Moody’s CDOROM™ v2.12 User Guide
Structured Finance Group
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Table of Contents
1
General Information ......................................................................................................................................... 4
1.1 Introduction............................................................................................................................................................. 4
1.2 Tool Design .............................................................................................................................................................. 4
1.3 Obtaining the Tool ................................................................................................................................................. 4
2
Model Inputs: Calculation Sheet ...................................................................................................................... 6
2.1 Table 1: Transaction Information .......................................................................................................................... 6
2.2 Table 3: Monte Carlo Parameters ......................................................................................................................... 6
2.3 Table 5: Capital Structure ....................................................................................................................................... 7
2.4 Run Simulation Options......................................................................................................................................... 9
3
Model Inputs: Portfolio(s) Sheet .....................................................................................................................16
3.1 Common Fields ...................................................................................................................................................... 16
3.2 Corporate Exposure Specific Fields ...................................................................................................................... 19
3.3 ABS Specific Fields ................................................................................................................................................ 20
3.4 Trust Preferred Securities (TruPs) Exposures .................................................................................................... 21
3.5 Choose Fields ......................................................................................................................................................... 21
3.6 Using the CDOROM Feed .................................................................................................................................... 23
3.7 Using the RefMaster Import ................................................................................................................................ 26
3.8 Show Data ............................................................................................................................................................. 26
3.9 Adding Inner CDOs for CDO^2 Modeling ......................................................................................................... 28
4
Reference Data: The ‘RefData’ Sheet ............................................................................................................. 30
4.1 Reference Data Applicable to All Asset Types ................................................................................................... 30
4.2 Corporate (Corp) .................................................................................................................................................. 32
4.3 ABS ......................................................................................................................................................................... 39
4.4 US TruPS ................................................................................................................................................................ 44
4.5 US Municipal (Muni) ............................................................................................................................................. 44
5
Output Data: ‘Portfolio Summary’ ................................................................................................................ 46
5.1 General................................................................................................................................................................... 46
5.2 Attributes............................................................................................................................................................... 46
5.3 Ratings (Graph and Data) .................................................................................................................................... 50
5.4 Tiers (Graph and Data) .......................................................................................................................................... 51
5.5 Regions (Graph and Data) ................................................................................................................................... 52
MOODY’S CDOROM™ V2.12 USER GUIDE
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
5.6 Industries (Graph and Data) ................................................................................................................................ 53
6
Model Outputs: ‘OutputData’........................................................................................................................ 54
6.1 General................................................................................................................................................................... 54
6.2 Table 1: Loss Distribution Data............................................................................................................................ 54
7
Additional Model Inputs: ’Asset Correl Matrix’ ............................................................................................. 55
7.1 The Multi-Factor Model and the Correlation Matrix ........................................................................................ 55
7.2 Manually Modify the Correlation Matrix ........................................................................................................... 55
7.3 Making the Matrix Positive Definite ................................................................................................................... 55
7.4 Dump to File Instead ............................................................................................................................................ 55
7.5 Max Columns ........................................................................................................................................................ 55
8
Additional Model Control: ‘Scenario Analysis’ .............................................................................................. 56
9
Appendix: Technical Information About CDOROM ...................................................................................... 57
9.1 The Monte Carlo Simulation Framework ............................................................................................................57
9.2 Description of the CDOROM Modelling Approach ...........................................................................................57
9.3 The Underlying Credit Universe ...........................................................................................................................57
9.4 The Capital Structure ........................................................................................................................................... 58
9.5 Random Recovery: Use of the Beta Distribution and Correlation Structure ................................................. 58
9.6 Parent Sector/Region Rules ................................................................................................................................. 60
9.7 Short Exposures .................................................................................................................................................... 60
9.8 The Correlated Binomial Methodology ............................................................................................................... 61
9.9 To Calculate the MAC of a CDO^1...................................................................................................................... 61
9.10 The Excel CDOROM Add-In ................................................................................................................................ 62
9.11 The GetRating Add-In .......................................................................................................................................... 63
9.12 Installing the GetRating Add-In .......................................................................................................................... 63
9.13 Using the GetRating Add-In ................................................................................................................................ 63
9.14 Per-Asset Default Timing Generation ................................................................................................................ 64
9.15 CDOROM - Technical Characteristics ................................................................................................................ 64
9.16 Technical Information About the CDOROM Data Feed File ........................................................................... 64
9.17 Corporate Sector Code Descriptions .................................................................................................................. 68
MOODY’S CDOROM™ V2.12 USER GUIDE
MOODY’S INVESTORS SERVICE
MOOD
1
Structured Finance Group
General Information
1.1
INTRODUCTION
Moody’s CDOROM™ is a Monte Carlo simulation tool used to calculate expected losses on tranches in pools of assets. The model simulates
asset correlations and calculates losses based on the default probabilities derived from asset ratings and recovery rates derived from asset
seniority and type. Recovery rates may also be simulated in a similar fashion. Moody’s CDOROM can be used to calculate portfolio statistics
and is sometimes used to generate loss distributions for use in cash flow modelling.
1.2
TOOL DESIGN
Moody’s CDOROM is laid out across six main tabs, with additional tabs hidden for ease of use. The following sections will guide the user
through the main inputs and outputs in these tabs.
Parameters to be input by the user are normally in blue text. Data in other cells should not be modified.
1.3
OBTAINING THE TOOL
Moody’s CDOROM is publicly available and free to subscribers. The model may be downloaded by going to http://www.moodys.com,
searching for “cdorom” and then clicking on the “products” section in the search results.
1.3.1
INSTALLATION
The Moody’s CDOROM package is supplied as a Windows Installer (MSI) file. Double-click the Setup.exe file in order to start the installation
process. The model’s DLL file(s) will automatically be installed in the Windows System32 folder. The Moody’s CDOROM Excel workbook
will be installed in the Program Files folder. Icons will be added to the Start menu and desktop that can be used to start the model.
The CDOROM Add-in will be registered automatically with Excel.
Moody’s CDOROM is also available as a .zip file if required – this can be found on the download page as the “Alternative Download”.
1.3.2
MANUALLY SPECIFYING THE CDOROM DLL LOCATION
If the CDOROM DLL files are placed in the Windows System32 folder, it is unnecessary to specifically tell the model where the DLL files
are located. If the DLL files need to be placed in a folder that is not in the “system paths,” the DLL folder’s location can be specified in the
RefData sheet under Table 6.
File and Folder Locations
Path that contains the CDOROMv2.5-13.dll file
.;C:\Moodys
To reference a specific location enter the path to the .dll in the box, e.g. C:\Moodys, C:\Windows\System, etc. It is not possible to modify
the name of the .dll, only the location can be changed.
If "." is used (without the quotes, the default setting) the DLL will be loaded from the folder that the workbook is stored in. Multiple paths
can be listed separated by semicolon (ie. ";") characters. The first that contains the DLL will apply.
Relative paths to the .xls file are also supported. For example,, “..\dll” will instruct CDOROM to look in a folder called.dll that belongs to the
parent folder of the folder that the .xls file is stored in.
1.3.3
CONFIGURING THE MOODY’S CDOROM DATA FEED
If you are a subscriber to Moody’s CDOROM Data Feed, in Moody’s CDOROM on the Portfolio(s) worksheet click Configure Feed. A
window appears that asks for a CDOROM FTP Feed Client ID. This will be provided by Moody’s and is distinct from Moodys.com
website logins.
MOODY’S CDOROM™ V2.12 USER GUIDE
4
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
1.4
HELP AND SUPPORT
For questions regarding the use of Moody’s CDOROM:
Email: [email protected]
Call the Client Service Desk:
»
London: +44.207.772.5454
»
»
New York: +1.212.553.1653
Tokyo: +81.3.5408.4100
»
»
»
Hong Kong: +852.3551.3077
Sydney: +61.2.9270.8100
Singapore: +65.6398.8308
MOODY’S CDOROM™ V2.12 USER GUIDE
5
MOODY’S INVESTORS SERVICE
MOOD
2
Structured Finance Group
Model Inputs: Calculation Sheet
The Calculation sheet is used to input tranche level information for a vanilla corporate synthetic collateralized debt obligation (CSO). The
structural characteristics of the deal and simulation parameters are inputted and the corresponding modeling results are outputted here on
this sheet.
2.1
TABLE 1: TRANSACTION INFORMATION
This is where basic information about the transaction is specified.
1. Transaction Inform ation
Model Type
As-Of Date
Maturity (years or Date)
Sw ap Rate
2.1.1
1
Synthetic CDO
12/31/2013
5
0.00%
MODEL TYPE
This drop-down box allows for quick reconfiguration of the model for the two most commonly applied methodologies. Selecting an option
in this drop-down is equivalent to enabling the appropriate fields through the Choose Fields button.
1)
Synthetic CDO (Default): This enables the capital structure table and the credit event table. This would be the typical setup when
modelling synthetic CDO tranches.
2)
Correlated Binomial Methodology: This enables the Correlated Binomial (CBET) fields and hides the Synthetic CDO Tranching and
Credit Event Definitions fields. This would be the typical setup when using the model to calculate a portfolio’s Moody’s Asset
Correlation (MAC) under the Correlated Binomial Methodology
2.1.2
AS-OF DATE
If exposure or tranche maturities are entered in date format, then this input defines the date from which the WAL, in years, will be
calculated. It must also be specified when using the Email to Monitoring feature (under the Run Simulation tab in the Calculation sheet)
to indicate the effective date of the portfolio data.
2.1.3
MATURITY (YEARS OR DATE)
This input contains the standard maturity that will be assumed for exposures unless a specified weighted average life (WAL) per asset or
CDO is applied. It may be entered in date format, or as the number of years from the as-of-date. If all the exposures have specific WAL
values in the portfolio sheet, then this input has no effect.
2.1.4
SWAP RATE
Enter the fixed/floating swap rate where the floating rate is the floating-rate index payable on the notesn issued against a fixed-rate
payment where the maturity of the swap was equal to the default date (years) (which appears in Capital Structure when Default Timing
is selected via the Choose Fields button). This rate and each tranche’s spread will be used to discount the expected loss.
Create tranched exposures to the underlying portfolio by adding exposures with the following inputs.
2.2
TABLE 3: MONTE CARLO PARAMETERS
Table 3 is where specifications for the Monte Carlo simulations are entered.
