediction markets frequently present clean examples:

  • Government officials trading on advance knowledge of regulatory or enforcement decisions

  • Corporate insiders trading on approvals, investigations, mergers, or litigation news

  • Lawyers, consultants, and advisors trading on client-confidential information

The instrument traded on MNPI does not need to be a security, although traditionally it has been.

How the DOJ and CFTC Build Prediction Market Insider Trading Cases

From an investigative standpoint, these cases follow a familiar pattern.

Trade Timing and Reconstruction

Investigators start with the trades:

  • Who controlled the account (commonly called “attribution”)

  • When trades were placed

  • How large they were

  • How they compared to prevailing market odds

  • What happened when the event resolved

Prediction markets create clean timelines. Large directional trades placed shortly before resolution draw attention.

Information Access and Role Analysis

Next comes access:

  • The trader’s professional role

  • His or her exposure to confidential deliberations or drafts

  • The timeline between access and trading

In regulatory and enforcement markets, the number of people with advance knowledge of an event is often small and traceable.

Digital Evidence and Financial Tracing

Investigators then build the record:

  • Emails, texts, and encrypted messages

  • Telephone calls and evidence of in-person meetings

  • Calendars and document access logs

  • Funding sources and withdrawals

  • Intermediaries or related accounts

Key Investigative Challenges

These cases are not automatic wins for the government. Evidence will take a long time to collect and is often difficult to track down.

Materiality Outside Securities Markets

There is no settled materiality test for prediction markets. Nonetheless, prosecutors will look to graft the materiality standard from the wire-fraud cases to this area.

Expertise Versus Inside Information

Many traders outperform markets through skill and public data analysis. Separating expertise from misuse of confidential information will be the central fight in these cases.

Regulatory Uncertainty

Evolving guidance creates room for argument on both sides.

Defense Strategy in Prediction Market Investigations

Defense strategy often focuses on:

  • Challenging market classification and jurisdiction

  • Attacking materiality and causation

  • Showing a consistent, lawful trading strategy

  • Suppressing improperly obtained digital evidence

  • Coordinating responses across DOJ and CFTC matters

Frequently Asked Questions

Is insider trading illegal on prediction markets?

It can be. Trading on material nonpublic information may violate the federal wire fraud statute and other “scheme to defraud” statutes in the U.S. Code.

Are prediction markets securities?

Generally, no. But insider-trading liability does not require the trading of a traditional security.

Can government employees trade on prediction markets?

Trading by government employees raises heightened risk when it involves advance knowledge of policy, regulatory, or enforcement actions.

Can a corporate insider trade on prediction markets?

It depends. A corporate insider may trade on prediction markets only if the trade is based entirely on public information and does not use confidential or nonpublic company information.

If a trade relies on material nonpublic information obtained through the insider’s position, it can trigger insider-trading or fraud liability even if the contract is not a traditional security.

How can I tell if I’m under investigation for insider trading?

In most cases, you are not told at the beginning of an investigation. Insider-trading investigations usually start quietly, through subpoenas to third parties, before any direct contact with the individual. This is the “covert” stage of an investigation.

What are the earliest warning signs of an insider trading investigation?

Common early indicators include:

  • Questions from compliance, legal, or HR about specific trades

  • Requests to preserve emails, messages, or devices

  • Enhanced due-diligence inquiries from financial institutions

  • Notification that a subpoena or document request was sent to your employer, broker, or bank

  • Law-enforcement agents asking to interview you

These steps often occur after regulators have already reviewed trading data.

Conclusion

Prediction markets now move real money, at real scale. Billions of dollars flow through these platforms. Prices influence narratives and decisions.

But old legal doctrines still apply.

For traders, platforms, advisors, and corporate insiders, the takeaway is straightforward: event-based markets are not a safe harbor for trading on nonpublic information. As volume and attention grow, prediction markets are likely to sit at the center of the next wave of insider-trading enforcement.

Questions? Contact Scott Armstrong, an experienced white-collar defense attorney. Scott is a defense attorney for individuals facing federal investigations involving securities and commodities fraud, insider trading, and crypto fraud. To defend individuals in these cases, Scott relies on his litigation experience in Miami, Chicago, Houston, Denver, DC, Alexandria, Newark, Nashville, Knoxville, Detroit, Columbus, Los Angeles, and New York.

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