NEW YORK, February 2, 2024: Markets continue to focus on interest rates and the timing of the Federal Reserve in cutting them. The end-of-month pullback reflected an adjustment to anticipated timing, but not a change in expectations that rates will come down. The other key market factor is the continuing bifurcation between winners and losers. Due to the nature of indices, even when a given market is up, many companies are exposed to increasing risks from leverage, refinancing, geopolitical conflicts, and many other factors. Looking at current conditions through the lens of the credit cycle, lending and capital access show signs of recovery. Taking a broader view, the next few years offer good opportunities for those who can interpret the risks.
There were 16 defaults in our coverage universe during the month, up from 15 last month. Six were in the U.S., three each in India and the U.K. and one each in China, Denmark, Japan, and Sweden. During 2023 we registered 88 defaults in the U.S., compared to 27 in 2022.
Contemporaneous credit conditions declined in January, with the Kamakura Troubled Company Index® closing the month at 9.14%, up 0.22% from the prior month and up 1.68% from a year ago. The index measures the percentage of 42,400 public firms worldwide with an annualized one-month default probability of over 1%. An increase in the index reflects declining credit quality, while a decrease reflects improving credit quality.
At the end of January, the percentage of companies with a default probability between 1% and 5% was 6.62%. The percentage with a default probability between 5% and 10% was 1.32%. Those with a default probability between 10% and 20% amounted to 0.85% of the total; and those with a default probability of over 20% amounted to 0.35%. For the month short-term default probabilities ranged from a low of 8.15% on January 8 to a high of 9.14% on January 31.
Figure 1: Troubled Company Index® — January 31, 2024
At the end of January, the riskiest 1% of rated public firms within the coverage universe included 11 companies in the U.S. and 1 in the U.K. The riskiest rated firm was Enviva Inc. (NYSE:EVA), with a one-month KDP of 50.51%, up 2.53% for the month.
Table 1: Riskiest Rated Companies Based on 1-month KDP – January 31, 2024
The Kamakura Expected Cumulative Default Rate, the only daily index of credit quality of rated firms worldwide, shows the one-year rate down 0.06% at 0.70%, with the 10-year rate down 0.59% at 9.99%. The implied forward default rate predicts an increase in the one-year default rate for both 2025 and 2026.
Figure 2: Expected Cumulative Default Rate — January 31, 2024
Commentary
Stas Melnikov and Martin Zorn
SAS Institute Inc.
Propelled by rising inflation and interest rates as well as deteriorating company balance sheets, the median risk of default in the United States has been rising steadily over the past two years (Figure 3). As we start 2024, there are several observations about the bond market that warrant attention, especially when considered in light of the rising default expectations for the year.
- Market size. The amount of corporate debt outstanding has doubled from about $5 trillion at the time of the Global Financial Crisis to over $10 trillion today[1].
- Ratings distribution. Much of the new debt issuance has been in the BBB credit ratings category over the past several years. That is right on the cusp of the investment grade. The disproportionately large size of this segment is unprecedented.
- Fallen angels. The likelihood of downgrades is expected to increase as higher rates and subdued growth put pressure on revenues and debt service coverage, while tightening credit conditions make refinancing more challenging. The size of the BBB segment combined with higher likelihood of downgrade may result in an unprecedented inflow into the fallen angels category. In such event, the behavior of the BBB sector and the corporate bond market in general may become notably more volatile.
Financial crises always have many explanations ex post, but virtually impossible to predict ex ante. What we can do is to monitor the fragility of the system and look for possible trigger events and vulnerabilities. The behavior of BBBs is one of those areas that can possibly become the falling grain of sand that causes the collapse of the sand pile[2].
Figure 3: Expected Cumulative Default Rate (Median) – United States
Beyond the first year, defaults are expected to accelerate further, as cumulative two- and three- year median forecasts have approached their all-time highs. Overall, the forecasts are notably more pessimistic for the smaller companies than larger ones. That is an important consideration when interpreting median figures.
Interestingly, examining the forecasts by business sector reveals no discernable winners or losers – the outlook is equally pessimistic for all sectors. That said, the dispersion of expected probabilities of default has grown considerably over the same two-year period (Figure 4).
Figure 4: Cumulative 3yr Default Probability Distribution – United States
The implication here is that individual company characteristics and idiosyncratic components are more important than ever. The ever-present and accelerating disruption driven by the mega-trends such as technological progress, geopolitics, climate, and demographics exacts an increasingly uneven impact at a company level.
From the risk management perspective this means that the cone of uncertainty is wide. There is a strong case for the need to understand the assumptions used to model risk. As changes are accelerating, all models are going to be challenged. While it has always been a good practice, the current environment demands utilizing multiple measurements.
The bottom line is that credit conditions are expected to worsen, especially on a two- to three-year horizon. While no forecast is a guarantee, it is a warning of a more fragile and uncertain environment. The good news is that there is still time to act to better position your portfolios and/or organization in anticipation of the coming changes. Paying heed to robust early warning mechanisms, using scenario-based analytics to consider possible paths forward, and adopting multiple risk quantification approaches to enhance precision and reduce blind spots are some of the most important steps you can take to prepare for what lies ahead.
About the Troubled Company Index
The Kamakura Troubled Company Index® measures the percentage of 42,100 public firms in 76 countries that have an annualized one-month default risk of over one percent. The average index value since January 1990 is 14.19%. Since July 2022, the Kamakura index has used the annualized one-month default probability produced by the KRIS version 7.0 Jarrow-Chava reduced form default probability model, a formula that bases default predictions on a sophisticated combination of financial ratios, stock price history, and macro-economic factors.
The KRIS version 7.0 models were developed using a data base of more than 4 million observations and more than 4,000 corporate failures. A complete technical guide, including full model test results and key parameters, is provided to subscribers. Available models include the non-public-firm default model, the U.S. bank model, and the sovereign model.
The version 7.0 model was estimated over the period from 1990, through the Great Recession and ending in February 2022. The 76 countries currently covered by the index are Argentina, Australia, Austria, Bahrain, Bangladesh, Belgium, Belize, Botswana, Brazil, Bulgaria, Canada, Chile, China, Colombia, Croatia, Cyprus, Czech Republic, Denmark, Egypt, Estonia, Finland, France, Germany, Ghana, Greece, Hungary, Hong Kong, Iceland, India, Indonesia, Ireland, Israel, Italy, Japan, Jordan, Kenya, Kuwait, Luxembourg, Malaysia, Malta, Mauritius, Mexico, Nigeria, the Netherlands, New Zealand, Norway, Oman, Pakistan, Peru, the Philippines, Poland, Portugal, Qatar, Romania, Russia, Saudi Arabia, Serbia, Singapore, Slovakia, Slovenia, South Africa, South Korea, Spain, Sri Lanka, Sweden, Switzerland, Tanzania, Taiwan, Thailand, Turkey, the United Arab Emirates, Uganda, the UK, the U.S., Vietnam and Zimbabwe.
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Editorial contacts:
- Martin Zorn – Martin.Zorn@sas.com
- Stas Melnikov – Stas.Melnikov@sas.com
[1] Source: SIFMA
[2] The sandpile analogy is inspired by the Bak–Tang–Wiesenfeld model: https://en.wikipedia.org/wiki/Abelian_sandpile_model#The_extended_sandpile_model