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A Ratings Agencys Perspective
to Structured CreditGilbert Ong, CFA
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The Basics CDOs to CDOSquared
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TypesTypes of CDO
Cashflow> Portfolio of cash assets (loans, bonds, ABS) purchased by a special
purpose vehicle (SPV).
Synthetic> The SPV gains credit exposure by selling credit protection using a
portfolio of credit derivatives.
Market Value
> Risk in Market Value CDOs related to asset market price, not default.> Asset market price is a function of> Rating migration (credit driven)> Spread widening (market driven)> Liquidity (market driven)
Motivations
Balance Sheet> Risk management
> Regulatory requirements
Arbitrage> Exploit pricing inefficiencies
> Increase assets under management
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Synthetic CDO
Credit Default
Swap
Premium
Credit Protection
Payment
Protection
Seller
Protection
Buyer
Arranging Bank
Structure of a
Synthetic CDO
Protection Buyer
(Swap
Counterparty)
ProtectionSeller
(SPV)
Credit-Linked Notes
issued
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Correlation Impact on Credit Portfolios
> Mean remains unchanged
> Higher correlation leads to more extreme events at both ends of the
distribution
Corr=10%
STDev=5.27
Corr=30%
STDev=12.42
0%
1%
2%
3%
4%
5%
6%
7%
8%
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49
Number of Defaulted Assets
Prob
ability
Portfolio Default Distribution ? (50 'B' rated assets)
Mean 12.41
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Common Synthetic Structures CDOs to CDO Squared
SCDO
Corporate
Reference
Pool
(100
names) Attachment
Point
Exhaustion
Point
> Single-Tranch CDO > Synthetic CDO2
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Portfolio Loss Distribution CDOs vs CDO Squared
> CDO Squared loss distribution has a fatter tail (max loss is higher)
> This is due to lower granularity (only a few inner CDOs in a CDO Squared),
higher correlation between CDOs and AP of tranches
0
5
10
1520
25
30
35
40
0 2 4 6 810
12
14
16
18
20
22
24
26
28
30
Portfolio Loss (%)
Pro
fita
bility
Portfolio Loss Distribution(100 IG Corporates)
(%)
Source: Fitch Ratings
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0 3 6 912
15
18
21
24
27
30
33
36
39
42
45
48
51
54
57
60
Portfolio Loss (%)
Pro
fita
bility
Portfolio Loss Distribution(CDO of 20 CDOs)
(%)
90.40%
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Impact of Correlation on Credit Enhancement(Rating Loss Rate) of CDO and CDO Squared
Rating Loss Rate Sensit ivi ty to Asset Correlation
CDO Squared
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
0.08 0.10 0.12 0.14 0.16 0.18 0.20 0.22 0.24
PCL
RLR
'AAA' Credit
Enhancement
'BBB' Credit
Enhancement
Aver age Po rt fo lio Cor re lation Level (PCL)
Rating Loss Rate (RLR) Sensi tivity to Asset
Correlation
Single Layer CDO
0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
8.00%
0.08 0.10 0.12 0.14 0.16 0.18 0.20 0.22 0.24
PCL
RLR
'AAA' CreditEnhancement
'BBB' Credit
Enhancement
Aver age Po rt fo lio Cor re lati on Level (PCL)
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Fitch Rating Approach
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VECTOR
Theory -
Structural
Form Model
> Default occurs if: Value of Assets < Value of Liabilities
> In a Monte Carlo Simulation
> The company defaults if
> a randomly drawn number representing the change in asset value
> Falls below the DEFAULT THRESHOLD
> Default threshold derived from Ratings and Historical Default Rates
> Cholesky decomposition used to incorporate asset correlations
> VECTOR runs multi-period Monte Carlo simulation
Book Liabilities
Asset Value
Time TNow
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FitchRatings
CDO Rating
Criteria
The Fitch default VECTOR model
> A multi-step Monte Carlo simulation model
> For Cash Flow CDOs: Used in conjunction with Cash Flow
model Sector specific correlation assumptions
> 25 industries and 34 countries
> 6 ABS sectors, 17 Sub Sectors, 22 countries/regions
Recovery rates tiered by ratings stress
An empirically based CDO default matrix
For Cash Flow CDOs: Revised interest rate and currency assumptionsfor CF Modeling
For Fully Managed CDOs: An adjustment for asset manager ratings
