The FOMC, Polymarket, and Kalshi: When the Rate Cut Is Priced Before the Call

I’m old enough to remember a time before prediction markets like Polymarket and Kalshi, and if you’re old enough to read and understand the acronym “FOMC,” then you probably remember that time, too (if you happen to be the world’s most literate two year old, then congratulations, and send us your résumé). 

Rate decisions from the Fed were always a spectacle, shrouded in a cloud of mystique, and while some decisions were much more predictable than others, you could never feel absolutely certain that analysts and public sentiment were correct. 

Now, times have changed. When I want to know how likely the Fed is to cut or raise rates, I no longer seek out commentary from analysts, or try to deduce what I can from the efficiency of the broader market. Rather, I open my browser, go to a prediction market’s website, and look at the exact chances - at least in the eyes of the efficient market - of every possible outcome. 

Having these “exact” chances at our disposal is a luxury, and as every good trader knows, efficient markets are seldom wrong, even as it pertains to private information. They help to smooth volatility, and prevent huge market corrections from “unexpected” Fed decisions. However, there could be some dangerous implications to having these “exact” chances publicly available, and all of them start with the same question: what happens if the prediction markets get it wrong?

For years, FOMC days all followed a similar script; even when traders felt fairly certain about the coming decision, there was always uncertainty present that could not be cleanly quantified. Attempting to price in the decision relied on a variety of nuanced factors, such as a slew of Fed speeches, economist and analyst notes, Eurodollar/SOFR curves, and the CME FedWatch tool (which, to be fair, is still an excellent resource).

As a result, the decision would be released, and even if the number confirmed the consensus predictions, stocks, rates, and the dollar would still make a final “confirmation move” pricing in that information as uncertainty collapsed. Volatility would fall after the print, but price typically moved too, because there were still some last-mile doubts that required resolution.

Enter Polymarket and Kalshi. The emergence and ever-growing prominence of these prediction markets means that instead of vibes like “likely cut,” traders and investors now have access to a live market that says “there is a 97% chance that the FOMC issues a 25 basis point cut.” That number is concrete, trackable, and hedgeable. 

These odds now filter into positioning days ahead of the meeting; the efficient market bends to the consensus path, equity sectors lean the way they “should,” and options markets crush implied volatility ahead of time. When the FOMC matches the posted odds, the aftermath is much quieter than in previous years; essentially, the decision gets priced in before it is officially released, and the FOMC’s narrative and details about the path forward are what do the work to move markets after the fact. 

There are many upsides to having these “exact” chances posted so publicly that have already been covered in depth by the broader media, but what may not be getting enough attention is the potential downsides to this new methodology. In the spirit of remaining impartial, I will list the pros alongside the cons, to be sure that the full picture is painted. 

Pros include:

• Smoother post-decision market action: Having clear, crowd-sourced odds reduces large corrections after FOMC decisions. Markets can spend less energy on pricing in the current decision and focus more on trying to price in future trajectory. 

• Easier, cleaner hedging: Odds let traders size their exposure properly and buy protection only where it matters. Furthermore, traders can directly buy contracts opposite their sentiment on prediction markets as a direct hedge against an unfavorable rate decision.

• Improved price discovery: Having publicly posted probabilities (try saying that five times fast) means bad takes get arbitraged away much faster. 

Cons include:

• Confirmation bias: Traders and investors may see prediction market odds that strongly indicate a decision will go one way, and then place a bunch of stock market trades reflecting that sentiment. Other traders and investors may then see that the stock market seems to be pricing in that same FOMC decision, and then go buy contracts on a prediction market reflecting that sentiment, pushing prediction market odds higher and restarting the cycle.

• Reflexivity: If everyone makes stock market trades based on the same prediction market odds, positioning gets one-sided. This can lead to overly pricing in a decision and then needing a correction the other way after it is released, or setting up larger air pockets should the prediction market odds shift late. 

• Overconfidence: A 90-97% confidence level can lull traders and investors into ignoring second-order risks, such as dots, growth/inflation wording, and balance sheet tweaks, that actually move multiples. 

• Tail Risk: Perhaps the most important con of them all is tail risk, where prediction markets price in a 95-99% chance of a decision and somehow get it wrong. This, at best, would send volatility soaring, and, at worst, could decimate all sorts of markets for a short time. 

This last point deserves the most attention, as it is the true disaster case. Let’s look at this through the lens of an example where prediction markets indicate a 95-99% chance that the Fed will cut rates in an upcoming meeting, and traders all position themselves that way. Then, suppose the Fed holds or hikes rates. In that scenario, here are all of the markets that would be impacted:

• Rates: Front-end yields would gap higher, the curve would snap flatter, and rate-sensitive equities would all dump. 

• Equities: Indexes would gap down, defensives and dollar-beneficiaries would rocket, and high-duration names would lag severely. 

• Forex and credit: The dollar would rocket, bonds would widen, and emerging markets would at least wobble. 

• Options: Implied volatility would rip higher, short-dated options would violently reprice, and corridors around the expected move would blow out. 

In short, the higher that the posted odds are on prediction markets, the bigger the gap will be if they’re wrong. While they’re almost never wrong, anybody who’s been trading options for long enough is all too aware of the fact that tail risk is very real, and eventually comes through in large enough sample sizes. 

All told, prediction markets didn’t make FOMC day irrelevant, they just moved the game earlier. In the modern era of prediction markets, the decision itself is often a non-event if it matches prediction market odds; the real action is in the path the Fed outlines for the future, or in the rare but explosive tail event where prediction markets get the odds wrong.