Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions March 28, 2019 (Editor's Note: In this study, we include the ratings history of all securities whose original rating was 'AAA'. This represents a change in methodology compared with editions of our global structured finance default and rating transitions study published prior to 2018. For further details, see "Treatment of 'AAA' ratings" in Appendix I and example summary statistics in Appendix III.) For the first time since the financial crisis, in 2018 the global default rate for structured finance fell below 2%, while the upgrade rate rose to a record high, according to S&P Global Ratings' annual analysis of defaults and rating transitions. The downgrade rate rose slightly but remained well below the long-term historical average. Overall credit quality increased for the third successive year to an all-time high. S&P Global Ratings had close to 33,900 ratings outstanding on global structured finance securities at the beginning of 2018. Of these securities, 1.9% defaulted during the year—an 11-year low. The upgrade rate rose to 13.1%—the highest on record and up from in 9.1% in 2017. The downgrade rate rose to 8.2% in 2018, up from 5.0% in 2017. Combining upgrades and downgrades with their severity, we raised our ratings on global structured finance securities by an average of 0.25 notches on aggregate, compared with a 0.10-notch increase in average credit quality during 2017. By far the most downgrades continued to be in the U.S. residential mortgage-backed securities (RMBS) sector, but the U.S. single-name synthetics and European commercial mortgage-backed securities (CMBS) sectors saw higher downgrade rates, which express the number of downgrades as a proportion of the number of ratings outstanding. By contrast, a variety of sectors exhibited strong credit performance, with the highest upgrade rate of 24.3% in the European RMBS sector, partly due to corresponding upgrades for related sovereigns. Overall, there were double-digit upgrade rates in each of the RMBS and asset-backed securities (ABS) sectors globally. Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions March 28, 2019 GLOBAL FIXED INCOME RESEARCH Andrew H South London (44) 20-7176-3712 andrew.south @spglobal.com Kirsten R Mccabe New York + 1 (212) 438 3196 kirsten.mccabe @spglobal.com RESEARCH CONTRIBUTOR Sundaram Iyer Mumbai sundaram.iyer @spglobal.com www.spglobal.com/ratingsdirect March 28, 2019 1
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Default, Transition, and Recovery:
2018 Annual Global Structured Finance DefaultStudy And Rating TransitionsMarch 28, 2019
(Editor's Note: In this study, we include the ratings history of all securities whose original rating was 'AAA'. This represents achange in methodology compared with editions of our global structured finance default and rating transitions study publishedprior to 2018. For further details, see "Treatment of 'AAA' ratings" in Appendix I and example summary statistics in Appendix III.)
For the first time since the financial crisis, in 2018 the global default rate for structured financefell below 2%, while the upgrade rate rose to a record high, according to S&P Global Ratings'annual analysis of defaults and rating transitions. The downgrade rate rose slightly but remainedwell below the long-term historical average. Overall credit quality increased for the thirdsuccessive year to an all-time high.
S&P Global Ratings had close to 33,900 ratings outstanding on global structured financesecurities at the beginning of 2018. Of these securities, 1.9% defaulted during the year—an11-year low. The upgrade rate rose to 13.1%—the highest on record and up from in 9.1% in 2017.The downgrade rate rose to 8.2% in 2018, up from 5.0% in 2017. Combining upgrades anddowngrades with their severity, we raised our ratings on global structured finance securities by anaverage of 0.25 notches on aggregate, compared with a 0.10-notch increase in average creditquality during 2017.
By far the most downgrades continued to be in the U.S. residential mortgage-backed securities(RMBS) sector, but the U.S. single-name synthetics and European commercial mortgage-backedsecurities (CMBS) sectors saw higher downgrade rates, which express the number of downgradesas a proportion of the number of ratings outstanding. By contrast, a variety of sectors exhibitedstrong credit performance, with the highest upgrade rate of 24.3% in the European RMBS sector,partly due to corresponding upgrades for related sovereigns. Overall, there were double-digitupgrade rates in each of the RMBS and asset-backed securities (ABS) sectors globally.
Default, Transition, and Recovery:
2018 Annual Global Structured Finance DefaultStudy And Rating TransitionsMarch 28, 2019
Defaults: Annual default rate declines to an 11-year low
- We lowered 634 global structured finance ratings to 'D' in 2018, for an overall defaultrate of 1.9%—down from 2.1% in 2017.
- This put the 2018 default rate well below the one-year average default rate of 3.9%.
Rating transitions: Average change in credit quality reached an all-time high in 2018
- Of the 33,896 global structured finance ratings outstanding at the start of 2018, we leftunchanged or raised 91.8% and lowered 8.2%. This compares with 95.0% and 5.0%,respectively, in 2017.
- We raised 13.1% of ratings in 2018, up from 9.1% in 2017.
- The 2018 downgrade rate of 8.2% was much lower than the long-term one-year averagedowngrade rate of 16.4%.
- The average change in credit quality was +0.25 notches in 2018—a record high, whichalso marked the third consecutive year this measure ended the period in positiveterritory.
Sector and region breakdown: Most downgrades in U.S. RMBS; upgrades spread acrossmany sectors
- In the U.S., the RMBS sector accounted for by far the majority of downgrades anddefaults, with a downgrade rate of 13.2% and a default rate of 2.9%.