3. Monte Carlo Param eters
Nb Sim ulations
View /Modify Correlation Matrix
Sim ulation Tim e:
MOODY’S CDOROM™ V2.12 USER GUIDE
1,000,000
FALSE
0h 0m 2s
6
MOODY’S INVESTORS SERVICE
MOOD
2.2.1
Structured Finance Group
NUMBER OF SIMULATIONS
The number of simulations desired is entered in the Nb Simulations cell. As a rough estimate, Moody’s recommends using 10 million
simulations if either the target rating is Aaa or if the average rating of the reference portfolio is Aaa; otherwise, 3 million simulations will
generally suffice.
Additionally, Moody’s suggests checking the Confidence Interval output (Section 2.3.8 below) to check whether the result appears to
have converged sufficiently.
2.2.2
VIEW/MODIFY CORRELATION MATRIX
To view and/or manually modify the asset correlation matrix underlying the simulations, tick this checkbox and the Asset Correl Matrix
sheet will appear. It is possible to manually modify the correlation matrix in some cases – please refer to Chapter 7 for more information.
2.2.3
SIMULATION TIME
The duration of the last simulation is printed automatically in the Simulation Time cell.
2.3
TABLE 5: CAPITAL STRUCTURE
Table 5 is where tranche information is inputted. These tranches correspond to the top layer in a CDO^2 and to the CDO^1 tranching in a
simple CDO. Up to 60 tranches can be analysed simultaneously. The simulation results will be stored under each tranche’s description.
5. Capital Structure
Input Form at: % (Percentage)
T1
Notional Size %
Notional Size
CE (Attachm ent Point) %
CE (Currency)
Initial / Target Rating
Spread
T2
T3
T4
T5
3.00%
3.00
6.00%
6.00
EL
Discounted EL
Indicative Model Rating *
Moody's Metric (MM)
0.00000%
Aaa
0.0000
Confidence Interval
0.0000
Tranche Life (WAL)
5.00
2.3.1
INPUT FORMAT
This specifies the format in which tranche notional amounts are exhibited, in either percentage or nominal terms. In addition, it allows for
the solving of minimum attachment points given a target rating. The options available are:
1)
% (Percentage) specifies the capital structure tranching in percentage terms
2)
Currency specifies the capital structure tranching in the nominal currency
3) Solve for CE finds the minimum CE (attachment point)% and CE (currency)given a target rating and a percentage of notional size.
When selecting this option, a target rating must be specified and the size of the tranche must be entered as a percentage. Entering a
tranche size of 100% and a target rating will find the minimum CE (attachment point)% and CE (currency) of a super senior tranche. At
the end of the simulation the field will be updated accordingly to reflect the size between the required attachment point and 100%.
2.3.2
NOTIONAL SIZE % AND CE
Input the notional size and the credit enhancement of each tranche in percentage of the portfolio size. Note that credit enhancement
corresponds to the attachment point, and the notional size is equal to the difference between the detachment and attachment points.
MOODY’S CDOROM™ V2.12 USER GUIDE
7
MOODY’S INVESTORS SERVICE
MOOD
2.3.3
Structured Finance Group
INITIAL / TARGET RATING
Unless the Solve for CE option is used, this is an optional input except for managed transactions. It may be required in order to facilitate
implementation of the Moody’s Metric tests.
2.3.4
SPREAD
Enter each tranche’s spread in the Spread cell. The sum of the spread rate and the base rate (i.e. swap rate) will be used to discount each
tranche’s expected loss.
2.3.5
EL AND DISCOUNTED EL
These outputs indicate the raw expected loss and the final discounted, confidence interval adjusted expected loss used to determine the
indicative rating and Moody’s Metric outputs.
2.3.6
RATING
This is an indicative quantitative rating obtained by benchmarking the discounted expected loss (EL) against the idealised expected loss
tables at the tranchet WAL..
2.3.7
MOODY’S METRIC
This is a numerical representation of a rating; Aaa=1.0, Aa1=2.0, etc.
2.3.8
CONFIDENCE INTERVAL
This is the difference in a Moody’s Metric result between the stated MM and the MM that would be obtained without adding Moody’s
standard 99% confidence interval. This serves as a measure of the convergence of the result.
2.3.9
TRANCHE WEIGHTED AVERAGE LIFE (“WAL”)
The tranche life is automatically calculated in the Tranche Life cell. The weighted average life (WAL) of a tranche is calculated from the
amortisation profile of the underlying portfolio, taking into account the position of the tranche within the liability structure. This calculation
is based on the following assumptions:
1)
Zero default of the underlying assets,
2)
Bullet amortisation of these assets at their respective WAL,
3) Sequential amortisation of the tranches.
4) Exposures with a default probability of 100% (after all stresses are taken into account) are assumed to have a 1 day WAL for the
purpose of the tranche WAL calculation.
For instance, consider the following amortisation profile.
200,000
100%
Amortisation Profile
180,000
160,000
75%
140,000
Amount
120,000
100,000
80,000
50%
detachment point 41%
40%
40%
60,000
attachment point 27.5%
20%
25%
40,000
20,000
0
0
2
4
6
7.6
8
9
10
0%
WAL
MOODY’S CDOROM™ V2.12 USER GUIDE
8
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
The total size of the portfolio is equal to 200,000. For a tranche with an attachment point of 27.5% and a detachment point of 41%, the
WAL will be equal to:
WAL = 40% * 7.6 + 40% * 8 + 20% * 9 = 8.04 years.
The tranche WAL may be overridden using the Tranche WAL Override feature.
2.4
RUN SIMULATIONS OPTIONS
Run Simulation
Import
2.4.1
Export
Clean Inputs
Email to Monitoring
RUN SIMULATION BUTTON
Once all the parameters are set, press the Run Simulation button to start the simulation. The progress bar window indicates the progress
of the simulation and estimated remaining time. The simulation can be stopped at anytime. To do so press Stop button on the progress bar
and confirm the action. If the simulation has been interrupted, the results will be calculated on the runs completed before the interruption.
2.4.2
THE IMPORT AND EXPORT BUTTONS
Export will copy the essential data about the deal to a smaller .xls file that can be read by the Import feature. Import will correspondingly
import data from an .xls file generated using the Export feature. The Import button can also be used to import data from another Moody’s
CDOROM workbook, including workbooks from earlier versions of the model.
Note: Changes to data in the RefData worksheet, such as correlation assumptions, FXBC ratings and recovery tier assignments are ignored
by the import/export process. Only deal level information is imported/exported.
2.4.3
CLEAN INPUTS
This button will clear deal data from the workbook. It will not reset any changes made to assumptions in the RefData worksheet. Use a fresh
copy of the model downloaded from Moodys.com to be sure that the workbook is in its original configuration.
2.4.4
THE EMAIL TO MONITORING BUTTON
This button will assist the user with the steps of exporting the model data to a file and emailing it to Moody’s monitoring team.
When this button is pressed the following steps are performed by the model:
1)
Moody’s CDOROM first checks that the Tranche & Deal Name, and Tranche ID fields are enabled and appear to be populated
correctly. To enter this information select the Tranche & Deal Name and Tranche ID options under Choose Fields and enter the
respective names/IDs in the appropriate fields.
2)
The Export function is used to export the deal data to a small .xls file
3) A new email is created with the exported .xls file as an attachment. The Send button is not pressed so that the user may review the
email before sending it
The first time this button is used a window will appear asking which monitoring email address at Moody’s to use. Once selected this setting
is stored in the registry and will apply from then on for any other workbook opened on the system by the current user. To change the email
address setting press the Click here to change the email address for monitoring emails button in the RefData worksheet, Table 6.
MOODY’S CDOROM™ V2.12 USER GUIDE
9
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
The automatic generation of an email on the user’s system may not function correctly if the mail client is not compatible with the method
of automation used by the model. If this is the case, please manually use the Export function and send it to the monitoring email address.
2.5
CHOOSE FIELDS
Additional changes and options are available for more complex transactions. The Choose Fields window allows selection of different input
and/or output fields required in the model.
2.5.1
DEAL & TRANCHE NAME
This enables the Deal Name and Tranche Name fields on the Calculation sheet. These fields do not affect the analysis but can be used for
record keeping purposes. When using the Email to Monitoring button these fields must be populated.
Deal Name
2.5.2
Tranche Name
TRANCHE ID
This enables the Deal ID and Tranche DebtNumber fields on the Calculation sheet. These fields must be populated when using the Email
to Monitoring feature.
Deal ID
MOODY’S CDOROM™ V2.12 USER GUIDE
Tranche DebtNumber
10
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Table 10: Additional Tranche Data contains fields where information on the swap counterparty and/or funding collateral may be entered.
The Swap Counterparty, S.C. OrgNumber and Collateral DebtNumber fields do not affect the analysis and are provided for record
keeping purposes only.
2.5.3
COLLATERAL EL
This enables several fields on the Calculation sheet through which additional expected lossel (EL) can be incorporated in the rating result for
each tranche, usually to reflect collateral or counterparty risks. The additional expected loss is added before the EL result is discounted by
Swap Rate + Spread.
MOODY'S CDOROMv2.5™
Choose Fields ...
1. Transaction Information
Deal Type
5. Capital Structure
1
Synthetic CDO
As-Of Date
09/06/2006
Maturity (years or Date)
5
Swap Rate
5.00%
Run Simulation
Import
Export
Clean Inputs
3. Monte Carlo Parameters
View/Modify Correlation Matrix
Simulation Time:
Input Format: % (Percentage)
T1
Notional Size %
T2
T3
T4
3.00%
Notional Size
300.00
CE (Attachment Point) %
6.00%
CE (Currency)
600.00
Initial / Target Rating
Email to Monitoring
Nb Simulations
Inputs in BLUE. Information-only inputs have GRAY background
1,000,000
TRUE
0h 0m 1s
Spread
EL
0.00000%
Additional EL
0.00000%
Discounted EL
8.63838%
Rating
B1
Moody's Metric (MM)
13.9153
Confidence Interval
0.0000
Tranche Life (WAL)
5.00
Collateral Rating
Aa1
Collateral EL Multiplier
Collateral EL Added
1.0
0.00000%
Additional EL: A specific amount of expected loss to be added to the EL
Since version 2.5 the expected loss may be added by specifying the rating of the collateral and a multiplicative factor. This allows the WAL
of the tranche to be taken into account automatically in the calculation of the additional EL.
