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Structured Finance

www.fitchratings.com 30 April 2008

Global Structured Finance Criteria Report

Global Rating Criteria for Corporate CDOs Introduction/Summary Fitch Ratings has updated its methodology for rating portfolios of corporate debt. This criteria update includes a number of material changes that are designed to challenge existing CDO rating assumptions, address areas of CDO underperformance, and fully incorporate Fitch’s most up‐to‐date views of corporate credit risk (especially addressing those risk factors in corporate portfolios that have increased in recent years).

A fundamental tenet of corporate CDOs is that, by pooling corporate risk into asset pools, investors could benefit from diversification. Over time, however, Fitch has observed an increase in the level of concentration risk in many CDO portfolios, which may increase the likelihood that a particular portfolio will exhibit default and loss rates that are inconsistent with long‐term observed average statistics. Additionally, uneven portfolio compositions and risks from single obligor concentrations can result in material deviations from historically‐derived default expectations. Finally, Fitch recognises that corporate balance sheets, particularly for more highly leveraged credits, have evolved significantly in recent years, rendering historical recovery statistics less meaningful for forward‐looking analysis.

Adverse portfolio selection is another risk that may be present in CDO portfolios. If assets which have a larger than average propensity to be downgraded are included in a portfolio, the result may be an unacceptable level of downgrade activity for these CDOs, often soon after issuance. There is evidence that in recent years, assets may have been included in CDO portfolios on the basis of their high spread relative to their peer group. In many instances the asset’s high spread was indicative of an increased risk of downgrade. Concentrations of such adversely selected assets frequently led to the early and, at times, material downgrades of the CDO’s ratings.

The following points reflect the highlights of the updated approach: • The overall CDO framework has been benchmarked against 30 years of global

default statistics to confirm CDOs carrying an investment grade rating are protected against historical peaks in the default cycles.

• The correlation framework has been calibrated to confirm that the basic model output conforms to a fundamental view of corporate portfolio credit risk, based on a minimum level of diversification and performance during periods of peak defaults.

• A correlation framework which captures the risk of industry and sector concentrations, as well as regional and country concentrations.

• Deterministic overlays have been used to stress input assumptions and penalise small portfolios or those with greater obligor concentrations.

• Screening tools are in place to decrease the likelihood of the early downgrade of CDOs due to adverse selection and above‐average underlying portfolio migration.

• Forward‐looking asset recovery rates assumptions are in place to reflect the additional risk currently in the system; these assumptions are further stressed for CDO securities rated in the ‘A’, ‘AA’ and ‘AAA’ categories.

Analysts Matthias Neugebauer +44 20 7417 4355 [email protected]

Jeremy Carter +44 20 7862 4122 [email protected]

Ken Gill +44 20 7417 6272 [email protected]

Contacts New York John Olert +1 212 908 0663 [email protected]

Roger Merritt +1 212 908 0636 [email protected]

London Philip McDuell +44 20 7417 3485 [email protected]

Hong Kong Rachel Hardee +852 2263 9918 [email protected]

Related Research

This report replaces the Proposed Rating Methodology for Corporate CDOs, published 4 February 2008.

The criteria described in this report can be applied through use of the Fitch Portfolio Credit Model (Fitch PCM). In order to use input data consistent with the criteria, the model can be used in conjunction with the Reference Entity Feed (REF). Both the Fitch PCM and the REF are freely available on the Fitch Ratings website

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Global Rating Criteria for Corporate CDOs April 2008 2

• Corporate default probability inputs now reflect the most up‐to‐date composite of empirically‐based and unadjusted observations.

• CDO target default rates have been applied which are equal to, or lower than, the relevant corporate input figures, and which build in additional conservatism for ‘AAA’ and ‘AA’ rated securities.

• An updated framework has been included for the adjustment of portfolio default and loss rates for rated asset managers, reflecting increased maturity of the market.

The methodology described in this criteria paper forms the cornerstone of the CDO rating methodology. However, Fitch recognises that the CDO market, and therefore its risk drivers, evolves over time, sometimes rapidly. Moreover, certain portfolios may contain risk characteristics not contemplated in the framework. Therefore, Fitch fully expects that this methodology will be supplemented by appropriate analytical judgment and deterministic overlays, where unique risks are identified and are deemed to fall outside the scope of this basic framework.

Overview of the Portfolio Credit Model Process

Source: Fitch

Default Probability

Rating

Term

Recovery Rate

Asset Type

Industry/Sector

Country

Asset Correlation

Asset Par Value

Monte Carlo Simulation

Reference Entity Feeder Assumptions Portfolio Credit

Model

Inputs Updated Default Probabilities The first stage in updating the approach to rating corporate CDOs was to review the primary default probability inputs. Fitch uses ‘rating’ and ‘term’ as the primary determinants of an asset’s default probability. There is a rich history of data related to the default experience of a wide spectrum of corporate entities, rated over the past three decades (from 1977 to 2007). Importantly, Fitch utilises the most up‐to‐date corporate default rates made available by all three major rating agencies. This data set is thought to be the most robust and objective, as it reflects the broadest set of default statistics available, and minimises the risk of any variances in ratings approach or industry coverage.

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Importantly, the period examined was marked by the emergence of the modern debt markets, including the growth of a true high‐yield debt class. The period also includes a number of moderate and severe economic downturns, with accompanying surges in corporate bankruptcies and defaults across a range of industries.

The long‐term default statistics reveal average default rates considerably higher than those observed in the more recent 2003‐07 period, largely characterised by ready availability of credit. The data also clearly shows that the average rates can be somewhat misleading, as they are heavily influenced by cyclical periods of peak default rates, with such periods coinciding with periods of economic stress. Recent developments in the credit markets suggest that corporate default rates are set to rise from recent history, as the effects of more stressful economic conditions compound the continuation of an unfavourable refinancing environment. Fitch’s focus on long‐term data for default probability inputs, and the cyclicality of this data, avoids over‐reliance on the highly favourable statistics of recent years.

Over time, the market has evolved to use so called ‘idealized’ default probabilities. Fitch’s methodology is grounded in the belief that any adjustment to the input default statistics be kept to an absolute minimum. There may be legitimate reasons to make some minor adjustments to the default input parameters. For example, some obvious anomalies that lead to counterintuitive results may need to be removed, or some minimal smoothing may be required to adjust for minor kinks in the term structure. However, to preserve the integrity of the model output, these adjustments should be minor in frequency as well as magnitude. Fitch’s current approach uses long‐term, composite default statistics on an unadjusted basis, and applies correlation as a calibration parameter to confirm consistency between model output and its fundamental view of portfolio credit risk (as measured by observed peak defaults statistics as discussed below).

CDO Target Default Probabilities The modelling process requires the default probability and correlation inputs to generate a portfolio default distribution. The remaining parameter required to determine the default expectation for a given rating stress is the CDO target default probability. This is sometimes referred to in the market as a ‘confidence interval’. It is also sometimes referred to as the ‘output curve’, as it in effect represents a threshold level. Simulated defaults that occur beyond the threshold level must be protected against. This is an extremely important input because it determines the proportion of tail events that are captured.

A target default probability that is higher than the input default probability may underestimate protection against tail events. A target default probability that is equal to the input default probability is the most theoretically unassailable. In

‐3

0

3

6

9

12

15

18

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007

Default rate GDP growth

U.S. High Yield Par Default Rates & GDP Growth (%)

Source: Fitch

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theory, if the input curve and output curve are the same, all else equal, the CDO ratings should perform similarly to the ratings of the underlying corporate. A CDO target default probability that is lower than the input default probability affords additional protection against tail events, as well as compensates for certain practical idiosyncrasies of the modelling process.

