2022: Defaults Accelerated On Tighter Financing Conditions And China's Property Sector Challenges

2022 was a year of increased uncertainty, both globally and in Asia. On one hand, post-pandemic recoveries were driving domestic recoveries in the region, with matching export strength from advanced economies' growth as well. On the other hand, cost push inflation was a major challenge, especially since the onset of the Russia-Ukraine conflict.

Stronger signs of demand pull inflation soon followed, leading central banks almost everywhere to tighten monetary conditions significantly. Funding costs both offshore and onshore rose for Asian borrowers, especially for the lower-rated issuers.

Meanwhile, China kept its dynamic-zero COVID policy until late into 2022. This exempted it from seeing the same spikes in inflation and interest rates as the rest of the region. However, weak demand stemming from public health policies, combined with prior years' policy tightening, weighed on the real estate sector, leading to it being a main source of defaults for the region.

Global corporate defaults in 2022 surpassed the 2021 total by 15% (83 in 2022 vs. 72 in 2021). These defaults reflected regional and sectoral vulnerabilities. In particular, many Asian defaults reflected signs of stress among homebuilders, particularly due to China's property market slump. In Asia, the number of defaults tripled to 18--a new historical high, from six last year.

Asia's speculative-grade default rate doubled to 6.4% in 2022, from 3.2% in 2021. Globally, the 2022 speculative-grade default rate was 1.9%, up from 1.7% in 2021. The default rate in the U.S. in 2022 increased to 1.7% from 1.5% the prior year; in Europe to 2.2% from 1.8%; and emerging and frontier markets (see Appendix I for details on the countries included) to 2.4% from 1.9% (see chart 1).

The total number of rated issuers in Asia decreased to 831 by end-2022 from 856 as of end-2021, with 6.43% of the latter seeing ratings withdrawn. There were 47 newly rated entities over the year, down from 62 in 2021. The distribution of these ratings was broadly steady from last year. Some 44.7% of newly rated Asian companies in 2022 were speculative-grade (rated 'BB+' or lower). The 55.3% share of newly rated investment-grade issuers was up only slightly, from 54.8% in 2021 and 53.1% in 2020.

For the purposes of this study, Asia consists of Bangladesh, Bhutan, British Indian Ocean Territories, Brunei Darussalam, Cambodia, China, Fiji, Hong Kong Special Administrative Region (SAR) of China, India, Indonesia, Japan, Republic of Korea, Macao SAR of China, Malaysia, Marshall Islands, Mongolia, Pakistan, Papua New Guinea, Philippines, Singapore, Sri Lanka, Taiwan, Thailand, and Vietnam. The statistics in this study refer only to corporate ratings and include financial and nonfinancial entities.

Regional Default Trends

The 18 defaults in the region in 2022 were over one-fifth of the global total of 83. Since 1993, the regional average number of annual defaults is 4.4, compared with a global average since 1981 of 77.5. Nonetheless, 83.4% of ratings in Asia remained unchanged between Jan. 1, 2022, and year-end, demonstrating the relative stability of most credit ratings in the region. Nearly 5.0% of rated entities from Asia were upgraded during the year, and only 3.86% were downgraded (excluding defaults), providing for a downgrade-to-upgrade ratio of 0.77 (see table 4).

The overall ratings stability in Asia owes partially to its high proportion of investment-grade issuers--at 83.2% (see chart 2) as of year-end 2022--which have markedly lower transition and default risk than their speculative-grade counterparts. Part of the reason for this distribution of ratings is that most of the region's total debt is held in the form of bank loans instead of bonds, especially for less well-known entities. By comparison, only 50.5% of rated issuers globally were investment-grade at the end of 2022.

Gini ratios

Like our global corporate default and transition study, this study illustrates that ratings are effective indicators of relative credit risk. S&P Global Ratings Credit Research & Insights has found a clear negative relationship between ratings and defaults: The higher the issuer rating, the lower the observed default frequency.

We use Gini coefficients to measure the correspondence between ratings and defaults. Gini coefficients measure the rank-ordering power of ratings over a given time horizon and compare the ratio of actual rank-ordering performance with theoretically perfect rank ordering.

