Monetary Policy & Inflation | US

**US treasury yields rose last week, **as investors prepared for the June 13-14 FOMC meeting. Mixed signals from Federal Reserve (Fed) officials and economic data in recent weeks have left investors with a degree of uncertainty over the future of interest rate hikes.

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**US treasury yields rose last week, **as investors prepared for the June 13-14 FOMC meeting. Mixed signals from Federal Reserve (Fed) officials and economic data in recent weeks have left investors with a degree of uncertainty over the future of interest rate hikes.

**We expect the Fed to pause next week **despite no progress on disinflation since the April FOMC meeting, highlighting the fact that the Fed’s reaction function has become more dovish. We get May CPI data this week, and we expect strong inflation dynamics to continue (no disinflation) but given it is released on the first day of the FOMC meeting, it is unlikely to impact the Fed decision.

**Turning to market moves, **US 10Y yields closed the week at 3.75% (+6bps WoW, +22bps MoM) while the yield on the policy-sensitive US 2Y closed the week at 4.59% (+9bps WoW, +58bps MoM). In terms of yield curve inversion, the magnitude of the 2s10s inversion sat at -84bps 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 91%. Meanwhile, the Fed’s recession model, which uses the 3M10Y part of the yield curve, produced a 65% 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.

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.