Fitch’s approach applies target default probabilities equal to the input default probabilities for all rating categories below the ‘AA’ category. The approach applies target default probabilities lower than the input default probabilities for the rating categories ‘AAA’ and ‘AA’. As stated in the prior section, Fitch looks to long‐term empirical statistics for its input default probabilities. The sample size of the data cohorts for the ‘AAA’ and ‘AA’ categories contained fewer observations relative to the other observed cohorts. Fitch believes it is therefore prudent to reduce the target default probability, or raise the threshold, when determining the level of support necessary to achieve these highest of ratings. The effect of the adjustment is to increase the credit enhancement in order for securities to achieve ‘AAA’ and ‘AA’ ratings.

Benchmarking to Peak Default Rates As stated earlier, Fitch views it as important that the model output can be tied to a fundamental view of credit risk. A primary credit view held is that CDO notes carrying an investment grade rating should perform robustly, even in periods of peak corporate default rates. Observed corporate default statistics are based on thousands of observations. While some cohorts may have more observations than others, there is a significant level of diversity implied in the observations. So before addressing additional risk factors such as concentration risk and adverse selection, Fitch first looked to calibrate its CDO methodology to provide sufficient coverage for hypothetical, diverse portfolios.

The first set of calibration portfolios are fully diverse portfolios, with 300 equally weighed assets equally distributed among 29 industries. One hypothetical diverse portfolio was created representing each credit quality, from the single‐‘B’ rating category to the ‘AAA’ rating category. Portfolios were also created representing various terms, from one‐ year to ten‐years. With this as a starting point, the correlation parameters were then set such that the model would result in output with

0

2

4

6

8

10

1981 1984 1987 1990 1993 1996

10‐year default rate Average

10‐Year Rolling Cohort ‘BBB’ Default Rate

(%)

Source: Fitch

0.0

0.5

1.0

1.5

2.0

2.5

0.0

1.0

1.9

2.9

3.8

4.8

5.7

6.7

7.6

8.6

9.5

10.5

11

.5

12.4

13

.4

14.3

15

.3

16.2

17

.2

18.1

19

.1

20.0

21

.0

21.9

22

.9

23.9

24

.8

25.8

26

.7

27.7

28

.6

29.6

30

.5

31.5

32

.4

33.4

34

.3

35.3

36

.3

37.2

(%)

'AAA' Asset and Liability Default Probabilities

Source: Hypothetical Portfolio

CDO PD Asset PD (%)

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the desired relationship to the observed default statistics for all rating levels and all terms.

Fitch believes that CDO notes rated in the ‘A’ category and above should perform well in periods of peak default rates, with little vulnerability to default consistent with the long‐term, observed default performance of ‘A’ rated obligations. So the target was for the model output to yield a portfolio default rate above the relevant historical peak default rate for each portfolio, based on its credit quality and term. In other words, the model was designed so that the protection afforded CDO notes rated in the ‘A’ category and above was at or above historical peak default rates. Fitch set correlation such that the model output rating default rate for the ‘A’ rating level (‘A’ RDR) compared to the peak default rate was greater than one (> 1.0x.).

Similarly, Fitch believes that CDO notes rated in the ‘BBB’ category should also perform robustly in times of peak default rates, although they may show some vulnerability to default should the worst of the historical peak rates be repeated, or exceeded. So the correlation levels were also set such that the ratio of the ‘BBB’ RDR to the relevant peak default rate was as close to one as possible (1.0x). This concept of backtesting and benchmarking the model output against ‘multiples’ of historical default data is an important concept in understanding the rationale for how correlation was set, and has the effect of embedding some explicit and easy to understand deterministic overlays onto the simulation‐derived results.

Portfolio Default Rate and Model Output Coverage BBB BB B

(%) Diverse 30% Industry Concentrated

1991 Industry Default Mix Diverse

30% Industry Concentrated

1991 Industry Default Mix Diverse

30% Industry Concentrated

1991 Industry Default Mix

RDR RDR RDR RDR RDR RDR RDR RDR RDR AAA 15.3 20.7 17.7 39.0 44.0 42.0 58.0 62.0 60.7 AA 12.7 16.0 14.3 34.3 38.7 37.0 53.3 56.7 55.7 A 10.3 12.0 11.3 30.0 33.0 31.7 48.0 51.0 50.0 BBB 8.7 9.7 9.3 27.0 29.0 28.0 44.3 47.0 46.0 BB 6.3 6.7 6.7 22.3 23.0 22.7 38.7 40.0 39.3 B 5.3 5.3 5.3 19.3 19.7 19.7 35.3 35.7 35.7

Source: Fitch

Coverage of Mean Default Rate BBB BB B

(%) 4.50 4.50 4.50 17.40 17.40 17.40 32.20 32.20 32.20 AAA 3.41 4.60 3.93 2.24 2.53 2.41 1.80 1.93 1.88 AA 2.82 3.56 3.19 1.97 2.22 2.13 1.66 1.76 1.73 A 2.30 2.67 2.52 1.72 1.90 1.82 1.49 1.58 1.55 BBB 1.93 2.15 2.08 1.55 1.67 1.61 1.38 1.46 1.43 BB 1.41 1.48 1.48 1.28 1.32 1.30 1.20 1.24 1.22 B 1.19 1.19 1.19 1.11 1.13 1.13 1.10 1.11 1.11

Source: Fitch

Coverage of Peak Default Rate BBB BB B

(%) 9.30 9.30 9.30 29.70 29.70 29.70 46.40 46.40 46.40 AAA 1.65 2.22 1.90 1.31 1.48 1.41 1.25 1.34 1.31 AA 1.37 1.72 1.54 1.15 .1.30 1.25 1.15 1.22 1.20 A 1.11 1.29 1.22 1.01 1.11 1.07 1.03 1.10 1.08 BBB 0.94 1.04 1.00 0.91 0.98 0.94 0.95 1.01 0.99 BB 0.68 0.72 0.72 0.75 0.77 0.76 0.83 0.86 0.85 B 0.57 0.57 0.57 0.65 0.66 0.66 0.76 0.77 0.77

Source: Fitch

Asset correlation assumptions are set to have the desired effect on the base calibration described in this section, as well as industry and geographic concentrations. The full matrix of correlation assumptions is described in the section on concentrations. For the purpose of this section, the relevant correlation figures are a base correlation of 2%, a sector add‐on of a further 2%, and an industry add‐on of a further 20%.

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www.fitchratings.com 30 April 2008

Business services Building & materials Chemicals Consumer products Computers & electronics Automobiles Aerospace & defense Banking & finance Cable Broadcasting/media/cable Food, beverage & tobacco Farming & agricultural services Energy Environmental services Gaming, leisure & entertainment Supermarkets & drugstores Retail (general) Real estate Telecommunications Utilities Transportation Textiles & furniture Industrial/manufacturing Pharmaceuticals Health care & pharmaceuticals Lodging & restaurants Paper & forest products Packaging & containers Metals & mining

Industry Distribution for 1990 Historical Peak

Source: Fitch



Source: Fitch



Source: Fitch

It must be noted that the modelling process is such that a single set of correlation assumptions will have a variable impact on the output depending on the term and the portfolio credit quality. For example, one set of correlation assumptions may produce the desired output relative to historical figures for 10‐year portfolios, but may indicate coverage over the target multiple for portfolios with shorter terms. Similarly, the same set of correlation assumptions may produce output at or near the target for portfolios of ‘BBB’ credit quality, but output greater than the target for ‘A’ rated portfolios.