If corporate ratings were perfectly rank ordered so that all defaults occurred only among the lowest-rated issuers, the Gini coefficient would be 100%. The one-year weighted average (1993-2022) Gini coefficient for rated Asian corporate issuers is 90.2%. This metric is based on ratings one year prior to default rather than those immediately preceding default (see Appendix II for details).

The weighted averages in this report use the issuer counts at the beginning of the year as the weights. Unless otherwise noted, the statistics in this study refer to S&P Global Market Intelligence's Credit Pro corporate local currency global-scale ratings universe. They include financial and nonfinancial Asian companies but exclude sovereigns, public finance, and project finance issuers. (For more details and definitions of the terms used, see Appendix I.)

Sovereign Ratings Backdrop

Most sovereign ratings in Asia-Pacific are investment grade (see table 1). The average sovereign rating in the region, lying between 'BBB' and 'BBB+', moved closer to 'BBB' in 2022 on account of our downgrades of Pakistan and Sri Lanka. Twenty of the 21 sovereign ratings in Asia-Pacific had stable outlooks as of Dec. 31, 2022.

There is no outlook on Sri Lanka since it is in default. (See "Asia-Pacific Sovereign Rating Trends 2023: A Break In The Weather," Jan. 27, 2023).

Table 1

Ratings Performance For Asia

We reached the following key conclusions regarding Asia's corporate ratings performance in 2022:

• The average time to default from initial rating for defaulters in Asia through 2022 was 3.6 years, lower than the global average of 5.9 years (from 1981-2022). Some 89.35% of the original ratings for Asian defaulters were speculative grade, similar to the global proportion.
• The average time to default from initial ratings for defaulting issuers with investment grade initial ratings was nearly half that of their global counterparts, at 6.3 years compared with 11.7 years globally. While for speculative grade, it is 3.3 years versus 5.1 years globally.
• In 2022, 95.7% of 'A' rated issuers in Asia retained that rating, and only 54.9% of the region's 'B' rated issuers retained that rating (see table 12).
• Singapore Technologies Engineering Ltd. was downgraded to 'AA+' from 'AAA' on elevated leverage after its acquisition of Transcore in March 2022, leaving one 'AAA' in the region.
• The 2022 Asia default rate in the 'CCC'/'C' rating category (encompassing all ratings of 'CCC+' and below, excluding defaults) was 58.3%, higher than the 13.8% rate globally, though the low number of total issuers in Asia creates volatility in the average statistics (see table 12).
• At the end of 2022, over four-fifths of the total ratings in Asia were investment grade. Only 50.5% of all global ratings were investment grade.

Table 2

Table 3

Globally, corporate defaults increased to 83 in 2022 from 72 in 2021, Asia and Europe accounting for 42%. Corporate defaults affected rated debt worth $107.0 billion in 2022 globally, from $66.3 billion in 2021. Defaults in Asia accounted for only 1.4% of debt affected by global defaults, at $1.5 billion.

The total number of downgrades in the region for 2022 decreased to 33 from 38 in 2021. Meanwhile, upgrades in the region decreased to 43, from 63 in 2021.

Table 4

Table 5

S&P Global Ratings assigned ratings to 47 new issuers in Asia in 2022, a decrease from 62 in 2021. Of the 47 new issuers, 21 were rated in the 'BBB' category, followed by the 'B'and 'CCC' category at nine each. 21 (44.7%) were rated speculative grade (see table 5).

The total ratings pool in Asia remains heavily weighted toward investment grade. The proportion of speculative-grade ratings for Asia remains low, at just 16.8% at the end of 2022 (see chart 2).

For comparison, when including Australia and New Zealand in the calculation, the proportion of speculative-grade issuers for Asia-Pacific was 16.3% in 2022. Conversely, emerging and frontier markets overall have a greater concentration of speculative-grade ratings, with 48.8% of all issuers rated 'BB+' or lower. For all global issuers, the proportion of speculative-grade ratings is about 49.5%, with the U.S. accounting for the bulk of them.

