In this section we consider key issues for investors when analyzing CDO tranches.
Risk and Return Analysis for CDOs
The return analysis for CDOs performed by potential investors is neces- sarily different to that undertaken for other securitized asset classes. For CDOs the three key factors to consider are:
■ Default probabilities and cumulative default rates ■ Default correlations
■ Recovery rates
Analysts make assumptions about each of these with regard to individ- ual reference assets, usually with recourse to historical data. We con- sider each factor in turn.
Default Probability Rates
The level of default probability rates will vary with each deal. Analysts such as the rating agencies will use a number of methods to estimate default probabilities, such as individual reference credit ratings and his- torical probability rates. Since there may be as much as 150 or more ref- erence names in a CDO’s collateral pool, a common approach is to use the average rating of the reference portfolio. Rating agencies such as Moody’s provide data on the default rates for different ratings as an
“average” class, which can be used in the analysis.
Correlation
The correlation between assets in the reference portfolio of a CDO is an important factor in CDO returns analysis. A problem arises with what precise correlation value to use; these can be correlation between default probabilities, correlation between timing of default and correlation between spreads. The diversity score value of the CDO plays a part in this: it represents the number of uncorrelated bonds with identical par value and the same default probability.
Recovery Rates
Recovery rates for individual obligors differ by issuer and industry clas- sification. Rating agencies such as Moody’s publish data on the average prices of all defaulted bonds, and generally analysts will construct a database of recovery rates by industry and credit rating for use in mod- eling the expected recovery rates of assets in the collateral pool. Note
that for synthetic CDOs with credit default swaps as assets in the port- folio, this factor is not relevant.
Analysts undertake simulation modeling to generate scenarios of default and expected return. For instance they may model the number of defaults up to maturity, the recovery rates of these defaults and the timing of defaults. All these variables are viewed as random variables, so they are modeled using a stochastic process. It is important to note that the recov- ery rates estimated by Moody’s and other rating agencies are average recovery rates. The actual recovery rate can vary widely depending upon the current macroeconomic environment.
CDO Yield Spreads
Fund managers consider investing in CDO-type products as they represent a diversification in fixed-income markets, with yields that are comparable to credit-card or auto-loan ABS. A cash CDO also gives investors expo- sure to sectors in the market that may not otherwise be accessible to most investors—for example, credits such as small- or medium-sized corporate entities that rely on entirely bank financing. Also, the extent of credit enhancement and note tranching in a CDO means that they may show better risk/reward profiles than straight conventional debt, with a higher yield but incorporating asset backing and insurance backing. In cash and synthetic CDOs, the notes issued are often bullet bonds, with fixed term to maturity, whereas other ABS and MBS product are amortizing securi- ties with only average (expected life) maturities. This may suit certain longer-dated investors.
An incidental perceived advantage of cash CDOs is that they are typically issued by financial institutions such as higher-rated banks. This usually provides comfort on the credit side but also on the underlying administration and servicing side with regard to underlying assets, com- pared to consumer receivables securitizations.
To illustrate yields in the European market, Exhibit 7.15 shows the spreads on a selected range of notes as at January 25, 2002 over the credit spectrum. Exhibit 7.16 shows a comparison of different asset classes in European structured products during February 2002. In Exhibit 7.17 we show the note spread at issue for a selected number of synthetic CDOs closed during 2001–2002. The regression of these and selected other AAA-rated note spreads against maturity shows an adjustedR2of 0.82, shown in Exhibit 7.18, which suggests that for a set of AAA rated securities, the term to maturity is not the only consider- ation.14 Other factors that may explain the difference in yields include
14Calculated from 12 synthetic CDO senior (AAA-rated) notes issued in Europe dur- ing January–June 2002 based on yields obtained from Bloomberg.
EXHIBIT 7.15 Rating Spreads for Synthetic CDOs in the European Market as at January 2002 for Deals Issued During Last Quarter 2001
Source:Bloomberg Financial Markets.
EXHIBIT 7.16 Average Speads Over LIBOR for Various Securitization Asset Classes in February 2002
EXHIBIT 7.17 Selected Synthetic Deal Spreads at Issue
Source:Bloomberg
EXHIBIT 7.18 AAA Spreads as at February 2002 (Selected European CDO Deals) Deal Name plus
Close Date Moody’s S&P Fitch
Spread
(bps) Index
Jazz CDO Mar-02
Class A Aaa AAA 47 6m LIBOR
Class B Aa2 AAA 75 6m LIBOR
Class C-1 A– 135 6m LIBOR
Class D BBB 240 6m LIBOR
Robeco III CSO Dec-01
Class A Aaa 55 3m LIBOR/EURIBOR
Class B Aa2 85 3m LIBOR
Class C Baa1 275 3m LIBOR
Marylebone Road CBO III Oct-01
Class A-1 Aaa AAA 45 3m LIBOR
Class A-2 Aa1 AAA 65 3m LIBOR
Class A-3 A2 AAA 160 3m LIBOR
BrooklandsA referenced linked notes Jul-01
Class A Aaa AAA 50 3m LIBOR
Class B Aa3 AA– 80 3m LIBOR
Class C Baa2 BBB 250 3m LIBOR
Class D-1 n/a BBB– 500 3m LIBOR
North Street referenced-linked notes 2000-2 Oct-00
Class A AAA 70 6m LIBOR
Class B AA 105 6m LIBOR
Class C A 175 6m LIBOR
perception of the collateral manager, secondary market liquidity. and the placing power of the arranger of the transaction.