CLO Credit Ratings Gone Awry

Co-authors Gene Phillips and Mark Adelson wrote the following article, which was published in the Fall 2020 edition of the Journal of Structured Finance (JSF); it is available in its entirety on the JSF's website at this link.

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The COVID-19 pandemic has had a broad reach, spanning most sectors and industries. This distinguishes it sharply from the mortgage meltdown and the 2008 financial crisis, which were mostly confined to the housing sector and financial institutions, respectively. Collateralized loan obligations (CLOs), which were largely immune to the perils of the mortgage meltdown and the financial crisis due to their diversity among corporate issuers, find themselves exposed by the COVID-19 pandemic. 

Rating agencies have been downgrading the speculative-grade loans that support these CLOs en masse: during the four-month period ending June 30, 2020, Moody’s downgraded the ratings of 755 speculative-grade borrowers, a full 31% of the speculative-graderated universe, across a range of industries (Moody’s Investors Service, n.d.). The industry sectors most affected are shown in Exhibit 1. 

While the loan-level downgrades continue, the rating agencies are also downgrading the CLOs backed by the loans. Meanwhile, corporate defaults are already on the high end. As of the end of July 2020, S&P reported 98 year-to-date defaults, already surpassing the full-year corporate default tally for 2008, which reached 95 (Serino, Kesh, and Pranshu 2020). 

This note focuses primarily on CLO ratings — but there have been oddities in the rating of residential mortgage-backed securities (“MBS”) during the pandemic as well. 

While the credit rating agencies are actively downgrading speculative-grade corporate loans and outstanding CLOs backed by these loans, they continue to rate new CLOs at the same time. Their approaches to this tricky proposition, and their communications describing their approaches, give us pause. We find that they are: 1) not being transparent about how they apply their methodologies, 2) either not applying their methodologies or not applying them consistently, and 3) not being consistent in their deviations when they deviate from their official methodologies. 

RATINGS DOWNGRADES AND NEW RATINGS 

In an inauspicious report of May 2020, titled “How COVID-19 Changed the European CLO Market in 60 Days” (Ryan and Tamburrano 2020), S&P explained that the changes have come “in a sudden and marked way” and that the “wave of negative [corporate loan] rating actions has affected several sectors, geographies, and products.” Strikingly, S&P noted that “[m]arket challenges that existed before COVID-19, including high leverage ratios, EBITDA add-backs, and cov-lite loans, are causing speculation that this may be the perfect storm for CLOs.” 

As of early June, Moody’s had placed 1,100 CLO notes on watch for possible downgrade. That amounted to 24% of all CLO notes by count and 7% by balance (Deshpande, Mogunov, and Chatterjee 2020). The rating agency stated, “Moody’s actions today follow the CLO actions Moody’s took on 17 April 2020, and are primarily prompted by a continuing decline in the credit quality of CLO portfolios as a result of economic shocks stemming from the coronavirus pandemic. Since April, the decline in corporate credit has resulted in a significant number of downgrades among the assets underlying some CLOs.” 

The downgrading continues, but some of it has been tepid. When downgrading, Moody’s has often opted for only a single notch downgrade. For example, on July 1, Moody’s noted significant collateral deterioration in a CLO called Nassau 2017-II Ltd. The rating agency stated: 

Based on Moody’s calculation, the weighted average rating factor (WARF) was 3764 as of June 2020, or 25% worse compared to 3006 reported in the March 2020 trustee report. Moody’s calculation also showed the WARF was failing the test level of 3022 reported in the June 2020 trustee report by 742 points. Moody’s noted that approximately 40% of the CLO’s par was from obligors assigned a negative outlook and 7% from obligors whose ratings are on review for possible downgrade. Additionally, based on Moody’s calculation, the proportion of obligors in the portfolio with Moody’s corporate family or other equivalent ratings of Caa1 or lower (after any adjustments for negative outlook and watchlist for possible downgrade) is approximately 30% as of June 2020 (Aeron and Ham 2020). 

Nevertheless, despite significant deterioration, and in the face of a 30% exposure to Caa1 or lowerrated assets, Moody’s downgraded the Class C, Class D, and Class E notes by only a single notch, from A2, Baa3, and Ba3 to A3, Ba1, and B1 respectively. Moody’s affirmed the rating of the Class B at Aa2. 

In late July, S&P downgraded 63 CLO tranches by an average of 1.2 rating notches. But 496 tranches across 287 CLOs remained on CreditWatch negative. As shown in Exhibit 2, data on the “S&P CLO Insights 2020 Index” reflected the weakened condition of the deals. 

Meanwhile, the performance of CLOs is to a degree based on the vigor with which the rating agencies downgrade the corporate loans. In addition to default events, downgrades themselves can impact a CLO managers’ ability to trade assets, especially once they start to fail collateral-quality tests. With CLOs being so heavily laden with B-rated collateral, even minor downgrades tend to quickly make an impression on their bucket for CCC-rated assets. 

LACK OF TRANSPARENCY 

The rating agencies’ communications around their ratings actions are confounding. This riddle is no easier to disentangle when visiting the rating agencies’ remarks. They provide only limited clarity about the specifics of how (if at all) they are considering the impact of the COVID-19 pandemic in their rating actions. 

When downgrading CLOs, Moody’s mentions that its “analysis has considered the effect of the coronavirus outbreak on the US economy as well as the effects that the announced government measures, put in place to contain the virus, will have on the performance of corporate assets” (Deshpande, Mogunov, and Chatterjee, 2020). But there are no specifics: Moody’s does not explain how. In what ways is Moody’s changing its approach to reflect the analysis it purports to be making? Did the prepayment rate assumptions change? Did the default rate assumptions change? Did the correlation assumptions change? Did the recovery rate assumptions change? Given that Moody’s identifies a largely quantitative methodology article (Kim, et al. 2019) as the “principal methodology” used in the downgrades, it is odd that Moody’s did not express its approach in any way that enables users of ratings to apply the purported considerations within a quantitative framework. 

S&P is similarly opaque. When rating new deals and reviewing existing deals, S&P sometimes mentions the pandemic and sometimes does not. For example, in April, S&P never mentioned the effect of COVID-19 on its rating of Deerpath Capital CLO 2020-1 (Kalinauskas, et al. 2020). Moreover, when S&P does discuss the impact of the pandemic, it does so in a nebulous way, which leaves the reader guessing about the particulars of how the rating agency accounts for the pandemic when assigning ratings. When S&P assigned new ratings in May 2020 to notes issued by Guggenheim CLO 2020-1 Ltd, its sole mention of the pandemic was the following boilerplate language: 

S&P Global Ratings acknowledges a high degree of uncertainty about the rate of spread and peak of the coronavirus outbreak. Some government authorities estimate the pandemic will peak about midyear, and we are using this assumption in assessing the economic and credit implications. We believe the measures adopted to contain COVID-19 have pushed the global economy into recession (see our macroeconomic and credit updates here: www.spglobal.com/ratings). As the situation evolves, we will update our assumptions and estimates accordingly. (Kalinauskas and Davis 2020). 

DEPARTURES AND DEVIATIONS FROM METHODOLOGIES, AND INCONSISTENT APPLICATIONS 

Beyond the disappointing lack of transparency, another challenge for investors is that rating agencies appear to be deviating from their published methodologies for assigning and maintaining ratings. Moreover, they deviate in inconsistent ways from one deal to the next. 

Example 1. In one telling example (Jiang and Vasudevan 2020), Moody’s downgraded 48 MBS on April 15, 2020. The rating agency identified a mostly-quantitative methodology as the “principle methodology” for the rating actions (Vasudevan, Hannoun-Costa, and Muni 2019). Of note, the principle methodology predates the start of the pandemic. 