A Closer Look At Asia's Defaulters

Of the 10 publicly rated Asian defaulters in 2022, Singapore-based Mulhacen Pte. Ltd. had the highest amount of debt outstanding at the time of default ($568.8 million, see table 6). In March 2022, the nonoperating holding company announced the completion of its €557 million PIK toggle bond restructuring, with 99.79% of its bondholders consenting.

Together, the 18 Asian defaults accounted for about 1.4% of the $107.0 billion in debt globally affected by defaults in 2022. Of the 10 public issuers in Asia, six defaulted through a distressed exchange in 2022, two missed principal or interest payments, with the remaining two defaulters filing Chapter 11 and Chapter 15, respectively.

Table 6

Higher Ratings Are Consistent With Fewer Defaults

During 1993-2022, there were a total of 131 corporate defaults in Asia, a small fraction of the 3,253 recorded globally from 1981-2022. This small sample size introduces some challenges in the analysis.

The average time to default (the average number of years between the initial rating date and the default date) for the 18 Asian defaulters in 2022 was 3.5 years, well below the 6.2 years average globally. The average for the entire long-term pool of Asian defaults is 3.6, compared with 5.9 years for long-term global defaults.

By and large, higher ratings take a longer time to default (see chart 5). For example, Asian issuers rated 'B' took an average of 3.4 years to default--less than the 4.3 years for 'BB' rated issuers (see table 7).

The average time to default from the original rating for Asian issuers is shorter across all rating categories than it is for the global pool. This is true regardless of whether the time to default is calculated from original rating (see table 7) or from subsequent ratings (see table 8).

Table 7

Table 8

This discrepancy in the average timing (and the associated standard deviation) results partly from the significantly smaller volume of defaults in every rating category in Asia. For example, of the global pool of issuers in the 'BBB' category, 227 defaulted during 1981-2022, whereas the comparable number for Asia (from 1993-2022) was only 11. Also, the 1997-1998 Asian financial crisis accelerated the average time to default in the region compared to global norms, but many policies have been put in place since then to mitigate the risks of a repeat.

The breakout of default rates by modifier shows that, historically, lower rating categories experience higher default rates on average, though variability is possible in any given year (see table 9). Nevertheless, the data from past default cycles indicate that most defaults stemmed from the lowest rungs of the ratings ladder.

Table 9

Defaults By Industry

Among nonfinancial industries, the 2022 aggregate one-year default rate was 1.90%, which is slightly higher compared to the 1993-2022 long-term average of 1.22% (see table 10). Two issuers in the Asian financial sector have defaulted in 2022. Among financial industries, the 2022 aggregate one-year default rate is 0.52%, also slightly higher than the 1993-2022 long-term average of 0.22%.

More specifically, out of 18 defaulted Asian issuers in 2022, six were from the real estate, five were from the forest & building products/homebuilders sector, three were from the consumer/service sectors and two from the financial institutions sectors, with one each from the utilities and the energy and natural resources sectors.

The default rates for 2022 exceeded their long-term weighted averages (weighted by number of issuers) in all of the above sectors (see table 11), though these sector statistics are based on a limited history with a small number of defaults.

Table 10

Table 11

Transition Tables And Cumulative Default Rates

An analysis of rating transitions in 2022 suggests that ratings behavior in Asia remains consistent with global trends, which have shown a negative correspondence between credit rating and default probability. Investment-grade issuers in Asia tend to have more credit stability (as measured by the frequency of rating transitions) than their speculative-grade counterparts (see table 12).

For instance, 95.7% of Asian issuers rated 'A' as of Jan. 1, 2022, were still rated 'A' as of Dec. 31, 2022, whereas the comparable share for issuers rated 'BB' was 79.1%. Of the Asian issuers rated 'AAA', 50% retained this rating after one year, after the aforementioned downgrade of Singapore Technologies Engineering Ltd. whereas 54.9% of issuers rated 'B' retained that rating (see table 12). This pattern is similar to the long-term (1981-2022) ratings trend among global issuers. This study--in line with previous default studies--confirms that higher-rated companies are generally more stable than lower-rated companies.