It can be argued that the historical default statistics are generated from cohorts that contain some level of industry concentration. If that is the case, then it would follow that using fully diverse portfolios to calibrate to peak default rates would produce output above the target multiples once any industry concentration

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penalties were added. To test this hypothesis, Fitch examined three periods of peak default rates to determine the level of industry concentration inherent in the observations. The peak periods of 1990, 1991, and 2001 were examined. The finding was that there were, in fact, some industry concentrations present in each of these three peak default periods. However, the degree of concentration varied. While the 2001 period showed the greatest level of concentration of defaults by industry, the 1991 period exhibited much lower concentrations of default by industry as the overall default rate was driven more by the recessionary environment. In order to test the impact that concentrations in the peak would have on the model output, Fitch created another set of calibration portfolios, with industry concentrations consistent with the 1991 peak default experience. The final correlation framework took into consideration the industry concentration observed in the early 1991 default peak.

Concentration Risk: Industries, Obligors, Geographic Over time, some CDOs have become less diversified, instead pursuing more concentrated strategies or investing in assets from higher‐yielding industries, issuers, or countries. This is particularly true in recent years as many managers and investors were pursuing strategies to maximize return in a tight credit spread environment.

The prior section discussed tying model output to market‐wide default statistics. In order to rely on the model output to accurately reflect the portfolio credit risk, there must be some consistency between the CDO portfolio, and the portfolio of assets from which the historical inputs derive. When a CDO portfolio becomes more concentrated, there is a greater risk that such portfolio will exhibit default characteristics the deviate from the historical data set against which the model output has been compared.

The CDO rating framework seeks to identify and make adjustments for CDO portfolio concentrations that may impact performance. It does this through a combination of base assumptions and an overlay of additional stresses that act to increase the credit enhancement if a portfolio were more concentrated.

Industry Concentrations The correlation parameter plays an important role in determining the shape of the default distribution. It determines the extent to which the default behaviour of one asset may influence that of another in the simulation. As stated, correlation levels are set to achieve the desired outcome for diversified portfolios.

Correlation is notoriously difficult to measure on any empirical basis. However, some basic tenets can be observed anecdotally. First, it is widely understood that assets within a single industry tend to behave similarly in terms of default and rating migration. This is, of course, intuitively sensible since companies within a particular industry are subject to similar economic factors, as well as supply and demand features. It has also been observed that the financing characteristics of a particular industry can influence the likelihood of asset co‐behaviour. In periods of credit expansion, particular industries have seen dramatic increases in the level of financing provided by the capital markets. The general increase in leverage on an industry basis makes companies in the industry more vulnerable to default during periods of economic contraction. An example of this can be seen in the experience of the telecommunications industry in the period of 2001‐02.

Applying one correlation assumption for assets in the same industry (‘intra‐ industry’) and another for those in different industries (‘inter‐industry’) is the simplest way to capture the industry effect in default modelling. However, Fitch concluded that simply distinguishing between inter‐ and intra‐industry correlation assumptions may not adequately reflect the correlation relationship between companies that may be in different, but related, industries. In order to better

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capture the correlation impact of related industries, the CDO modelling framework groups industries into five sectors, each containing one to eight industries. Each asset is assumed to be correlated to another by a base 2% level, then by an additional level of 2% if they are in the same sector. If they are also in the same industry, the correlation is assumed to be even higher, set at 20%.

With additional levels in the correlation structure, correlation can be varied at the base level, the sector level or the industry level. This framework better allows for the capturing of evolving risk over time than a standard two‐dimensional framework would allow. For example, if the characteristics of an industry change over time, it might be justifiable to break out an industry. But the new industry may still be largely influenced by the same factors that affect its industry of origin, which would limit the diversification benefit. If that were the case, the sector‐level add‐ on could be raised to offset some of the benefit of separating the industries.

With the base, sector, and industry correlation framework set, the assumptions were tested to confirm that risks associated with industry concentration were captured in the model. Once again, hypothetical portfolios were created and the model output was examined. In this instance, portfolios were created with an industry concentration of 30%. This level of concentration was chosen as it is a fairly typical level of industry concentration observed in synthetic corporate CDOs referencing primarily investment‐grade assets. The output for the concentrated portfolios was compared with that of the diversified portfolios to observe the level of additional default protection the concentration implies. For example, for a 10‐ year portfolio of ‘BBB’ assets, the model output for the diversified portfolio indicated that protection against defaults totalling 15.3% of the portfolio (46 assets) would be necessary if a ‘AAA’ rating were to be achieved on the CDO. For the industry concentrated portfolio, the default protection would increase to [20.7%], or (62 assets) more than for the diversified portfolio. (See table on Portfolio Default Rate and Coverage tables on Page 5).

Fitch believes that CDO performance and analysis relies on some minimum level of diversification as a core principle. And it has been established that correlation is difficult to measure on any empirical basis. So while the correlation framework has been shown to be effective at capturing the risk sector and industry concentrations, excessive industry concentrations (over 30%) will be subject to additional scrutiny and may be subject to additional stresses beyond those reflected in the model. These additional stresses seek to mitigate the risk of over‐reliance on model assumptions, and test the ability of a rating to withstand some basic ‘what‐if’ scenarios. These stresses will depend upon the specific portfolio characteristics, but are likely to include industry‐wide default and migration scenarios, and may be supplemented with qualitative limits of the levels of ratings achievable. Wherever such stresses are applied, they will be communicated in the rationale for the individual rating.

Obligor Concentrations Portfolios with a small number of assets or those where individual assets balances represent a disproportionate exposure within the portfolio, carry the risk that portfolio performance may be adversely impacted by a few assets that may under‐ perform relative to the statistics suggested by their ratings. Fitch’s methodology applies additional stresses to certain inputs to mitigate the risk to CDO portfolio performance posed by outsize assets.

The basic model framework is already sensitive to obligor concentrations in that as portfolios contain fewer assets, all else equal, the portfolio default rate increases. This is because the variability of defaults inherently increases with a reducing number of assets, in the same way that the variability of the return on a portfolio increases with fewer assets.

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Above and beyond this, the methodology includes additional scenario stresses such that the model produces the default of a minimum number of assets given a portfolio credit quality and target CDO rating. This approach creates what can be thought of as a floor in the assumed default rate, such that CDO investors are protected in the event that the larger assets default. This is particularly important where the portfolio credit quality is relatively high, and individual assets can represent a large proportion of the support available to a particular class of rated notes. For example, as shown in the table below a AAA CDO rating would be protected against the default of a minimum of the largest 5 BBB exposures and 10 of the largest B exposures.

Minimum Default Coverage CDO Liability rating

BB BBB A AA AAA AAA 1 AA 1 2 A 2 3 BBB 1 3 5 BB 2 5 6 7

Asset rating

B 1 5 6 8 10

Source: Fitch

The stress is applied by increasing the pair‐wise correlation of the 5 largest risk contributors by 50%. This addition is applied irrespective any correlation uplifts applied for sector and industry. The largest risk contributors are determined on a pre‐simulation basis, and are based on size of exposure, default probability implied by the rating, and recovery rate. It is important to take into account the default probability and recovery rate when determining the assets to which the stress is applied, as applying the stress to assets with high‐ratings, or high recovery rates relative to other assets in the portfolio would have a negligible effect on the output.