What was particularly striking about the April 15 rating actions was that Moody’s downgraded all of 48 MBS to the same rating level (Baa3) even though they previously carried ratings at a variety of levels (A3, Baa1 and Baa2). Moody’s did not describe a concrete basis for the Baa3 outcome. Although it explained the need for taking action, it provided no details about why Baa3 was the right rating level for the 48 tranches. The rating agency stated: “Our analysis has considered the increased uncertainty relating to the effect of the coronavirus outbreak on the US economy.” But later in the press release it revealed that it “did not use any models, or loss or cash flow analysis, in its analysis” and that it “did not use any stress scenario simulations in its analysis” (Jiang and Vasudevan 2020). It is difficult to reconcile that statement with others to the effect that 1) a quantitative methodology was used and 2) the analysis considered the increased uncertainty relating to the onset of the pandemic. 

In June, Moody’s took action on 415 US MBS, confirming its ratings on 35 of them, while downgrading the other 380 (Rossetti and Vasudevan 2020). The announcement, however, contained no language about Moody’s departing from the application of any models. Instead, the boilerplate verbiage in the announcement stated: 

Moody’s estimates expected collateral losses or cash flows using a quantitative tool that takes into account credit enhancement, loss allocation and other structural features, to derive the expected loss for each rated instrument. Moody’s quantitative analysis entails an evaluation of scenarios that stress factors contributing to sensitivity of ratings and take into account the likelihood of severe collateral losses or impaired cash flows. Moody’s weights the impact on the rated instruments based on its assumptions of the likelihood of the events in such scenarios occurring (Rossetti and Vasudevan 2020, emphasis added). 

Most interestingly, 47 of the 48 MBS, which had been downgraded to Baa3 in April (without the use of a model), were addressed again in June (Rossetti and Vasudevan 2020), this time ostensibly using a quantitative tool. The results were that the securities received different ratings: 

• 10 MBS maintained their Baa3 ratings upon review with a model.
• 15 were downgraded to Ba2 (i.e., a further two notch downgrade). 
• 22 were downgraded to B1 (i.e., a further four notch downgrade). 

Example 2. In recent surveillance updates on CLO ratings, Fitch appears to be applying new scenarios that are not included in its official methodology. For example, in the updates for Jubilee CLO 2014-XII and Penta CLO 5, the agency explained: 

Coronavirus Baseline Scenario Impact: Fitch carried out a sensitivity analysis on the current portfolio to envisage the coronavirus baseline scenario. The agency notched down the ratings for all assets with corporate issuers on Negative Outlook regardless of sector. 

∗ ∗ ∗ 

In addition to the base scenario, Fitch has defined a downside scenario for the coronavirus crisis, whereby all ratings in the ‘B’ category would be downgraded by one notch and recoveries would be lowered by 15% (Kelmer and Brewer 2020a; Segato and Brewer 2020a). 

More pointedly, Fitch has been regularly deviating from its model-implied ratings (MIRs) in downgrading CLOs notes. In addition, the deviations have not been consistent. 

For example, in reviewing certain European CLOs, Fitch refrained from downgrading tranches for which the MIR indicated a one-notch drop. Where the MIR indicated a two-notch drop, the rating agency either refrained from downgrading[1], or did so by just one notch[2]. In some cases, Fitch explained that the deviations were because the MIR results had been “driven by the back-loaded default timing scenario only” (Choraria and Brewer 2020; Ishidoya and Brewer 2020; Segato and Brewer 2020a, 2020b). In other cases, Fitch asserted that it had deviated from the MIRs because the results did not comport with its view of credit quality and also because the MIRs had been “driven by the rising interest rate scenario only, which is not our immediate expectation” (Kelmer and Brewer 2020a, 2020b). 

Fitch made several similar out-of-model adjustments when reviewing the ratings across seven CLOs in late July (Torres and Pak 2020). The rating agency stated: 

The class C notes in PSLF 2018-4, Ltd., class B notes in PSLF 2019-4, Ltd., and class B notes in PSLF 2020-1, Ltd. experienced shortfalls in some scenarios and the model-implied ratings (MIRs) of these notes were one notch below their current rating levels. However, Fitch considered the magnitude of these failures as minor and isolated to the back-loaded default timing and rising interest rate scenario that was given less weight in the analysis. 

∗ ∗ ∗ 

In addition, MIRs of the following classes were at least one notch higher than their current ratings based on current portfolio analyses, but were not upgraded in light of the ongoing economic disruption … (Torres and Pak 2020). 

In contrast to its surveillance practices, Fitch generally makes no mention of ignoring its model-based outcomes in rating new US CLOs. However, in some cases, Fitch has indicated that it is applying stress scenarios in a way similar (but not identical) to surveillance stress scenarios. 

For example, when providing ratings to two newly-issued CLO in July 2020, the rating agency explained: 

Fitch has applied two additional stress scenarios to the indicative portfolio that envisage negative rating migration as a result of business disruptions from the coronavirus. The first scenario applies a one-notch downgrade (with a CCC-floor) for all assets in the indicative portfolio with a Negative Rating Outlook.… The second scenario assumes a 5% increase in the indicative portfolio’s PCM rating default rates (RDR) for all rating levels. 

∗ ∗ ∗ 

Fitch added a sensitivity analysis that contemplates a more severe and prolonged economic stress caused by a re-emergence of infections in the major economies, before a halting recovery begins in 2Q21. (See Weiss, Joswiak, and Hughes 2020; Hunter, Lycos, and Hughes 2020, with emphasis added). 

The second stress scenario used in rating new deals is entirely absent when performing surveillance. It is unclear whether the downside scenarios are being applied equally, as Fitch has left the specifics undefined. 

It is somewhat surprising that Fitch would choose to make manual, ad-hoc, overrides to its model-driven outputs in every pandemic-era CLO surveillance action we found because it could not rely on the results produced using its official methodology. Under such a scenario, it would be easier to understand a basic adjustment to the methodology (and the associated model), so that it provides a reliable result that reflects Fitch’s actual views. 

WHY IT ALL MATTERS 

Investors and other market participants use credit ratings as signals or indicators of creditworthiness that figure, inter alia, into their processes for valuing securities and allocating capital. Securities can also be interrelated. The ratings awarded to some securities also, as we note above, directly impact the performance of other securities that reference or support them. In order for credit ratings to be useful, they must embody a measure of reliability. One of the key aspects of that reliability is that ratings are produced through a consistent, replicable process: the application of a rating agency’s official methodologies. 

The ideas of applying official methodologies to produce ratings and doing so in a consistent manner are prominent features of each rating agency’s code of conduct (Moody’s Investors Service 2020, § 1.3; S&P Global Ratings 2018, § 1.2; Fitch Ratings 2017, § 2.1.3). At least one court has held that statements in a rating agency’s code of conduct constitute “specific assertions of current and ongoing policies” and cannot be dismissed as mere puffery upon which investors cannot reasonably rely, United States v. McGraw Hill (2013). Today, applying official methodologies to produce ratings is explicitly required under US [3] and European [4] law . 

Likewise, the rating agencies undertake, in their codes of conduct, to provide clear explanations of the rationale behind each rating action (Moody’s Investors Service 2020, § 3.6(b), (c); S&P Global Ratings 2018, § 4.1; Fitch Ratings 2017, § 4.1.3). That is also required under US [5] and European [6] law. 

There are compelling reasons for why rating agencies are required to produce ratings by applying their official methodologies. One reason is that it decreases the potential for an individual analyst or team of analysts to abandon criteria in an effort to win new deals by providing advantageous ratings. Rating agencies might argue that they must have some flexibility to stray from their methodologies. To the extent that such a position is valid (and does not violate a rating agency’s legal obligations), we believe that when a rating agency deviates from its official methodology, it has an obligation to explain the rationale for the deviation and to explain in detail how it arrived at the rating produced with the deviation. Moreover, when deviations become the norm, or when they are inconsistent or poorly articulated, we believe that the rating agencies have gone too far. At times, as shown herein, rating agencies have deviated from their methodologies, but failed to explain the analyses that ensued and how they determined the final ratings that they assigned. 