- In Europe, CMBS was the weakest sector, with a downgrade rate of 14.0% and a defaultrate of 8.4%.
- By contrast, ABS ratings saw a high upgrade rate of 12.6% globally and only six defaults.
Credit Performance—Lowest Default Rate In 11 Years
The overall credit performance of global structured finance securities that we rate was positive in2018. During the year, we raised 13.1% of our ratings on global structured finance securities thatwere outstanding at the beginning of the year (see chart 1). This was a sharp increase from 9.1% in2017, and strongly exceeded the downgrade rate (8.0%) for only the third time since 2006.
The 12-month trailing average change in credit quality (see definition in Appendix I) for globalstructured finance was +0.25 rating notches at the end of 2018—a record high. This measure hadbeen negative for several years since mid-2007, indicating that, on average, ratings were driftinglower, but turned positive in early 2016. In August 2018, this measure moved above +0.2 notchesfor the first time (see chart 1).
The default rate of 1.9% in 2018 was lower than in the previous year and well below the one-yearaverage default rate of 3.9%. Viewing the default rate on a 12-month trailing basis reveals a broaddowntrend in the default rate since mid-2016 (see chart 2). The default rate for investment-grade
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
ratings fell significantly to 0.01% in 2018, down from 0.15% in 2017, representing just twodefaults among 20,469 investment-grade ratings outstanding at the beginning of the year. Thespeculative-grade default rate was 4.7%. The annual default rates for both investment- andspeculative-grade structured finance securities have stabilized since their peaks in 2009 and arenow similar to pre-crisis levels.
Chart 1
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 2
Region and sector comparisons
Structured finance credit performance in 2018 diverged significantly between sectors and regions.Globally, the ABS sector had the lowest default and downgrade rates of 0.1% and 1.5%,respectively. The upgrade rate for ABS was 12.6% in 2018, and ratings in the sector rose by anaverage of 0.34 notches. The RMBS sector recorded the highest upgrade rate of 16.1% and sawratings rising by an average of 0.30 notches over the year. However, the RMBS sector alsorecorded the highest downgrade rate of the year at 11.6%.
The region-sector combination with the highest upgrade rate was European RMBS, where weraised nearly one-quarter of the ratings that were outstanding at the beginning of the year, partlydue to country risk considerations and corresponding upgrades for related sovereigns. The U.S.RMBS sector recorded the second-highest upgrade rate of 16.1%. However, unlike in 2017,several areas reported upgrade rates lower than their one-year weighted averages, including U.S.and European structured credit (see chart 3). Nearly all areas had downgrade rates well belowtheir one-year weighted averages.
In 2018, the U.S. single-name synthetics sector had the highest downgrade rate of 20.5%, wellabove its one-year average of 13.6%. The sector's upgrade rate, however, was well below itsone-year average of 6.1%, at 3.8% in 2018. The European CMBS sector had the second-highestdowngrade rate of 14.0%, compared with a one-year average of 22.3%. The nature of theperformance deterioration differed between the two sectors, with European CMBS also recordingthe highest default rate of 8.4%, while there was only one default among U.S. single-name
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
synthetics, for a default rate of 0.5%. The European CMBS sector was the only one to report a2018 default rate higher than its one-year weighted-average (see chart 4).
Outside the U.S. and Europe, the number of upgrades generally far exceeded the number ofdowngrades in 2018, with the exception of Latin America, which experienced the highestdowngrade rate of any region at 22.4%. Many Latin American downgrades stemmed from ourlowering of the Brazilian sovereign rating in early 2018. However, outside the U.S. and Europethere were no defaults in 2018 among nearly 1,600 ratings outstanding at the beginning of theyear.
Chart 3
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 4
Vintages
Credit performance continues to be differentiated by the year of issuance—or vintage—ofstructured finance securities. The fundamental credit characteristics and economic environmentof a transaction's vintage can influence its subsequent credit behavior.
Segmenting global structured finance credit performance by transaction vintage reveals that theupgrade rate in 2018 was highest for the 2005 vintage (see chart 5). In 2018, downgrade rates werehighest in the 2006 and 2007 vintages, with most in U.S. RMBS. The downgrade rate for the2006-2007 vintages has normalized somewhat over recent years, relative to the weak creditperformance these transactions exhibited during the financial crisis, putting recent downgraderates well below their one-year weighted averages. However, these vintages continue toexperience downgrade rates higher than those of other vintages. The 2006-2007 vintages alsoexhibit the highest one-year average default rates, given their performance during the financialcrisis, but default rates for these vintages in 2018 were much lower and on a par with those ofother vintages (see chart 6).
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 5
Chart 6
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Table 1 shows a summary of 2018 credit performance for global structured finance segmented invarious ways and compared with the 1976-2018 one-year weighted-average statistics.
Table 1
Global Structured Finance Transition And Default Summary
*Including defaults. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&P Global FixedIncome Research.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Ratings Performance—Ratings Have Historically Differentiated DefaultRates
Our structured finance ratings express an opinion of securities' creditworthiness, for which thecenterpiece is an assessment of default likelihood, rather than the likelihood of upgrade ordowngrade. That said, our ratings do also consider credit stability as a secondary factor.