The second element of the stress is to reduce by 25% the assumed recovery rate on the same 5 assets. This stress is applied within the model framework, and has an impact on the portfolio loss distribution. This stress to recovery rates acts to reduce the risk posed by individual assets experiencing recoveries upon default at lower rates than historical average rates. Individual assets experiencing low recoveries will cause them to erode a disproportionate amount of support available to rated note holders. The stress to recovery rates is applied only where standard recovery rates are applied, and not where asset‐specific recovery rates have been assigned by Fitch.

Geographic Concentrations Fitch’s framework for geographic diversification is designed to be straightforward and has the effect of penalizing for geographic concentrations, while at the same time providing appropriate, limited benefit for geographic diversification.

Fitch recognizes that diversity among different regions and countries can be of benefit to CDO portfolios. However, quantifying credit for geographical diversity is problematic for several reasons. The main issue is that the richest data on defaults is available for the US, which by definition is a country‐concentrated portfolio. That said, as the world’s largest economy, it can be argued that there is a significant level of regional diversification within the country.

The base and industry calibration was done against primarily US data. The result were the following correlation assumptions for US portfolios: Base = 2%; Sector + 2%; Industry + 20%. In order to vary correlation assumptions to reflect geographic diversity or concentration, Fitch began with the following guiding principles:

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Geographic Correlation Framework Industry Add‐on

(%) Base Level Sector Add‐on High Medium Low Same country 4 (2 if US) +2 +20 +20 +20 Same region, different countries 2 +2 +20 +15 +10 Different regions 1 +2 +20 +15 +10

Source: Fitch

Portfolio Default Rates for European and US 'BBB' 10 Year Portfolios Calibration portfolio

(%) European US Master RDR RDR AAA 16.7 17.7 AA 13.7 14.3 A 11.0 11.3 BBB 9.0 9.3 BB 6.7 6.7 B 5.3 5.3 Mean 4.5 4.5

Source: Fitch

Country Distribution of the European Portfolio Country Country distribution (%) Germany 20.00 France 20.00 Italy 20.00 United Kingdom 20.00 Sweden 20.00

Source: Fitch

• Advanced economy countries smaller than the US would not benefit from the same level of regional diversification, therefore the base correlation between companies in countries other than the US should be higher than the 2% US assumption.

• The global economy results in relatively limited benefit within a region. For example, a portfolio diversified within western Europe should not yield materially different portfolio default rates than a US portfolio.

• Different industries benefit from geographic diversification to varying degrees.

With those guiding principles, the above correlation framework is applied, with a base level of correlation for companies located in different regions, with add‐ons for commonality of country, sector, and industry.

Risk of Adverse Selection & Negative Rating Migration The portfolio credit model output provides indication of support corresponding to each rating category. If managers or arrangers choose to issue transactions with little or no cushion relative to the relevant model output, there may be an increased risk of negative migration to the rated notes. The risk is especially acute if underlying portfolio assets are subject to downgrade soon after the rating of a CDO.

To address the risk of early CDO downgrade due to excessive underlying portfolio migration, Fitch incorporates the use RatingsWatch and Outlooks, in conjunction

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with the Fitch CDS Implied Ratings (‘Fitch CDS‐IRs’) into the methodology. 1 The Fitch CDS‐IR will be used to supplement the asset rating information in determining the default probability input in certain instances. For all assets subject to negative rating watch, the lower of the Fitch CDS‐IR or the credit rating minus two notches will be applied. For assets subject to negative outlook, the lower of the Fitch CDS‐ IR or the credit rating minus one notch will be applied.

If no Fitch CDS‐IR is available, and the asset is subject to a negative rating watch indication, the credit rating will be reduced by an assumed two notches for the purpose of determining the appropriate input default probability. In the case of assets subject to a negative outlook, and where no Fitch CDS‐IR is available, the reduction will be assumed to be a single notch.

The approach calls for the use of a Fitch rating where available. Where a particular asset is not rated by Fitch, the lower of the rating assigned by either S&P or Moody’s will be applied. Should the rating be subject to a negative watch status, it will be reduced by two notches before the comparison is made, and if it is subject to negative outlook, it will be reduced by one notch before the comparison is made. The approach still calls for use of the Fitch CDS‐IR for assets subject to negative watch or negative outlook status. So if the rating applied was subject to a negative watch or a negative outlook (before adjustment), it will be compared to the Fitch CDS‐IR (where available), and the lower of the two applied. A schematic of the process is shown in Appendix 3

Fitch believes that Fitch CDS‐IR can act as effective screening tools to generate cushion to protect investors in rated CDO notes against downgrades caused by adverse portfolio selection. Both the negative rating watch and outlook status have proven to be good indicators of rating momentum. But the magnitude of ultimate downgrade has varied considerably. For assets subject to negative rating watch or outlook, the Fitch CDS‐IRs are being used to supplement a ‘rule‐based’ notching to discourage the systematic inclusion of assets that are at risk of being subject to an above‐average downgrade.

In addition to using the Fitch CDS‐IR in the systematic fashion described, committees will also be provided with a comparison of the Fitch CDS‐IR and the credit rating for all assets, regardless of watch or outlook status. If there is indication that the portfolio has been subject to significant adverse selection, additional adjustments may apply. Any additional adjustments will be described in the rating rationale.

1 Fitch CDS Implied Ratings are a subscription product provided by Fitch Solutions. However, the data will be made available to users of Fitch Ratings’ Portfolio Credit Model through the Reference Entity Feed (REF). The Fitch CDS IR will be disclosed in those instances where the criteria calls for its use. See Appendix 4 for a fuller description of its use.

Back‐Tested Effectiveness of Adverse Selection Criteria

Original rating Assets downgraded 1

notch or more (%) Assets downgraded 3 notches or more (%)

Implied downgrade under proposed methodology

(rating notches) CDO1 AAA 34 10 1 CDO2 AAA 39 12 0 CDO3 AAA 37 8 0 CDO4 AAA 26 5 0 CDO5 AAA 30 6 0 CDO6 AA 37 12 0 CDO7 AA 23 4 0 CDO8 AA 24 7 0

Source: Fitch

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Recovery Rates Many corporate balance sheets, particularly for less creditworthy companies, have become increasingly leveraged with loan‐heavy capital structures. As a result, historically‐based recovery assumptions may not appropriately reflect the risk of lower recoveries in the next default cycle. Fitch has updated its standard assumptions to reflect the risk of lower recoveries. The framework recognizes the pro‐cyclical nature of defaults and recoveries, with lower recoveries occurring during periods of higher defaults. As such, the assumed asset recovery rate will be reduced when assigning CDO ratings in the ‘AAA’, ‘AA’, and ‘A’ categories.

Corporate Recovery Rate Assumptions Seniority (%) Group A Group B Group C Group D Senior secured 70 50 40 30 Mezz, second Lien, Jr secured 25* 5 5 5 Senior unsecured 40 35 35 25 Subordinate 25 15 10 10

Source: Fitch

*Fitch studies of European mezzanine debt indicate that recovery prospects may be lower than 25%. The standard recovery rate assumption may therefore be reduced for mezzanine debt from European countries in Group A.

In some instances, Fitch is requested to provide asset‐specific recovery rates in the form of Recovery Ratings, which reflect a fundamentally‐derived, forward‐looking view of a company’s unique recovery prospects. In such instances, the asset‐ specific rate will be applied in preference to the standard assumptions, although the same recognition of pro‐cyclicality will be applied.

