We recreated the Atlanta Fed's Market Probability Tracker — and it's way more interactive

What is the Atlanta Fed Market Probability Tracker?

The Atlanta Fed's Market Probability Tracker is a lesser-known but powerful tool that extracts the full probability distribution of future interest rates from SOFR options. While CME's FedWatch gives you discrete probabilities (e.g., '84% chance of a cut'), the Atlanta Fed tool shows the continuous probability density function — the shape of the market's uncertainty.

This is a fundamentally richer view. Instead of 'the market expects a cut,' you can see 'the market expects a cut, but there's a fat tail of outcomes where rates stay higher for longer.' The shape of the distribution matters for risk management, options pricing, and macro analysis.

How does the Atlanta Fed tool differ from CME FedWatch?

FedWatch uses Fed Funds futures, which are linear instruments. They tell you the expected average rate, from which you can infer probabilities of discrete outcomes (hold, 25bp cut, etc.). The resolution is limited to the standard 25bp grid of Fed decisions.

The Atlanta Fed tool uses SOFR options, which are nonlinear instruments. A butterfly spread at a given strike gives you the probability density at that specific rate. By constructing butterflies across all available strikes, you build the full probability distribution — including tail risks that discrete probabilities miss.

How does the Atlanta Fed extract probability distributions from options?

The mathematical foundation is the Breeden-Litzenberger result from 1978: the second derivative of the call option price with respect to the strike price gives you the risk-neutral probability density function.

In practice, you don't take actual derivatives. Instead, you construct butterfly spreads:

PDF(K) ≈ [C(K - ΔK) - 2C(K) + C(K + ΔK)] / ΔK²

where C(K) is the call option price at strike K, and ΔK is the strike spacing.

This gives you a discrete approximation of the probability density at each strike. Sum these across all strikes (with appropriate normalization) and you have the full distribution.

What are the challenges in implementing the Atlanta Fed methodology?

The theoretical formula is clean, but the implementation has several practical challenges:

Strike availability: SOFR options don't have strikes at every basis point. You need to interpolate between available strikes, which introduces model dependence.

Bid-ask spread: For deep out-of-the-money strikes, the bid-ask spread can be wider than the theoretical butterfly value. You need to filter or smooth these observations.

Expiry mapping: You need to map SOFR option expiry dates to FOMC meeting dates. This isn't always one-to-one, requiring interpolation between expiries that bracket the meeting.

Normalization: The raw butterfly values don't sum to exactly 1. You need to normalize and ensure the distribution integrates correctly.

Is there a free version of the Atlanta Fed tool?

We rebuilt the full Atlanta Fed methodology in Quadesto, with improvements that make it more accessible:

Adjustable parameters: Choose the FOMC meeting, the strike range, and the smoothing bandwidth. See how these choices affect the shape of the distribution.

Multiple distributions: Overlay probability distributions for different meetings on the same chart. See how uncertainty evolves across the FOMC calendar.

Historical comparison: Compare today's distribution with the distribution from 3 months ago. Has the market's uncertainty increased or decreased?

Embeddable: Every chart is embeddable with one line of code. Finance newsletters can show their readers the full probability landscape, not just a single number.

What can a probability distribution tell you that FedWatch can't?

A bimodal distribution (two peaks) suggests the market is split between two distinct scenarios — for example, 'the economy is fine and rates stay high' vs 'something breaks and the Fed cuts aggressively.' FedWatch's discrete probabilities can hint at this, but the full distribution makes it visually obvious.

Fat tails indicate the market is pricing significant probability of extreme outcomes. A wide distribution with heavy tails before an FOMC meeting means the market expects a volatile reaction regardless of the decision.

Skew (asymmetry) shows directional bias. A left-skewed distribution means the market sees more downside risk to rates than upside. This is valuable information for rates traders and macro analysts.

Try it yourself

Our rebuild is free to use and embed. Connect your own SOFR options data or use our sample dataset to explore the probability distributions across the FOMC calendar.