Recession Probability Shows No Signs of Abating Yet

US treasury yields moved higher last week as expectations for a further Federal Reserve (Fed) two hikes, following the FOMC meeting, outweighed the suggested cooling in the inflation data (CPI and PPI). Headline CPI fell to +4.0% YoY (+0.1% MoM) while headline PPI came in at +1.1% YoY (-0.3% MoM). Elsewhere, the European Central Bank (ECB) hiked rates by 25bps.

We think the Fed is dovish despite the 50bp increase in the SEP 2023 FFR. The SEP projections raised the Fed forecast of Q4 2023 inflation but see unemployment remaining close to cycle lows. The data shows that the Fed is more focused on employment data than inflation and we believe the limited responsiveness of Fed policies to high and persistent inflation meets the definition of dovishness.

Turning to market moves, US 10Y yields closed the week at 3.77% (+2bps WoW, +23bps MoM) while the yield on the policy-sensitive US 2Y closed the week at 4.70% (+11bps WoW, +64bps MoM). In terms of yield curve inversion, the magnitude of the 2s10s inversion sat at -93bps on Friday. The probability of recession increases with yield curve inversion.

The probability of recession within the next twelve months, assigned by our recession model, which uses the 2Y10Y part of the yield curve, closed the week at 93%. It is also worth noting that the probability has not dropped below 88% this month. Meanwhile, the Fed’s recession model, which uses the 3M10Y part of the yield curve, produced a 64% 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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