CONCLUSION 

In the aftermath of the 2008 financial crisis, the credit rating agencies experienced criticism, private litigation, and government enforcement actions. Enforcement actions in the US were taxing, culminating in f ines of $1.375 billion for S&P and $864 million for Moody’s (US Department of Justice 2015, 2017). The enforcement actions particularly noted that the rating agencies had violated their codes of conduct, which required them to provide objective, independent ratings. 

Although the regulatory environment has gotten tougher since the Dodd-Frank Act was signed into law, we remain concerned that rating agencies continue to deviate from their published methodologies whenever it suits them. Based on recent evidence, they appear to view the directive to determine ratings pursuant to their official methodologies and to apply methodologies in a consistent manner as mere suggestions, rather than as mandatory rules. 

FOOTNOTES

[1] Adagio VII, classes E and F (Segato and Brewer 2020b); St Paul CLO 5, class F-R (Kelmer and Brewer 2020b); St Paul CLO 6, class E-R (Kelmer and Brewer 2020b); Jubilee 2014-XII, class F-R (Kelmer and Brewer 2020a); Jubilee 2016-XVII, class F-R (Kelmer and Brewer 2020a); Penta 5, class F (Segato and Brewer 2020a). 

[2] Euro Galaxy III, class E (Choraria and Brewer 2020); Toro European 4, class E (Ishidoya and Brewer 2020). 

[3] 15 U.S.C. § 78o-7(r) (2018), https://www.govinfo.gov/content/pkg/USCODE-2018-title15/pdf/USCODE-2018-title15-chap2B-sec78o-7.pdf; 17 C.F.R. § 17g-8(a)(3)(i), (d) (2019), https://www.govinfo.gov/content/pkg/CFR-2019-title17-vol4/pdf/CFR-2019-title17-vol4-sec240-17g-8.pdf. 

[4] Regulation (EU) No 462/2013 of the European Parliament and of the Council of 21 May 2013 amending Regulation (EC) No 1060/2009 on Credit Rating Agencies, Art. 1, § 10(a) & Annex II, ¶ 1(h), 2013 O.J. (L146/1) at 16, 31 (May 31, 2013), https://eurlex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32013R0462&from=EN; Commission Delegated Regulation (EU) No 447/2012 of 21 March 2012 Supplementing Regulation (EC) No 1060/2009 of the European Parliament and of the Council on Credit Rating Agencies by Laying Down Regulatory Technical Standards for the Assessment of Compliance of Credit Rating Methodologies, Art. 5, § 1, 2012 O.J. (L140/14) at 15 (May 30, 2012), https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32012R0447&from=EN; Regulation (EC) No 1060/2009 of the European Parliament and of the Council of 16 September 2009 on Credit Rating Agencies, Art. 8, § 2, 2009 O.J. (L302/1) at 13 (November 17, 2009), https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32009R1060&from=EN. 

[5] 15 U.S.C. § 78o-7(s) (2018), https://www.govinfo.gov/content/pkg/USCODE-2018-title15/pdf/USCODE-2018-title15-chap2B-sec78o-7.pdf; 17 C.F.R. § 17g-7(a)(1)(ii)(B), (C) (2019), https://www.govinfo.gov/content/pkg/CFR-2019-title17-vol4/pdf/CFR-2019-title17-vol4-sec240-17g-7.pdf. 

[6] Regulation (EU) No 462/2013 of the European Parliament and of the Council of 21 May 2013 amending Regulation (EC) No 1060/2009 on Credit Rating Agencies, Annex II, § 4(f), 2013 O.J. (L146/1) at 27 (May 31, 2013), https://eur-lex.europa.eu/legalcontent/EN/TXT/PDF/?uri=CELEX:32013R0462&from=EN; Regulation (EC) No 1060/2009 of the European Parliament and of the Council of 16 September 2009 on Credit Rating Agencies, Annex II, Section D, ¶ 5, 2009 O.J. (L302/1) at 28 (November 17, 2009), https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32009R1060&from=EN. 

REFERENCES 

Aeron, N., and D. Ham. 2020. “Moody’s Downgrades Ratings on $72 Million of CLO Notes Issued by Nassau 2017-II Ltd.; Actions Conclude Review.” Moody’s press release. July 1. 

https://www.moodys.com/research/Moodys-downgrades-ratings-on-72-million-of-CLO-notes-issued--PR_ 427681. 

Choraria, P., and A. Brewer. 2020. “Fitch Downgrades One Tranche of Euro Galaxy III CLO B.V., Maintains RWN on One and Affirms the Rest.” Fitch press release. May 7. 

https://www.fitchratings.com/research/structured-finance/fitch-downgrades-one-tranche-of-euro-galaxy-iii-clo-bv-maintains-rwn-on-one-affirms-rest-07-05-2020. 

Deshpande, A., L. Mogunov, and D. Chatterjee. 2020. “Moody’s Places Ratings on 241 Securities From 115 US CLOs on Review for Possible Downgrade; Also Places Ratings on 2 Linked Securities on Review for Possible Downgrade.” Moody’s press release. June 3. 

https://www.moodys.com/research/Moodys-places-ratings-on-241-securities-from-115-US-CLOs--PR_425620. 

Dodd-Frank Wall Street Reform and Consumer Protection Act, Pub. Law No. 111-203, 124 Stat. 1376 (2010)

https://www.govinfo.gov/content/pkg/PLAW-111publ203/pdf/PLAW-111publ203.pdf. 

Fitch Ratings. 2017. “Code of Conduct and Ethics.” July. 

https://assets.ctfassets.net/03fbs7oah13w/25SiZhnpbDYTLd1S8Elrc7/c75f55b3ac3ee5c95c9bdbfeda95488b/Bulletin_01_Code_of_Conduct_and_Ethics.pdf. 

Hu, D., S. Anderberg, R. E. Schulz, S. Wilkinson, and R. Muthukrishnan. 2020. “CLO Insights: 63 CLO Tranches Downgraded by 1.2 Notches on Average in July.” S&P newsletter. July 31. 

Hunter, M., K. Lycos, and A. Hughes. 2020. “Fitch Rates Ballyrock CLO 2020-1 Ltd.” Fitch press release. July 8. https://www.fitchratings.com/research/structured-finance/fitch-rates-ballyrock-clo-2020-1-ltd-08-07-2020. 

Ishidoya, K. and A. Brewer. 2020. “Fitch Downgrades One Tranche of Toro European CLO 4 DAC and Affirms Rest; Two Tranches on RWN.” Fitch press release. May 18. 

https://www.fitchratings.com/research/structured-finance/fitch-downgrades-one-tranche-of-toro-european-clo-4-dac-affirms-rest-two-tranches-on-rwn-18-05-2020. 

Jiang, Z., and S. Vasudevan. 2020. “Moody’s Places 404 Classes of Legacy US RMBS on Review for Downgrade.” Moody’s press release. April 15. 

https://www.moodys.com/research/Moodys-places-404-classes-of-legacy-US-RMBS-on-review--PR_422633. 

Kalinauskas, P., and C. Davis. 2020. “Guggenheim CLO 2020-1 Ltd. Notes Assigned Ratings.” S&P press release. May 4. 

https://www.standardandpoors.com/en_US/web/guest/article/-/view/type/HTML/id/2424307. 

Kalinauskas, P., T. Walsh, W. Sweatt, and D. Haynes. 2020. “Deerpath Capital CLO 2020-1 Ltd. Notes Assigned Ratings.” S&P press release. April 7. 

https://www.standardandpoors.com/en_US/web/guest/article/-/view/type/HTML/id/2408885. 

