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

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

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

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

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

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

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

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

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 1981-1997  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

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 (www.cdoevaluator.standardandpoors.com) 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

Input Sheet

Industry Distribution

Rating Distribution

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

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

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

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

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, www.standardandpoors.com