Collateral Rating: Enter the rating of the collateral, from which the EL will be calculated
Collateral EL Multiplier: Enter a factor by which the collateral’s rating will be multiplied
Collateral EL Added (Output): The EL added will be displayed in this field after the simulation has completed.
2.5.4
DEFAULT TIMING
Moody’s CDOROM is a single period model that calculates the undiscounted expected losses (EL) of the tranche (the EL result) using Monte
Carlo simulation. This EL figure is then discounted by the swap ratesr and spreads of the tranche in order to find the present value of these
expected losses. The discount is normally applied with a horizon equal to 60% of the tranche life. These fields allow you to change this
assumption when necessary.
MOODY’S CDOROM™ V2.12 USER GUIDE
11
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
MOODY'S CDOROMv2.5™
Choose Fields ...
1. Transaction Information
Deal Type
5. Capital Structure
09/06/2006
Maturity (years or Date)
5.00%
Run Simulation
Export
Clean Inputs
T1
Notional Size %
5
Swap Rate
Import
T2
T3
T4
3.00%
Notional Size
300.00
CE (Attachment Point) %
6.00%
CE (Currency)
600.00
Initial / Target Rating
Email to Monitoring
3. Monte Carlo Parameters
Spread
EL
100.00000%
Discounted EL
Nb Simulations
1,000,000
View/Modify Correlation Matrix
Input Format: % (Percentage)
1
Synthetic CDO
As-Of Date
Inputs in BLUE. Information-only inputs have GRAY background
TRUE
Simulation Time:
0h 0m 6s
78.35262%
Rating
C
Moody's Metric (MM)
20.5919
Confidence Interval
0.0000
Tranche Life (WAL)
5.00
Default Timing (normally 0.6x)
1.0
Default Date (year)
5.00
Default Timing (normally 0.6x): Leave blank to let the model apply the standard 0.6x default timing. Enter another figure as appropriate.
For instance, a factor of 1.0 may be appropriate if tranche write-downs only occur at the end of the deal and the noteholder receives
interest on the full principal amount until then regardless of losses.
Default Date (year) (Output): This indicates the default timing assumption made, in years.
2.5.5
TRANCHE WAL OVERRIDE
These fields allow the tranche WAL, used for benchmarking the rating and Moody’s Metric, to be overridden.
Tranche WAL Override or CapAtPf: Specify a tranche WAL in years or as a date. This will override the WAL calculation normally made by
the model. A special text value of CapAtPf will instruct the model to take the minimum of the normal Tranche WAL and the underlying
portfolio’s average WAL. This is a feature that may be used in manage-to-model transactions.
2.5.6
CORRELATED BINOMIAL (CBET) AND ADDITIONAL CBET OUTPUTS
See section 9.9 for complete information about the Correlated Binomial Methodology and Moody’s CDOROM.
2.5.7
TRANCHE EL VARIANCE & FREQUENCY
This enables additional outputs in the capital structure table:
»
»
2.5.8
Variance: The variance of the tranche loss distribution.
Frequency: The frequency with which the tranche loss is greater than zero.
OUTPUT TO FILE
This field outputs additional information from the Monte Carlo simulation.
1)
Full Data (binary): generates a dense binary file in the specified location that contains detailed information on the default dates and
recovery levels of the assets in the simulation. Please contact Moody’s for further information.
2)
Full Data (text): please contact Moody’s for further information.
Output to text or binary file?
Full Data (binary)
MOODY’S CDOROM™ V2.12 USER GUIDE
Output Filename
C:\data.bin
12
MOODY’S INVESTORS SERVICE
MOOD
2.5.9
Structured Finance Group
UNUSED CASH-FLOW INPUTS
These fields are not used by the analytical engine but may be used by other models that automate the model for other purposes.
2.5.10
TABLE 11: SYNTHETIC CDO TRANCHING
This option enables the capital structure table in the Calculation sheet. It is disabled automatically when selecting Correlated Binomial
Methodology from the Deal Type input.
2.5.11
TABLE 4: CREDIT EVENT DEFINITIONS
By default, the credit event definitions applied by the model correspond to the market standard definitions that Moody’s has observed in
recently rated transactions. Enabling this option applies the stresses and haircuts in Table 4.
4. CREDIT EVENT DEFINITIONS
Enabled
Note: NO stress applies to Bankruptcy, Failure to pay, Repudiation Moratorium
TRUE
Please define either a Region, Country,
Sector, Country;Sector, Region;Sector,
Seniority;Region;Sector, OrgNum ber or Entity
Nam e
Credit Event Type
Stress Applied
Haircut Applied
IG
NIG
North America
Corp-MR
5.00%
10.00%
10.00%
Europe
Corp-MMR
5.00%
10.00%
10.00%
Asia
Corp-OR+MHO
5.00%
10.00%
10.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
Corp-OR+OA
25.00%
10.00%
10.00%
South Africa
Japan
Corp-OR
12.50%
10.00%
10.00%
Australia
Corp-MR
5.00%
10.00%
10.00%
New Zealand
Corp-MR
5.00%
10.00%
10.00%
Central America
Corp-OR+OA
25.00%
10.00%
10.00%
South America
Corp-OR+OA
25.00%
10.00%
10.00%
Eastern Europe & Former Soviet Union
Corp-OR+OA
25.00%
10.00%
10.00%
Middle East & North Africa
Corp-OR+OA
25.00%
10.00%
10.00%
Sub-Saharan Africa
Corp-OR+OA
25.00%
10.00%
10.00%
Indian Subcontinent
Corp-OR+OA
25.00%
10.00%
10.00%
276550
Corp-MR
5.00%
10.00%
10.00%
276455
Corp-MR
5.00%
10.00%
10.00%
661600
Corp-MR
5.00%
10.00%
10.00%
0.00%
0.00%
0.00%
SB;Europe;115
Corp-OR+MHO
5.00%
10.00%
10.00%
128
Sov-OR
12.50%
10.00%
10.00%
0.00%
0.00%
0.00%
Sov-OR+MHO
5.00%
10.00%
10.00%
Japan;128
Sov-OR
12.50%
10.00%
10.00%
Europe;128
Sov-OR+MHO
5.00%
10.00%
10.00%
0.00%
0.00%
0.00%
5.00%
10.00%
10.00%
Asia;128
Australia;128
Sov-MR
New Zealand;128
Sov-MR
5.00%
10.00%
10.00%
Central America;128
Sov-OR
12.50%
10.00%
10.00%
South America;128
Sov-OR
12.50%
10.00%
10.00%
Eastern Europe & Former Soviet Union;128
Sov-OR
12.50%
10.00%
10.00%
Middle East & North Africa;128
Sov-OR
12.50%
10.00%
10.00%
Note that these values cannot be overridden in Table 4. To override these values, go to the RefData sheet, Table 2.
Set Enabled to ”false” if credit event definitions are not applicable.
To modify the credit event definition of an existing region, select the appropriate definition in the drop-down menu in the Credit Event
Type column.
MOODY’S CDOROM™ V2.12 USER GUIDE
13
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
To add/modify the credit event definition of a specific country, sector or entity:
1)
Enter either the country name, sector’s number, entity’s organization number or entity name in the first column of Table 4.
2)
Select the appropriate definition in the drop-down menu in the Credit Event Type column
The user must check that the resulting assumptions on the multiple holder obligation, maturity limitation etc., are in line with the
documentation of the transaction.
In order to determine the credit event types applicable to a given entity, the model considers in decreasing order of priority:
1)
Organisation Number
2)
Name of the reference entity
3) Country
4) Industry
5)
Region
6) Exposure Type.
In Table 4 above, the credit event stress and haircut figures corresponding to a given category of asset appear in the last three columns. A
specific credit event type may also be assigned asset-by-asset from the Portfolio(s) sheet.
2.5.12
DIGITAL CDS STRESS
For digital corporate CDS, to account for shifting incentives and to mitigate potential moral hazard, Moody’s may use additional objective
criteria for restructuring credit events to attest to the occurrence of an actual credit event. If Moody’s language on digital CDS is not
included in the documentation, use the credit event types with DigCDSStress appended to the credit event type, e.g. Corp-MRDigCDSStress. This replaces the Apply Digital CDS Stress tick-box in version 2.4 and earlier.
MOODY’S CDOROM™ V2.12 USER GUIDE
14
MOODY’S INVESTORS SERVICE
MOOD
2.5.13
Structured Finance Group
ABS LIQUIDITY HAIRCUTS
These haircuts were introduced in version 2.5 and have been available since. In synthetic ABS CDOs where a market valuation method is
used to settle a credit event, an adjustment may be necessary to account for the additional liquidity risk. These may be applied to all ABS by
specifying a credit event definition of ABS with one of the following credit event types:
Credit Event Type
ABS-Liq-3month
ABS-Liq-6month
ABS-Liq-1year
ABS-Liq-2years
ABS-Iliq-3month
ABS-Iliq-6month
ABS-Iliq-1year
ABS-Iliq-2years
DP Stress
Applied
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
RR Haircut Applied
IG
NIG
75.00%
25.00%
5.00%
0.00%
85.00%
50.00%
35.00%
10.00%
75.00%
25.00%
5.00%
0.00%
85.00%
50.00%
35.00%
10.00%
The credit event type may also be overridden on an asset-by-asset basis from the portfolio(s) sheet.
MOODY’S CDOROM™ V2.12 USER GUIDE
15
MOODY’S INVESTORS SERVICE
MOOD
3
Structured Finance Group
Model Inputs: Portfolio(s) Sheet
This section describes the use of the Portfolio(s) sheet and any additional inner CDO portfolio sheets added in order to describe a CDO^2
structure. Fields that are always visible are described first, and then the various additional fields available through the Choose Fields menu
are described in turn.
3.1
COMMON FIELDS
MOODY'S CDOROM™: Portfolio Data
100
Type
3.1.1
TYPE
ID Type
Org
Number/ ID
Reference Entity
Choose Fields ...
Amount
Update with Feed
SU Rating
Industry/
ABS Code
Configure Feed
ISO/Country
This field indicates whether the exposure is corporate (Corp), ABS, municipal (Muni), trust preferred (TruPS) or a tranche exposure to an
inner CDO. It can be left blank for corporate and ABS exposures. The model will determine the exposure type from the sector code.