Kelmer, S., and A. Brewer. 2020a. “Fitch Assigns Negative Outlook to 1 Tranche and Downgrades Another of Jubilee CLO 2014-XII B.V.” Fitch press release. July 3. 

https://www.fitchratings.com/research/structured-finance/fitch-assigns-negative-outlook-to-1-tranche-downgrades-another-of-jubilee-clo-2014-xii-bv-03-07-2020. 

——. 2020b. “Fitch Downgrades 2 St Paul’s CLOs with 3 Tranches of Each CLO on RWN or Negative Outlook.” Fitch press release. June 29. 

https://www.fitchratings.com/research/structured-finance/fitch-downgrades-2-st-paul-clos-with-3-tranches-of-each-clo-on-rwn-negative-outlook-29-06-2020. 

Kim, J., R.O. Torres, I. Perrin, T. Klotz, A. Remeza, and J. Hu. 2019. “Moody’s Global Approach to Rating Collateralized Loan Obligations.” Moody’s methodology report. March 8. 

https://www.moodys.com/researchdocumentcontentpage.aspx?docid=PBS_1111156. 

Moody’s Investors Service. n.d. “Non-Financial Corporates: Rating Activity During COVID-19.” Moody’s infographic. 

https://www.moodys.com/sites/products/ProductAttachments/Infographics/non-finanancial-corporates-rating-activity-06July.pdf. 

Moody’s Investors Service. 2020. “Code of Professional Conduct.” March. 

https://www.moodys.com/uploadpage/Mco%20Documents/Documents_professional_conduct.pdf

Rossetti, N., and S. Vasudevan. 2020. “Moody’s Takes Action on 415 US RMBS Bonds from 237 Deals Issued Prior to 2009.” Moody’s press release. June 9. 

https://www.moodys.com/research/Moodys-takes-action-on-415-US-RMBS-bonds-from-237--PR_425884. 

Ryan, S., and E. Tamburrano. 2020. “How COVID-19 Changed the European CLO Market in 60 Days.” S&P comment. May 6. 

https://www.spglobal.com/ratings/en/research/articles/200506-how-covid-19-changed-the-european-clo-market-in-60-days-11444644. 

Segato, G., and A. Brewer. 2020a. “Fitch Ratings Revises One Tranche of Penta CLO 5 DAC to Negative Outlook; Affirms Ratings.” Fitch press release. July 6. 

https://www.fitchratings.com/research/structured-finance/fitch-ratings-revises-one-tranche-of-penta-clo-5-dac-to-negative-outlook-affirms-ratings-06-07-2020. 

——. 2020b. “Fitch Revises One Tranche of Adagio VII CLO DAC to Negative Outlook; Affirms Ratings.” Fitch press release. June 26. 

https://www.fitchratings.com/research/structured-finance/fitch-revises-one-tranche-of-adagio-vii-clo-dac-to-negative-outlook-affirms-ratings-26-06-2020. 

Serino, N., S. Kesh, and S. Pranshu. 2020. “Default, Transition, and Recovery: Consumer and Service Sector Defaults Help Push The 2020 Corporate Tally To 147,” S&P comment. July 31. https://www.spglobal.com/ratings/en/research/articles/200731-default-transition-and-recovery-consumer-and-service-sector-defaults-help-push-the-2020-corporate-tally-to-11596242. 

S&P Global Ratings. 2018. “S&P Global Ratings Code of Conduct.” March 1. 

https://www.standardandpoors.com/en_US/delegate/getPDF?articleId=2194115&type=COMMENTS&subType=REGULATORY. 

Torres, C., and A. Pak. 2020. “Fitch Affirms 38 Tranches from Seven Static CLOs; Removes Rating Watch Negative,” Fitch rating action commentary. July 29. 

https://www.fitchratings.com/research/structured-finance/fitch-affirms-38-tranches-from-seven-static-clos-removes-rating-watch-negative-29-07-2020. 

US Department of Justice. 2015. “Justice Department and State Partners Secure $1.375 Billion Settlement with S&P for Defrauding Investors in the Lead Up to the Financial Crisis.” Press release. February 3. 

https://www.justice.gov/opa/pr/justice-department-and-state-partners-secure-1375-billion-settlement-sp-defrauding-investors. 

US Department of Justice. 2017. “Justice Department and State Partners Secure Nearly $864 Million Settlement with Moody’s Arising From Conduct in the Lead up to the Financial Crisis.” Press release. January 13. https://www.justice.gov/opa/pr/justice-department-and-state-partners-secure-nearly-864-million-settlement-moody-s-arising. 

US v. McGraw Hill, No. CV-13-0779 (C.D.Ca., July 16, 2013) (order denying defendants’ motion to dismiss). https://online.wsj.com/public/resources/documents/sandpdismiss0717.pdf. 

Vasudevan, S., O. Hannoun-Costa, and K. Muni. 2019. “US RMBS Surveillance Methodology.” Moody’s rating methodology. February 22. 

https://www.moodys.com/research-documentcontentpage.aspx?&docid=PBS_1127300. 

Weiss, C., A. Joswiak, and A. Hughes. 2020. “Fitch Rates HalseyPoint CLO II, Ltd.” Fitch press release. July 1. 

https://www.fitchratings.com/research/structured-finance/fitch-rates-halseypoint-clo-ii-ltd-01-07-2020. 

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Gene Phillips is the CEO of PF2 Securities Evaluations, Inc. in Los Angeles, CA. gene.phillips@pf2se.com 

Mark Adelson is the editor of The Journal of Structured Finance, in New York, NY. m.adelson@pageantmedia.com

Leveraged Loan CLOs and Rating Agencies - Policy Solutions

Over the last couple of years, financial market commentators have become concerned that leveraged loans and Collateralized Loan Obligations (CLOs) are becoming the newest “financial weapons of mass destruction”.  The fear is that mispricing and over-production of these assets could lead to a bubble that would ultimately take down our financial system – just as subprime mortgage backed securities did a dozen year ago.

Further, critics worry that rating agencies – still following the traditional issuer-pays model – lack the incentive to protect us from a leveraged lending meltdown. Instead, agencies are thought to be engaged in a "race-to-the-bottom," lowering their rating standards to enable (or keep) even the less credible corporate borrowers in the Investment Grade category.

If SEC-licensed Nationally Recognized Statistical Rating Organizations (NRSROs) – or so-called credit rating agencies -- are not up to the task, investors could turn to non-licensed analytics firms to more objectively evaluate leveraged loans and the securitization vehicles that house them.  Outside of the market for debt and credit-based financial products, we see many types of ratings published by non-licensed providers. For example, Consumer Reports assigns ratings to a wide array of products, US News ranks colleges and Yelp assigns ratings to service establishments. These systems are imperfect and sometimes deservedly attract criticism, but no rating system is perfect and the widespread use of these assessments suggests that users find them valuable.

The main barrier to entry for non-NRSROs that would want to assess leveraged loans and CLOs specifically is lack of access to data, and this is an issue that the SEC could rectify. The leveraged loans at the center of CLOs are often borrowings made by privately held companies – including holdings of private equity firms – that are not required to make their financial statements public. Only current investors and the rating agencies hired to rate these entities can see these financial statements.

The SEC could simply require all such companies that borrow on the leveraged loan market, subject to a minimum borrowing size, to file their 10-Q and 10-K statements on the EDGAR system. That way independent firms could assess their financial status and estimate default probabilities and expected losses on their loan facilities.

Second, CLO issuers should be required to post both their loan portfolios and details of their capital structures on EDGAR as well. In such a scenario, CLOs could no longer be exempted under Section 4(a)(2) of the Securities Act and sold as Rule 144A private securities. Instead, they would be regulated as public securities.