The number of 'AAA' rated issuers globally declined to just seven by the end of 2022 from 89 at the beginning of 2008. Quite different from usual norms, in 2022 only 50% of Asian issuers rated 'AAA' retained this rating after a year. This is due to the aforementioned Singapore Technologies Engineering Ltd., which was downgraded to 'AA+' on elevated leverage post-acquisition of Transcore in March 2022.

In 2022, 58.3% of Asian issuers within the 'CCC'/'C' rating category transitioned to 'D' in 2022, compared with 13.8% for global issuers (see table 12). Although when interpreting the lower stability rates associated with the 'CCC'/'C' rating category, it's important to take into account the small sample size in Asia, especially for the speculative-grade space.

Issuer-specific factors may influence the default trends more than they do on a global scale. Also, the 1997-1998 Asian financial crisis did result in long-term average rating transitions for several rating categories exceeding the global averages (see table 13).

Table 12

Table 13

Notwithstanding the slightly higher ratings volatility, this study confirms that our ratings on Asian issuers are generally consistent with global patterns. Based on the transition analysis for a time horizon of two years rather than one year, lower ratings also tend to display less stability than higher ratings do (see table 14).

Transitions at the rating modifier level also display the same relationship by and large, though differences in sample size occasionally create slight variations between adjacent rating categories (see table 15).

Table 14

Table 15

The result that higher ratings correspond with lower frequency of default--and vice versa--remains true over time, as illustrated by the cumulative average default rates in tables 16 and 17 and in chart 6. On average, from 1993-2022, 'BBB' rated issuers in Asia had a less than a 0.11% default rate in the first year after they were rated and an only marginally higher default rate in the second year and beyond. Issuers rated 'B' had an average default rate of 3.3% in the first year and 6.8% in the second year (see table 16).

Our findings are qualified by the small number of issuers in the pool and the short period of the study. Although the study period for Asia is 1993-2022, almost 88.9% of the total issuer ratings were assigned since 2000. Therefore, a significant portion of the pool is not as seasoned as its global counterparts.

Table 16

Table 17

Gini Ratios And Lorenz Curves

A quantitative measure of ratings performance indicates that the relative rank ordering of ratings in Asia is consistent across time horizons. To measure ratings performance, or ratings accuracy, the cumulative share of issuers by rating is plotted against the cumulative share of defaulters in a Lorenz curve to render the accuracy of their rank ordering visually (see charts 7-9).

Our calculations indicate that the one-year weighted average (1993-2022) Gini coefficient for Asia was 90.2%, the three-year Gini was 84.8%, and the five-year was 79.4% (see table 18). By contrast, the global one-year weighted average Gini coefficient was 82.4%, the three-year was 75.4%, and the five-year was 71.6%.

If corporate ratings only randomly approximated default risk, the Gini coefficient would be zero. On the other hand, if corporate ratings were perfectly rank ordered so that all defaults occurred only among the lowest-rated issuers, the Lorenz curve would capture all of the area on the graph above the diagonal, and the Gini coefficient would be 1. For more, see Appendix II.

As we expected, the Gini coefficients decline as the time horizon lengthens because longer time horizons allow for more credit degradation among higher-rated issuers (see table 18). In the one-year Asia Lorenz curve, for example, 94.8% of defaults occurred in the speculative-grade category, while speculative-grade ratings constituted only 24.9% of all Asian corporate issuers (see chart 7).

In the three-year Lorenz curve, 93.9% of defaults occurred in the speculative-grade category, which was only 25.5% of all Asian corporate issuers (see chart 8). The five-year Lorenz curve shows that speculative-grade issuers constituted 90.3% of defaulters and 25.6% of the entire sample (see chart 9).

Table 18

Appendix I: Data Approach And Definitions

This long-term corporate default and rating transition study uses S&P Global Market Intelligence's CreditPro® database of long-term local currency issuer credit ratings. Most exhibits in this study are the direct output of the CreditPro® interface, while others reflect manipulation of the underlying database.

An issuer credit rating reflects S&P Global Ratings' forward-looking opinion of a company's overall creditworthiness. This opinion focuses on the obligor's capacity and willingness to meet its financial commitments as they come due. It does not apply to any specific financial obligation because it does not take into account the nature and provisions of the obligation, its standing in bankruptcy or liquidation, statutory preferences, or the legality and enforceability of the obligation. It is not necessary for a company to have rated debt to have an issuer credit rating.