3.1.2
ID TYPE AND ORG NUMBER/ID
If ID type is left blank or set to organization number, then Moody’s reference number for corporate entities (numerical input) may be
entered in the Org Number column for use during the Moody’s CDOROM Data Feed import and for correct identification of Tier G
sovereign exposures. The ID Type column can be used to indicate that another type of ID, such as an ISIN or CUSIPs, is provided in the ID
field for the purpose of the data import.
3.1.3
REFERENCE ENTITY
This is the Moody’s organization name (or the entity name if not rated by Moody’s) for corporate exposures or the reference obligation
namefor ABS exposures.
If two entities in the portfolio have the same value for Reference Entity (not case sensitive), they are assumed to refer to the same
company or organization, and are correlated at 100%. In order to get the most accurate results, it is important to check that:
these entries do not accidentally have the same value if the exposures are not completely equivalent (i.e. different companies for corporate
exposures and different notes or classes of notes for ABS exposures.)
this field is identical between exposures that do refer to the same company or, for ABS exposures , to the same class of notes.
3.1.4
AMOUNT
This numerical field should be equal to the notional amount at risk on this exposure. It is imperative that all the notional amounts are
expressed in the same units and currency. It is possible to enter negative values for short exposures..
3.1.5
SU/RO RATING
This input specifies the Moody’s Applied Rating used to determine the default probability of the asset. Typically, Moody’s ratings are based
on expected losses, which reflect both the default probability and the recovery of the reference asset.
For corporate and ABS real estate investment trust (REIT), when the reference asset is a subordinated debt, this typically means the default
probability of the reference is the same as if it were a senior unsecured or any other kind of debt, while the recovery rate is lower than that
assumed for senior secured or senior unsecured debt.
For ABS exposures other than REITs, enter the Moody’s rating of the specific security included in the portfolio. This is called the reference
obligation (RO) rating.
MOODY’S CDOROM™ V2.12 USER GUIDE
16
MOODY’S INVESTORS SERVICE
MOOD
3.1.6
Structured Finance Group
INDUSTRY/ABS CODE
This field specifies the numerical input corresponding to the industry code of the exposure. Corporate exposures have industry numbers
between 101 and 135 and ABS exposures have industry numbers between 136 and 176. Version 2.4 ABS codes between 36 and 68 will be
automatically converted to new codes, with the exception of CMBS, for which Moody’s CDOROM version 2.5 and onwards has new codes
based on the CMBS property type.
For corporate exposures, this information is automatically retrieved by the Data Feed import.
This input may be left blank for tranche exposures.
For reference, the corporate and ABS sector classifications are reproduced below. The complete list of Moody’s sector codes appears in the
RefDatasheet.
Moody's Sector Code
Sector Name
101
CORP - Aerospace & Defense
102
CORP - Automotive
103
CORP - Banking
104
CORP - Beverage, Food & Tobacco
105
CORP - Capital Equipment
106
CORP - Chemicals, Plastics, & Rubber
107
CORP - Construction & Building
108
CORP - Consumer goods: Durable
CORP - Consumer goods: Non-durable
109
110
CORP - Containers, Packaging & Glass
111
CORP - Energy: Electricity
112
CORP - Energy: Oil & Gas
CORP - Environmental Industries
113
114
CORP - FIRE: Finance
115
CORP - FIRE: Insurance
116
CORP - FIRE: Real Estate
117
CORP - Forest Products & Paper
118
CORP - Healthcare & Pharmaceuticals
119
CORP - High Tech Industries
120
CORP - Hotel, Gaming & Leisure
121
CORP - Media: Advertising, Printing & Publishing
122
CORP - Media: Broadcasting & Subscription
123
CORP - Media: Diversified & Production
124
CORP - Metals & Mining
125
CORP - Retail
126
CORP - Services: Business
127
CORP - Services: Consumer
128
CORP - Sovereign & Public Finance
129
CORP - Telecommunications
130
CORP - Transportation: Cargo
131
CORP - Transportation: Consumer
CORP - Utilities: Electric
132
133
CORP - Utilities: Oil & Gas
134
CORP - Utilities: Water
CORP - Wholesale
135
MOODY’S CDOROM™ V2.12 USER GUIDE
17
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Moody's Sector Code
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
3.1.7
Sector Name
ABS - Consumer - Cons.ABS - Auto
ABS - Consumer - Cons.ABS - Credit Card and other Consumer Unsecured Loans
ABS - Consumer - Cons.ABS - Student Loans
ABS - Consumer - RMBS - Prime
ABS - Consumer - RMBS - Subprime
ABS - Consumer - RMBS - CDO of RMBS
ABS - Consumer - RMBS - Manufactured Housing
ABS - Consumer - Div.SF.CDO - CDO of SF - Diversified
ABS - Corporate - CRE - REIT - Hotel
ABS - Corporate - CRE - REIT - Multi family
ABS - Corporate - CRE - REIT - Office
ABS - Corporate - CRE - REIT - Retail
ABS - Corporate - CRE - REIT - Industrial
ABS - Corporate - CRE - REIT - Healthcare
ABS - Corporate - CRE - REIT - Self-storage
ABS - Corporate - CRE - REIT - Diversified
ABS - Corporate - CRE - CMBS - Credit Tenant Lease
ABS - Corporate - CRE - CRE CDO
ABS - Corporate - CRE - CMBS - Diversified
ABS - Corporate - CRE - CMBS - Office
ABS - Corporate - CRE - CMBS - Retail
ABS - Corporate - CRE - CMBS - Hotel
ABS - Corporate - CRE - CMBS - Industrial
ABS - Corporate - CRE - CMBS - Nursing Home
ABS - Corporate - CRE - CMBS - Residential/Multi-Family
ABS - Corporate - CRE - CMBS - Warehouse / Self-storage
ABS - Corporate - CRE - CMBS - Healthcare
ABS - Corporate - Specific - Tax Lien
ABS - Corporate - Specific - Mutual Fund Fees
ABS - Corporate - Specific - Structured Settlement
ABS - Corporate - Specific - Utility Stranded Cost
ABS - Corporate - Specific - Big Ticket Lease
ABS - Corporate - Specific - IP (including Entertainment Royalties)
ABS - Corporate - Specific - Dealer's Floorplan
ABS - Corporate - Specific - Tobacco Bonds
ABS - Corporate - Corp.CDO - Market Value CDO & CDO^2
ABS - Corporate - Corp.CDO - CDO exposed to IG
ABS - Corporate - Corp.CDO - CDO exposed to HY
ABS - Corporate - Corp.CDO - CDO exposed to EM
ABS - Corporate - Corp.CDO - ABS or CDO exposured to SME risk
ABS - Corporate - Corp.CDO - CDO - Franchise Loans
Key Agent
Originator
Originator
Originator
Originator
Originator
Arranger
Originator
Manager/Arranger if static
NA
NA
NA
NA
NA
NA
NA
NA
NA
Manager/Arranger if static
NA
NA
NA
NA
NA
NA
NA
NA
NA
Servicer
Manager
Servicer
NA
Servicer
Originator
Seller
NA
NA (but check Manager)
Manager/Arranger if static
Manager/Arranger if static
Manager/Arranger if static
Manager / Originator
Originator
unless
specified?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
TRUE
TRUE
TRUE
TRUE
TRUE
ISO/COUNTRY
This field specifies name or ISO code of the country where the exposure is principally located.
For corporate exposures, this information is automatically retrieved by the Data Feed import.
For ABS exposures, enter the country where the majority of the security’s underlying assets are located. If these assets are widely spread
across countries, it is possible to enter special region names, i.e. “Global”, “Euromarket”, “Asia-no EM”.
This input may be left blank for tranche exposures.
MOODY’S CDOROM™ V2.12 USER GUIDE
18
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
3.2
CORPORATE EXPOSURE SPECIFIC FIELDS
In addition to the fields described above, two further fields are required when modelling corporate exposures. To enable these fields click
Choose Fields and select Corporate Exposures, then press Ok.
3.2.1
PARENT ENTITY NAME
This information is automatically retrieved by the Data Feed import and is used in the correlation calculations. In order to get the most
accurate results, it is important to check that:
When two companies are affiliated (e.g. parent firm and subsidiary, or two related subsidiaries), the text in this field is identical. They will be
then 100% correlated
If an entity is not affiliated with any other in the portfolio, this field is either unique or left blank
3.2.2
REFERENCE OBLIGATION SENIORITY
This field specifies the seniority of the reference obligation debt. In the drop-down menu, select one of the following reference
obligation seniorities:
1) SS-1st lien: First lien only senior secured loan
2)
SS-Other: Non-first lien senior secured loan or senior secured bond
3) SU: Senior unsecured loan or senior unsecured bond
4) SB: Subordinated bond
5)
FG: Monoline (financial guarantor for which 0% fixed RR should be assumed (see Input Description sheet, Appendix II)
The default assumption is SU: Bond or Loan.
MOODY’S CDOROM™ V2.12 USER GUIDE
19
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
3.3
ABS SPECIFIC FIELDS
To enable these fields, click Choose Fields and select ABS Exposures, then press OK.
Additional Input Required for ABS
Transaction
Name
3.3.1
Issue Date
Guarantor/
Wrapper
Key Agent
% in initial
deal
Initial Rating/
REIT: Current
RO Rating
Master Trust
Name
Managed?
(override)
TRANSACTION NAME
This field uniquely describes the name of the ABS transaction. For reference entities that come from the same transaction, the text in this
field must be identical.
Series issued by the same SPV should be viewed as belonging to the same transaction only if they are exposed to the strictly same pool of
assets. Otherwise, specify different transaction names. If a tranche is fully guaranteed, enter the name of the guarantor as transaction name.
When simulating the portfolio, CDOROM considers ABS with the same transaction name to have higher asset correlation.
3.3.2
ISSUE DATE
Enter the date that the ABS reference entity was issued. This must be an excel date value, not just Text that looks like a date. To convert
text to dates follow these steps.
» Select the cells in this column with the date values
» From the Excel main menu, select Data->Text to Columns…
» Select Delimited, and press Next twice
» From the Column data format box, select Date: and the appropriate format (DMY / MDY …)
» Press Finish
Depending on other inputs in the model, CDOROM may introduce extra correlation between assets that have similar closing dates (known
as vintage penalty).