Finally, many CLOs have complex rules governing how proceeds from the collateral pool should be distributed among the various classes of noteholders and the firms – like the asset manager – that provides services to the CLO deal. These “priority of payment” provisions are outlined in dense legalese included in the CLO's offering documents. Rather than compelling investors and analysts to decipher these legal provisions, issuers should be required to code them as computer algorithms which would also be published as part of the deal’s disclosure. CLOs could then operate like any other “smart contract,” easing the work of deal participants and third parties who need to analyze the many “what-ifs” that can occur over the life of a transaction.

Leveraged loans and CLOs may or may not be the ticking time bomb that will blow up our economy. One way to limit the potential for bubble-creation is to remove dependence on parties (like the incumbent credit rating agencies) that are financially motivated to provide high ratings, thus prompting issuers and other market participants to seek out their services. Thus, our solution is, in short, to make these transactions more transparent, so that other third parties can access information on the securities and analyze them in a cost-effective manner.

Disclosure, or What You Will

Seven years after the demise of Lehman Brothers, lawsuits on related financial products are heating up, with a number of RMBS and CDO cases seeing reversals of fortune. 

But first, some background. 

This may seem odd – but so far most of the arguments have had little to do with whether the defendants did anything wrong.[1]  

Rather, the focus has been on peripheral issues, like: (1) jurisdiction; (2) whether the plaintiffs had standing to sue; (3) whether the plaintiffs sued within the permissible time frame; (4) whether the defendants were indeed obligated to fulfill any of the duties they are accused of violating; and (5) whether the investment risks were appropriately disclosed. 

Recent rulings have focused on this final element, and have been rendered in a way largely favorable to the plaintiffs. This is the focal point of today’s post. 

Disclosures and Disclosures – Five Shades of Grey 

Disclosures are subjective issues; they are forms of art. And, most importantly, they are not Boolean – they are not simply present or absent. 

There are various shades of grey. Consider for example the following possible disclosures regarding a bridge: 

1. Cross bridge at your own risk 
2. We have performed one or more tests and happen to believe that this bridge is particularly risky, or more risky than other bridges 
3. This bridge fails to satisfy the criteria set for bridges by the relevant architectural/building standards and safety boards 
4. We built this bridge and know that it suffers from certain structural flaws 
5. This may look like a bridge, but it is made of straw and has simply been dressed up to look like a bridge. Do not cross! 

These disclosures differ greatly, and one cannot reasonably argue that all provide the same informational content. 

Of course, it may be okay to sell a distressed asset or a structurally flawed house, as long as its known shortcomings are appropriately disclosed; but when a particular risk is known to one party (often the seller) we argue that the material information needs to be properly disclosed. 

For our purposes, it may be helpful to break disclosures down into three broad categories: 

1. Those that are general (non-specific) and describe overall risk
2. Those that describe particular risk(s)
3. Those that describe the advanced knowledge that one party to an agreement has (over the other) pertaining to particular risk(s) 

Reliance – A Practitioner’s Perspective[2] 

The recent rulings, which we’ll get to in a moment, give us some confidence that the legal system is supporting the essence of what investing in the US financial markets is all about. 

The defenses that “it was disclosed that the investment contained risk” or that “we warned the investor to perform his own due diligence” seem to us to be off-point and insufficient. 

From a practitioner’s perspective, it should be noted that investors are just about always warned that investments contain risks. Of course they do – there’s seldom a reason to invest without the expectation of a positive return[3], and risk and return go hand in hand. And due diligence can often be impractical or prohibitively expensive, and even if it can be performed it may not uncover the true nature of hidden risks, especially if they are known only to certain insiders. 

But in this “trust -but-verify” bargain, is the “trust” element still there? 

Let’s suppose that due diligence could be performed. Should investors have to check everything – every piece of data represented to them to be true and accurate, every potential conflict disclosed or undisclosed, every legal opinion upon which the transaction’s solidity is based, and every accounting record? What is the purpose of a representation or warranty, if the onus remains on the person accepting the representation or warranty? 

In short, shouldn’t investors be allowed to rely on some things? 

Buying a new car encourages some level of diligence too – one may want to take it for a test-drive. But is it healthy to expect or require each car buyer to have advanced engineering or mechanical skills and to test each part for herself? 

We argue it isn’t: such due diligence, while commendable, defeats the purpose. When buying a new car, a purchaser ought to be able to rest easy, relying on her property rights and on the manufacturer’s name and representations, and fairly assume that the parts used are new, in working order, and are expected (certainly by the manufacturer) to last. 

Similarly, when buying a financial product that has been structured by a bank, it would promote market efficiency and be most expedient if investors were able to freely rely on representations and warranties made to them by the banks about the collateral supporting the product. And when a representation turns out to have been faulty, investors could then expect to have recourse through the court system – one of the very reasons overseas investors invest in US-based financial products! 

Decisions, Decisions… 

On the RMBS/CDO side, a recent lower court ruling and a slew of higher court rulings have ended favorably for plaintiffs, finding that the disclosures and disclaimers[4]  provided were not specific enough – reversing decisions made by lower courts that those disclosures had been sufficiently specific. 

Various groups of defendants, in different litigation matters, had regularly made the argument that they had disclosed that some of the thousands of loans that made their way into the mortgage pool may fail to comply with the representations and warranties made of them. Well that’s fair enough – there may have been a data error here or there that is yet to be discovered. 

But at the time of writing this disclosure that “some” loans “may” fail, the truth was very different. Often some loans were already failing (and known to have been failing) to meet one or more of the criteria needed to pass. Moreover, and importantly, it was even the expectation of some defendants at that time that several other loans would imminently be found to fail too. 

In other words, several defendants made the weakest possible disclosure: that something may possibly happen. Meanwhile, defendants often already knew that it was happening, and often en masse. Disclosing that a violation may occur is different from disclosing (1) that violations are known to be occurring, or (2) that the procedures employed leave ample room for the occurrence of violations (and so forthcoming violations should be expected).[5] 

As it happens, in some cases defendants had set up tests to identify noncompliance in loans sampled within the pool. When they found that a high percentage of the sampled loans failed to comply with the representations and warranties, they failed to re-examine the non-sampled loans, but waived them into the securitization trusts anyway. Thus, they knew, or should have known, that a high percentage of the non-sampled loans would fail to meet the criteria upon which they were being purchased into the trusts. In FHFA v Nomura, the court examined the true nature of the mortgage loans being waived into the trust as conforming collateral: 

"Measured conservatively, the deviations from originators’ guidelines made anywhere from 45% to 59% of the loans in each [supporting loan group] materially defective, with underwriting defects that substantially increased the credit risk of the loan."[6] 

Some Examples – Decisions Favorable to Plaintiffs 

     Basis Yield v Goldman (CDO) [7]

The First Department decided that the disclosures were “boilerplate statements” that failed to put the investors on notice of the nature of the risks inherent in the investment (as alleged by the plaintiffs) [8]. The court held that if “plaintiff's allegations are accepted as true, there is a ‘vast gap’ between the speculative picture Goldman presented to investors and the events Goldman knew had already occurred.”[9]  

     ACA v Goldman (CDO) 

In May 2015, the New York Court of Appeals – the state’s highest court – reversed an order by the Appellate Division, holding that “plaintiff here claims that defendant knew that [co-defendant] Paulson was taking a position contrary to plaintiff's interest, but withheld that information, despite plaintiff's inquiries.”[10] 

     FHFA v Nomura (RMBS) 

In this bench trial, the court honed in on the direct issue at hand, ruling in favor of the plaintiff: 

“This case is complex from almost any angle, but at its core there is a single, simple question. Did defendants accurately describe the home mortgages in the Offering Documents for the securities they sold that were backed by those mortgages?”[11] 

     Basis Yield v Morgan Stanley (CDO) 

The court leaned heavily on several prior rulings[12] of the First Department which had recently rejected most of the contentions raised by Morgan Stanley, similar to those advanced in the same court. 

