Prediction markets are proving an interesting point — retail traders are actually outperforming Wall Street analysts who wear suits every day in predicting US inflation data. This is not a joke; recent research data released by Kalshi clearly shows it.

According to Kalshi Research's first public report, they compared 25 months of CPI prediction data. The results were surprising: market traders not only achieved higher accuracy but also kept prediction errors within 50% during periods of intense market volatility. In comparison, traditional analysts' performance appears somewhat awkward.

What supports this? Kalshi has just established a dedicated research department — Kalshi Research — which is opening up the world's largest prediction market data and platform information to academia. They also plan to host the first Prediction Market Conference, bringing together researchers, predictors, traders, and community players.

The academic community has already begun paying attention. Scholars from prestigious universities such as Harvard, Stanford, Yale, and the University of Chicago are signing on for collaborations. Meanwhile, a leading exchange, a compliant platform, CNN, Google Finance, and even Grok AI are integrating Kalshi's data and frontend features, aiming to share in the benefits of prediction markets. Mainstream adoption of prediction markets is not far off.