High Yield Credit Spreads

Measures financial stress by comparing risky corporate debt to government bonds.

Key Insight

High-yield spreads sit near 320 bps, hovering in the bottom quartile of their 20-year distribution and roughly half their long-run median near 525 bps — the credit market is pricing materially less recession risk than either economists or prediction markets.

Generated by Claude on Apr 22, 2026

2.8%

Trend YoY growth is +0.2%, accelerating by 61 bps/year over the last 2Y. Deviations have remained below trend for 30 consecutive periods. Latest: -0.8%, 101 bps below trend, a 1.5σ deviation. The latest YoY reading is depressed by 105 bps due to an tough comparison base from May 1.

Level

YoY Change

y = −1.0% + 61 bps/yr · t

Deviation from trend

Forecast

Projected value by forecast vintage (%)

Projected value (%)

Forecast made inOct '25Nov '25Dec '25Jan '26Feb '26Mar '26Apr '26May '26Jun '26Jul '26Aug '26Sep '26Oct '26Nov '26Dec '26Jan '27Feb '27Mar '27Apr '27May '27Jun '27MAPE
Oct '252.92.93.12.93.24.04.43.93.63.53.63.63.93.93.94.04.34.54.24.25.1158%
Nov '252.93.12.93.13.94.33.83.53.43.43.53.73.73.63.84.14.33.93.94.6155%
Dec '252.82.83.03.84.23.63.33.23.23.23.43.43.43.53.73.93.53.54.0104%
Jan '262.92.93.64.03.43.03.02.92.93.13.03.03.03.33.53.03.03.2106%
Feb '263.13.53.93.32.92.82.82.82.92.92.72.83.03.22.72.72.8100%
Mar '263.33.93.32.92.82.82.72.82.82.72.73.03.12.62.62.7100%
Apr '262.83.12.72.62.52.52.62.52.42.42.62.82.32.22.164%
May '262.82.72.52.52.42.62.52.42.42.62.82.32.22.1
Jun '262.72.52.52.42.62.52.42.42.62.82.32.22.1

YoY change forecast

Forecast made inOct '25Nov '25Dec '25Jan '26Feb '26Mar '26Apr '26May '26Jun '26Jul '26Aug '26Sep '26Oct '26Nov '26Dec '26Jan '27Feb '27Mar '27Apr '27May '27Jun '27MAPE
Oct '25+0.1%+0.1%+0.2%+0.3%+0.3%+0.4%+0.5%+0.5%+0.6%+0.7%+0.8%+0.8%+0.9%+1.0%+1.1%+1.1%+1.2%+1.3%+1.3%+1.4%+1.5%158%
Nov '25+0.2%+0.2%+0.2%+0.3%+0.3%+0.4%+0.4%+0.5%+0.5%+0.6%+0.7%+0.7%+0.8%+0.8%+0.9%+0.9%+1.0%+1.0%+1.1%+1.2%155%
Dec '25-0.1%+0.1%+0.2%+0.2%+0.2%+0.3%+0.3%+0.4%+0.4%+0.4%+0.5%+0.5%+0.5%+0.6%+0.6%+0.7%+0.7%+0.7%+0.8%104%
Jan '26+0.2%+0.0%+0.0%+0.1%+0.1%+0.1%+0.1%+0.1%+0.1%+0.1%+0.1%+0.1%+0.1%+0.2%+0.2%+0.2%+0.2%+0.2%106%
Feb '26+0.3%+0.0%+0.0%+0.0%+0.0%+0.0%+0.0%+0.0%-0.1%-0.1%-0.1%-0.1%-0.1%-0.1%-0.1%-0.1%-0.1%100%
Mar '26-0.2%+0.0%+0.0%-0.1%-0.1%-0.1%-0.1%-0.1%-0.1%-0.1%-0.1%-0.2%-0.2%-0.2%-0.2%-0.2%100%
Apr '26-0.9%-0.3%-0.3%-0.3%-0.3%-0.4%-0.4%-0.4%-0.4%-0.4%-0.5%-0.5%-0.5%-0.5%-0.6%64%
May '26-0.8%-0.3%-0.3%-0.3%-0.4%-0.4%-0.4%-0.4%-0.4%-0.5%-0.5%-0.5%-0.5%-0.6%
Jun '26-0.3%-0.3%-0.3%-0.4%-0.4%-0.4%-0.4%-0.4%-0.5%-0.5%-0.5%-0.5%-0.6%

Forecasts use ordinary least-squares linear regression fitted to the YoY change series over a rolling 1Y window. Each row shows a vintage — the forecast as it would have appeared at that point in time. Projected values apply the forecasted YoY change to the prior year's level, chaining forward where actuals are unavailable. MAPE measures forecast accuracy against realized values. These are mechanical trend extrapolations, not economic models.