3.3.3
GUARANTOR / WRAPPER
Enter the name of any guarantor or monoline insurance company guaranteeing such reference security. The model will introduce some
extra correlation between assets that have the same guarantor or wrapper. In order to get accurate results, it is important that this field is
filled and that the text in this field matches exactly when they refer to the same company.
When an asset is guaranteed or wrapped, it will be modeled as a corporate exposure to the insurance sector. The recovery rate modeling to
use for this corporate exposure must be specified, typically as “random recovery” as opposed to “fixed,” which would be used for an
unwrapped ABS exposure.
The Guarantor/Wrapper must match one of the entries in Table ABS 4in the RefDatasheet, which describes the known guarantors/wrappers,
their parent entities and the country input to be used.
3.3.4
KEY AGENT
For certain ABS types, the Key Agent field must be filled with the name of the originator, servicer or managerof an ABS transaction
(depending of the ABS type). When two ABS have the same key agent, the model may introduce additional asset correlation between these
reference entities. The key agent depends on the ABS sectors.
3.3.5
% IN INITIAL DEAL
Enter the size of the referenced ABS tranche as a percentage of the total liabilities issued in the referenced ABS transaction. For multi-series
issuances, do not aggregate the percentage of different series unless the series are pari passu.
For REIT exposures leave this field blank.
MOODY’S CDOROM™ V2.12 USER GUIDE
20
MOODY’S INVESTORS SERVICE
MOOD
3.3.6
Structured Finance Group
INITIAL RATING / REIT: CURRENT RO RATING
Enter the initial rating of the referenced ABS tranche.
For REIT exposures, there is a different method of calculating the recovery rate based on the difference between the SU rating and the
actual obligation rating. For this reason, enter the current obligation rating of the exposure in the Initial Rating / REIT: Current RO
Rating field.
3.3.7
MASTER TRUST NAME
In the case of credit card transactions where the different transactions are issued out of the same master trust, enter the name of the
master trust in this field so that CDOROM can recognize the increased level of correlation between the exposures.
3.3.8
MANAGED (OVERRIDE)
CDOROM will assume ”static” or ”managed” for an exposure on the basis of its industry code… This can be overridden on an exposure by
exposure basis by entering “true” or “false” (1 or 0 are equivalent) in this field.
3.4
TRUPS EXPOSURES
To specify TruPS exposures, enter “TruPS” as the exposure type and populate the sector code information using the TruPS sectors or
Regions, as listed in RefData Table TRUP1 – Regional Correlations. In order to specify that synthetic credit event stresses should not be
applied to a TruPSexposure, ensure that Table 4: Credit Event Definitions on the Calculation sheet is either disabled, or for each TruPS
obligation the Credit Event Type field contains an “N/A” entry.
3.5
CHOOSE FIELDS
The Choose Fields button on the portfolio(s) sheet allows additional fields to be enabled..
MOODY’S CDOROM™ V2.12 USER GUIDE
21
MOODY’S INVESTORS SERVICE
MOOD
3.5.1
Structured Finance Group
SPECIFIC WAL PER ASSET
This enables the Asset Weighted Average Life (years) field, which can be used to specify the maturity (corporate exposure) or the
remaining weighted average life (ABS) of an exposure. If the field is not enabled, or it is enabled but left blank, then the exposure will take
the maturity specified in the calculation sheet for the transaction.
3.5.2
e Feed
RECOVERY RATE OVERRIDES
Show Data
RO
Industry/
Seniority ABS Code
Add inner CDO ...
ISO/Country
103
US
103
US
103
US
103
US
Var RR
Modelling
Digital
RR %
FALSE
40%
TRUE
45%
Std Dev
RR%
Rating Comments (no input required here)
25.0%
If these fields are not enabled, or are left blank for a particular exposure, then the standard recovery rate assumptions will be applied by the
model for corporates and ABS.
In order to override these assumptions for an exposure, indicate whether the recoveries are fixed or random by entering “false” or ”true”,
respectively, in the Var RR Modelling field.
If the recoveries are fixed (Var RR Modelling = false), specify the fixed recovery rate level in the Digital RR % column. Credit event based
recovery rate haircuts will not be applied in this case.
If the recoveries are random (Var RR Modelling = true), specify the mean level in the Digital RR % field and the desired standard deviation
in the Std Dev RR% field. Credit event based recovery rate haircuts will be applied as normal.
3.5.3
NOTCHING COLUMN
This enables the Notching column, which can be used to specify a whole or fractional notching to apply to the exposure’s rating when
calculating the default probability. Fractional notching is implemented using logarithmic interpolation in the same fashion as the Moody’s
Metric calculation.
A positive number indicates notching upwards on the rating scale (reducing default probability) and a negative number indicates that the
rating is to be notched downwards.
3.5.4
DP STRESS
This enables the Add DP Stress column, through which extra stress on the default probability can be applied using the formula:
Net Default Probability = [1 + (Extra Stress + CE Stress)] * Default Probability.
3.5.5
RR HAIRCUT
This enables the Add RR Haircut column. The RR haircut is applied using the formula:
Net Recovery Rate Mean = (1 – Extra haircut) * (1 – CE haircut) * Raw Recovery Rate
3.5.6
CREDIT EVENT OVERRIDE
This column allows the credit event type to be specified on a per-exposure basis.
MOODY’S CDOROM™ V2.12 USER GUIDE
22
MOODY’S INVESTORS SERVICE
MOOD
3.5.7
Structured Finance Group
DEBT NUMBER / CUSIP / ISIN
This enables additional fields that can be used for reporting purposes. These fields do not affect CDOROM’s analysis.
3.5.8
INNER CDO
This enables the fields used by Tranche exposures when entering a CDO^2.
3.5.10
SUMMARY COLUMNS
These fields are automatically enabled when the Show Data button is pressed.
3.5.11
MIR GAP
If enabled, this field will be populated by the CDOROM data feed with the Market Implied Ratings (MIR) Gap for exposures. The MIR gap is
expressed as a number of notches between the MIR and the fundamental rating of the reference asset. A positive value indicates an MIR
that is higher in credit quality than the fundamental rating of the reference asset. A negative value indicates that the MIR is lower in credit
quality than the fundamental rating of the reference asset.
The MIR Gap column can be hidden by un-ticking the Show MIR Gap column option in the Configure Feed window.
3.5.12
COUPON (NOT USED BY THE MODEL)
These fields are provided for convenience and are not used by CDOROM’s analytical engine.
3.5.13
PARENT ENTITY ORG NUM
This optional field provides an area of the Moody’s organization number of the parent entity to be recorded. It is not used by CDOROM’s
analytical engine.
3.5.14
UNUSED FIELDS
These fields are not used by the model.
3.5.15
MATURITY MATRIX FOR INNER CDOS AND EXPOSURE MATRIX FOR INNER CDOS
Please see section Section 3.9.
3.6
USING THE CDOROM FEED
The CDOROM Feed is a daily FTP service provided by Moody’s that contains the information on corporate issuers needed by CDOROM
when they are referenced on the Portfolio(s) page:
»
»
Rating
Parent entity name
»
»
Industry code
Country
The Feed also contains MIR data, and is able to identify corporate issuers using some ISIN, CUSIP, and RED codes (subject to availability) as
well as entity name or organization number.
The feed is a subscription based service - please contact Moody’s for more information. A “RefMaster” workbook is available at no charge
from Moody’s - this does not contain rating, MIR or RED data.
MOODY’S CDOROM™ V2.12 USER GUIDE
23
MOODY’S INVESTORS SERVICE
MOOD
3.6.1
Structured Finance Group
SETUP
In CDOROM on the Portfolio(s) worksheet, click Configure Feed. A window appears that asks for a CDOROM FTP Feed Client ID. This will
be provided by Moody’s and is distinct from Moodys.com website logins.
Leave the ID field blank if you do not have a subscription to the Feed. CDOROM will then use the original RefMaster system by default.
See the next section for more information. Note that the ID is stored in the system registry, not in the CDOROM file.
Tick the Use alternative download method option if you have problems connecting to the feed. The Test button can be used to check
whether the connection can be made to the Moody’s FTP server.
The Update with RefMaster button will be renamed to Update with Feed when the Feed has been configured.
3.6.2
DOWNLOADING THE LATEST FEED FILE FROM THE FTP SERVER
CDOROM will automatically download the latest feed data the first time that CDOROM is used each day. The feed data will be stored in a
file specified by the option in RefData Table 6: Path and File name for temporary CDOROM Feed File. Path and Filename for temporary
CDOROM Feed file.
Path and Filename for temporary CDOROM Feed file
.\Feed_Cache.xls
To force CDOROM to re-download the latest data, delete the existing Feed_Cache.xls file and click Update with Feed on the
Portfolio(s) sheet.
If CDOROM is stored in multiple locations on your system, each copy of CDOROM will store the Feed_Cache.xls file in its own folder by
default. You may wish instead to specify a single location on your system where the feed cache file is stored, using the option above.
3.6.3
UPDATING THE PORTFOLIO USING THE FEED
Corporate issuers may be identified by organization number, ISIN, CUSIP, RED code (if available) or name. Specify the type of ID that is
being used in the ID Type column, and the ID itself in the Org Number/ID column. If ID Type is left blank, CDOROM assumes that any
value in Org Number/ID is an organization number...
MOODY’S CDOROM™ V2.12 USER GUIDE
24
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
In order to identify the issuer by name without knowing an ID, enter the entity name in the Reference Entity column and leave Org
Number/ID blank. If the issuer name is recognised, the Org Number/ID column will be populated with the ID according to the selection
in the ID Type field. If both a name and an ID are specified, the ID takes precedence.
Click on the Update with Feed button to update the portfolio data with the data from the feed.
3.6.4
INEXACT NAME MATCHES
If an issuer is identified by name only, and there are no exact matches in the Feed, a window will appear allowing the user to manually
select which issuer the name refers to.
3.6.5
RESULTS OF THE FEED UPDATE
Call-out style comments will be added to the portfolio sheet to describe any problems that occurred trying to locate an entity in the Feed;
for example, the ID or Name not being known.