While an issue credit rating is an assessment of default risk, it may also incorporate an assessment of the relative seniority or ultimate recovery of the issue in the event of default. The junior obligations of a company are typically rated lower than the senior obligations to reflect their lower priority in bankruptcy and ultimate recovery expectations.

Alternatively, secured debt may be rated higher than the issuer credit rating. Notching also applies to the structural subordination of debt issued by operating subsidiaries or holding companies that are part of an enterprise that we view as a single economic entity.

S&P Global Ratings Research's ongoing enhancement of the CreditPro database used to generate this study could lead to outcomes that differ to some degree from those reported in previous studies. However, this poses no continuity problem because each study reports statistics going back to Jan. 1, 1993. Therefore, each annual default study is self-contained and effectively supersedes all previous versions.

Issuers included in this study

For purposes of this study, Asia consists of Bangladesh, Bhutan, British Indian Ocean Territories, Brunei Darussalam, Cambodia, China, Fiji, Hong Kong Special Administrative Region of China, India, Indonesia, Japan, Republic of Korea, Macao Special Administrative Region of China, Malaysia, Marshall Islands, Mongolia, Pakistan, Papua New Guinea, Philippines, Singapore, Sri Lanka, Taiwan, Thailand, and Vietnam.

This study analyzes the rating histories of 2,064 Asian companies that S&P Global Ratings rated from Jan. 1, 1993 to Dec. 31, 2022. These include industrials, utilities, financial institutions, and insurance companies with long-term local currency ratings. The analysis excludes public information ("pi") ratings and ratings based on the guarantee of another company.

Structured finance vehicles, public-sector issuers, and sovereign issuers are the subjects of separate default and transition studies, and we excluded these from this study.

To avoid double-counting, the CreditPro database excludes subsidiaries with debt that is fully guaranteed by a parent or with default risk that is considered identical to that of a parent. The latter are companies with obligations that are not legally guaranteed by a parent but that have operating or financing activities that are so inextricably entwined with those of the parent that it would be impossible to imagine the default of one and not the other.

At times, however, some of these subsidiaries might not yet have been covered by a parent's guarantee, or the relationship that combines the default risk of parent and subsidiary might have come to an end or might not have begun. We included such subsidiaries for the period during which they had a distinct and separate risk of default.

Issuers with withdrawn ratings

S&P Global Ratings withdraws ratings when an entity's entire debt is paid off or when the program or programs rated are terminated and the relevant debt extinguished. For the purposes of this study, a rating may be withdrawn as a result of a merger or acquisition. Others are withdrawn because of a lack of cooperation, particularly when a company is experiencing financial difficulties and refuses to provide all the information needed to continue surveillance on the ratings, or at the entity's request.

Definition of default

An obligor rated 'SD' (selective default) or 'D' (default) is in payment default on one or more of its financial obligations (rated or unrated) unless S&P Global Ratings believes that such payments will be made within five business days, irrespective of any grace period. S&P Global Ratings also lowers a rating to 'D' when an issuer files for bankruptcy or takes a similar action that jeopardizes its payments on a financial obligation.

A 'D' rating is assigned when S&P Global Ratings believes the default will be a general default and that the obligor will fail to pay all or substantially all of its obligations as they come due. S&P Global assigns an 'SD' rating when it believes that the obligor has selectively defaulted on a specific issue or class of obligations but will continue to meet its payment obligations on other issues or classes of obligations in a timely manner.

A selective default includes the completion of a distressed exchange offer whereby one or more financial obligations are either repurchased for an amount of cash or replaced by other instruments having a total value that is less than par.

'R' (regulatory intervention) indicates that an obligor is under regulatory supervision owing to its financial condition. This does not necessarily indicate a default event, but the regulator might have the power to favor one class of obligations over another or pay some obligations and not others. Preferred stock is not considered a financial obligation, and thus a missed preferred stock dividend is not normally equated with default.