Ability to analyze short positions in credits and in CDO tranches (within aCDO Squared)
Added new functionality to accommodate CDO Squared Transactions
> Look-through approach
> Cross-subordination
> Overlap Analysis
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Portfolio Inputs cont
Default
Probability
Recovery
Rate
Asset
Correlation
Term
Rating
Asset
Type
Country
Industry/
Sector
Asset Par
Value
Monte Carlo
Simulation
Default Distribution
(Rating Default
Rate or RDR)
Loss Distribution
(Rating Loss Rate
or RLR)
Recovery Rate Stress
(Rating Recovery Rate
or RRR)
Timing of Default
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Fitch Report: Comparative Empirical Study of AssetCorrelation (6 June 2005)
> Vector Model> Use of equity correlation data to derive asset correlation
> Can capture differences in di fferent regions, e.g. Europe, North America, Asia, and so for th
> Can yield name-specific pairwise correlations. Any possible (overestimation) bias can be adjusted by calibration> De Servigny and Renault:
> Averages the joint defaul t probabil ity by weighing i t by the number of obl igors in each cohor t.
> Frey and McNeal:> Joint default probabilities are aggregated using a simple average over all of the cohorts.
> RACM or Robust Average Correlation Measure:> Average of the Frey-McNei l and De Servigny-Renault .
> Gupton, Finger, and Bhatia
> Does not explicitly use timing o f the defaults.> Rating Transition Model
> measured directly using the co-movement of ratings. Cannot capture differences in regional dynamics (Asia vs. North America)
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Credit Default
Swaps
Referencing
ABS
> Developments
> Retention of bankruptcy / insolvency
> FTP Interest recognises concept of PiK> New Credit Events
> Permanent Loss
> Rating Downgrade
> Valuation> Extended valuation period
> Minimum Recovery Rates> Fixed Recovery Rates
> Challenges
> Corporate Credit Events not Applicable> Bankruptcy
> Failure to Pay> Insolvency
> Pass through/long dated maturity structure of ABS Assets
> Illiquidity / transparency
> ISDA has formed working groups towards developing
standards.
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Credit Event Definitions and Valuation Process
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Credit Event Study for 2004
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Factors to consider in determining recovery ratehaircuts due to valuation process
> the time period over which the bids are conducted and how soon
they begin after the occurrence of a credit event;> the source and number of bids: a low number of bids and bids that
include transaction participants in the valuation process have
tended to produce below-average recoveries;
> the number of valuation dates;
> how the final value is calculated (i.e. the highest bid, the average
of bids, etc.);
> the ability to include partial bids and WA quotations before
assuming a zero recovery value.
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Analysis of
Short Positions
0%
20%
40%
60%
80%
100%
-5.0
%
-4.0
%
-3.0
%
-2.0
%
-1.0
%
0.0
%
1.0
%
2.0
%
3.0
%
4.0
%
5.0
%
6.0
%
7.0
%
8.0
%
9.0
%
Cumulative Portfolio Loss
Cumula
tive
Pro
ba
bility
No Shorts 20 Shorts 40 shorts
# of Shorts
40200Confidence Level
6%7%8%99%
5%5%5%95%
Effect of Short Positions on RLR
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Synthetic
Index: A
surveillance
tool
> Definition
> Scope: 260 Fitch rated static synthetic corporate
CDOs 1160 underlying corporate names, comprising
the index
> Measure: WAR tracking CDO portfolio performance> Reporting frequency: Monthly
> Uses
> Tool to track CDO performance by vintage /
manager / type
> A proxy for CDS name liquidity> An indicator of negative name selection
> A tool to track macro credit trends
Chart above presents five vintage indices, which follow the same methodology as for the Synthetic Index calculation,except that the reference universe for the vintage indices comprises only those transactions which closed in the
respective period.
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CDO
S.M.A.R.T.
SurveillanceMetrics
Analytics
ResearchTools
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www.fitchratings.com
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