Across global structured finance, upgrade and downgrade rates in 2018 were generallydifferentiated by securities' ratings at the beginning of the year. Downgrade rates were generallyhigher for lower rating categories, with a downgrade rate of 1.5% for securities rated 'AAA' at thebeginning of the year compared with 22.1% for those rated 'CCC' (see chart 7). Securities rated inthe 'BBB' category at the beginning of the year recorded the highest upgrade rate of 26.6%.
Based on a longer time horizon, the observed weighted-average one-year downgrade rates forglobal structured finance are generally aligned with rating categories, except at the 'CCC' ratingcategory (see chart 7). Upgrade rates have historically been more consistent across most ratingcategories.
Chart 7
In contrast to credit stability, default likelihood is the primary factor in our assessment ofcreditworthiness that the ratings reflect. As such, we would typically expect default rates to be
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
lower for higher-rated securities, provided that observations are made over sufficiently long timehorizons and large samples. Over shorter timeframes or smaller samples, this relationship maynot always hold, and default rates can also vary over time.
For global structured finance, higher-rated securities have clearly been associated with lowerweighted-average one-year default rates between 1976 and 2018 (see chart 8). Default rates in2018 were higher at lower ratings, as expected. For example, there were no defaults in each of the'AAA', 'AA', and 'A' rating categories in 2018. Further, securities we rated in the 'BBB' category atthe beginning of the year had a default rate of 0.1%, contrasting with a 6.2% default rate for thosein the 'CCC' rating category.
Chart 8
To further explore how well our structured finance ratings have rank-ordered creditworthinessover time, we can calculate cumulative default rates by rating category for various time horizonsas we do for our corporate default and transition studies. This approach constructs averagemultiyear cumulative default rates by first aggregating across static pools the period-to-periodone-year marginal default rates that are conditional on the securities' survival (that, is nondefault)in the prior one-year period (see Appendix I for more details). We note that this approach differsfrom the calculations we use in constructing the weighted-average multiyear default andtransition rates elsewhere in this study, where default rates are not conditional on survival.
The cumulative default rates (conditional on survival) based on our full data history—from thebeginning of 1976 to the end of 2018—show that lower ratings have generally been associatedwith higher default rates and vice versa (see table 2). In other words, ratings appear to havesuccessfully ranked-ordered creditworthiness over each time horizon.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Table 2
Global Structured Finance Cumulative Default Rates, Conditional On Survival,1976-2018 (%)
IG--Investment-grade. SG--Speculative-grade. Source: S&P Global Fixed Income Research.
Default rates calculated on a rolling basis for a given horizon (for example, five years) furtherdemonstrate that this ratings-based rank ordering has generally remained in place over time,even as absolute default rates have fluctuated with differing levels of credit stress. For example,the five-year trailing 'AAA' default rate for global structured finance was only 0.03% at the end of2018, down from 0.37% at the end of 2017 and a peak of 17.4% in 2012. By contrast, the five-yeartrailing 'BBB' default rate was 1.3%, down from 1.7% at the end of 2017 and a peak of 48.8% in2012 (see chart 9).
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 9
We also calculate Gini coefficients to quantify the rank-ordering power of our ratings in relation tosecurities' observed default propensity. The Gini coefficient is a summary metric that can rangebetween zero and 100%—the closer to 100%, the higher the rank ordering power of the ratingsunder observation (see Appendix I for more details).
In 2018, the one-year Gini coefficient for defaults of rated global structured finance securities was79.2%—up from 74.6% the previous year. Looking at longer timeframes, the three-year Ginicoefficient was more stable compared with the end of 2017 at 79.4%, while and five-year Ginicoefficient declined to 81.1% (see chart 10). This follows the pronounced dip in Gini coefficientvalues several years ago, related to the 2008-2009 financial crisis. During this period, a relativelylarge number of defaults in certain sectors—such as U.S. RMBS and U.S. structuredcredit—coincided with fewer defaults in lower-rated securities from other sectors, lowering theGini coefficients.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 10
Finally, we also calculated sector-specific historical one-year Gini coefficients. For most sectors,the Gini coefficients have returned to the 80%-100% range since the end of 2011, following a dropin 2007 (see chart 11). The Gini coefficient for global RMBS remains lower, at close to 70%, despitereversing course and rising from 65.4% at the end of 2017. Although more than 95% of the globalRMBS defaults in 2018 were from the 'CCC' and 'CC' rating categories, there were still somedefaults from higher rating levels, lowering the Gini coefficient for this sector.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 11
The Gini coefficient metric is useful, but has some significant shortcomings. For example, a valueof 100% would only be attained if all defaults occurred only on securities rated below some criticalrating threshold, with no defaults among securities rated higher than this threshold. However, in adiverse sample of rated securities—such as the universe of global structured financesecurities—sector- and region-specific credit stresses of differing severity and likelihood maycause higher-rated securities in more stressed areas to default, while at the same timelower-rated securities in less stressed areas do not default. This effect would lower the reportedGini coefficient, despite being a feature of the sample composition rather than reflecting a declinein ratings' accuracy.
