Recession Probability Stays High After FOMC Meeting

US treasury yields rose last week as markets digested the outcome of the latest FOMC meeting on Wednesday. The Federal Reserve (Fed) stayed on hold and the SEP showed one more hike in 2023, two 2024 cuts instead of four in the June SEP, an unchanged inflation trajectory, and a higher growth trajectory. Dominique continues to expect  a November hike, contrary to markets pricing in just a 20% chance. However, she highlights that the resumption of student loan repayments and the end of the weather-related tax relief are a risk to this view which may cause the Fed to hike in December instead of November.  

Turning to market moves, US 10Y yields closed the week at 4.44% (+11bps WoW, +10bps MoM) while the yield on the policy-sensitive US 2Y closed the week at 5.10% (+8bps WoW, +8bps MoM). In terms of yield curve inversion, the magnitude of the 2s10s inversion sat at -66bps on Friday, up from year lows of -109bps seen in early July. The probability of recession increases with yield curve inversion. 

The probability of recession within the next twelve months, assigned by the 2Y10Y part of the yield curve, closed the week at 87% (Chart 1). Meanwhile, the Fed’s recession model, which uses the 3M10Y part of the yield curve, produced a 52% chance of recession (Chart 2). 

Background to Models 

We introduced two models for predicting US recessions using the slope of the US yield curve. When long-term yields start to fall towards or below short-term yields, the curve flattens or inverts. This has often predicted a recession in subsequent months. Our model is based on the 2s10s curve compared to a model from the Fed that is based on 3M10Y curve. We believe that the 2Y better captures expectations for Fed hikes in coming years and is therefore more forward-looking. 

Dalvir Mandara is a Quantitative Researcher at Macro Hive. Dalvir has a BSc Mathematics and Computer Science and an MSc Mathematical Finance both from the University of Birmingham. His areas of interest are in the applications of machine learning, deep learning and alternative data for predictive modelling of financial markets.

Bilal Hafeez is the CEO and Editor of Macro Hive. He spent over twenty years doing research at big banks – JPMorgan, Deutsche Bank, and Nomura, where he had various “Global Head” roles and did FX, rates and cross-markets research.

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