We deem 'D', 'SD', and 'R' issuer ratings to be defaults for the purposes of this study. A default is assumed to take place on the earliest of: the date S&P Global Ratings revised the rating(s) to 'D', 'SD', or 'R'; the date a debt payment was missed; the date a distressed exchange offer was announced; or the date the debtor filed for or was forced into bankruptcy.

When an issuer defaults, it is not uncommon for S&P Global Ratings to subsequently withdraw the 'D' rating. For the purposes of this study, if an issuer defaults, we end its rating history at 'D'. If any defaulting entity reemerges from bankruptcy--or otherwise restructures its defaulted debt instruments, thereby reestablishing regular, timely payment of all its debts--we reenter this issuer into the database as a new entity. Its rating history after the default event is included in all calculations, separate from its experience leading up to its earlier default.

Many practitioners use statistics from this default study to estimate "probability of default" and "probability of rating transition." S&P Global Ratings' credit ratings do not imply a specific probability of default.

Regional definitions

Within this study, tables and charts are often presented using specific geographic regions. Some countries or markets can be included in multiple regions, and S&P Global Ratings does not have corporate ratings within every country or market. The regions covered in this study are:

Emerging and frontier markets:

Bangladesh, Bhutan, British Indian Ocean Territories, China, Fiji, Hong Kong Special Administrative Region of China, India, Indonesia, Macao Special Administrative Region of China, Malaysia, Mongolia, Pakistan, Papua New Guinea, Philippines, Sri Lanka, Taiwan, Thailand, Vietnam, Angola, Armenia, Azerbaijan, Bahrain, Belarus, Bosnia and Herzegovina, Bulgaria, Cote d'Ivoire, Croatia, Cyprus, Egypt, Estonia, Gabon, Georgia, Ghana, Hungary, Jordan, Kazakhstan, Kenya, Kuwait, Latvia, Lebanon, Lithuania, Mauritius, Montenegro, Morocco, Namibia, Nigeria, Oman, Poland, Qatar, Republic of Moldova, Romania, Russia, Saudi Arabia, Slovakia, South Africa, Tunisia, Turkey, Ukraine, United Arab Emirates, Uzbekistan, Argentina, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Grenada, Guatemala, Honduras, Jamaica, Mexico, Panama, Paraguay, Peru, Trinidad and Tobago, Uruguay, Cambodia, Marshall Islands, Liberia, Syrian Arab Republic, Togo, Aruba, Bahamas, Curacao, Netherlands Antilles, Turks and Caicos Islands, and Venezuela.

Calculations

Static pools.  S&P Global Ratings Research conducts its default studies on the basis of groupings called static pools. For the purposes of this study, we form static pools by grouping issuers by rating category at the beginning of each year covered by the study. Each static pool is followed from that point forward. All companies included in the study are assigned to one or more static pools. When an issuer defaults, we assign that default back to all of the static pools to which the issuer belonged.

We use static pools to avoid certain pitfalls in estimating default rates. This is to ensure that default rates account for rating migration and to allow for default rates to be calculated across multiperiod time horizons. Some methods for calculating default and rating transition rates might charge defaults against only the initial rating on the issuer, ignoring more recent rating changes that supply more current information. Other methods calculate default rates using only the most recent year's default and rating data, which might yield comparatively low default rates during periods of high rating activity because they ignore prior years' default activity.

Membership in static pools remains constant. Each static pool can be interpreted as a buy-and-hold portfolio. Because errors, if any, are corrected by every new update and because the criteria for inclusion or exclusion of companies in the default study are subject to minor revisions as time goes by, it is not possible to compare static pools across different studies. Therefore, every new update revises results back to the starting date so as to avoid continuity problems.

Issuers that have had ratings withdrawn--that is, revised to not rated ("NR")--are surveilled with the aim of capturing a potential default. Because static pools only include issuers with active ratings as of their beginning date, we exclude companies with withdrawn ratings, as well as those that have defaulted, from subsequent static pools. If the rating on an entity is withdrawn after the start date of a particular static pool and the entity subsequently defaults, we will include it in that static pool as a default and categorize it in the rating category of which it was a member at that time.