Regions And Sectors In Detail
U.S. RMBS
In 2018, the upgrade rate in U.S. RMBS rose sharply to a record high of 16.1%, up from 5.7% in2017. However, the downgrade rate also rose, to 13.2% (see chart 12). Incorporating both themagnitude and frequency of rating actions, the overall average change in credit quality for U.S.RMBS ended the year in positive territory for only the second time since 2007, at +0.30 notches.On a 12-month trailing basis, the U.S. RMBS default rate continued its long-term downward trendto finish the year at 2.9%—the lowest year-end level since 2007 (see chart 13).
The Alt-A subsector saw the highest default rate and second-highest downgrade rate of the year,at 5.7% and 16.7% respectively, although these measures remained below their respectiveone-year weighted averages. These transactions now constitute about 17% of U.S. RMBS that werate, by number of ratings (see table 3). Ratings migration for U.S. prime RMBS was more positive
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
in 2018, as the upgrade rate rose to 12.9%, the downgrade rate fell to 8.5%, and the default ratefell to 3.2%. The highest upgrade rate of 25.2% was in the "outsides guidelines" subsector.
Credit performance was mixed across transaction vintages in U.S. RMBS. For example, in the 2000to 2007 pre-crisis vintages, downgrade rates ranged from 4.4% for the 2001 vintage to 34.5% forthe 2007 vintage, reflecting ongoing weaker credit performance for transactions that were issuedcloser to the downturn (see table 3). The downgrade rates of 12.1% and 33.3%, respectively, for2016 and 2017 vintages in the U.S. RMBS sector were atypical for such unseasoned transactions.However, most of these actions were due to a revision of our criteria for rating post-2008 U.S.RMBS, partly explaining the widespread nature of the rating changes.
The vast majority (97%) of U.S. RMBS defaults in 2018 were from the 'CCC' and 'CC' ratingcategories, which constituted more than 40% of our U.S. RMBS ratings universe at the beginningof 2018.
Chart 12
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
*Including defaults. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&P Global FixedIncome Research.
U.S. structured credit
From 2011 to 2016, the U.S. structured credit sector saw consistently high upgrade rates of more
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
than 10% a year, but the upgrade rate declined into single digits in 2017 (7.8%) and slippedfurther to 2.8% in 2018 (see chart 14). This decline in the upgrade rate has been largely due tomanagers of collateralized loan obligations (CLOs) increasingly opting to call and refinancetransactions a few years after issuance, rather than allowing them to run into their amortizationperiods, when upgrades would be more likely to occur. Meanwhile, the U.S. structured creditdowngrade rate has generally been in a downward trend since 2009, and remained close to recentlows at 1.1% in 2018.
Despite fewer upgrades, the average change in credit quality remained in positive territory, ending2018 at +0.05 notches, although this was less than one-third of the value at the end of 2017. U.S.structured credit ratings have consistently been trending higher on this 12-month trailing basissince late 2012.
In line with the low downgrade rate for U.S. structured credit, the 2018 default rate was only 0.5%,on a par with 2017's rate (see chart 15). We note that the U.S. structured credit default rate spikedconsiderably higher in 2011 when we moved to 'D' a large number of ratings on collateralized debtobligation (CDO) tranches backed by other structured finance securities, notably U.S. subprimeRMBS. At that time, these securities had, in our view, little realistic prospects of repayment, andmany were unlikely to receive any future principal payments due to the ongoing collateraldeterioration of the RMBS and other securities backing the transactions.
The overall U.S. structured credit sector remains polarized between CLOs—which have historicallyperformed very well—and some other types of structured credit transactions that performedpoorly after 2007, but now constitute only a small portion of our outstanding ratings. For example,in 2018, CLOs constituted more than 85% of the U.S. structured credit sector and had adowngrade rate of only 0.7% and no defaults, compared with 14 defaults across the now muchsmaller structured finance CDO subsector (see table 4). In fact, the one-year average default ratefor CLOs remains only 0.1%, compared with 13.0% for structured finance CDOs. As CLOs haveevolved to become the largest subsector within U.S. structured credit, so the aggregateperformance statistics for the sector as a whole have also improved significantly.
Considering only vintages with more than 30 ratings outstanding at the beginning of 2018, thehighest upgrade rate was in the 2012 vintage, where CLO transactions in particular are nowamortizing, increasing the relative credit enhancement for the rated securities and thereforeraising their creditworthiness, all else being equal.
Finally, all 14 of the defaults in U.S. structured credit were on securities that we rated in the 'CCC'or 'CC' categories at the beginning of the year.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 14
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 15
Table 4
U.S. Structured Credit Transition And Default Summary
*Including defaults. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. SF--Structured finance.Source: S&P Global Fixed Income Research.
U.S. ABS
Credit performance for the U.S. ABS sector was positive in 2018, with the upgrade rate rising to anall-time high of 12.8%, up from 12.3% a year earlier (see chart 16). The downgrade and defaultrates remained relatively unchanged at only 1.3% and 0.1%, respectively. As a result, the annualaverage change in credit quality for 2018 reached a new high of +0.36 notches.
The U.S. ABS default rate has historically remained very low, especially relative to some othersectors such as U.S. RMBS and U.S. structured credit. The 12-month trailing default rate peakedat only 1.6% in mid-2003, and has remained less than 0.5% since early 2008, even despite thefinancial crisis that severely affected other sectors (see chart 17, noting the separate y-axisscales).
