Tiger Research: Predicting that the market is becoming a macro data infrastructure

Research institution Tiger Research researcher Ryan Yoon released the final report of the prediction market series, discussing whether prediction markets have practical utility. The report states that participants bear the judgment results with funds, and prices are updated in real-time with new information, forming probability distributions comparable to traditional polls, expert surveys, and economic forecasts; prediction markets have expanded from sports and election predictions to macroeconomic and geopolitical data infrastructure.

The report lists that Google Finance, CNBC, CNN, and The Wall Street Journal have displayed prediction market probabilities, and the parent company of the New York Stock Exchange, Intercontinental Exchange, along with the electronic bond trading platform Tradeweb, distributes relevant data to institutional clients. A working paper from the Federal Reserve Board describes the prediction market Kalshi as a high-frequency, continuously updated benchmark with rich information distribution. The paper states that Kalshi's median and mode predictions for the federal funds rate recorded perfectly the day before the FOMC meeting and significantly outperformed federal funds futures during that period; compared to Bloomberg consensus, it is more accurate for overall CPI and statistically similar for core CPI and unemployment rate.

The report also cites research from the Iowa Electronic Markets: in five U.S. presidential elections from 1988 to 2004, and in a comparison of 964 polls, it was more accurate in 74% of cases; the average voting share error one week before the election was 1.5 percentage points, lower than Gallup's final poll of 2.1 percentage points. The report suggests that the platform needs to deepen liquidity to resist manipulation, communicate with regulatory agencies, and position itself as a monitoring tool while maintaining open transparency and data supported by independent research.