Within a jurisdiction, debt type is the primary determinant of recovery prospects. Fitch distinguishes among five different debt types. They are: Senior Secured; Senior Unsecured; Second Lien/Junior Secured; European Mezzanine Debt; Subordinated Debt.

Another important determinant of recovery prospects is jurisdiction. Fitch examined creditor friendliness and insolvency regimes across countries to determine recovery rate expectations for non‐US corporate obligors. For more information on this research, see the report entitled “Country‐Specific Treatment of Recovery Ratings – Revised”, dated 21 August 2006. This research determined the grouping of countries based on comparable levels of expected recoveries. Obligors from Group A countries are expected to exhibit recovery prospects consistent with those for US obligors, while Group B, C and D obligors are expected to exhibit decreasing levels of recovery. A full list of Fitch’s base recovery assumptions, and a description of the tiering applied depending on CDO rating stress can be found in Appendix 1.

Adjustments for Rated Managers Fitch introduced CDO Asset Manager (CAM) ratings in 2002. The number of managers holding a Fitch CAM rating has greatly increased since the time of introduction. The data available to assess the impact of a manager has also increased in recent years. Fitch believes that the growth of the corporate CDO market, the amount of data available to managers and the general maturity of the market may have limited a manager’s ability to “out‐perform” the market. At the same time, the agency recognises that the quality of a manager will continue to be an important CDO performance driver. In its revised methodology, Fitch retains credit for those managers with the highest CAM ratings. There is no credit given to managers rated in the ‘CAM 3’ category. Transactions with managers carrying a ‘CAM 4’ rating will be penalised, particularly at the higher rating stresses.

The methodology calls for relative adjustments to the model‐derived output default rate on the basis of the manager’s CAM rating and the rating stress (target CDO

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rating). The approach recognises that the most highly rated managers may be better able to execute investment strategies consistent with the interests of investors, although they will have more difficulty providing relative benefit in times of increased stress. The more lowly rated managers may negatively impact CDO performance relative to model output, and the negative impact may be greater in times of increased stress. The following table illustrates the adjustments.

Default and Loss Rate Haircuts for CAM Managers (%) CAM 1 CAM 2 CAM 3 CAM 4 CAM 5 AAA ‐2.50 0.00 0.00 17.00 n.a. a

AA ‐4.0 0.00 0.00 12.50 n.a. A ‐5.00 0.00 0.00 10.00 n.a. BBB ‐6.25 ‐4.00 0.00 7.50 n.a. BB ‐8.50 ‐6.00 0.00 5.00 n.a.

Note: negative numbers indicate Fitch would reduce the rating default or rating loss rate for the CDO. For example, Fitch would reduce the ‘AAA’ model‐implied portfolio loss rate by 2.5% if the portfolio was managed by a ‘CAM 1’ rated manager a Fitch would not rate a CDO managed by a ‘CAM 5’ manager Source: Fitch

Managed Transactions Transactions may be static or managed. If managed, Fitch’s analysis recognises that the underlying portfolio may change over time as a result of substitutions or trading and that, depending on the structure of the transaction, available credit enhancement may be affected by realised gains or losses that result from trades, as well as from defaults and amortisation. The considerations presented in this section apply equally to substitution agents, portfolio advisors, liquidation agents, and other parties that perform “manager” functions.

In its forward‐looking analysis, Fitch will make assumptions that the portfolio may be managed towards, though not necessarily at, the limits defined by the transaction structure and documentation. Fitch’s analysis will include such “worst‐ case” portfolios that introduce a significant degree of default, recovery and correlation stress at different parts of the CDO’s capital structure. In making its analytical assumptions about the worst‐case portfolio, Fitch will consider the transaction covenants and portfolio guidelines in its analysis.

Certain managed CDOs have covenants that require the manager to maintain a defined base level of portfolio credit quality. For example, the manager may covenant to a maximum Fitch Weighted Average Rating Factor (WARF) to limit the average portfolio credit risk profile. Equally, the manager may covenant to maintain other parameters, such as minimum weighted average recovery rate, weighted average spread, region or single country exposure, industry and obligor concentrations, and so forth, within defined limits.

The transaction documentation may contain further portfolio guidelines, such as eligibility criteria that limit, eg the types of assets that can be purchased by the manager. For example, a CLO may specify that only leveraged loans from certain jurisdictions and certain other asset classes (within limits) are eligible to be included in the portfolio.

Some managers may choose to structure their portfolio management guidelines to include an expected loss test. An expected loss test is often implemented to specify that any substitutions must pass a predetermined test level in a base model chosen by the manager. The manager undertakes that any proposed revisions to the portfolio will be run in the base model, with the result compared against the limits specified in the transaction documentation. Such self‐imposed limits and the application of the test will be taken into account when determining the worst‐case portfolio that the manager might migrate to.

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When analysing transactions that include portfolio covenants and eligibility criteria in their documentation, Fitch will consider all covenants and all aspects of the management guidelines, including asset eligibility criteria and the manager’s ability to:

• substitute reference entities freely or subject to defined covenants; • substitute impaired credits freely or not; • withdraw or monetise “surplus” credit enhancement; and • obtain quotes or trade with dealers other than the arranging bank.

In its analysis of the portfolio, Fitch assumes worst case portfolios with the aim of testing the robustness of the transaction structure against its covenants and portfolio guidelines. For example, where a manager covenants to maintain the portfolio inside some combination of WARF, minimum recoveries and weighted average spread, Fitch will stress the portfolio against those limits and simultaneously stress other portfolio guidelines – eg. obligor, industry and country concentrations ‐ to a level that would introduce a significant conservative degree of default, recovery and correlation stress at each part of the CDO’s capital structure.

Special Applications Short Positions The Portfolio Credit Model will not accept the input of short positions. The default probability, recovery rate and correlation assumptions have been calibrated to measure the risk of default and loss for a long position. Applying the same assumptions to a short position may overestimate the credit gained by the inclusion of a short position. The risk/benefit of short‐positions will be analysed on a case‐by‐case base, but are likely to include different assumptions for probability of default, recovery and correlation.

CDOs of CDOs The corporate CDO criteria naturally extends to corporate synthetic CDOs that reference other corporate synthetic CDOs. The model allows the inclusion of up to 30 inner CDOs, and the same default, recovery and correlation assumptions are applied to assets whether at the inner or master level. The model applies a 'look‐through' basis to fully reflect the correlation of the underlying corporate assets, and to confirm that if an asset is assumed to default in a particular scenario, it defaults in all portfolios where it is referenced. Stressed inputs (described in the section entitled 'Obligor Concentrations') are applied to the 5 largest risk contributors on an aggregate basis. This functionality is included for the convenience of users of the model; however, rating committees may consider additional scenarios to account for the unique risks posed by CDO‐squareds.

Emerging Market Assets The standard corporate criteria will not to apply to CDOs with exposure to emerging market assets.

In its worst case analysis, Fitch will consider the expected ability of the manager to create a portfolio at the limit of its covenants. The absolute limit of some covenants may not be achievable in reality. An example would be the absence of a covenanted country concentration limit in a European CLO, where historically no portfolio had more than 35% exposure per country. In such cases, Fitch will create a stressed portfolio that may have less than 100% single country concentration, despite the lack of a country limit. The stressed portfolio will be agreed in Fitch’s committee process.