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
In terms of downgrades and defaults, the U.S. ABS subsector with the weakest credit performancein 2018 was once again the manufactured housing segment, where we lowered 9.2% of our ratingsduring the year and the default rate was 2.1% (see table 5).
A relatively large number of downgrades were in the 2001 and earlier vintages, where downgraderates exceeded their one-year weighted averages. However, the largest downgrade rate of 32.8%came from the 2008 vintage, due to rating actions on a number of related student loantransactions. Of the six defaults on U.S. ABS in 2018, five were on securities that were rated in the'CC' category at the beginning of the year, while the remaining default was from the 'B' category.
Chart 16
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
*Including defaults. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&P Global FixedIncome Research.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
U.S. CMBS
U.S. CMBS credit performance in 2018 remained positive on aggregate, but with fewer upgradesthan in the previous year. The upgrade rate slipped to 5.9% from 12.2% a year earlier, although thedowngrade rate also declined, to 3.8% from 5.4%. At 1.8%, the annual default rate marked a10-year low and a level not seen since before the start of the financial crisis in 2008 when thedefault rate was 0.29% (see chart 18). The 12-month trailing average change in credit qualitydecreased during 2018 to +0.05 notches at the end of the year, compared with an average +0.36notches at the end of the previous year.
The U.S. CMBS sector saw defaults peak later than in some other sectors—such as U.S.RMBS—with the 12-month trailing default rate peaking at 15.9% in September 2011, rather thansome years earlier (see chart 19). While the U.S. CMBS default rate has fluctuated since 2014, itended 2018 at close to post-crisis lows.
In terms of downgrade and defaults, by far the weakest 2018 credit performance in U.S. CMBSwas in the conduit/fusion subsector, which saw a default rate of 4.0%, compared with 0.5% for thelarge loan/floaters subsector and 0.1% for the single borrower subsector (see table 6). In fact, theconduit/fusion subsector accounted for 44 of the 46 U.S. CMBS defaults that occurred during2018. The conduit/fusion subsector's default rate was also above its one-year weighted average of3.8%, but all U.S. CMBS subsectors saw below-average downgrade rates in 2018.
Downgrade and default rates were most elevated in the 2006-2008 vintages, which were exposedto collateral originated with relatively lower lending standards before the financial crisis andsubsequent falling real estate values, and where some loans are now reaching maturity withborrowers unable to refinance, leading to loan defaults. Most U.S. CMBS defaults in 2018occurred on securities that we rated in the 'B' and 'CCC' categories at the beginning of the year.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 18
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
*Including defaults. N/A--Not applicable. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'.Source: S&P Global Fixed Income Research.
Europe
Compared with some of the U.S. sectors, European structured finance credit performance hashistorically been more positive, although the sector did suffer from elevated default rates after2007 and an aggregate decline in ratings that was at its most severe in 2009.
In 2018, European structured finance credit performance was broadly positive, as in the previousyear. The upgrade rate was 15.6%, which marked a retreat from an all-time high of 22.3% in 2017.However, the downgrade rate also declined to an 11-year low of 2.3% from 3.8% a year earlier (seechart 20). The average change in credit quality was +0.27 notches, down from 0.35 notches at
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
year-end 2017. The default rate also indicated improving credit performance, declining to 0.7%from 1.0% a year earlier (see chart 21).
The European structured finance sector includes a diverse array of subsectors. In terms ofdefaults, CMBS was once again the worst-performing European structured finance subsector in2018, although it is also small, constituting only about 5% of our European structured financeratings outstanding at the beginning of 2018. Of the 26 defaults in European structured finance in2018, 15 (58%) were in CMBS, giving that sector a default rate of 8.4% for the year, well above itsone-year average of 3.0% (see table 7).
All subsectors of European RMBS saw unusually high upgrade rates, ranging from 16.6% for thenonconforming subsector to 31.1% for prime transactions. These widespread upgrades werepartly due to country risk considerations that affected several transactions at the same time: inearly 2018, we upgraded several Spanish RMBS tranches after we raised our long-term sovereignrating on Spain to 'A-' from 'BBB+', given economic growth and budgetary consolidation.
European consumer ABS saw an unusually high upgrade rate of 37.3% in 2018, making it thebest-performing sector in the region, with no downgrade or default activity, although thissubsector only accounted for 59 ratings at the beginning of 2018.
Subsectors that saw the most stress during the financial crisis of 2008-2009—such as structuredfinance CDOs—have now largely seen negative credit performance play out. While the structuredfinance CDO subsector has the highest one-year weighted-average downgrade rate (23.8%)among the European subsectors in table 7, the 2018 downgrade rate was well below this average,at 5.2%.
CLOs are now one of the largest European subsectors by ratings outstanding and generallyperformed well in 2018, with a downgrade rate of 0.9% and an upgrade rate of 2.2%. As in the U.S.,however, the European CLO upgrade rate has trended significantly lower than in the past fewyears, as many transactions undergo refinancing rather than entering their amortization periods,when upgrades would otherwise be most likely to occur. The CLO sector also saw four defaults in2018, giving a default rate of 0.5%.
European structured finance downgrades in 2018 were concentrated in the 2005-2007 vintages,with generally higher downgrade rates at the lowest rating categories (that is, 'CCC' and 'CC'). Theinvestment-grade downgrade rate was 1.4%, compared with a speculative-grade downgrade rateof 4.9%.
