Prediction Markets: Smart Finance Tool or Dressed-Up Gambling?

The Prediction Market Gold Rush Has a Serious Problem

Prediction markets are on a tear. Platforms like Kalshi and Polymarket are processing billions in monthly volume, minting billionaire founders, and attracting partnerships with CNN, Fox, CNBC, Google, the MLB, and the UFC. The CFTC — the federal regulator that now claims sole jurisdiction over these platforms — has publicly cheered the industry on, even suing states that tried to shut it down. By almost every external measure, prediction markets look like one of the hottest financial innovations in years.

But strip away the hype, and the numbers tell a different story. An independent blockchain analysis of Polymarket found that 84% of users have realized losses, with just 2% of 2.5 million participants ever making more than $1,000 over their entire trading history. A separate analysis by Jordan Bender, Managing Director of Gaming Equity Research at Citizens, put the median retail ROI at negative 8% — worse than the median for legal US sports betting, which sits at negative 5%.

For a financial product that markets itself as a sophisticated forecasting tool and a leveller of the playing field for ordinary investors, those are damning figures. Here's what ambitious professionals actually need to know before they put money into this space.

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What Prediction Markets Actually Are — and Why They're Legal

At their core, prediction markets let users bet on the outcome of future events — anything from US elections to Elon Musk's tweet count to whether Jesus returns before 2027. Users buy binary contracts priced according to the implied probability of a given outcome. Hold the contract to resolution and you either win a predetermined return or lose everything. Sell early, and the price reflects the market's current odds.

The legal architecture here is non-trivial. Event contracts — technically a type of swap — have existed since the North American Derivatives Exchange (NADEX, formerly HedgeStreet Inc.) began listing them in 2004. The critical distinction prediction market operators lean on is that they don't take the other side of bets the way traditional bookmakers do. Instead, they facilitate trades between users and collect a fee — typically a few basis points to over 3% depending on the contract odds — positioning themselves as derivatives exchanges, not casinos.

That framing matters legally because it places these platforms under the jurisdiction of the federal CFTC rather than state gambling laws. For years, the CFTC held a tight rein — it blocked Kalshi from listing election contracts as recently as 2023. But Kalshi sued, a federal judge ruled in its favour, and the floodgates opened. Under CFTC chair Michael Celig, the regulator has not only permitted the expansion but actively defended it, filing legal actions against states — including Arizona and Nevada — that tried to apply their own gambling statutes.

Key takeaway: The regulatory moat protecting prediction markets is thinner than it appears. It rests on a single court ruling and a sympathetic CFTC leadership. A change in either could reshape the entire industry overnight.

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The Forecasting Argument: Genuinely Useful or Convenient Cover?

The most intellectually serious case for prediction markets rests on the wisdom of crowds. The theory — closely related to the efficient market hypothesis — holds that when enough informed participants trade on a question with real money at stake, the resulting price reflects genuinely useful probability estimates. Unlike polls, bettors have a financial incentive to be accurate rather than ideologically consistent.

The evidence here is real, if selective. The Iowa Electronic Markets, operating under strict non-commercial research conditions since the 1980s, beat more than 900 professional polls 74% of the time in predicting election outcomes. Polymarket's 2024 US presidential election odds showed Donald Trump as the likely winner weeks before mainstream polling aggregators caught up.

But context matters. Those results come from markets with serious participants, genuine expertise in the underlying event, and meaningful stakes. The current prediction market landscape is dominated by sports betting, which accounts for roughly 79% of Kalshi's $13 billion in monthly volume. The second-largest category is crypto — an asset class that already has its own liquid markets. The forecasting value proposition looks considerably weaker when the platform's revenue engine is whether the Lakers cover the spread.

There's also a structural issue. The accuracy of prediction market forecasts depends on a broad, informed participant base free from perverse incentives. As insider trading and market manipulation grow — more on that shortly — the forecasting signal degrades. A market where insiders exploit information asymmetry isn't surfacing wisdom; it's transferring wealth from retail users to those with privileged access.

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Who Actually Makes Money on Prediction Markets

The retail loss data is stark, but the breakdown is even more instructive. The Citizens analysis found that:

• Median retail ROI: -8%
• Users trading over $500,000 saw ROI improve to +2.6%
• Just 2% of Polymarket's 2.5 million users have made more than $1,000 lifetime

This distribution isn't random. It mirrors what decades of research show about other leveraged, speculative markets — from retail forex trading to options — where a small cohort of professional or institutional participants capture the bulk of returns at the expense of retail traders.

In prediction markets, that professional cohort includes:

• Arbitrageurs exploiting price discrepancies across platforms
• Market makers providing liquidity and earning the spread
• Infrastructure-advantaged traders executing faster than retail users can react
• Insiders — discussed below — trading on non-public information

The platforms' own marketing cuts against the reality. Kalshi's NBA Finals ad depicted a cocaine-fuelled celebration of winning bets. Social media ads showcase users counting stacks and screaming at screens. These ads are almost exclusively built around sports contracts — the highest-volume, most casino-like product on offer — despite executives simultaneously arguing in court that their platforms are serious financial infrastructure.

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The Insider Trading Problem Nobody Wants to Fix

In regulated financial markets, insider trading is illegal because it erodes trust and disadvantages ordinary participants. Executives are required to disclose trades. Enforcement, while imperfect, exists.

