1. Collateralized Debt Obligations
Agenda for today
talk about S&P approach to rating CDO
Diane KY Lam, CFA
Director
Structured Finance, Hong Kong
July 7th, 2004

2. Agenda  What is a CDO?  Motivations
 Rating CDO – Case study of synthetic CDO

3. What is a CDO?
An obligation to an investor collateralized by debt obligations from third parties

4. What is a CDO? Types of CDOs
 Cash Flow: Cash flow generated by the assets pays back investors
 Market Value: Market value of the assets is monitored and assets are sold to repay investors if market value drops
 Synthetic: Assets are referenced through a credit default swap (CDS). SPV pays the swap counterparty if an referenced asset defaults
 Hybrid: A combination of the above

5. Motivations  Yield opportunity  Arbitrage  Capital relief
 Risk management
 Funding
 Management fee
 Investment capacity

6. Rating CDO – Case Study of Synthetic CDO
3-Step Approach
 Structural
 Analytical
 Legal
Similar to rating other abs structures
3 steps in rating cdo structure
Collateral Quality and expected default rates
Recoveries on Defaults & Capital Structure
Legal & Structural Analyses

7. Rating CDO – Case Study of Synthetic CDO
Similar to rating other abs structures
3 steps in rating cdo structure
Collateral Quality and expected default rates
Recoveries on Defaults & Capital Structure
Legal & Structural Analyses

8. Rating CDO – Case Study of Synthetic CDO (Structural)
Counterparty Rating and Collateral Requirement
 Swap counterparty
 Account Bank / Agents / Custodian
 Collateral
Asset Manager Review
 Asset management experience and focus
 Investment strategy
 Experience with CDO structures
 Infrastructure and internal control
“S & P’s CDO Manager Focus”
Default rates for a portfolio are Driven by
Asset type (Corporate, ABS)
Different Default assumptions of each asset class
Rating of each asset
Exposure to each obligor
If an obligor default, all the related securities will likely to default
Industry
issuers from many different jurisdictions
affect by macroeconomic factors
local industry
only affected by the macroeconomic forces within the country
eg Building industry
Regional Industry
only affected by macroeconomic forces of the region.
eg Food services industry
GLOBAL industry
assumes same economic forces affect all companies in that industry, regardless of location
e.g Telecommunication
Maturity
higher prob for default for longer tenor corp assets
CDO Evaluator
model uses Monte Carlo Simulation
calculate expected default rates at each rating level
Example – portfolio of assets with
AAA = 40%
AA = 35%
A = 30%
“AA” rating for the CDO tranche
It needs to survive at least 35% gross default rates

9. Rating CDO – Case Study of Synthetic CDO (Analytical)
S & P CDO Evaluator
 Utilizes Monte Carlo simulation technology
 Used for pools of corporate and sovereign credits, ABS and CDO (i.e. CDO2)
 Based on corporate default study over the period of
 Default transition matrix driven by rating and maturity
 Creates probability distribution of portfolio default rates
 Output  Cumulative gross default over the life of the asset portfolio (Scenario Default Rate “SDR”)
Default rates for a portfolio are Driven by
Asset type (Corporate, ABS)
Different Default assumptions of each asset class
Rating of each asset
Exposure to each obligor
If an obligor default, all the related securities will likely to default
Industry
issuers from many different jurisdictions
affect by macroeconomic factors
local industry
only affected by the macroeconomic forces within the country
eg Building industry
Regional Industry
only affected by macroeconomic forces of the region.
eg Food services industry
GLOBAL industry
assumes same economic forces affect all companies in that industry, regardless of location
e.g Telecommunication
Maturity
higher prob for default for longer tenor corp assets
CDO Evaluator
model uses Monte Carlo Simulation
calculate expected default rates at each rating level
Example – portfolio of assets with
AAA = 40%
AA = 35%
A = 30%
“AA” rating for the CDO tranche
It needs to survive at least 35% gross default rates

10. Rating CDO – Case Study of Synthetic CDO (Analytical)
S & P CDO Evaluator
 Highly transparent to issuers, investors, arrangers and asset managers
 Version 2.2 – pools of corporate and sovereign credits as well as ABS
 Version 2.3 (BETA) – pools of corporate and sovereign credits, ABS as well as CDO (i.e. CDO2)
 Available FREE OF CHARGE at S & P’s website (
Default rates for a portfolio are Driven by
Asset type (Corporate, ABS)
Different Default assumptions of each asset class
Rating of each asset
Exposure to each obligor
If an obligor default, all the related securities will likely to default
Industry
issuers from many different jurisdictions
affect by macroeconomic factors
local industry
only affected by the macroeconomic forces within the country
eg Building industry
Regional Industry
only affected by macroeconomic forces of the region.
eg Food services industry
GLOBAL industry
assumes same economic forces affect all companies in that industry, regardless of location
e.g Telecommunication
Maturity
higher prob for default for longer tenor corp assets
CDO Evaluator
model uses Monte Carlo Simulation
calculate expected default rates at each rating level
Example – portfolio of assets with
AAA = 40%
AA = 35%
A = 30%
“AA” rating for the CDO tranche
It needs to survive at least 35% gross default rates