All of the defaults were from deeply speculative-grade rating levels. More than half of theEuropean structured finance defaults in 2018 were in CMBS transactions structured shortlypre-crisis, which were most affected by the lower lending standards applied at the height of thecredit boom and subsequent declines in real estate values, and which have now reached maturityin an environment of more subdued lending volumes and real estate values.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 20
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 21
Table 7
European Structured Finance Transition And Default Summary
*Including defaults. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. SF--Structured finance.Source: S&P Global Fixed Income Research.
Other regions
Outside the U.S. and Europe, most of the structured finance ratings included in this study and stilloutstanding at the beginning of 2018 were on Japanese and Australian RMBS. However, we alsohave ratings outstanding on securities from a wide range of sectors in Canada, Latin America, andother emerging markets and parts of Asia.
This mixed collection of securities exhibited broadly positive credit performance on aggregate in2018, with the upgrade rate of 6.1% exceeding the downgrade rate of 2.6%, and no defaults (seechart 22). In general, the structured finance default rate outside Europe and the U.S. hashistorically been highest in Japan, but has since settled to a level well below the global average(see chart 23).
The two largest sectors outside the U.S. and Europe—Japanese and AustralianRMBS—performed well in 2018, with no defaults. There were no downgrades for Japanese RMBSand only a modest downgrade rate of 3.2% for Australian RMBS (see table 8). Latin Americansecurities exhibited the highest downgrade rate, at 22.4%, due to our downgrade of the Braziliansovereign in January 2018. That said, we only had 49 global scale ratings outstanding on LatinAmerican structured finance securities at the beginning of 2018.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 22
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 23
Table 8
Other Region Structured Finance Transition And Default Summary
*Including defaults. N/A--Not applicable. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'.Source: S&P Global Fixed Income Research.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Appendix I: Terminology, Data Selection, And Calculation Approaches
This Appendix discusses the data and calculations, and explains the terminology we use in thisreport.
This global structured finance default and ratings transition study uses our database oflong-term, global-scale issue credit ratings. We do not include national and regional scale ratings,such as those we may assign in Argentina, Brazil, Mexico, and Taiwan, for example, which are notcomparable among countries. The analysis also excludes public information ("pi") ratings, issuercredit ratings, and short-term issue ratings, such as those on asset-backed commercial paper(ABCP) conduits.
Our ongoing enhancement of the database used to generate this study occasionally leads tochanges in the reported statistics from one edition of the study to the next. However, each studyincludes statistics for previous years, ensuring that the study is self-consistent and effectivelysupersedes all previous editions.
Issues included in this study
The study analyzes the rating histories of 232,708 global structured finance instruments that S&PGlobal Ratings first rated from 1973 until Dec. 31, 2018. The term "structured finance" in thisreport refers to ABS, CMBS, RMBS, structured credit, and single-name synthetic transactions. Forsome analyses, we break down these sectors further into subsectors.
Sector definitions
ABS includes underlying collateral types such as credit card receivables, student loans, and autoloans and leases. The sector also includes manufactured housing, franchise loans, 12b-1transactions, and corporate securitizations.
RMBS includes transactions backed by subprime mortgage loans, as well as home equity loantransactions and re-REMICS. Structured credit includes CLOs, both cash and synthetic CDOsbacked by exposures to corporate credit and/or other structured finance securities, as well asmarket-value CDOs and other leveraged funds. We include transactions backed by loans to smalland midsize enterprises (SMEs) in the structured credit sector.
CMBS also includes re-REMICS, as well as some CDOs primarily collateralized by commercial realestate loans (CRE CDOs). Single-name synthetic transactions are also referred to as repackagedtransactions (or "repacks"), especially in Europe. The definition of a repack in this instance is anissue backed by a single credit, where the rating on the note is directly linked to that on theunderlying credit.
In this study, we no longer include structured covered bonds, which we previously treated as aseparate sector.
Region definitions
This study presents rating transitions for global structured finance transactions. In someanalyses, we segment default and transition statistics by region. In defining a transaction's region,we use the location where we perform surveillance as the primary way to determine its region. Wemay also consider the transaction's issuer country (unless this is a tax-haven country such as the
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Cayman Islands) and/or its domicile of assets. In some cases, the domicile of assets may fail toprovide additional insights into the region, especially when a transaction is backed by assets frommore than one country.
In table 1 of the study, the "Asia (excl. Japan)" region includes transactions with collateral fromHong Kong, Singapore, Korea, and Taiwan, as well as other countries in the region. The "otheremerging markets" region includes emerging market countries that are not included in otherregions, such as Turkey and South Africa.
Vintage definition
In this report, we classify a security's vintage based on the date when we first assigned a rating.Usually this is close to the security's original issuance date. However, in some cases we may firstassign a rating to a security some time after closing.
Rating transitions
Our rating transition statistics use a "static pool" approach. To calculate the transition statisticsover a given time period (or "transition window"), we consider the static pool of ratingsoutstanding at the beginning of that time period. The transition statistics for that static pool ofratings are then based on the movements in ratings between the start and end of the transitionwindow. For instance, we calculate the 2018 transition rates by determining the ratings on eachsecurity outstanding at the start of 2018 and determining the ratings on those same securities atthe end of 2018. We then calculate statistics such as upgrade, downgrade, and stability rates,equivalent to the proportion of securities in the static pool whose ratings moved up, down, orremained that same, respectively, over the transition window. During this process, we count eachsecurity only once, even if the security experienced more than one rating change during thetransition window being observed. In other words, we use a security's rating at the start and end ofthe transition window to calculate the transition rates, disregarding any interim rating changes.
