**High-Yield Spreads Are Too Thin Vis-a-Vis Default Risk and Business Activity**
Industrial commodity price deflation increases high-yield default risk and vice versa.

Feb 16, 2018

The market value of U.S. common stock has rebounded by 5.8% from February 8’s bottom, but remains 4.8% under its record high of January. A corporate bond rally that began on Wednesday continued today. On Thursday, a composite speculative-grade bond yield sank by 12 basis points to 6.34%, which narrowed the high-yield bond spread to 366 bp.

Nevertheless, from the perspectives of the U.S.’ actual and projected high-yield default rates, as well as the recent average and median expected default frequency metrics of U.S./Canadian high-yield issuers, the credit quality of U.S. corporations has yet to return to its highs of the current recovery, which it reached in 2014. For example the high yield default rate is projected to slide from January’s 3.2% to 2.0% by January 2019, and the latter would still top September 2014’s low of 1.62% for the current upturn. Moreover, the default rate’s moving 12-month average of the current recovery troughed at the 1.81% of the span ended May 2015, or just prior an outbreak of severe industrial commodity price deflation.

The yearly percentage-point change for the EDF measure of high-yield default risk shows inverse correlations of -0.73 with the annual percent change of Moody’s industrial metals price index and -0.39 with the annual percent change by the price of WTI crude oil. In other words, industrial commodity price deflation increases high-yield default risk and vice versa.

According to an explanatory model showing a very meaningful adjusted r-square statistic of 0.89, the high-yield bond spread now appears to be too thin both with and excluding the now-elevated VIX index. Using various lags, the model explains the high-yield bond spread in terms of (i) the average expected default frequency metric of U.S./Canadian high-yield issuers, (ii) the VIX index, and (iii) the moving three-month average of the Chicago Fed’s national activity index. When including the recent VIX index of 19.8 points, the model recently predicted a 460 bp midpoint for the high-yield bond spread, which was much wider than Thursday’s 366 bp.

After removing the VIX index from the set of explanatory variables, the adjusted r-square eases somewhat to a still-respectable 0.84. Despite the removal of a now above-trend VIX index, the remaining explanatory variables predict a midpoint of 424 bp for the high-yield spread that still exceeds the actual spread.

Thus, barring significantly lower readings for the high-yield EDF metric and the VIX index, as well as a jump by the national activity index, the high-yield bond spread is more likely to widen than narrow. By the way, the recent high-yield EDF metric of 3.53% compares unfavorably with its yearlong 2014 average of 2.31%.

Given the recent intense focus on the effect of labor market conditions on price inflation, it’s worthwhile to examine the historical correlations of the several variables in the news, namely the 10-year Treasury yield and the annual rate of personal consumption expenditure price index inflation with and excluding food and energy prices. For a sample that begins in July 1985, the 10-year Treasury yield shows its strongest correlations with the percentage of the workforce at least 55 years old (-0.87,) the annual rate of core PCE price index inflation (0.79), the percentage of industrial capacity in use (0.65), the labor force participation rate (0.64), PCE price index inflation (0.63), and the year-to-year change of the labor force participation rate (0.57).

Though the growth of the average hourly wage shows a meaningful correlation of 0.45 with the 10-year Treasury yield, it still falls well behind the previously mentioned indicators. One surprise might be the 10-year Treasury yield’s comparatively weak correlation of -0.16 with the unemployment rate, especially relative to the Treasury yield’s 0.65 correlation with the percentage of industrial capacity in use.

The annual rate of PCE price index inflation shows its strongest correlation of 0.52 with the percentage of industrial capacity in use (or the capacity utilization rate), followed by correlations of 0.46 with the annual percentage change by the price of West Texas Intermediate crude oil, and -0.43 with the percentage of household-survey employment for those at least 55 years old. PCE price index inflation’s other notable correlations are 0.37 with the yearly change of the labor force participation rate, 0.35 with the yearly change of the capacity utilization rate, and 0.32 with the labor force participation rate.

The much-cited yearly change of the average hourly wage reveals an uninspiring correlation of 0.25 with PCE price index inflation. Finally, the unemployment rate and its year-to-year change generated correlations of -0.12 and -0.16, respectively, with the annual rate of PCE price index inflation.

Relative to core PCE price index inflation, the unemployment rate and its year-to-year change revealed meaningless correlations of -0.02 and -0.06, respectively. In stark contrast, the yearly percentage-point change of the labor force participation rate revealed a noteworthy correlation of 0.52 with the annual rate of core PCE price index inflation.

And, once again, the percentage of household-survey employment at least 55 years old reveals a substantial inverse correlation of -0.52 with the annual rate of core PCE price index inflation. The capacity utilization rate’s 0.48 correlation with the annual rate of core PCE price index inflation easily doubled average hourly earnings’ 0.21 correlation with inflation’s underlying pace.

High-Yield Spreads Are Too Thin Vis-a-Vis Default Risk and Business Activity | Moody's Analytics Economy.com