When monitoring managed transactions, Fitch will apply its standard surveillance approach. That is, it will apply the stated criteria to the actual portfolio, regardless of any portfolio covenants. Standard adjustments will be applied in

Structured Finance


determining the default probability of assets subject to a Rating Watch status. Fitch CDS Implied Ratings will be used as an informational tool to identify any systematic adverse selection in the management process, and further adjustments may be made.

Rating Surveillance Fitch employs a monitoring team dedicated to maintaining timely and accurate ratings, and producing performance‐related research.

Once a rating has been assigned, the monitoring team initiates active surveillance by reviewing the composition and performance of a portfolio as well as the transaction structure on a regular basis. This allows Fitch to provide accurate and timely information and insightful commentary to the market. This service also helps promote efficiency in the CDO secondary market. Without timely surveillance, potential risk may not be readily apparent to all market participants.

Fitch typically receives and reviews remittance reports on a monthly basis. Automated credit alert systems allow Fitch analysts to quickly detect changes in underlying portfolio performance and adjust review committee schedules accordingly. A number of these systems are available to the public on the CDO S.M.A.R.T. (Surveillance Metrics Analytics Research Tools) section of www.fitchreseach.com. The actual frequency of reviews depends on the nature of the transaction. Outstanding ratings are formally reviewed by a credit committee at least annually. However, transactions may be taken to credit committee more frequently, as warranted by performance, to maintain timely ratings on all Fitch‐ rated CDOs. Performance reviews involve a detailed analysis of the portfolio, the transaction’s structure and ultimately, the rated liabilities of the transaction. When possible, the portfolio manager is also contacted to discuss distressed or special assets as well as their general strategy.

In the monitoring process, a strong emphasis is placed on actual changes in performance relative to the previous rating action, as well as the projections made in the new issue analysis. The methodology is generally consistent with the new issue approach. The performance analysis is based on the actual current portfolio, regardless of any covenants with respect to portfolio composition. There is no formulaic application of the Fitch CDS‐IR as there is in the new issue analysis , because the risk of adverse selection is reduced where portfolios have already been selected. The monitoring approach calls for a standard adjustment of minus one rating notch for assets subject to Rating Watch Negative, and plus one rating notch for assets subject to Rating Watch Positive status and a minus one notch adjustment for Negative Outlook status in those instances where more than 5% of the portfolio is subject to such status. Rating committees will be provided with information comparing the Fitch CDS‐IRs to the credit ratings, as well as the percentage of the portfolio subject to Negative Outlook, and may make adjustments to standard inputs if it is determined that there is a high likelihood for negative portfolio migration in the near term. Any adjustments to standard assumptions will be communicated in the relevant individual rating action commentary.

While the standard criteria and assumptions set out the guidelines for assessing portfolio risk, the ultimate rating decision rests with the credit committee. Committees may make adjustments to standard assumptions, or call for bespoke analysis. In addition, general economic outlooks for certain sectors or industries may be taken into account. Fitch recognises the need to balance independence and prudent credit judgement with consistency. The rationale for any public rating action, including any deviation from standard criteria or assumptions, will be clearly communicated in a public rating action commentary.

Structured Finance


In addition to standard rating actions (affirmations, downgrades, and withdrawals), Rating Watch status is employed to signal changes in portfolio performance where Fitch sees a specific positive or negative event and requires additional information to ensure an accurate rating. The most common application of Rating Watch for synthetic CDOs occurs when a reference entity defaults and final valuation is pending. In these cases, Fitch will estimate the recovery to allow a credit committee to determine if a downgrade is expected. If the credit event is deemed to make a material impact on the transaction, Fitch will place the affected tranches on Rating Watch until a final recovery notification is received. Once the final recovery is established, the transaction will be removed from Rating Watch status and either affirmed or downgraded accordingly. Rating Watch will also be employed for cash flow CDOs when the portfolio is expected to suffer negative migration with an uncertain outcome. For example, if a significant number of underlying assets are placed on Rating Watch, then the CDO liabilities may also be placed on Rating Watch until the outcome of the underlying assets is resolved.

Fitch is committed to providing subscribers with substantive transaction analysis and commentary as part of its performance‐related products via its performance analytics products, available at www.fitchresearch.com.

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Appendix 1 Portfolio Credit Model Loss Coverage Indications for Standard Index Portfolios as of April 2008.

CDX IG Series 10 5 Year 10 Year

(%) New Issue Surveillance New Issue Surveillance RLR RLR RLR RLR

AAA 9.2 7.0 13.7 11.3 AA 7.9 6.0 11.2 8.9 A 6.5 4.6 8.6 6.7 BBB 5.4 3.6 7.3 5.3 BB 3.9 2.3 5.5 3.6 B 3.1 1.6 4.6 2.9 Mean 2.1 1.1 3.8 2.3

Source: Fitch

CDX HY Series 10 5 Year 10 Year


AAA 35.7 32.3 43.5 40.8 AA 32.2 28.9 39 36.2 A 27.9 24.7 33.7 30.5 BBB 25.2 22.1 30.3 27.2 BB 21.5 18.5 26.5 23.4 B 19.1 16.3 24.1 21.4 Mean 16 13.3 22.1 19.3

Source: Fitch

iTraxx Europe Series 9 5 Year 10 Year


AAA 6.30 5.80 10.00 9.40 AA 5.20 4.70 8.00 7.40 A 4.00 3.70 5.90 5.40 BBB 3.20 2.80 4.70 4.30 BB 2.10 1.70 3.20 3.00 B 1.50 1.10 2.60 2.10 Mean 0.90 0.80 2.10 1.80

Source: Fitch

iTraxx Europe HiVol Series 9 5 Year 10 Year


AAA 17.8 17.4 24.3 22.5 AA 15.2 14.6 19.5 17.5 A 12.1 10 14.2 13.1 BBB 9.2 7.4 11.1 9.5 BB 4.6 4.5 6.7 6.4 B 2.4 2.2 4.5 4.3 Mean 1.8 1.4 3.7 3.1

Source: Fitch

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Appendix 2: Asset and CDO Target Default Rates

Cumulative Asset Default Rates Fitch (%) 1 2 3 4 5 6 7 8 9 10

Asset Asset Asset Asset Asset Asset Asset Asset Asset Asset AAA 0.01 0.01 0.01 0.037 0.082 0.135 0.174 0.190 0.192 0.193 AA+ 0.01 0.01 0.02 0.060 0.118 0.186 0.247 0.293 0.328 0.350 AA 0.01 0.02 0.05 0.097 0.169 0.257 0.350 0.452 0.560 0.638 AA‐ 0.01 0.04 0.09 0.157 0.256 0.372 0.493 0.623 0.760 0.863 A+ 0.03 0.08 0.15 0.254 0.387 0.538 0.695 0.859 1.031 1.168 A 0.07 0.16 0.27 0.411 0.586 0.779 0.978 1.185 1.398 1.580 A‐ 0.10 0.23 0.40 0.611 0.869 1.154 1.442 1.727 2.009 2.246 BBB+ 0.14 0.33 0.59 0.907 1.289 1.711 2.126 2.517 2.887 3.192 BBB 0.19 0.49 0.87 1.348 1.913 2.536 3.134 3.669 4.149 4.536 BBB‐ 0.34 0.97 1.77 2.667 3.611 4.546 5.380 6.082 6.673 7.130 BB+ 0.75 2.07 3.63 5.261 6.869 8.365 9.649 10.698 11.550 12.193 BB 1.16 3.12 5.40 7.753 10.026 12.112 13.896 15.355 16.535 17.434 BB‐ 1.49 4.00 6.90 9.887 12.785 15.465 17.816 19.806 21.469 22.805 B+ 2.89 7.15 10.83 14.106 17.186 20.024 22.513 24.620 26.381 27.795 B 5.36 11.16 15.17 18.490 21.572 24.410 26.899 29.007 30.767 32.182 B‐ 8.35 18.74 24.31 27.663 30.585 33.265 35.616 37.607 39.269 40.605 CCC+ 22.93 33.94 39.83 43.388 46.482 49.320 51.809 53.917 55.677 57.091 CCC 25.228 37.337 43.817 47.727 51.130 54.252 56.990 59.308 61.245 62.800 CCC‐ 30.273 44.805 52.581 57.272 61.356 65.10 68.388 71.170 73.494 75.360 CC 50.500 56.500 62.500 68.500 74.500 80.500 86.500 92.500 98.500 100 C 75.00 81.50 87.50 93.50 100 100 100 100 100 100 D 100 100 100 100 100 100 100 100 100 100