For instance, the 2001 static pool consists of all companies rated as of 12:01 a.m. on Jan. 1, 2001. Companies first rated in 2001 and surviving members of the 2001 static pool form the 2002 static pool. All rating changes that took place are reflected in the newly formed 2002 static pool through these issuer ratings as of 12:01 a.m. on Jan. 1, 2002.

Consider the following example: An issuer is originally rated 'BB' in mid-2000, and S&P Global Ratings downgrades the company to 'B' in 2002. This is followed by a rating withdrawal in 2003 and a default in 2004. We would include this hypothetical company in the 2001 and 2002 pools with the 'BB' rating, which was the rating on the issuer at the beginning of those years. Likewise, we would include it in the 2003 pool with the 'B' rating. It would not be part of the 2004 pool because it was not rated as of the first day of that year, and we would not include it in any pool after the last day of 2004 because S&P Global Ratings had withdrawn its rating on the company by then. Yet each of the three pools in which this company was included (2001-2003) would record its 2004 default at the appropriate time horizon.

Default rates.  We calculated annual default rates for each static pool, first in units and later as percentages with respect to the number of issuers in each rating category. We combined these percentages to obtain cumulative default rates for the 42 years (globally) the study covers (30 years in Asia).

Issuer-weighted default rates.  All default rates that appear in this study are based on the number of issuers rather than the dollar amounts affected by defaults or rating changes. Although dollar amounts provide information about the portion of the market that is affected by defaults or rating changes, issuer-weighted averages are more useful measures of the performance of ratings.

Average cumulative default rates.  The cumulative default rates in this study average the experience of all static pools by first calculating marginal default rates for each possible time horizon and for each static pool, weight-averaging the marginal default rates conditional on survival (survivors being nondefaulters), and accumulating the average conditional marginal default rates. We calculated conditional default rates by dividing the number of issuers in a static pool that default at a specific time horizon by the number of issuers that survived (did not default) to that point in time. Weights are based on the number of issuers in each static pool. Cumulative default rates are one minus the product of the proportion of survivors (nondefaulters).

Transition analysis.  Transition rates compare issuer ratings at the beginning of a period with ratings at the end of the period. To compute one-year rating transition rates by rating category, we compared the rating on each entity at the end of a particular year with the rating at the beginning of the same year. An issuer that remained rated for more than one year was counted as many times as the number of years it was rated.

For instance, an issuer continually rated from the middle of 1984 to the middle of 1991 would appear in the seven consecutive one-year transition matrices from 1985-1991. If the rating on the issuer was withdrawn in the middle of 1991, it would be included in the column representing transitions to "NR" in the 1991 transition matrix. Similarly, if it defaulted in the middle of 1991, it would be included in the column representing transitions to 'D' in the 1991 one-year transition matrix.

All 1981 static pool members still rated on Jan. 1, 2022, had 42 one-year transitions, while companies first rated on Jan. 1, 2022, had only one. Each one-year transition matrix displays all rating movements between letter categories from the beginning of the year through year-end. For each rating listed in the matrix's leftmost column, there are nine ratios listed in the rows, corresponding to the ratings from 'AAA' to 'D', plus an entry for "NR."

The only ratings considered in these calculations are those on issuers at the beginning of each static pool and those at the end. All rating changes that occur in between are ignored. For example, if an entity was rated 'A' on Jan. 1, 2022 and the rating was lowered to 'BBB' in the middle of the year and later raised to 'A' (with no other subsequent rating changes), this entity would be included only in the percentage of issuers that began the year as 'A' and ended the year as 'A'. This also applies to transition matrices that span longer time horizons. If an issuer defaults or the rating is withdrawn in the middle of the year, then the issuer would be considered rated 'D' or not rated on Dec. 31.

Multiyear transitions.  Multiyear transitions were also calculated for periods of two to five years. In this case, we compared the rating at the beginning of the multiyear period with the rating at the end. For example, three-year transition matrices were the result of comparing ratings at the beginning of the years 1993-2020 with the ratings at the end of the years 1995-2022. Otherwise, our approach was identical to that used for single-year transitions.

