Prediction markets are becoming more professionalized, but also harder to beat

Prediction-market platforms’ courtship of Wall Street stands to bring in deeper professional liquidity and intensify competition, but will also mean it’s harder for many traders to make money.

Roughly 27% of dollar profits were captured by just 3% of accounts that are “persistently skilled,” repeatedly moving market prices towards outcomes that eventually occurred, according to an academic working paper analyzing $13.76 billion of Polymarket trades.

Skilled accounts earned consistent profits by reacting more quickly to publicly available news, arbitraging inconsistent pricing across related contracts and trading against behavioral errors. But as more institutions chase the same discrepancies, prices adjust faster and the available edge becomes scarcer.

“If you have a lot of skilled people, then they compete, and in doing so, they make prices more correct,” said Theis Jensen, Yale economist and co-author of the paper.

That means strategies that depend on wide spreads and straightforward arbitrage across related contracts may find it more difficult to profit.

“It’s harder as markets get more efficient and spreads get tighter. It’s going to be harder to find these mispricing and arbitrage opportunities,” Julie Hoover, Bank of America equity research analyst, told CNBC.

As competition intensifies, Jensen expects the proportion of traders considered to have an edge to shrink from 3% to potentially below 1%.

“I think it’s only going to be the very, very best — say hedge funds — that are able to beat prediction markets,” he said.

Hoover, however, said smaller skilled traders could still retain an edge in niche markets, as the sheer breadth of contracts allows traders to develop highly specialized expertise and even become market makers.

Large institutions also face scale constraints in thin markets. Relatively small orders can move the price enough to “evaporate the institution’s own edge”, according to Jensen, making large firms less likely to enter lower-liquidity markets where specialists may retain an advantage.

Counterintuitively, the participants without a persistent edge may stand to benefit from more sophisticated competition through better pricing.

Better-calibrated prices reduce the risk that such players repeatedly overpay by taking the wrong side of pricing errors.

“In an efficient market, it’s harder to make mistakes consistently,” Jensen said.

He said the maturation of prediction markets could make them more of a “fair gamble”: participants may still lose on any individual contract, and frequent traders remain likely to lose after transaction costs, but quoted prices should more closely reflect the risks they are taking.

While the professionalization of prediction markets come as a mixed bag to users, there’s a clear benefit for the platforms. Greater institutional trading volume can expand transaction fee opportunities, while better-calibrated prices can strengthen the appeal of event contracts as hedging, forecasting and market-data tools.

Prediction markets are already seen by many as reliable. Federal Reserve researchers found that Kalshi’s macroeconomic contracts matched or, in some cases, even outperformed conventional forecasting benchmarks: its headline CPI forecast outperformed the Bloomberg consensus, while its core CPI and unemployment forecasts performed on par with the market data institution.

“Everyone will start referencing the data, and then people will start trading the data,” Hoover said.

Disclosure: CNBC and Kalshi have a commercial relationship that includes customer acquisition and a minority investment.