When an entity is found in the Feed, the Rating, Country, Industry Code and Parent Entity Name fields in the portfolio will be
overwritten with the information from the Feed. Comments are used to indicate which cells have been changed (if they weren’t blank
before). These comments are indicated by a red triangle in the top-right corner of the cell. Place the mouse cursor over the cell to see the
comment.
If the rating in the Feed was not directly taken from the issuer, but derived according to Moody’s rules for determining an implied rating, a
comment will be added to the rating cell indicating where the rating comes from.
The rating comments are also given in a column on the far right of the portfolio page.
To clear these comments from the portfolio(s) sheet, select the cells, right click and select Delete Comment.
MOODY’S CDOROM™ V2.12 USER GUIDE
25
MOODY’S INVESTORS SERVICE
MOOD
3.6.6
Structured Finance Group
IMPORTING RO SENIORITY FROM THE FEED
The feed contains some information on reference obligations for corporate issuers. If the ID that is used to identify an issuer in CDOROM is
reference obligation specific ( e.g., a 12-digit ISIN, 12-digit CUSIP or 9-digit RED code), the Feed will also import the seniority of the
reference obligation (SU/SB).
A message will appear informing the user if any of the seniority inputs in the portfolio page have been changed.
3.6.7
MARKET IMPLIED RATINGS
To run CDOROM with MIRs, copy and paste the MIR Gap data into the Notching column.
3.7
USING THE REFMASTER IMPORT
Subscribers to Moody’s CDOROM Data Feed may skip this section.
RefMaster is a spreadsheet provided by Moody’s that contains the country, industry code and parent entity information for a large universe
of corporate assets known to Moody’s. Using the RefMaster Import saves time. Enter the organization number and/or name of the entities
in the portfolioand then use the RefMaster Import to automatically populate the portfolio sheet with rest of the information.
3.7.1
SETUP
The path to the RefMaster spreadsheet must be specified in Table 6 of the CDOROM RefDatasheet, Link Settings and Advanced Options.
Path and Filename for RefMaster import
C:\MDYs_RefMaster_Q404a.xls
Contact information for obtaining CDOROM and the RefMaster spreadsheets from Moody’s are given at the start of this document.
3.7.2
IMPORTING FROM REFMASTER
Enter either the Moody’sorganization number or the entity name in the portfolio sheet. Press the Update with RefMaster button to start
the RefMaster import.
3.7.3
RESULTS OF THE REFMASTER IMPORT
Call-out style comments will be added to the portfolio sheet to describe any problems that occurred trying to locate an entity in the
RefMaster; for example, the organization number or name not being known.
When an entity is found in RefMaster, the Country, Industry Code and Parent Entity Name fields in the portfolio will be overwritten
with the information from the RefMaster. If the RefMaster file has a column including ratings (with a header named ”Rating”), this data will
be imported and will overwrite the existing value in the portfolio(s) sheet’s Rating column.
3.8
SHOW DATA
The Show Data button on the portfolio(s) sheet can be used to validate the inputs before moving to the Calculation sheet to specify
tranching and/or run the Monte Carlo simulation. It will enable the Summary Columns to the right of the worksheet. Note that the
summary columns can also be enabled through the Choose Fields window.
In CDOROM, the summary data, on all portfolio sheet(s) as well as the Portfolio Summary sheet, is updated whenever any of the
following buttons are pressed in the model: Show Data, Run Simulation, Update (Portfolio Summary), Regenerate the Matrix
(Asset Correl Matrix)
In the case of CDO^2 any fields for which the values vary between the inner CDO exposures will be populated with the text (varies).
Industry name
MOODY’S CDOROM™ V2.12 USER GUIDE
Parent Continent
(Region Code),
Country
RR
Tier
CE Type
CE
Stress
Total Dp
Stress Applied
Theoretical RR used to
calculate DP (was
Theoretical ABS RR)
CE RR
Haircut
Total RR
Haircuts RR Mean
(CE ,Extra)
RR Std
Dev
Default
Prob
26
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Industry Name
Gives the full industry name specified by the Industry/ABS Sector Code input.
Parent Continent (Region Code), Country
For corporate exposures, this field will contain the results of the Parent Sector Region rules. For ABS exposures, this field will indicate the
highest rating of all exposures to the same transaction in the portfolio, which will be used for the purpose of calculating the ABS
correlations.
RR Tier
The recovery rate tier of the entity. Determined using the country input and used to calculate the recovery rate.
CE Type
The credit event type chosen for the entity. This is normally determined by the information on the calculation sheet (See Section 2.5.11)
or on a per-exposure basis using the Credit Event Override field.
CE Stress
The stress on the default probability due to the Credit Event definition.
Total Dp Stress Applied
This is the sum of the CE Stress, any additional DP stress, and any other default probability stress factors being applied automatically by
CDOROM.
Theoretical RR is used to calculate DP (was Theoretical ABS RR).
This indicates the recovery rate on the basis of which the Rating input was converted into a default probability. This is normally 45% for
corporate exposures, but may vary for ABS exposures as per the ABS methodology.
CE RR Haircut
This is the haircut applied to the recovery rate determined by the credit event definition for this entity.
Total RR Haircuts (CE ,Extra)
The sum of the RR haircuts applied.
RR Mean
The recovery rate mean that will be used if random recoveries are to be used for this exposure, or the fixed recovery rate level that will be
used if recoveries are fixed.
Std Dev
The recovery rate standard deviation used in the RR modelling, if random recovery rates are being applied to this entity.
Default Prob
The probability of default associated with the rating and maturity of this asset, after all CE and DP stresses have been applied. Please note
that CDOROM versions 2.4 and earlier showed the gross DP before stress.
MOODY’S CDOROM™ V2.12 USER GUIDE
27
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
3.9
ADDING INNER CDOS FOR CDO^2 MODELLING
Please note that the way in which CDO^2 structures are described in CDOROM version 2.5 & later is significantly different from earlier
versions of CDOROM. Users familiar with CDOROM version 2.4 are advised to read this section carefully.
Generally, a tranche exposure can be added to any portfolio sheet to describe a synthetically tranched exposure to a sub-portfolio described
on another worksheet. A single sub-portfolio sheet may be used with an exposure matrix specifying the exposure of each name to each
inner CDO, or separate portfolio worksheets may be added for each inner CDO. Both approaches may be combined.
3.9.1
ADD INNER CDO …
On the portfolio(s) sheet press the Add inner CDO button to create a new portfolio sheet for the underlying exposures. Give the sheet a
name such as “Underlying”. Populate the portfolio as normal, enabling ABS exposure inputs, corporate exposure inputs or any other
required fields using the Choose Fields button on the new portfolio sheet.
3.9.2
EXPOSURE MATRIX FOR INNER CDO
In order to use an exposure matrix to specify the underlying exposures, click Choose Fields on the underlying portfolio worksheet and
enable the Exposure Matrix for Inner CDO fields.
Exposure Matrix - use by specifying column index in Tranche reference e.g. InnerCDOSheet:1
1.0
0.0
1.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1
2
3
4
5
6
7
8
9
10
1.0
0.0
1.0
0.0
1.0
1.0
0.0
0.0
0.0
1.0
1.0
0.0
Use the same currency for all notional amounts. On the portfolio sheet where the Tranche exposure is described (see below) populate the
Reference Entity Name field with the name of this underlying portfolio worksheet, followed by a colon, followed by the index of the
column in the matrix to be read.
3.9.3
THE INNER CDO FIELDS
The Inner CDO fields will automatically have been enabled by CDOROM when the Add inner CDO button was used; however they can
also be enabled using the Choose Fields button.
Type
Enter Tranche in the Type column to indicate that the row describes a synthetically tranched exposure to a portfolio described on
another worksheet.
Reference Entity
Enter the name of the worksheet that contains the underlying portfolio, followed by a colon and the column number for which the exposure
amounts should be read from the exposure matrix (1 = the first column).
If the colon and column number are omitted and just the worksheet name is given then the amounts are read from the underlying
worksheet’s Amount column.
MOODY’S CDOROM™ V2.12 USER GUIDE
28
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Amount
Enter the size of the tranche in currency. To calculate it from a percentage use a formula reference to the total portfolio exposure. For
example: “=’Underlying’!BZ9*3%”
Credit Enhancement
Enter the credit enhancement of the tranche, in currency. To calculate it from a percentage use a formula reference to the total portfolio
exposure. For example “=’Underlying’!BZ9*3%”
Inclusion Multiplier
Enter 100% to include the tranche normally in the CDO^2 structure. Other values will effectively scale the exposure to the inner CDO
tranche. Negative values indicate short tranches.
Spread / Coupon
CDOROM will output the tranche EL, WAL, Moody’s Metric and rating on the portfolio sheet so this input provides the equivalent of the
wwap rate + spread inputs on the calculation sheet. This value does not affect the losses of the repacked CDO^2 structure.
Tranche EL, Var, WAL, MM, SU Rating
These fields measure the expected loss of the inner CDO tranche and its rating and Moody’s Metric benchmarks. They are not used by
CDOROM’s analytical engine for any other purpose.
3.9.4
SPECIFIC MATURITY PER INNER CDOS
This is implemented using the Specific WAL per Asset field on the tranche exposure. It effectively caps the maturity of all the underlying
exposures. If the underlying exposures have no specific maturity defined then the underlying exposure’s maturity is assumed to equal the
WAL entered for the tranche.
MOODY’S CDOROM™ V2.12 USER GUIDE
29
MOODY’S INVESTORS SERVICE
MOOD
4
Structured Finance Group
Reference Data: The ‘RefData’ Sheet
Reference data used by the model in the implementation of the various methodologies can be found on the RefDataworksheet.This
section describes these inputs as well as providing additional information on how the model implements the methodologies and applies
the assumptions.