In the court’s words, “The First Department held that New York law is ‘abundantly clear’ that ‘a buyer’s disclaimer of reliance cannot preclude a claim of justifiable reliance on the seller’s misrepresentations or omissions unless (1) the disclaimer is made sufficiently specific to the particular type of fact misrepresented or undisclosed; and (2) the alleged misrepresentations or omissions did not concern facts peculiarly within the seller’s knowledge.” 

In denying Morgan Stanley’s motion to dismiss, the court held that, assuming plaintiff’s allegations to be true, the disclosures “did not apprise investors that Morgan Stanley had deliberately sabotaged assets in the CDO to profit from its short positions.”[13] 

Some Examples – Decisions Favorable to Defendants 

     HSH Nordbank v UBS AG (RMBS) 

HSH Nordbank is one example of an RMBS ruling that went the way of defendants. 

The court ruled that “Here, the core subject of the complained-of representations was the reliability of the credit ratings used to define the permissible composition of the reference pool. The reliability of those ratings was the premise on which the entire deal was sold to HSH. Far from being peculiarly within UBS's knowledge, the reliability of the credit ratings could be tested against the public market's valuation of rated securities.” 

In other words, plaintiff HSH could reasonably have uncovered that the ratings were misrepresented had HSH exercised the necessary due diligence.[14] 

     Lanier v BATS (HFT) 

Lanier, a case concerning high-frequency trading (or HFT), presents a more recent set-back for plaintiffs. 

Lanier’s argument, to a degree, is this: Lanier paid for time-sensitive trading information from NASDAQ; NASDAQ has other clients who paid more, and so they got this time-sensitive information before Lanier did, rendering the information stale and inaccurate by the time it arrived at Lanier’s desk. Lanier argues that he was not appropriately informed that he was being trumped – and that the spirit of the agreement was that nobody would get information before him. 

To use the court’s words, Lanier’s argument is that “when defendants make market data available to preferred data customers more quickly than other customers, they violate Regulation NMS, which is incorporated by reference into contracts between plaintiff Lanier and defendants.” In his words, he seeks “redress for a violation of a contractual commitment prohibiting defendants from providing earlier access to market data to Preferred Data Customers” and as a result, the sale of stale data to him. 

In Lanier’s words, “The Preferred Data Customers are then able to cancel orders and execute trades before Subscribers [like Lanier] even receive the market data.” 

But the court sympathized with the provision of what seems to us to be an extraordinarily weak form of disclosure. The court viewed the following paragraph in the subscription agreement to have been, in the court’s words, “pertinent.” 

“Neither NYSE, any Authorizing SRO nor the Processor (the “disseminating parties”) guarantees the timeliness, sequence, accuracy, or completeness of Market Data or other market information or messages disseminated by any disseminating party. No disseminating party shall be liable in any way to Subscriber or to any other person for (a) any inaccuracy, error or delay in, or omission of, (i) any such data, information, or message, or (ii) the transmission or delivery of any such data, information or message, or (b) any loss or damage arising from or occasioned by (i) any such inaccuracy, error, delay or omission, [or] (ii) non-performance . . . .” (emphasis added by the court) [15]

The court also took particular comfort in the provision within the Nasdaq Subscriber Agreement of a disclosure that reads “STOCK QUOTES MIGHT NOT BE CURRENT OR ACCURATE” and grants the motion to dismiss, preventing any further discovery.[16] 

 Indeed Nasdaq warranted to Lanier that it would “endeavor to offer the Information as promptly and accurately as is reasonably practicable.” If we take plaintiff’s allegations to be true, as we must at the motion to dismiss stage, then clearly NASDAQ did not provide it to Lanier as promptly as reasonably practicable, and it knew it wasn’t doing so. 

The court asserted that Lanier’s “argument misreads the Subscriber Agreements, which promise one thing: the provision of consolidated market data to Lanier and other subscribers like him. The contracts do not prohibit provision of the same data in different forms to different kinds of customers, whether in consolidated or unconsolidated form. And in general the duty of good faith and fair dealing does not provide a cause of action separate from a breach of contract claim, as “breach of that duty is merely a breach of the underlying contract.” 

Sadly, in rendering its opinion the court ignores the spirit of the agreement – the intent – and probably the content too. 

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FOOTNOTES

[1] For example, in a bench trial (FHFA v Nomura), the court noted that no real defense was presented as to the inappropriateness of defendants’ actions. “Today, defendants do not defend the underwriting practices of their originators. They did not seek at trial to show that the loans within the SLGs were actually underwritten in compliance with their originators’ guidelines. At summation, defense counsel essentially argued that everyone understood back in 2005 to 2007 that the loans were lousy and had not been properly underwritten.” Opinion at page 267. 

[2] Our goal here is to share a practitioner’s perspective. We do not provide advice of any kind –certainly not legal advice. 

[3] As scientists we must disclose our awareness of several situations in which investments are made without the expectation of a directly positive return, above 0%. While such examples exist, they are in the great minority of investments. For example, 5-year Swiss government bonds currently yield negative 0.539%, and there do exist rational arguments for investing in a negative yielding instrument, including for lack of available alternatives.) 

[4] Hereafter, we will use the short-hand “disclosures” to describe both disclosures and disclaimers. 

[5] An argument could be made that disclosure is faulty when it describes an occurrence as a remote possibility, when it’s known to be likely or inevitable – akin to a form of false advertising. Such disclosure disguises the true nature of the possibility. 

[6] Opinion at page 171 

[7] First Department decision and opinion at page 9 (1/30/2014) 

[8] In the court’s words “These disclaimers and disclosures, in our view, fall well short of tracking the particular misrepresentations and omissions alleged by plaintiff.” 

[9] A similar finding was made by the First Department in Loreley v Citigroup. 

[10] ACA Financial Guaranty Corp., Appellant, v. Goldman, Sachs & Co., Respondent, Paulson & Co., Inc. et al., NY INDEX NO. 650027/2011; Court of Appeals, No. 49, at page 4 (5/7/2015). Importantly, the court notes that ACA’s case differs from a prior case, in which the plaintiffs "knew that defendants had not supplied them with the financial information to which they were entitled, triggering 'a heightened degree of diligence.'" (Pappas v Tzolis, 20 NY3d 228, 232-233 [2012], quoting Centro Empresarial Cempresa S.A. 17 NY3d at 279). 

[11] Opinion and order at page 7

[12] Specifically, Loreley v Citigroup; Loreley v Merrill Lynch; Basis Yield v Goldman; and CDIB v Morgan Stanley 

[13] For example, the court specifically notes that the disclosure that Morgan Stanley would be acting in ‘its own commercial interest’ was … insufficient to put the Fund on notice of Morgan Stanley’s intent to offload low-rated RMBS from its books.” 

[14] For what it’s worth, our opinion is that it is impractical to have to second guess every party to a transaction; and having tried to, we can argue that it is very difficult if not impossible for a non-rating agency expert (and possibly even for a ratings expert) to effectively reverse-engineer ratings agencies’ complex models – which are often black-boxes, driven by and reliant on internal assumptions that cannot be seen by the most sophisticated of users. Having said that, the court raised its concern that, according to its reading of the amended complaint, HSH may not have provided sufficient factual information to support such the allegation, in the court’s words, “that the credit rating conferred on a security by a rating agency did not necessarily correspond to the security's risk level as perceived by the market.” 

[15] Ruling at page 26

[16] Here we have the same issue: Does disclosing the potential for delays in data distribution appropriately notify the subscriber that the data provided to him was always or regularly or intentionally being delayed? Aside from the omissions complained of, this disclosure, itself seems untruthful. Is it not misleading to state that “a quote might not be current,” when knowing that it is not current? If one wanted to be honest, one would disclose: “quotes are not current – beware!” 