We calculated average transition matrices on the basis of the multiyear matrices just described. These average matrices are a true summary, the ratios of which represent the historical incidence of the ratings listed in the first column changing to the ones listed in the top row over the course of the multiyear period. Transition matrices that present averages over multiple time horizons are also calculated as issuer-weighted averages.

Rating modifiers.  We use rating modifiers (plus and minus signs) to calculate upgrade and downgrade percentages, as well as the magnitude of rating changes, throughout this study. However, some transition tables may use full rating categories for practical reasons. In other words, the use of a rating category suggests that transitions to, for example, 'AA-' from 'AA' or to 'BBB-' from 'BBB+' are not considered to be rating transitions because the rating remained within the rating category.

Standard deviations.  Many of the tables and charts in this study display averages of default rates, transition rates, and Gini ratios. Often these are issuer-weighted averages. Prior studies have shown that fluctuations within default rates and transitions can vary greatly depending on many circumstances specific to particular timeframes, industries, and geographic regions. As a supplement to many of the averages and time series presented in this study, standard deviations are also shown to provide a gauge of the dispersion of data behind these averages.

For the transition matrices, the standard deviation for each cell in a given matrix is a weighted standard deviation, calculated using the data from each of the underlying cohort years that contribute to the averages, weighted by that cohort year's issuer base for each rating level. For example, in the average one-year transition matrix, each cell's weighted standard deviation is calculated from the series of that particular cell in each of the 30 cohorts beginning with the 1993 cohort and ending with the 2022 cohort.

The squared difference between each cohort's transition rate and the weighted average--which is the data point in each cell--is multiplied by each cohort's weight. These weights are based on the contribution of each cohort's rating level to the 30-year total issuer base for each rating level. We then divide this by the ratio of the total number of nonzero weights minus one and the total number of nonzero weights.

The standard deviations of Gini ratios are derived from the time series for all of their constituent annual cohorts. As an example, the standard deviation applied to the seven-year weighted average global Gini ratio was calculated from the time series of all available seven-year Gini ratios by cohort. In this case, these are the seven-year Gini ratios beginning with the 1993 cohort through the 2016 seven-year cohort. We calculated standard deviations for Gini ratios in this study as the standard deviations of a sample, not those of a population.

Time sample.  This update limits the reporting of default rates to the 10-year time horizon. However, the Asia data were gathered for 30 years, and all calculations are based on the rating experience of that period. In addition, average default statistics become less reliable at longer time horizons as the sample size becomes smaller and the cyclical nature of default rates has a bigger effect on averages.

Additional Tables

Table 19

Table 20

Table 21

Table 22

Table 23

Table 24

Table 25

Table 26

Appendix II: Calculating Gini Coefficients

To measure ratings performance, or ratings accuracy, we plotted the cumulative share of issuers by rating against the cumulative share of defaulters in a Lorenz curve to visually render the accuracy of their rank ordering. The Lorenz curve was developed by Max O. Lorenz as a graphical representation of the proportionality of a distribution. To build the Lorenz curve, the observations are ordered from the low end of the ratings scale ('CCC'/ 'C') to the high end ('AAA').

If S&P Global Ratings' corporate ratings only randomly approximated default risk, the Lorenz curve would fall along the diagonal. Their Gini coefficient--which is a summary statistic of the Lorenz curve--would therefore be zero. If corporate ratings were perfectly rank ordered so that all defaults occurred only among the lowest-rated issuers, the curve would capture all the area above the diagonal on the graph, and the Gini coefficient would be 1 (see chart 10).

The procedure for calculating Gini coefficients is shown in chart 10 and is accomplished by dividing area B by the total of area A plus area B. In other words, the Gini coefficient captures the extent to which actual ratings accuracy diverges from the random scenario and aspires to the ideal scenario.

Digital designer: Halie Mustow

Editor: Lex Hall

Related Research

• S&P Global Ratings Definitions, June 9, 2023
• 2022 Annual Global Corporate Default And Rating Transition Study, April 26, 2023
• Asia-Pacific Sovereign Rating Trends 2023: A Break In The Weather, Jan. 27, 2023
• 2021 Annual Asia Corporate Default And Rating Transition Study, Dec. 13, 2022