Additionally there are some technical settings on this worksheet (Table 6)
MOODY'S CDOROM™: Reference Data
Version: CDOROMv2.10-9 2013-09-03
Corporate (CORP)
Reference data applicable to all asset types
Table C1: Sector Codes, Correlations
Table 1: Country Definitions : ISO, Region, Recovery Tier, Credit Event Type
Table C2: Adverse Selection Stress
Table 2: Credit Event Definitions: DP Stresses and Recovery Rate Haircuts
Table C3: Recovery Rates
Table 3: Moody's Rating IG/NIG
Table C4: Emerging Market Methodology
Table 4: Moody's Expected Loss Tables
ABS
Table 5: Recovery Rate Correlation
Table ABS1: Sector Codes, Key Agent Definitions, Correlations
Table 6: Link Settings and Advanced Options
Table ABS2: Resecuritisation Stress
Table ABS3: Recovery Rates
Table ABS4: Wrapper / Guarantor List
US Trust Preferred Securities (TRUPS)
Table TRUP1: Sector Codes, Correlations
Table TRUP2: Recovery Rates and Correlations
US Municipal (MUNI)
Table MUNI1: Sector Codes, Recovery Rates, Correlations
Table MUNI2: Notching
4.1
REFERENCE DATA APPLICABLE TO ALL ASSET TYPES
4.1.1
TABLE 1 – COUNTRY DEFINITION
Table 1 contains a list of countries, with the corresponding ISO codes, regions and recovery tiers. This table has not been reproduced in this
document due to its size. Note that both region and tier can be modified manually by the user.
The foreign currency bond ceiling (FXBC) ratings of the countries are also given in this table and should be updated when modelling
portfolios with emerging market exposure.
Below Table 1 is a list of organization numbers for which Tier G recovery assumptions should be applied.
4.1.2
TABLE 2 - CREDIT EVENT DEFINITIONS: DP STRESSES AND RECOVERY RATE HAIRCUTS
This table contains a list of the standard credit event types with the corresponding default probability stresses and recovery rate haircuts.
These values are used when specifying the credit event types in the calculation sheet or on a per-exposure basis.
The abbreviations used are as follows:
»
»
Corp = Corporate exposure
Sov = Sovereign exposure
»
»
ProjFin = Project finance exposure
ABS = ABS exposure
MOODY’S CDOROM™ V2.12 USER GUIDE
30
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
» MR = Modified restructuring
»
»
»
MMR = Modified modified restructuring
OR = Old restructuring
NoR = No restructuring
»
»
OA = Obligation acceleration
MHO = Multiple holder obligation
»
»
BO= Bond only
RML = Restructuring maturity limitation
4.1.3
TABLE 3 – MOODY’S RATING IG/NIG
Table 3 contains the list of Moody’s ratings with the corresponding IG/NIG level, metrics higher limit and metrics lower limit.
4.1.4
TABLE 4 - MOODY’S EXPECTED LOSS TABLES
The Moody’s expected loss tables are given for user reference only.
4.1.5
TABLE 5 – RECOVERY RATE CORRELATION
Recoveries are correlated based on the value entered here. Recoveries may be correlated amongst themselves, or with the global (or inter-)
factor in simulating default probabilities.
4.1.6
TABLE 6 – LINK SETTINGS AND ADVANCED OPTIONS
File and Folder locations
Path that contains the CDOROMv2.X-Y.dll file: This indicates where the .dll file should be loaded from. See Section 1.3.2 Manually
Specifying the CDOROM DLL Location for complete details on how to install the model.
The following two inputs are of interest to clients of the Moody’s CDOROM API only:
Standard Assumptions File (XML, optional): This is the path to an assumptions.xml file. Entries in this file will be excluded from the
XML generated by the second option;
Filename to log XML passed to CDOROM Engine: Specify the path of an .xml file that will be populated with all the data read from or
written to the workbook, excluding data that matches the data in the assumptions file specified above.
Path and Filename for RefMaster import (if Feed not used): If not using the Moody’s CDOROM Data Feed, the path to the reference
entity File can be put in here. See section 3.7 for more details.
Path and Filename for temporary CDOROM Feed file: If for any reason the %TEMP% folder cannot be used to temporarily store
downloaded data feed files, an alternative path and filename can be specified here.
Advanced CBET Options
Input fixed "N" Value: When calculating the MAC, the number of assets N in the CBET distribution is fixed to the given “N” value.
Input fixed “WARR” Value: When calculating the MAC, the pool WARR is fixed to the given value. See Section 9.9 for more information
about the Correlated Binomial Methodology.
Model Managed Deals: Apply pre February 28 2005 test definition: Tick the check box if you use CDOROM to manage a deal whose
documentation refers to pre-February 28 2005 test definitions
MOODY’S CDOROM™ V2.12 USER GUIDE
31
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Model Managed Deals: Test 1 - Use of buffer is unrestricted: Tick the check box if you use CDOROM to manage a deal using Test 1
and whose documentation refers to the use of an unrestricted buffer.
Maturity override for 100% DP assets (years)
Assets with a default probability of 100% will be assumed to have the specified WAL for the purpose of portfolio and tranche WAL
calculations. To disable this and let the portfolio and tranche WAL calculations consider the defaulted asset’s WAL entered on the
portfolio(s) sheet or set via the global maturity input on the Calculation sheet, set this field to -1.
Include 100% DP assets in overconcentration calculation
This affects the old overconcentration stress calculations, which are disabled by default from v2.12 onwards in accordance with the
updated methodology. This input would only have effect if the over-concentration stresses are enabled in 4.2.1 Table C1 – Sector
Codes, Correlations.
Use MultiFactor Model
This should normally be set to “true” to enable the new Multi-Factor Model. It would only be set to “false” if the Correlation Matrix model
is required. Note that when the Correlation Matrix model is used, stochastic correlations will not be available so the standard corporate
methodology will not be able to be used. Please contact Moody’s to discuss the parameters if using the correlation model.
4.2
CORPORATE (CORP)
4.2.1
TABLE C1 – SECTOR CODES, CORRELATIONS
These tables contain the full list of corporate sectors and the various characteristics relevant for the implementation of the corporate
exposure methodology. Values in blue may be modified by the user. Please note that the Import and Clean Inputs functions will not reset
these values, so to revert to Moody’s original assumptions please start with a fresh copy of the Moody’s CDOROM workbook (available
from Moodys.com).
The table will be explained in sections. The first section provides basic information about the sectors:
Table C1: Sector Codes, Correlations
Moody's Sector
Code
>Back to top
Sector Nam e
Map to
Global/ Local Classification
101
CORP - Aerospace & Defense
101
Medium
G
102
103
CORP - Automotive
CORP - Banking
102
103
Medium
High
G
G
104
CORP - Beverage, Food & Tobacco
104
Medium
SL
105
CORP - Capital Equipment
105
Medium
SL
106
CORP - Chemicals, Plastics, & Rubber
106
Medium
G
107
CORP - Construction & Building
107
High
SL
108
CORP - Consumer goods: Durable
108
Medium
SL
109
CORP - Consumer goods: Non-durable
109
Medium
SL
110
CORP - Containers, Packaging & Glass
110
Medium
SL
111
CORP - Energy: Electricity
111
Medium
SL
112
CORP - Energy: Oil & Gas
112
Medium
G
113
CORP - Environmental Industries
113
Medium
L
114
CORP - FIRE: Finance
103
High
G
115
CORP - FIRE: Insurance
103
High
G
116
CORP - FIRE: Real Estate
103
High
G
117
CORP - Forest Products & Paper
117
Medium
SL
118
119
CORP - Healthcare & Pharmaceuticals
CORP - High Tech Industries
118
119
Medium
Medium
SL
G
120
CORP - Hotel, Gaming & Leisure
120
Medium
SL
121
122
CORP - Media: Advertising, Printing & Publishing
CORP - Media: Broadcasting & Subscription
121
122
Medium
Medium
SL
SL
123
124
CORP - Media: Diversified & Production
CORP - Metals & Mining
123
124
Medium
Medium
G
G
125
CORP - Retail
125
Medium
SL
126
CORP - Services: Business
126
Medium
SL
127
CORP - Services: Consumer
127
Medium
SL
128
129
CORP - Sovereign & Public Finance
CORP - Telecommunications
128
129
Medium
Medium
L
G
130
CORP - Transportation: Cargo
130
Medium
SL
131
CORP - Transportation: Consumer
131
High
SL
132
133
CORP - Utilities: Electric
CORP - Utilities: Oil & Gas
132
133
High
High
L
L
134
135
CORP - Utilities: Water
CORP - Wholesale
134
135
High
Medium
L
SL
MOODY’S CDOROM™ V2.12 USER GUIDE
32
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Map to: This indicates the sector code that should be used for the purpose of computation. By having Sector Codes 103,114,115 and 116 all
map to Code 103, it effectively models assets in any of these sectors as being in the same sector. By default, this table is configured to
reflect the standard assumptions in the corporate methodology.
Global/Local Classification
Although not directly read by the model, these cells serve as a reference and are used by cell formulas in the Same Industry Correlation
cells in order to lookup the correct factor weights.
The next section defines the global and intra-industry correlation levels:
Global (ABS-Corp)
This defines the correlation level between corporate and ABS exposures. The global factor (Stochastic) correlation levels may not be lower
than this value
Same industry and region correlation / Same industry correlation
These columns define the weight that an exposure would have to the “industry-region” and “industry” factors, respectively. The three
columns allow the weight to be stochastic, although at the time of publication of this user guide the industry factors are not stochastic. For
example, if 100% is entered as the first value and 0% for the following values, the weights in the second and third columns are not used by
the model.
Additional Correlation Stress
Allows additional correlation to be added to a sector. The additional weight on the factors will be
»
Sqrt(allocation to global factor x additional correlation) on the global factor
»
Sqrt( (1-allocation to global factor) x additional correlation) on the industry factor
MOODY’S CDOROM™ V2.12 USER GUIDE
33
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Over-concentration Stress
This displays the level of additional correlation being applied due to the “over-concentration stress” settings. It does not include the
additional correlation stress
Global Corporate Correlation
Next is a separate table that defines the stochastic global (inter-industry) correlations:
Global Factor (Stochastic) (must be greater than or equal to non-stochastic global)
Rating\Probability
Aaa
Aa1
Aa2
Aa3
A1
A2
A3
Baa1
Baa2
Baa3
Ba1
Ba2
Ba3
B1
B2
B3
Caa1
Caa2
Caa3
Ca (redundant)
70%
20%
10%
5.0000%
5.0000%
5.0000%
5.0000%
5.0000%
5.0000%
5.0000%
5.0000%
5.0000%
5.0000%
3.0000%
3.0000%
3.0000%
3.0000%
3.0000%
3.0000%
3.0000%
3.0000%
3.0000%
3.0000%
10.0000%
10.0000%
10.0000%
10.0000%
10.0000%
10.0000%
10.0000%
10.0000%
10.0000%
10.0000%
9.0000%
9.0000%
9.0000%
7.0000%
7.0000%
7.0000%
7.0000%
7.0000%
7.0000%
7.0000%
20.0000%
20.0000%
20.0000%
20.0000%
20.0000%
20.0000%
20.0000%
20.0000%
20.0000%
20.0000%
12.0000%
12.0000%
12.0000%
10.0000%
10.0000%
10.0000%
10.0000%
10.0000%
10.0000%
10.0000%
The three columns define the correlation levels for the three correlation scenarios, where each scenario has a probability given by the values
in the column headers (70%, 20%, 10% in the screenshot above). To revert to a fixed correlation format, simply enter 100% for one of the
states and 0% for the other two.