Rating modifiers
We use rating modifiers ('+' and '-') to calculate the upgrade, downgrade, and stability ratesquoted in the text, tables, and charts throughout this study. However, the transition matrices inAppendix II of this report show only the less granular full rating categories for practical reasons. Inother words, we count transitions such as 'AA' to 'AA+' as an upgrade and 'BBB+' to 'BBB-' as adowngrade in the transition statistics we cite in this report. However, in the correspondingtransition matrices, these transitions would appear in the cells corresponding to a stable ratingcategory classification, such as 'AA' to 'AA', or 'BBB' to 'BBB'.
Rating discontinuance or withdrawal
We may discontinue ratings when, for example, a rated obligation's payments have been made infull in accordance with its terms or when a rated issue matures. Ratings may also be withdrawn,for example, because of a lack of sufficient information of satisfactory quality or at the issuer'srequest. In these cases, the rating may change to 'NR' (not rated). When we withdraw ordiscontinue ratings within the transition window under consideration we may either derive ourreported statistics by classifying the rating transition as a move to 'NR' (the "NR-included"approach), or—for some other analyses—we may classify the transition as a move to the last
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
"non-NR" rating before withdrawal or discontinuance (the "NR-adjusted" approach). In the text ofthis report, when we refer to upgrade and downgrade rates, for example, we use the latterapproach. In the tables and charts, we clarify the approach used in the footnotes. We do notinclude a security with a withdrawn rating at the beginning of a transition window in the transitionand default rate calculations for that period.
Treatment of 'AAA' ratings
In this study, we include the ratings history of all securities whose original rating was 'AAA', whichwe term the "uncollapsed" approach. This represents a change in methodology compared withprevious editions of our global structured finance default and rating transitions study publishedbefore 2018. In these previous editions, for each structured finance transaction, we generally onlyincluded one of the securities that we originally rated 'AAA', terming this the "collapsed"approach. This was because historically some transactions had a disproportionate number of'AAA'-rated tranches that were likely to exhibit similar or identical credit performance. Byincluding only one such security per transaction we aimed to avoid overweighting their behavior inaggregate performance statistics. However, we now include all securities' rating histories,regardless of their original rating, for completeness and consistency with some of our otherreporting on ratings performance, for example, in regulatory submissions. The effects on someexample summary statistics of altering the treatment of 'AAA' ratings are shown in Appendix III.
Treatment of 'D' ratings
Counts of defaults and default rate statistics in this report are based on securities whose ratingswe lowered to 'D'. For the purposes of this report, when a security's rating has moved to 'D', weconsider this a terminal state and do not, for example, include such a security in any transitionwindows that start on a subsequent date. In practice, however, some securities whose ratingshave migrated to 'D' may later once again be assigned a different rating. This can occur, forexample, if the defaulted security is subsequently restructured to different terms, such as a lowercoupon. In these cases, we treat the security's post-default rating history as if it were a newsecurity, beginning from the date that the rating changed from 'D'. Where we segment statistics byvintage, however, we continue to base the vintage on the date we originally assigned a rating to thesecurity.
Average change in credit quality calculation
Certain analyses in this study refer to the "average change in credit quality" of a set of structuredfinance securities over a given transition window. We define the average change in credit qualityas the average number of rating notches by which ratings changed during the stated transitionwindow, where we take the average across all ratings in the set under consideration (for example,a particular region or sector). In this averaging, we count downgrades as a negative number ofnotches, whereas we count upgrades as a positive number. We consider stable ratings to haveundergone a transition of zero notches. We believe this measure acts as a useful summary of thecredit performance of, for example, a given sector, since it combines the relative number of ratingsundergoing transition with the severity of that transition.
Weighted-average transition and default rate calculation
For weighted-average transition rates (including default rates), we calculate the individual
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
transition rates for different static pools. We then calculate a single averaged transition rate,weighted by the number of ratings in each static pool. We use this technique, for example, todetermine the five-year weighted-average transition rates by analyzing the transition rates fordifferent static pools over different five-year periods and then aggregating them.
Average cumulative default rate calculation
In this report, we also calculate and present average cumulative default rates (CDRs) for differenttime horizons. For example, table 2 shows that the one-year average cumulative default rate for'A'-rated global structured finance has been 0.44% and the three-year average has been 6.57%.
We first consider the static pool of ratings at the beginning of each calendar year. For each staticpool, we calculate the marginal default rates for each calendar year after the static pool'sformation. These one-year marginal default rates are "conditional on survival". For example, themarginal default rate for the third year is the number of defaults during the third year, divided bythe number of ratings from the static pool that had "survived" (i.e., not moved to 'D') by thebeginning of the third year. We then average the marginal default rates for each time horizonacross static pools, weighting by the number of surviving ratings at the beginning of each timehorizon, to give an average marginal default rate per time horizon, as well as average marginalsurvival rates (equal to one minus the average marginal default rate). Finally, the averagecumulative default rate to each time horizon is calculated as one minus the product of marginalsurvival rates up to that time horizon.
