Prediction-market platforms are drawing increasing interest from Wall Street, a shift that could bring deeper professional liquidity into the sector. But the same trend is also set to intensify competition and make it harder for traders to profit from pricing gaps and arbitrage, CNBC reports.
An academic working paper based on $13.76 billion in Polymarket trades found that roughly 27% of dollar profits went to just 3% of accounts. The authors describe those traders as “persistently skilled,” meaning they repeatedly moved prices toward outcomes that ultimately came to pass.
According to the paper, those accounts generated consistent gains by reacting faster to public news, exploiting inconsistent pricing across related contracts and trading against behavioral mistakes. As more institutional players pursue the same discrepancies, however, prices adjust faster and the available edge becomes smaller.
Theis Jensen, a Yale economist and co-author of the study, said that when many skilled participants compete against one another, prices become more accurate. That implies strategies built on wide spreads and straightforward arbitrage across related contracts will find it increasingly difficult to produce profits.
Julie Hoover, a Bank of America equity research analyst, told CNBC that as markets become more efficient and spreads tighten, mispricings and arbitrage opportunities become harder to find. Jensen also expects the share of traders with a genuine edge to shrink from 3% to potentially below 1%. In his view, only the very strongest participants — such as hedge funds — may ultimately be able to beat prediction markets consistently.
At the same time, Hoover argued that smaller but highly skilled traders could still retain an advantage in niche segments. The sheer range of contracts allows market participants to build specialized expertise and even act as market makers. Jensen added that large institutions face scale limits in thin markets: relatively small orders can move prices enough to “evaporate the institution’s own edge.” That makes big firms less likely to enter lower-liquidity areas where specialists may still have room to outperform.
Counterintuitively, participants without a persistent edge may also benefit from more sophisticated competition. Better-calibrated prices lower the risk that such traders repeatedly overpay by taking the wrong side of pricing errors. In Jensen’s view, it is harder to make mistakes consistently in an efficient market. As prediction markets mature, he said, they may become more of a “fair gamble”: participants can still lose on individual contracts, and frequent traders are still likely to lose after transaction costs, but quoted prices should more closely reflect the risks involved.
For the platforms themselves, the trend carries a clear upside. Larger institutional trading volumes can expand fee revenue, while more accurate pricing can strengthen the role of event contracts as tools for hedging, forecasting and market data.
Prediction markets are already viewed by many as credible information sources. Federal Reserve researchers found that Kalshi’s macroeconomic contracts matched conventional forecasting benchmarks and in some cases outperformed them. Its headline CPI forecast beat the Bloomberg consensus, while its core CPI and unemployment forecasts performed in line with the market data institution. As Hoover put it, “Everyone will start referencing the data, and then people will start trading the data.”
Disclosure: CNBC and Kalshi have a commercial relationship that includes customer acquisition and a minority investment.
