US Recession Probability Remains High

US Treasury yields rose on Friday despite the Federal Reserve’s (Fed) preferred inflation measure, PCE, rising +4.4% YoY for December compared to +4.7% YoY for November. Markets also digested a stronger-than-expected Q4 GDP print (+2.9% QoQ versus +2.8% QoQ expected). Overall, since the December 2022 FOMC meeting, lower inflation and strong employment growth have created an ambiguous macro backdrop that decisively validates neither hawks nor doves. A busy data and Fed week lie ahead, chief of which includes the 1 February FOMC meeting and January NFP data (Friday) – Dominique expects a 25bp hike and NFP to continue to slow closer to labour supply.

Turning to market moves, US 10Y yields closed the week at 3.52% (+4bps WoW) compared to 4.19% (+5bps WoW) for the 2Y and 4.57% (flat WoW) for the 3M. Important parts of the yield curve remain deeply inverted. The magnitude of the 2s10s inversion sits at -67bps while that of the 3M10Y part of the yield curve sits at -105bps. The probability of recession increases with yield curve inversion.

Our recession model, which uses the 2Y10Y part of the yield curve, assigns an 87% chance of a recession within the next twelve months (Charts 1 and 3). Meanwhile, the Fed recession model, which uses the 3M10Y part of the yield curve, produces a 57% chance of recession (Chart 2). Notably, both models are producing recession probabilities higher than that of the 2007-2008 Global Financial Crisis (GFC).

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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