We note that this approach differs from the calculations we use in constructing theweighted-average multiyear default and transition rates included elsewhere in this study (and asdescribed above), where default rates are not conditional on survival.
Gini coefficient calculation
We calculate Gini coefficients as one way to quantify our ratings' rank-ordering power ofcreditworthiness, based on observed default rates.
We first construct a Lorenz curve, which plots the cumulative proportion of all structured financeratings per rating level on the x-axis, against the cumulative proportion of defaults per rating levelon the y-axis (see chart 24). For both axes of the Lorenz curve, the observations are ordered fromthe low end of the ratings scale ('C') to the high end ('AAA').
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 24
If our structured finance ratings only randomly approximated default propensity, the Lorenz curvewould fall along the diagonal, shown as the "random curve" in chart 24. On the other hand, if alldefaults only occurred among the lowest-rated securities, with no defaults among thehigher-rated securities, the Lorenz curve would lie along the line shown as the "ideal curve" inchart 24. Typically, the observed Lorenz curve falls between the "ideal" and "random" curves, andwe use the Gini coefficient as a summary statistic to quantify its proximity to the "ideal" curve.
The procedure for calculating the Gini coefficient is illustrated in chart 24. Area B is bounded bythe random curve and the Lorenz curve, while area A is bounded by the Lorenz curve and the idealcurve. The Gini coefficient is defined as area B divided by the sum of area A and area B. The Ginicoefficient can therefore range between 0% (if the Lorenz curve follows the random curve) and100% (if the Lorenz curve follows the ideal curve). In general, therefore, the higher the Ginicoefficient, the greater the link between our ratings and the securities' observed defaultpropensity.
Appendix II: Detailed Default And Transition Statistics
Tables 9-52 provide various default and transition rate statistics for global structured financesecurities and major sectors.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Global structured finance
Table 9
Global Structured Finance Cumulative Default Rates, Conditional On Survival,1976-2018 (%)
N/A--Not applicable. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&PGlobal Fixed Income Research.
Table 12
Global Structured Finance Rating Transitions, 2018 And Multi-Year Averages, NRIncluded (%)
N/A--Not applicable. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&PGlobal Fixed Income Research.
Table 16
U.S. RMBS Rating Transitions, 2018 And Multi-Year Averages, NR Included (%)
N/A--Not applicable. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&PGlobal Fixed Income Research.
Table 20
U.S. Structured Credit Rating Transitions, 2018 And Multi-Year Averages, NRIncluded (%)
N/A--Not applicable. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&PGlobal Fixed Income Research.
Table 24
U.S. ABS Rating Transitions, 2018 And Multi-Year Averages, NR Included (%)
N/A--Not applicable. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&PGlobal Fixed Income Research.
Table 28
U.S. CMBS Rating Transitions, 2018 And Multi-Year Averages, NR Included (%)
N/A--Not applicable. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&PGlobal Fixed Income Research.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Table 32
European Structured Finance Rating Transitions, 2018 And Multi-Year Averages, NRIncluded (%)
N/A--Not applicable. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&PGlobal Fixed Income Research.
Table 36
Other Region Structured Finance Rating Transitions, 2018 And Multi-Year Averages,NR Included (%)
N/A--Not applicable. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&PGlobal Fixed Income Research.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Table 40
Global RMBS Rating Transitions, 2018 And Multi-Year Averages, NR Included (%)
N/A--Not applicable. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&PGlobal Fixed Income Research.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Table 44
Global Structured Credit Rating Transitions, 2018 And Multi-Year Averages, NRIncluded (%)
N/A--Not applicable. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&PGlobal Fixed Income Research.
Table 48
Global ABS Rating Transitions, 2018 And Multi-Year Averages, NR Included (%)
N/A--Not applicable. Securities whose ratings migrated to 'NR' over the period are classified based on their rating prior to 'NR'. Source: S&PGlobal Fixed Income Research.
Table 52
Global CMBS Rating Transitions, 2018 And Multi-Year Averages, NR Included (%)
N/A--Not applicable. Source: S&P Global Fixed Income Research.
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Appendix III: Comparison Of Alternative Treatments For 'AAA' Ratings
This edition of our global structured finance default and rating transition study adopts a newapproach to the treatment of securities whose original rating was 'AAA'. As detailed in Appendix I,this study uses the "uncollapsed" approach to the treatment of securities whose original ratingwas 'AAA', rather than the "collapsed" approach, which was used in previous studies publishedbefore 2018. Charts 25-28 illustrate the resulting differences in some example summarystatistics.
Chart 25
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 26
Chart 27
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Default, Transition, and Recovery: 2018 Annual Global Structured Finance Default Study And Rating Transitions
Chart 28
Related Criteria And Research
Related Criteria
- Credit Stability Criteria, May 3, 2010
- Understanding S&P Global Ratings' Rating Definitions, June 3, 2009
Related Research
- 2018 Annual Japanese Structured Finance Default Study And Rating Transitions, March 26,2019
- Credit Conditions: Global Conditions Are Tightening As Trade And Economic Worries Mount,Dec. 5, 2018
This report does not constitute a rating action.
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