Yields Surge as US Payrolls Far Exceed Expectations

US treasury yields increased last week as an unexpectedly strong US jobs report strengthened the case for more tightening from the Federal Reserve (Fed). Nonfarm payrolls increased by 336k in September against expectations of 170k. Furthermore, the 187k increase recorded in August was revised up to 227k. Dominique notes that this is yet another instance of a huge discrepancy between payrolls (+336k) and the household survey employment (+86k) which is why participation is unchanged and unemployment is up 10bp, despite the bumper payrolls. And while wages were weaker than expected, Dominique believes this is driven by an influx of foreign labour supply who have accounted for 3.3mn of the 3.7mn increase in labour supply since 2019. 

Turning to market moves, US 10Y yields edged closer to 5% having closed the week at their highest level since 2007 at 4.78% (19+bps WoW, +48bps MoM). Mustafa believes the US 10Y can reach 5.5%. Meanwhile, the yield on the policy-sensitive US 2Y closed the week at 5.08% (+5bps WoW, +7bps MoM). In terms of yield curve inversion, the magnitude of the 2s10s inversion sat at -30bps 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, dropped to 73% from 79% a week earlier (Chart 1). Meanwhile, the Fed’s recession model, which uses the 3M10Y part of the yield curve, produced a 43% 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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