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Forecasting Federal Reserve actions is vital for financial markets, policymakers, and economic journalists due to its economic impact. While CME FedWatch probabilities have been widely used, Kalshi Fed Markets, a prediction market, is challenging this approach with potentially improved forecasts. This post examines CME FedWatch limitations, highlights prediction markets' advantages, and compares their performances historically. It emphasizes the value of prediction markets for understanding and reporting on Federal Reserve action, especially for economics journalists.

The Limitations of CME FedWatch Probabilities

CME FedWatch probabilities are derived from the prices of federal funds futures contracts traded on the Chicago Mercantile Exchange. These probabilities are meant to represent the market's expectations regarding the likelihood of a change in the target federal funds rate at the upcoming Federal Open Market Committee (FOMC) meeting. Despite their widespread use in economics commentary, CME FedWatch probabilities have several limitations that prevent them from being an accurate representation of market sentiment.

The federal funds futures are a function of what the target federal funds rate will be at the end of a given month. CME FedWatch works by comparing market forecasts for adjacent months against each other, and treating the difference between subsequent months as the average change in the target rate over the course of that month. For example, if the implied target fed funds rate at the end of December is 20 basis points lower than the equivalent rate for the end of November, FedWatch interprets that to mean there’s an 80% probability that the Fed will decrease the target rate by a single 25 basis points increment, and a 20% probability the rate is going to be unchanged. A 0% probability is assigned to any other outcome, such as increases of 25 or 50 basis points, or a decrease of 50 or more basis points.

The problem with this process is that there are more than two possible outcomes for any given FOMC meeting, especially ones happening more than 1 meeting into the future. The probability that the Fed will increase rates in the December meeting is certainly greater than 0%, and the same is true for the probability that the Fed will be driven to make significant cuts in case there’s a financial crisis or a recession. It is accurate to say that the market thinks there will be a 20 basis points cut in December on average, but it is impossible to infer the probability of the many different potential outcomes with a single data point. It is not accurate to say that the market thinks there’s a 0% probability the FOMC will decide to increase rates in their December meeting.

This is not meant to be taken as criticism of FedWatch. The FedWatch developers understand this limitation and state it very clearly in the methodology section of their website. The information they have access to is simply not enough to describe all potential outcomes. During most of the 2010s, when there were actually only two possibilities for every FOMC meeting, the method worked very well. In the 2020s, the economic landscape has changed dramatically. There is now a much wider range of plausible economic scenarios, and the tool is simply no longer fit for purpose.

To get a complete understanding of the probabilities for each scenario, it is necessary to have a market per scenario, instead of a single market describing the average case. Kalshi offers markets on every possible value for the target federal funds rate after every FOMC meeting, which is the only reliable way to get a full distribution of the probabilities of each outcome.

Faster to the Correct Answer: Prediction Markets' Speed Advantage

Prediction markets, such as Kalshi Fed Markets, have a notable advantage over CME FedWatch in terms of speed and responsiveness to new information. Unlike CME FedWatch, which calculates probabilities based on federal funds futures contracts with a 10-minute delay, prediction markets aggregate the diverse opinions of market participants in real-time, allowing for rapid adjustments in response to new data or events.

For economics journalists and other stakeholders, the speed advantage of prediction markets has crucial implications. Faster access to updated forecasts enables better-informed decision-making, more accurate analyses, and a competitive edge in reporting on Federal Reserve actions. By embracing prediction markets, journalists can deliver more timely and insightful content to their audience, helping them stay ahead of market trends and economic developments.

Stability and Reliability: The Consistency of Prediction Markets

When it comes to forecasting Federal Reserve actions, stability and reliability are paramount. A comparative analysis of the historical stability of Kalshi Fed Markets probabilities and CME FedWatch probabilities can reveal significant differences in their performance.

The stability of prediction markets can be attributed to factors such as the diversity of opinions and the incentives for accurate predictions. These probabilities are directly derived from the opinion of the traders, and not from a wonky and flawed math formula based on futures prices. While the futures markets do have predictive content, it is not cleanly translated into an actual probabilistic forecast. This results in the probabilities on FedWatch to swing back and forth throughout the day in a manner that reflects the futures contract price’s minute movements, but not the actual probability of the hike, pause, or cut occurring.

While FedWatch and Kalshi forecasts both waver according to price action, in a moment where the the trading is ranging 5 cents on Kalshi, the probability implied by FedWatch would range 10 or 15%. So, if you’re looking for a data point to quote in your story, the CME probability is far more likely to change between when you file your story and when it’s published.

In conclusion, the speed, stability, and clarity of prediction markets make them an essential tool for forecasting Federal Reserve actions. Prediction markets can help economics journalists and other stakeholders make better-informed decisions, craft more accurate analyses, and ultimately improve the overall understanding of the factors influencing the Federal Reserve's policy decisions.