U.S. corporate spreads narrowed to exceptionally tight levels in 2024. The mean reverting nature of credit risk premia might lead to the conclusion that imminent decompression will likely result in negative excess returns over the foreseeable future. However, a careful study of credit cycles suggests that the tendency of regressing to the mean is asymmetric—i.e., levels above the average often prove ephemeral while mid-cycle periods of spread compression typically last longer.1 This behavior is related to the nature of economic cycles. Risky securities depreciate in price during recessions, which tend to be short-lived. Valuations for most securities then bounce back quickly once the economic contraction ends and remain buoyant during the expansionary phases, which tend to last much longer than recessions.
Economic cycles are just one driver of spread levels. Other variables, such as corporate fundamentals and technical factors, are also critical to arriving at a valuation judgement. By creating simple market barometers comparing credit spreads with a variety of macro, corporate fundamental, and technical drivers, we can better understand whether the credit market is currently over, under, or fairly valued.2 To be sure, this is a measure of credit market drivers based on the current/static snapshot of these indicators and provides a starting point for our more comprehensive macro scenario analysis.
As an example of how we construct our market barometers, we’ll use U.S. ISM services—a widely followed purchasing managers’ diffusion index. Figure 1 shows the z-scores of ISM plotted against U.S. IG corporate spreads (inverted on the right axis). U.S. IG spreads usually move in tandem with the ISM measure which, in turn, tracks U.S. economic activity. Yet, there are periods when these two series deviate from each other.
ISM Services (z-score) vs. U.S. IG Corporate Spread (z-score)
Source: Bloomberg and PGIM Fixed Income as of November 2024.
To compare the relative deviation of U.S. IG corporate spreads versus this particular macro driver, we take the sum of the z-scores of spreads and the ISM services and calculate the percentile relative to history. Figure 2 shows the historical percentile of the relative z-scores. The current configuration leaves us at the low end of the historical distribution because the sum of z-scores results in a deeply negative number. This signifies a market that is rich relative to the soft economic backdrop implied by the level of ISM.
ISM Services vs. US IG Corporate Spread: Percentile of the Relative Z-score
Source: Bloomberg and PGIM Fixed Income as of November 2024.
In the rest of the post, we outline the chosen macro, corporate fundamental, and technical drivers of corporate spreads, highlight the nature/strength of the relationship, and summarize the current framework score on a scale between 0 (worst) and 10 (best). See Footnote 2 for greater detail into how we construct the composite valuation metrics.
Macro Driver Barometers
Source: Bloomberg, PGIM Fixed Income as of November 2024.
Corporate Fundamental Barometers
Source: Bloomberg, Leverage and Interest Coverage from JPM, PGIM Fixed Income as of Q2 2024.
Technical Variable Barometers
Source: Bloomberg, PGIM Fixed Income as of November 2024, except mutual fund cash which is as of October 2024.
Figure 6 shows our summary valuation judgment as of November 2024. Individual scores are combined, weighting them by the absolute value of the correlation of the explanatory variable with spreads. Consequently, short-term technical drivers such as primary dealer positions and hedged yields don’t find their way into the composite because their correlation with spreads is unreliable. In summary, spreads appear to be tight relative to the fundamental and technical drivers we have chosen. Most of the richness is driven by macro indicators (Current Score: 2). This influence of economic data is offset by better corporate fundamentals (Current Score: 4) and technical drivers (Current Score: 3).
Composite Credit Barometer
Source: PGIM Fixed Income as of November 2024.
Currently the barometer suggests that spreads are tight versus the chosen macro, corporate fundamental, and technical drivers. These barometers provide a comprehensive, unbiased, and non-parametric assessment based on history and sets the stage for further inquiry and debate. For instance, spreads screen rich based on key macro drivers. The obvious question is why have spreads remained so tight and if they can continue to do so. This analysis provides potential answers.
One, corporate fundamentals appear to be faring much better in face of weak PMIs.
Two, heavy Treasury issuance relative to corporate paper supply may also be working to keep spreads tight.
Our list of explanatory variables is far from exhaustive, and the goal is to research and add more variables that help to predict spreads. In addition, individual scores have been combined by using the correlation with spreads as the weight. Other combinatorial schemes such as beta weighting could also be helpful.
Finally, this is a static analysis and provides a stepping-stone for our more comprehensive macro scenario analysis. The barometer provides a valuation judgment based on the latest available value of the chosen variables. We build on this first step by mapping the explanatory variables to different macro scenarios, both qualitatively and quantitatively, to arrive at a probabilistic assessment of the risk-reward in the credit market over the next 12-months.
1 As evidenced by the periods 1994-1997 and 2004-2007.
2 To construct the composite valuation metric, we take the z-score of credit spreads and add/subtract it to/from the z-score of the explanatory driver based on the direction of the correlation. Then we take a historical percentile of this series to arrive at a raw valuation score for spreads based on the selected variable. This exercise is conducted for each of the chosen explanatory parameter, and finally the individual scores are weighted by the strength of correlation with spreads to arrive at the overall composite valuation barometer, as well as those for macro, corporate fundamentals and technical drivers. Finally, the rounded percentile is the score for spreads based (10th percentile being a 1 and median a 5).
Source(s) of data (unless otherwise noted): PGIM Fixed Income, as of November 22, 2024.
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