Source: Fitch

Cumulative Asset and CDO Target Default Rates (Compared) Fitch (%) 1 2 3 4 5 6 7 8 9 10

Asset/CDO Asset/CDO Asset/CDO Asset/CDO Asset/CDO Asset/CDO Asset/CDO Asset/CDO Asset/CDO Asset/CDO AAA 0.01/0.01 0.01/0.01 0.01/0.01 0.037/0.015 0.082/0.033 0.135/0.033 0.174/0.033 0.190/0.033 0.192/0.033 0.193/0.033 AA+ 0.01/0.01 0.01/0.01 0.02/0.02 0.060/0.042 0.118/0.082 0.186/0.082 0.247/0.082 0.293/0.082 0.328/0.082 0.350/0.082 AA 0.01/0.01 0.02/0.02 0.05/0.04 0.097/0.078 0.169/0.135 0.257/0.135 0.350/0.140 0.452/0.181 0.560/0.224 0.638/0.255 AA‐ 0.01/0.01 0.04/0.03 0.09/0.08 0.157/0.142 0.256/0.230 0.372/0.335 0.493/0.444 0.623/0.561 0.760/0.684 0.863/0.777 A+ 0.03 0.08 0.15 0.254 0.387 0.538 0.695 0.859 1.031 1.168 A 0.07 0.16 0.27 0.411 0.586 0.779 0.978 1.185 1.398 1.580 A‐ 0.10 0.23 0.40 0.611 0.869 1.154 1.442 1.727 2.009 2.246 BBB+ 0.14 0.33 0.59 0.907 1.289 1.711 2.126 2.517 2.887 3.192 BBB 0.19 0.49 0.87 1.348 1.913 2.536 3.134 3.669 4.149 4.536 BBB‐ 0.34 0.97 1.77 2.667 3.611 4.546 5.380 6.082 6.673 7.130 BB+ 0.75 2.07 3.63 5.261 6.869 8.365 9.649 10.698 11.550 12.193 BB 1.16 3.12 5.40 7.753 10.026 12.112 13.896 15.355 16.535 17.434 BB‐ 1.49 4.00 6.90 9.887 12.785 15.465 17.816 19.806 21.469 22.805 B+ 2.89 7.15 10.83 14.106 17.186 20.024 22.513 24.620 26.381 27.795 B 5.36 11.16 15.17 18.490 21.572 24.410 26.899 29.007 30.767 32.182 B‐ 8.35 18.74 24.31 27.663 30.585 33.265 35.616 37.607 39.269 40.605 CCC+ 22.93 33.94 39.83 43.388 46.482 49.320 51.809 53.917 55.677 57.091 CCC 25.228 37.337 43.817 47.727 51.130 54.252 56.990 59.308 61.245 62.800 CCC‐ 30.273 44.805 52.581 57.272 61.356 65.10 68.388 71.170 73.494 75.360 CC 50.500 56.500 62.500 68.500 74.500 80.500 86.500 92.500 98.500 100 C 75.00 81.50 87.50 93.50 100 100 100 100 100 100 D 100 100 100 100 100 100 100 100 100 100

Notes: Asset and CDO default rates are the same for CDO liabilities below AA‐(minus). The CDO default rates are lower for AA and above ratings to reflect an additional stress on CDO ratings Source: Fitch

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Appendix 3: The Fitch Derived Rating Process

Fitch Derived Rating: New Issue

Source: Fitch

Is the asset rated by Fitch?

Is there a rating by another NRSRO?

Is it on Rating Watch or Outlook?

Is the CDS Implied Rating lower?

Select the lower of the

available ratings after

notching

Use a Fitch Credit

Assessment

Downgrade the Rating

1 Notch

Downgrade the Rating 2 Notches

Use the Credit Rating

Use the Notched Credit Rating

Use the CDS‐IR

Yes No

Yes No No Rating Watch

Negative

Outlook Negative

Yes No

a A one notch downward adjustment for Negative Outlook status will be made in those instances where more than 5% of the portfolio is subject to such status. Source: Fitch

Is the asset rated by Fitch?

Is there a rating by another NRSRO?

Is it on Rating Watch or Outlook?

Select the lower of the

available ratings after

notching

Use a Fitch Credit

Assessment

Upgrade the Rating

1 Notch

Downgrade the Rating

1 Notch

Use the Credit Rating

Yes No

Yes No No Rating Watch

Negative a

Rating Watch

Positive

Fitch Derived Rating: Surveillance

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Appendix 4: Fitch CDS Implied Ratings

The Fitch (CDS) Implied Ratings (IRs) model processes the collective marketplace view of a company’s credit condition based on its recent CDS pricing, region and industry. It then calculates and converts these into implied ratings, which it outputs as a forward‐looking credit assessment expressed in the traditional rating grade format. The model covers over 2,500 reference entities in 84 countries globally.

The Fitch CDS‐IR methodology follows a two‐step approach: 1) smoothing, and 2) nonparametric mapping. The CDS market spreads in their raw state are noisy and individual spreads on any given day may be influenced by technical market factors. This volatility is especially evident in the pre‐2003, Asian or less liquid obligors, but it is an issue to be considered across the entire universe. For more information on the methodology please refer to the “Fitch CDS Implied Ratings (CDS‐IR) Model” report published on 13 June 2007.

Differences between the credit rating and CDS‐IR of an obligor would suggest that either 1) ratings include additional issues such as volatility, or 2) they have different opinions about the future performance of individual companies. It is clear from the table below that agency rating adjustments are frequently anticipated by CDS implied ratings. For Europe at three months, in about 52% of mismatched ratings the implied rating leads agency rating changes and about 14% of agency rating changes lead the implied rating, which indicates that the Fitch CDS‐IR model can add information to a forecast of agency rating change for many cases.