Prediction markets have a version of this problem that is structurally harder to police. When you allow people to bet on literally anything — military strikes, celebrity pregnancies, political pardons, sports results — you create an enormous surface area for insider abuse.

The examples are piling up:

• Polymarket users made substantial bets on US military actions in Iran and Venezuela days and hours before those actions became public
• An NPR analysis identified a trader who made $300,000 betting on Biden pardons at near-zero odds before the pardons were announced
• College and professional sports have seen a series of insider trading scandals involving athletes and team personnel
• Discord communities have allegedly coordinated to influence how news events are described to affect contract resolution

To date, the CFTC has issued just two publicly reported enforcement actions against prediction market users — one against a political candidate trading on their own election, one against a producer for MrBeast. Both were referred by Kalshi itself. The regulator has filed more legal actions against states trying to regulate these markets than against bad actors operating within them.

The platforms have taken steps — banning athletes from betting on their own sport, for instance — but these moves came only after proposed legislation threatened their sports betting revenue. That timing reveals where the incentives lie. Insider trading, perversely, improves the quality of forecasting data in the short term (insiders push prices toward the correct outcome) even as it destroys the fairness of the market for everyone else.

Key takeaway: Self-regulation in prediction markets is structurally compromised. The platforms benefit from the data that insider activity produces, and regulators have shown little appetite for enforcement. Retail users bear the cost.

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What the Industry Boom Means for Traditional Finance

The prediction market industry is not operating in isolation. Traditional financial infrastructure is moving toward it:

• CME Group, one of the world's largest derivatives exchanges, partnered with FanDuel — an outright gambling company — to launch a prediction market product
• Major exchanges have made direct investments in the space
• CNN, CNBC, Fox News, and Google have all announced commercial partnerships with prediction market platforms

This convergence creates real questions about market integrity and competitive dynamics in adjacent industries. If prediction markets are treated as derivatives exchanges rather than gambling platforms, they access a different regulatory regime, different tax treatment, and different investor protections than state-licensed sportsbooks. Companies that built their business under strict state gambling regulations — and paid the associated taxes and compliance costs — are understandably hostile.

For finance professionals, the more pressing question is what prediction markets signal about broader investor behaviour. The same retail speculation impulse that drove meme stocks, zero-day options, and crypto leverage trading is finding a new home here. The products change; the dynamic of retail money flowing toward high-friction, structurally disadvantaged speculative instruments does not.

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The Bottom Line on Prediction Markets

Prediction markets occupy a genuinely interesting space in the financial ecosystem. The theoretical case for market-based forecasting is sound, and the Iowa Electronic Markets data over decades provides legitimate academic support for the concept. In narrow, well-designed applications — political forecasting, economic indicator prediction, corporate risk hedging — they offer real value.

But the industry as it currently operates looks considerably less like a forecasting infrastructure and considerably more like a casino with a CFTC filing. Here's what the data actually supports:

• 84% of users lose money on the leading global platform
• 79% of volume on the leading US platform is sports betting
• Insider trading enforcement is near-zero despite documented abuse
• Returns improve materially only above $500,000 in trading volume — a threshold irrelevant to the retail users these platforms actively target

For ambitious professionals weighing whether to participate: the asymmetry of information and execution speed means retail users are structurally disadvantaged. The forecasting data these platforms generate is real — but you don't need to lose money to read it. Many platforms make aggregate odds publicly available. That's the product worth consuming.

The executives building these platforms are genuinely wealthy. The regulators protecting them are genuinely motivated. The retail users funding both? The numbers suggest they should read the fine print before the next ad convinces them otherwise.

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Frequently Asked Questions

Are prediction markets legal in the United States?

Currently, yes — under federal CFTC jurisdiction, following a 2023 court ruling in favour of Kalshi. However, a number of US states have challenged this classification, arguing that sports prediction markets constitute gambling and should fall under state law. The legal situation remains actively contested, and the regulatory landscape could shift with changes in CFTC leadership or further court rulings.

Do most people make money trading on prediction markets?

No. Available data suggests the opposite. An independent blockchain analysis of Polymarket found 84% of users have realised losses. A separate industry analysis put the median retail ROI at -8%, worse than the median for legal US sports betting at -5%. Positive returns are concentrated among high-volume traders and professional market participants with infrastructure advantages.

How are prediction markets different from traditional sports betting?

Legally, prediction market operators argue they facilitate trades between users — like a derivatives exchange — rather than taking the other side of bets themselves. This positions them under federal CFTC oversight rather than state gambling regulations. In practice, sports contracts account for roughly 79% of volume on the leading US platform, making the operational distinction less clear than the legal one.

What is the insider trading risk on prediction markets?

Significant and largely unpoliced. Because users can bet on virtually any event — military actions, political decisions, sports outcomes — those with privileged access to non-public information can exploit it. Documentation includes substantial winning bets placed hours before military strikes became public, and trades on political pardons at near-zero odds before announcements. The CFTC has issued only two publicly reported enforcement actions against prediction market users to date.

Can prediction market data be useful even if I don't trade?

Yes. The aggregate probability data generated by these markets — particularly for political and economic events — has demonstrated forecasting value in academic research. Many platforms make this data publicly available. Analysts, risk managers, and policy researchers can access the forecasting signal without participating in the trading activity.

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This article is for informational purposes only and does not constitute financial advice. Always consult a qualified financial professional before making investment decisions.