A New Era for Economic Forecasting: The Role of Prediction Markets

The Fed recently released a working paper that highlights the promising potential of prediction markets for forecasting economic data releases.

The study scrapes trade-level data from Kalshi, the largest federally regulated prediction market, which allows for trading on economic indicators. The platform offers event-based contracts for headline figures, such as inflation, interest rates, GDP growth and employment. The price of a “yes” contract was treated as the market’s baseline expectation of an event occurring. This was then compared to more traditional forecasting tools, such as Bloomberg consensus estimates and the Fed's Survey of Market Expectations.

The research revealed that Kalshi's expectations for headline CPI (YoY) represented a "statistically significant improvement" compared to the Bloomberg consensus. Expectations for core CPI and unemployment were statistically similar.

The study also noted that several headline indicators, such as GDP growth and unemployment, previously lacked financial derivatives trading options, creating a significant data gap that Kalshi now fills with its intra-day trade data. While option-implied distributions exist for equities, interest rates, and CPI headline inflation swaps, Kalshi extends this to other headline macro indicators at high frequency while providing a more retail-investor perspective.

Other market participants have also shown a bullish outlook on Kalshi's economic data. ARK Invest recently announced a partnership with Kalshi to utilise its economic data streams, allowing them to forecast key economic indicators ahead of official releases.

Ark tested several predictive analytics platforms before choosing Kalshi as its primary partner for economic data, highlighting the platform's impressive accuracy in labour market predictions.

While Kalshi claims that professional traders and hedge funds now make up about 40% of its user base, reports on broader industry adoption remain mixed. The uptake has faced challenges due to regulatory ambiguities, risks of insider trading, and ongoing legal disputes with state regulators.

The Fed's vote of confidence may accelerate the adoption of prediction markets among institutional investors. Issues around insider trading on these platforms seem to be more prevalent in random events than in economic releases. It will be interesting to see whether BLS statisticians are the type to engage in insider trading by betting on the figures they help build (this is a joke). For the time being, compliance teams may face increasing pressure to approve the use of prediction markets for economic bets.