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CASE CAPTIONS (links can be clicked to download opinions)

ACA v Goldman: ACA Financial Guaranty Corp., Appellant, v. Goldman, Sachs & Co., Respondent, Paulson & Co., Inc. et al., NY INDEX NO. 650027/2011 

Basis Yield v Goldman: Basis Yield Alpha Fund (Master) v Goldman Sachs Group, Inc., NY INDEX NO. 652996/2011; 2014 NY Slip Op 00587 

Basis Yield v Morgan Stanley: Basis Yield Alpha Fund Master v Morgan Stanley, NY INDEX NO. 652129/2012 

CDIB v Morgan Stanley: China Development Industrial Bank v Morgan Stanley & Co. Incorporated et al, NY INDEX NO. 650957/2010 

FHFA v Nomura: Federal Housing Finance Agency (“FHFA”) v Nomura Holding America, Inc., et al, 11-cv-06201-DLC 

HSH Nordbank: HSH Nordbank AG v UBS AG et al, 2012 NY Slip Op 02276 

Lanier v BATS: HAROLD R. LANIER, on behalf of himself individually and on behalf of others similarly situated v BATS Exchange, Inc. et al, 14-cv-03865-KBF 

Loreley v Citigroup: Loreley Financing (Jersey) No. 3 Ltd., et al v Citigroup Global Markets Inc., et al, NY INDEX NO. 650212/2012; 2014 N.Y. Slip Op. 03358 (N.Y. App. Div. 2014) 

Loreley v Merrill Lynch: Loreley Financing (Jersey) No. 28, Limited v Merrill Lynch, Pierce, Fenner & Smith Incorporated, et al., NY INDEX NO. 652732/2011; 2014 NY Slip Op 03326 (N.Y. App. Div. 2014) 

DISCLAIMER:  This blog has been posted for informational purposes only.  PF2 does not provide advice of any kind.

TruPS CDOs - Still Underrated?

Hello readers, and welcome to 2014!

In our first post of the year, we're going to continue with a theme we've been commenting on for years: we're noticing that many TruPS CDOs languish at deflated ratings levels, not having been adequately attended to by the rating agencies since their 2009 downgrades.  

Consider for example this first pay, amortizing bond (CUSIP 903329AB6) from one deal (US Capital Funding I) -- which has strengthened dramatically since its original Aaa/AAA ratings were provided back in 2004. It now has much more than 100% principal cushion! Yet, oddly enough, the ratings remain much lower to this date.  S&P still has this in deep junk territory, at B+, albeit on "watch" for upgrade.

Let us know if you would like to join the call for appropriate upgrades in 2014!

~PF2

Agency Shortcuts and Shortfalls

Investors in certain "AAA" resecuritizations won't be happy. Late last night, Moody's downgraded a bunch of securities, even though they are supported by Agency-guaranteed RMBS.

Many of these were downgraded from Aaa to junk (some at Ba1, others all the way to B1) in one fell swoop, while others went only to A1.  (It looks like S&P still carries most of these securities at AA+, which is lower than Moody's Aaa as S&P has downgraded the United States to AA+.)

What's most interesting here is the reason.  It's not the case that either Fannie or Freddie hasn't paid up on their guarantees, but it looks like the deals may not have been modeled (possibly ever!) - or at least may not have been modeled correctly.  According to their press release, the resecuritization vehicles seem not to have the necessary protections in place to support the bonds issued, or the ratings provided.  Some of these deals were structured in 2007 and even late 2008.  Many of these deals are already suffering shortfalls.

From Moody's press release:

"The downgrade rating actions on the bonds are a result of continual interest shortfalls or lack of adequate structural mechanisms to prevent future interest shortfalls should the deals incur any extraordinary expenses."

... and ...

"Interest due on the resecuritization bonds is not subject to any net weighted average coupon (WAC) cap whereas interest due on some of the underlying bonds backing these deals is subject to a net WAC cap."

... and ...

"Since the coupon on the resecuritization bonds is currently higher than that of the underlying bonds, the resecuritization bonds are experiencing interest shortfalls which on a deal basis are accruing steadily."

Total issuance of $483mm affected, according to Moody's. Deals are of Structured Asset Securities Corp. and Structured Asset Mortgage Investments shelves.

Relevant CUSIPs Downgraded Last Night
86363TAA4
86363TAC0
86363TAD8
86363TAF3
86363TAG1
86363TAB2
86363TAH9
86363TAJ5
86365HAA8
86365HAB6
86365HAD2
86365HAG5
86365GAA0
863594AA5
86359LPA1
86359LPB9
86359LPC7

Withdrawing, Confidently

As structured finance deals wind down and the asset pools grow smaller, the situation often arises that the effectiveness of outstanding tranche ratings – previously based on a portfolio-level diversification – can hinge on the performance of one or two bonds. The problem is compounded, of course, in that many of the models work best for large, diverse, portfolios and often break down when the portfolios become arbitrarily small.

The question then becomes, if a rated tranche can just as easily be rated AAA or D, what does one do?

This tricky situation, now part skill, part luck, calls into question the predictive content of highly sophisticated ratings models when the outcome is really not a model-driven result, but simply a short-term occurrence (e.g., a payoff or a default) or the lack of an occurrence, in a credit-default swap environment.

Moody’s and S&P suffered severe blushes in January when a well-structured CDO, backed heavily by other CDOs and RMBS (including substantial subprime, yes subprime), paid off in full ­– with their outstanding ratings on all tranches having been in the CC to CCC range. What was interesting was that both ratings agencies had visited this deal as recently as June of last year.
From our conversation with analysts at one of the agencies, what happened here was simply that as the deal was winding down, the manager was able to sell the few remaining assets at prices high enough to pay down all the notes, rendering irrelevant the Monte Carlo default simulation trials being run by the raters. In other words, the model let them down.

In an interesting, perhaps prudent decision, S&P took a different course in an announcement they made earlier today, entitled “S&P Takes Various Ratings Actions on 30 U.S. RMBS Deals.” As certain deals dwindled down, compromising the predictive content of their ratings, they chose to simply withdraw the ratings.

“We subsequently withdrew our ratings on certain affected classes that are backed by a pool with a small number of remaining loans. If any of the remaining loans in these pools default, the resulting loss could have a greater effect on the pool's performance than if the pool consisted of a larger number of loans. Because this performance volatility may have an adverse affect on our outstanding ratings, we withdrew our ratings on the related transactions.”

While it may cause frustration to note holders to see the ratings withdrawn, it augurs well that a rating agency is able and willing to say that it cannot have confidence in the outcome, and therefore chooses to withdraw its rating rather than have investors rely, perhaps falsely, on a rating in which it does not have confidence.

Analysis of The Shortcomings of Statistical Sampling in the Mortgage Loan Due Diligence Process

This is a popular litigation-related piece on our website we thought we'd share through this post (pdf version available here) - enjoy the read.



Introduction

Financial institutions, when assembling mortgage pools for the purpose of inclusion in residential mortgage-backed securities (RMBS), often hire independent analytical companies, like Clayton Holdings LLC (“Clayton”), to perform due diligence on the loans and flag any that are problematic.

Leading up to the financial downturn, Clayton reviewed mortgages for its clients - investment and commercial banks and lending platforms, including those of Bear Stearns, Barclays, Bank of America, C-Bass, Countrywide, Credit Suisse, Citigroup, Deutsche Bank, Doral, Ellington, Freddie Mac, Greenwich, Goldman, HSBC, JP Morgan, Lehman, Merrill Lynch, Morgan Stanley, Nomura, Société Générale, UBS and Washington Mutual (the “Issuers”). As such Clayton was purportedly one of the larger due diligence companies that analyzed whether these loans met specifications like loan-to-value ratios, credit scores and the income levels of borrowers.