Lead‐Lag Analysis for CDS Implied Ratings and Credit Ratings IR leads agency

rating Agency leads IR Convergence Divergence

(%) Americas &

Oceania Europe Americas &



Oceania Europe 1 month 64.1 63.6 8.4 9.2 7.6 9.2 19.9 18.0 2 months 58.0 55.9 12.2 12.5 12.5 14.1 17.4 17.4 3 months 51.7 52.2 15.5 14.4 15.9 17.2 17.0 16.2 a Convergence is when the credit rating and IR move towards each other and divergence is when the credit rating and IR move in opposite directions Source: Fitch

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Appendix 5: Standard Recovery Rate Assumptions

Recovery Rate Assumptions Seniority (%) AAA AA A BBB BB B Group A Senior secured 56.000 59.500 66.500 70.000 70.000 70.000 Mezzanine, second lien, jr secured

20.000 21.250 23.750 25.000 25.000 25.000

Senior unsecured 32.000 34.000 38.000 40.000 40.000 40.000 Subordinate 20.000 21.250 23.750 25.000 25.000 25.000

Group B Senior secured 40.000 42.500 47.500 50.000 50.000 50.000 Mezzanine, second lien, jr secured

4.000 4.250 4.750 5.000 5.000 5.000


Group C Senior secured 32.000 34.000 38.000 40.000 40.000 40.000 Mezzanine, second lien, jr secured

4.000 4.250 4.7500 5.000 5.000 5.000


Group D Senior secured 24.000 25.500 28.500 30.000 30.000 30.000 Mezzanine, second lien, jr secured

4.000 4.250 4.750 5.000 5.000 5.000


Source: Fitch

Group A Countries Australia, Austria, Bahamas, Bermuda, Canada, Cayman Islands, Denmark, Finland, Germany, Gibraltar, Hong Kong, Iceland, Ireland, Japan*, Jersey, Liechtenstein, Netherlands, New Zealand, Norway, Singapore, Sweden, Switzerland, UK, US.

(*Fitch created distinct recovery rate assumptions for Japanese senior unsecured obligations. These are assumed to recover at 25%).

Group B Countries Belgium, Chile, Cyprus, France, Italy, Luxembourg, Portugal, South Africa, South Korea, Spain, Taiwan.

Group C Countries Bulgaria, Costa Rica, Croatia, Czech Republic, Estonia, Greece, Hungary, Israel, Latvia, Lithuania, Malaysia, Malta, Mauritius, Mexico, Morocco, Panama, Poland, Romania, Slovakia, Slovenia, Thailand, Tunisia, Uruguay.

Group D Countries Albania, Argentina, Asia Others, Barbados, Bosnia and Herzegovina, Brazil, China, Colombia, Dominican Republic, Eastern Europe Others, Ecuador, Egypt, El Salvador, Guatemala, India, Indonesia, Iran, Jamaica, Kazakhstan, Liberia, Macedonia, Marshall Islands, Middle East and North Africa Others, Moldova, Other Central America, Other South America, Other Sub Saharan Africa, Pakistan, Peru, Philippines, Puerto Rico, Qatar, Russia, Saudi Arabia, Serbia and Montenegro, Turkey, Ukraine, Venezuela, Vietnam.

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Appendix 6: Sector and Industry Breakdowns

Sector and Industry Breakdown Correlation band

SECTOR: Telecom Media and Technology Computer & electronics High Telecommunications Medium Broadcasting & media Medium Cable Medium Business services Medium SECTOR: Industrials Aerospace & defence High Automobiles Medium Building & materials Low Chemicals Medium Industrial/manufacturing Medium Metals & mining High Packaging & containers Medium Paper & forest products Medium Real estate Low Transportation & distribution Low SECTOR: Retail leisure and consumer Consumer products Medium Environmental services Medium Farming & agricultural services Medium Food, beverage & tobacco Medium Food & drug retail Low Gaming, leisure & entertainment Medium General retail Low Healthcare Medium Lodging & restaurants Low Pharmaceuticals Medium Textiles & furniture Medium SECTOR: Energy Energy (oil & gas) High Utilities (power) Low SECTOR: Financial institutions Banking & finance High Sovereigns High

Source: Fitch

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Appendix 7: Public CAM Ratings

Corporate CAM Public Ratings Asset manager CAM rating Asset class Aladdin Capital Management LLC CAM2‐ US Leveraged Loan Alcentra Ltd. CAM1‐ European Leveraged Loan Ares Management CAM2+ US Leveraged Loan Avoca Capital CAM2+ European Leveraged Loan Barclays Global Investors CAM2 Investment Grade Corporate Blackrock CAM1‐ Investment Grade Corporate Deerfield Capital Management LLC CAM1‐ US Leveraged Loan Deutsche Asset Management International GmbH CAM1‐ Investment Grade Corporate GoldenTree Asset Management CAM2‐ European Leveraged Loan

CAM2+ US Leveraged Loan Harbourmaster Capital Management CAM1‐ European Leveraged Loan Hartford Investment Management CAM2+ US Leveraged Loan INVESCO Senior Secured Management, Inc CAM2+ US Leveraged Loan KBC FP CAM1‐ Investment Grade Corporate Lyon Capital Management LLC CAM2‐ US Leveraged Loan Mizuho Investment Management UK CAM2 European Leveraged Loan NewStar Financial CAM2 US Leveraged Loan Ofi Asset Management CAM2 Investment Grade Corporate Pacific Investment Management Co. (PIMCO) CAM1‐ Investment Grade Corporate

CAM2+ US Leveraged Loan PIMCO Europe Ltd. CAM2 European Leveraged Loan PPM America (IL) CAM1‐ US Leveraged Loan Prudential M&G CAM1‐ European Leveraged Loan Scottish Widows Investment Partners CAM3 Investment Grade Corporate Societe Generale Asset Management Alternative Investments

CAM2+ Investment Grade Corporate

Solent Capital Group CAM2; outlook negative

Investment Grade Corporate

Source: Fitch

Copyright © 2008 by Fitch, Inc., Fitch Ratings Ltd. and its subsidiaries. One State Street Plaza, NY, NY 10004.Telephone: 1‐800‐753‐4824, (212) 908‐0500. Fax: (212) 480‐4435. Reproduction or retransmission in whole or in part is prohibited except by permission. All rights reserved. All of the information contained herein is based on information obtained from issuers, other obligors, underwriters, and other sources which Fitch believes to be reliable. Fitch does not audit or verify the truth or accuracy of any such information. As a result, the information in this report is provided "as is" without any representation or warranty of any kind. A Fitch rating is an opinion as to the creditworthiness of a security. The rating does not address the risk of loss due to risks other than credit risk, unless such risk is specifically mentioned. Fitch is not engaged in the offer or sale of any security. A report providing a Fitch rating is neither a prospectus nor a substitute for the information assembled, verified and presented to investors by the issuer and its agents in connection with the sale of the securities. Ratings may be changed, suspended, or withdrawn at anytime for any reason in the sole discretion of Fitch. Fitch does not provide investment advice of any sort. Ratings are not a recommendation to buy, sell, or hold any security. Ratings do not comment on the adequacy of market price, the suitability of any security for a particular investor, or the tax‐exempt nature or taxability of payments made in respect to any security. Fitch receives fees from issuers, insurers, guarantors, other obligors, and underwriters for rating securities. Such fees generally vary from US$1,000 to US$750,000 (or the applicable currency equivalent) per issue. In certain cases, Fitch will rate all or a number of issues issued by a particular issuer, or insured or guaranteed by a particular insurer or guarantor, for a single annual fee. Such fees are expected to vary from US$10,000 to US$1,500,000 (or the applicable currency equivalent). The assignment, publication, or dissemination of a rating by Fitch shall not constitute a consent by Fitch to use its name as an expert in connection with any registration statement filed under the United States securities laws, the Financial Services and Markets Act of 2000 of Great Britain, or the securities laws of any particular jurisdiction. Due to the relative efficiency of electronic publishing and distribution, Fitch research may be available to electronic subscribers up to three days earlier than to print subscribers.

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