11. Input Sheet

12. Industry Distribution

13. Rating Distribution

14. Rating CDO – Case Study of Synthetic CDO (Analytical)
Default rates for a portfolio are Driven by
Asset type (Corporate, ABS)
Different Default assumptions of each asset class
Rating of each asset
Exposure to each obligor
If an obligor default, all the related securities will likely to default
Industry
issuers from many different jurisdictions
affect by macroeconomic factors
local industry
only affected by the macroeconomic forces within the country
eg Building industry
Regional Industry
only affected by macroeconomic forces of the region.
eg Food services industry
GLOBAL industry
assumes same economic forces affect all companies in that industry, regardless of location
e.g Telecommunication
Maturity
higher prob for default for longer tenor corp assets
CDO Evaluator
model uses Monte Carlo Simulation
calculate expected default rates at each rating level
Example – portfolio of assets with
AAA = 40%
AA = 35%
A = 30%
“AA” rating for the CDO tranche
It needs to survive at least 35% gross default rates

15. Rating CDO – Case Study of Synthetic CDO (Analytical)
Recovery Rate (WARR)
 Not a function of credit rating or issued notes’ rating
 Determined by seniority and domicile of the underlying assets in the portfolio
 Influenced by the action of asset manager
Different countries have different rates
Senior vs. Subordinated status assigns different rates
Haircuts such as cheapest to deliver and restructuring type etc.
Experience and expertise of asset manager matter; thus, due diligence becomes necessary (In US, S & P’s evaluates major asset managers and issues formal public reports (“CDO Manager Focus”)
Default rates for a portfolio are Driven by
Asset type (Corporate, ABS)
Different Default assumptions of each asset class
Rating of each asset
Exposure to each obligor
If an obligor default, all the related securities will likely to default
Industry
issuers from many different jurisdictions
affect by macroeconomic factors
local industry
only affected by the macroeconomic forces within the country
eg Building industry
Regional Industry
only affected by macroeconomic forces of the region.
eg Food services industry
GLOBAL industry
assumes same economic forces affect all companies in that industry, regardless of location
e.g Telecommunication
Maturity
higher prob for default for longer tenor corp assets
CDO Evaluator
model uses Monte Carlo Simulation
calculate expected default rates at each rating level
Example – portfolio of assets with
AAA = 40%
AA = 35%
A = 30%
“AA” rating for the CDO tranche
It needs to survive at least 35% gross default rates

16. Rating CDO – Case Study of Synthetic CDO (Analytical)
Capital Structure
 SDRs:
AAA = 40%
BBB = 20%
 WARR:
25%, thus loss = 75% of defaults Losses on each rating:
AAA = 40% defaults * 75% loss = 30% BBB = 20% defaults * 75% loss = 15%
 Capital Structure (Tranche Size) is
AAA = 70% BBB = 15% Equity (NR) = 15%
Default rates for a portfolio are Driven by
Asset type (Corporate, ABS)
Different Default assumptions of each asset class
Rating of each asset
Exposure to each obligor
If an obligor default, all the related securities will likely to default
Industry
issuers from many different jurisdictions
affect by macroeconomic factors
local industry
only affected by the macroeconomic forces within the country
eg Building industry
Regional Industry
only affected by macroeconomic forces of the region.
eg Food services industry
GLOBAL industry
assumes same economic forces affect all companies in that industry, regardless of location
e.g Telecommunication
Maturity
higher prob for default for longer tenor corp assets
CDO Evaluator
model uses Monte Carlo Simulation
calculate expected default rates at each rating level
Example – portfolio of assets with
AAA = 40%
AA = 35%
A = 30%
“AA” rating for the CDO tranche
It needs to survive at least 35% gross default rates

17. Rating CDO – Case Study of Synthetic CDO (Legal)
Legal Analysis
 Governing jurisdiction
 Program and series documentation
 Swap agreements and ISDA documentation
 Legal and tax opinions
Default rates for a portfolio are Driven by
Asset type (Corporate, ABS)
Different Default assumptions of each asset class
Rating of each asset
Exposure to each obligor
If an obligor default, all the related securities will likely to default
Industry
issuers from many different jurisdictions
affect by macroeconomic factors
local industry
only affected by the macroeconomic forces within the country
eg Building industry
Regional Industry
only affected by macroeconomic forces of the region.
eg Food services industry
GLOBAL industry
assumes same economic forces affect all companies in that industry, regardless of location
e.g Telecommunication
Maturity
higher prob for default for longer tenor corp assets
CDO Evaluator
model uses Monte Carlo Simulation
calculate expected default rates at each rating level
Example – portfolio of assets with
AAA = 40%
AA = 35%
A = 30%
“AA” rating for the CDO tranche
It needs to survive at least 35% gross default rates

18. Additional Information
 Global Cash Flow and Synthetic CDO Criteria – March 2002
 Criteria for rating Synthetic CDO Transactions – September 2003
All publications are available at:
S&P’s RatingsDirect,