Clayton describes, in the presentation it provided to the Financial Crisis Inquiry Commission (“FCIC”), the results of its review of a total of 911,039 mortgage loans between Q1 2006 and Q2 2007 ₁. As can be seen from the chart, of the loans shown to Clayton, Clayton determined approximately 72% of them to be in compliance, and 28% of them to be out of compliance with the standards tested, or “non-conforming.”

Upon determining that a loan failed to meet its guidelines, an Issuer (i.e., Clayton’s client) would have the ability to exercise their contractual right in “putting back” these non-conforming loans to the mortgage lenders – New Century, Fremont, Countrywide, Decision One Mortgage – rather than include them in securitizations.

The regulatory bodies, and the media, have concentrated heavily on the sizeable portions of non-conforming loans, and the lowering of underwriting standards throughout this period; but for this analysis, we concentrate on a more illuminating aspect of the way in which non-conforming loans ultimately found their way into the securitized RMBS pools.

There are at least two ways that non-conforming loans can find their way into the securitizations:

• First, the Issuer may choose to waive the loan back into the pool, despite its being originally rejected by Clayton.

• Second, a more overwhelming mechanism, is to not show the loan to Clayton.

The Intricacies of Loan Sampling

Importantly, it seems to have been common practice for Issuers to show only a sample of the loans to Clayton. A sample risks being unreflective of the population of loans, but random sampling can provide an effective statistical approximation under very strict conditions. It can be a cheaper process and, if the sample is well chosen, can accurately reflect the pool.

The objective of sampling is satisfied if the randomly-selected sample is sufficiently large, and is deemed to be in order. Alternatively, if the sample fails to meet expectations, the entire portfolio ought to be revisited. However, in the mortgage due diligence process the samples were often deemed to be problematic – they resulted in an average of 28% of loans failing their criteria. Importantly, the samples were then adjusted, as we understand it, but the original portfolios were not: the Issuers would only put back certain non-conforming loans from that sample.

In this case, the resulting sample, after throwing out certain non-conforming loans, fails to accurately depict the remaining portfolio of loans it was chosen to represent.



How the Sampling Process Worked, and Difficulties Therewith

Former President and COO of Clayton, D. Keith Johnson, explained to the FCIC committee, during their hearing of September 2010, that in the 2004 to 2006 time period, sample sizes went down to the region of two to three percent₂. As the sample size decreases, which it did, the effect of the sampling process alone begins to undermine the effectiveness of the due diligence process.

The media have focused their attentions on what happened to the 28% non-conforming loans – the slices in red in the associated charts. Indeed, many of these non-conforming loans, approximately 39%, were not “kicked out” or put back to the mortgage lenders, but were “waived” back in to the to-be-securitized portfolio. This 39% is substantial, and a factor worthy of the media’s attentions.

But the game-changing fact is not among these 28% non-conformers, or the 39% of them which remained in the securitized pool. These are only part of a sample, and when the sample becomes insignificantly small, its overall contribution to the portfolio as a whole is rendered less meaningful. Rather, it is more prudent to consider the composition of the pool as a whole.

For illustrative purposes, let us assume that the sample loans shown to Clayton represented 3% of the pools, on the higher end of those referred to in the abovementioned Johnson hearing. Let us conservatively assume that the sample provided to Clayton was truly randomly selected.₃

For a pool of 10,000 loans, Clayton would have been presented with approximately 300 loans, or 3%.

As we can see from the analysis performed, the effect of “throwing out” 61% of all non-conforming loans is marginal: the pool’s overall composition decreased only from 28% non-conforming to 27.67% non-conforming thanks to the due diligence process. Even had the Issuers returned all 84 non-conforming loans, the overall portfolio would not have been greatly altered –non-conforming loans would have declined from 28% to 27.16%.

When a random sample is tampered with, the final product, by definition, no longer represents the original pool. Here, the sample reflects that ultimately 89% of the pool is conforming and 11% are non-conforming (11% = 28% x 39%). But given the reality of the situation, with the original pool remaining status quo, in fact 27.76%, not 11%, of the overall pool was non-conforming, even after the put backs administered as part of the due diligence process.

A well-selected random sample can effectively capture the characteristics of a pool under certain conditions. But an altered sample seldom accurately reflects the original pool.



1 http://fcic-static.law.stanford.edu/cdn_media/fcic-testimony/2010-0923-Clayton-All-Trending-Report.pdf
2 http://fcic.law.stanford.edu/resource/interviews#J
3 course, the sample sizes used and the percentages rejected by Clayton will differ from Issuer to Issuer. So too will the waiver rate.

Return of the TruPS CDO

The good news, for investors in TruPS CDOs, is that at least one rating agency has responded to our calls for upgrades.

Moody’s, in two separate actions over the last two weeks, upgraded three tranches of Trapeza CDO VI and two tranches of Alesco Preferred Funding CDO I.

All five of the upgraded Alesco and Trapeza bonds were previously downgraded on July 13, 2010.

When you analyze ratings migrations, you notice raters have a tendency to inflate the initial ratings on new structures (the “Type I” error). When things go wrong, rating agencies then tend to exaggerate their downgrades to avoid being caught looking foolish when AAA or AA securities default. But they then run the second risk, which is seldom monitored or advertised, of the “Type II” error – the rating too low of a security that pays off in full. Both of these errors have the potential to be damaging to investors: investors get insufficient coupon reward for taking outsized risks at the beginning, and then they pay too much, in ratings-based margin, for holding under-rated bonds after the magnified downgrades.

We felt we had noticed the exaggeration of downgrades for at least some TruPS CDO bonds. We expect certain of the bonds that have been downgraded, to as low as CCC, to pay off in full. We therefore called for upgrades, of at least certain of these bonds, after noticing a growing disconnect between the actual asset-level performance of TruPS CDOs and the ratings performance of the asset class.

Upgrading bonds is a good thing for TruPS CDO investors: it may provide the support needed to mark them up, or to reduce capital reserves (or margin) held against them. In the best case, for bonds expected to ultimately pay out in full, the upgrade provides “leverage” for small bank managers to justify holding these securities at par in hold-to-maturity accounts; or to combat regulatory pressure to mark them to fair value based on an OTTI write-down.

While Moody’s upgrading intentions are a healthy sign, they do not always precipitate a similar response from the other rating agencies in the short term:

- The upgrades are due, in no small part, to the generation of excess spread by the underlying assets. Fitch, for one, does not model these structures and so by definition cannot adequately capture, in their ratings, the effects of this excess spread. It may thus be reasonable to expect Fitch’s TruPS CDO ratings to linger in this regard, until they ultimately follow the direction of the other rating agencies. (To be fair to Fitch, Fitch did in its September review retroactively upgrade a single tranche when Fitch saw the tranche was being paid down – but it also downgraded seven tranches and affirmed the ratings of 488 tranches. The A2 tranche of PreTSL 8 was upgraded, wait for it, from CC to B, less than one year after it was downgraded from B to CC. The bond was originally rated AAA by Fitch.)

- Rating agencies also, understandably, have a natural tendency to want to avoid flip-flopping on their ratings. The CLO downgrade-turn-upgrades within a year have caused the raters significant embarrassment. How will they look if, so soon after downgrading these 30 year TruPS CDOS, they then re-upgrade them? The market may be led to believe that the raters’ economic models hold little predictive content.

Trading in TruPS CDOs presents serious money-making opportunities, heightened somewhat by the ratings arbitrage available: for example, the recently upgraded A1A tranche of Trapeza VI is now rated Aa3 by Moody's, A by Fitch, while rated CCC+ by S&P. This dynamic should also provide holders with all the encouragement they need to examine the “true” flow of funds of their TruPS CDOs, rather than relying purely on their ratings (and succumbing to associated regulatory pressure to boost reserves).