The weight on the global factor will be computed by taking the square root of the desired correlation level in the table, on the basis of the
rating of the exposure (after notching) and the scenario that has been chosen for the Monte Carlo scenario.
Over -concentration Stress
The “end point stress”being is set to 0% by default, to disable this stress, which was used in versions 2.5-2.8 only.
If enabled, the Over-concentration Stress function is f(C) = 30% * (C – Start Point) / (End Point – Start Point) where “C” is the
concentration in the given sector, and “C” is bound between the Start Point and End Point values.
MOODY’S CDOROM™ V2.12 USER GUIDE
34
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Summary of the Corporate Exposure Correlation Model
In summary, the correlation between two exposures will be the sum of
»
»
»
The global correlation for the stochastic scenario and rating level of the exposures. If the ratings are different, the geo-mean of the
values for the two exposure will effectively be applied
The same industry correlation, if they are in the same industry
The same industry region correlation, if they are in the same industry and region
» The over-concentration stress, if enabled (but by default it is not)
If the EM method applies, then the correlation value is modified by the emerging market correlation calculations. Please refer to Section
4.2.4 below.
4.2.2
TABLE C2 – ADVERSE SELECTION STRESS
The adverse selection stress will be applied in the following manner:
»
For the industry with the largest exposure in the portfolio, as well as any industry with a concentration over 15%, the default
probability of each credit within that industry is increased by the equivalent of –
OC adjustment = one notch + 2 x | max (0, OC MIR gap) |
»
For credits other than those in over-concentrated industries, a default probability adjustment equivalent of Non-OC adjustment = | max (0, Non-OC MIR gap) |
The calculations are made automatically and notching of the default probabilities are applied. The calculated stress value may be overridden
by entering values under “Notching Override.”
Adverse Selection Stress
Concentration Percentage w ith
Notching
OC Sector
2%
77%
Average MIR
1.1
0.0
0
3%
100%
0.1
0.0
0
22%
76%
-1.0
-3.0
1
6%
74%
1.2
0.0
0
3%
65%
-0.3
0.0
0
2%
64%
0.7
0.0
0
1%
25%
1.7
0.0
0
2%
67%
2.0
0.0
0
2%
85%
2.4
0.0
0
1%
100%
2.0
0.0
0
3%
67%
-0.5
0.0
0
5%
68%
0.3
0.0
0
0%
100%
2.8
0.0
0
0%
0%
0.0
0.0
0
0%
0%
0.0
0.0
0
0%
0%
0.0
0.0
0
2%
100%
3.1
0.0
0
4%
86%
3.6
0.0
0
2%
79%
-0.2
0.0
0
2%
44%
0.8
0.0
0
2%
34%
2.4
0.0
0
0%
100%
6.0
0.0
0
1%
100%
3.4
0.0
0
3%
67%
-1.3
0.0
0
8%
60%
0.9
0.0
0
1%
38%
-1.4
0.0
0
0%
0%
0.0
0.0
0
2%
100%
-2.5
0.0
0
9%
66%
0.6
0.0
0
1%
50%
5.0
0.0
0
2%
83%
-0.4
0.0
0
5%
63%
2.3
0.0
0
0%
0%
0.0
0.0
0
0%
1%
0%
100%
0.0
9.0
0.0
0.0
0
0
Total
72%
0.5
MOODY’S CDOROM™ V2.12 USER GUIDE
Notching
35
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
The average gap for all over concentrated industries as well as the portfolio-wide gap is also provided:
OC MIR Gap
Non OC MIR Gap
-1.02
1.04
Summary of the Corporate Exposure Default Probability Calculation
The SU/RO Rating input is first notched by the whole number of notches input in the Notching column, and the notching required by the
adverse selection stress. It is then converted to an expected loss (EL) using the idealized expected loss tables and the weighted average life
(WAL) of the exposure.
The exposure default probability (DP) is calculated as
DP = EL * DP_Factor * (1 + CE_Stress + DP_Stress) / (1 – 45%)
Where,
»
»
DP_Factor is an adjustable point in time stress
CE_Stress is the credit event DP stress
»
DP_Stress is additional DP stress entered by the user using the Add DP Stress column in the Portfolio(s) sheet
Fractional Notching column values are applied by logarithmically interpolating the implied DP that would be obtained using the ratings
above and below the exact notching required. When the adverse selection adjustment is enabled, an adjustment in the form of additional
default probability stress will be applied at the reference level.
4.2.3
TABLE C3 – CORPORATE RECOVERY RATE AND STANDARD DEVIATION
These tables contain the recovery rate mean and standard deviation assumptions for corporate exposures in various tiers and seniorities.
The recovery rate tier is determined using the tier value for the country that the exposure is domiciled in. The seniority is determined from
the seniority input on the Portfolio(s) sheet.
MOODY’S CDOROM™ V2.12 USER GUIDE
36
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Table C3: Recovery Rates
Tier
Corporate Recovery Rate Means
SS-1st Lien
SS-Loan
>Back to top
SS-Other
SU-Loan
SU
SB
FG
A
60.0%
60.0%
45.0%
35.0%
35.0%
25.0%
0.0%
A <Baa2
60.0%
60.0%
45.0%
35.0%
35.0%
25.0%
0.0%
B
C
60.0%
60.0%
60.0%
60.0%
45.0%
45.0%
35.0%
35.0%
35.0%
35.0%
25.0%
25.0%
0.0%
0.0%
D
60.0%
60.0%
45.0%
35.0%
35.0%
25.0%
0.0%
E
60.0%
60.0%
45.0%
35.0%
35.0%
25.0%
0.0%
F
60.0%
60.0%
45.0%
35.0%
35.0%
25.0%
0.0%
G
60.0%
60.0%
45.0%
35.0%
35.0%
25.0%
0.0%
JP
60.0%
60.0%
45.0%
35.0%
35.0%
25.0%
0.0%
US
60.0%
60.0%
45.0%
35.0%
35.0%
25.0%
0.0%
ABS
0.0%
0.0%
0.0%
0.0%
75.0%
0.0%
0.0%
Corporate Recovery Rate Standard Deviations
Tier
SS-1st Lien
SS-Loan
SS-Other
SU-Loan
SU
SB
FG
A
25.0%
30.0%
30.0%
30.0%
30.0%
25.0%
0.0%
A <Baa2
25.0%
30.0%
30.0%
30.0%
30.0%
25.0%
0.0%
B
25.0%
30.0%
30.0%
30.0%
30.0%
25.0%
0.0%
C
D
25.0%
25.0%
30.0%
30.0%
30.0%
30.0%
30.0%
30.0%
30.0%
30.0%
25.0%
25.0%
0.0%
0.0%
E
25.0%
30.0%
30.0%
30.0%
30.0%
25.0%
0.0%
F
G
25.0%
25.0%
30.0%
30.0%
30.0%
30.0%
30.0%
30.0%
30.0%
30.0%
25.0%
25.0%
0.0%
0.0%
JP
US
25.0%
25.0%
30.0%
30.0%
30.0%
30.0%
30.0%
30.0%
30.0%
30.0%
25.0%
25.0%
0.0%
0.0%
ABS
0.0%
0.0%
0.0%
0.0%
1.0%
0.0%
0.0%
There is an exception for sovereign exposures to governments, which are identified either by their org number (a list is given below Table 1
of the RefData sheet) or by having “G” input in the Seniority column.
Recovery rates specified by the user using the RR inputs on the Portfolio(s) sheet will override these assumptions.
Recovery Rate Haircut
The mean and standard deviation describe a beta distribution from which the random recoveries will be drawn. These are subsequently
haircut by this formula:
Final_Recovery = Random_Recovery * (1 – CE_Haircut) * (1 – RR_Haircut)
Where,
»
»
CE_Haircut is the cheapest-to-deliver RR haircut, unless fixed recoveries are specified by the user in which case CE_Haircut is zero
RR_Haircut are additional RR haircuts specified by the user in the Add RR Haircut column of the Portfolio(s) sheet
Recovery Rate Correlation
If a value is entered here, then random recoveries are correlated at this level between all exposures assuming a beta distribution. Exposures
that have 100% asset correlation for defaults are given 100% correlated recovery rate processes also.
4.2.4
TABLE C4 – EMERGING MARKET CDOS
MOODY’S CDOROM™ V2.12 USER GUIDE
37
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
These tables are used specifically for the modeling of emerging market CDOs.
The global (or inter-) correlation is inputted in the Inter-Region Sovereign Correlation field.
Inter-Region Sovereign Correlation
1%
Moody’s designates high or low levels of contagion risk in each region and attributes high and low correlations accordingly. The Intra-region
Sovereign Correlation table contains these designations and assigned correlation values.
Intra-Region Sovereign Correlation
Level
g
Purposes
Correlation
1
North America
Low
10% 1
US
2
Europe
Low
10% 2
EU
3
6
Asia
Eastern Europe & Former Soviet Union
High
High
25% 3
25% 6
AP
EU
7
Indian Subcontinent
High
25% 7
8
Middle East & North Africa
Low
10% 8
9
Central America
Low
10% 9
10
South Africa
High
25% 10
11
South America
High
25% 11
12
Sub-Saharan Africa
High
25% 12
13
Supranational
N/A
0% 13
The table of W EM values corresponds to weights between a reference entity and its sovereign and are inputted in the Wem – Sovereign
Correlation Level by Rating field.
Wem - Sovereign Correlation Level by Rating
Wem
Aaa
0.00%
Aa1
0.00%
Aa2
0.00%
Aa3
3.64%
A1
4.01%
A2
4.64%
A3
Baa1
5.38%
6.38%
Baa2
Baa3
7.63%
10.74%
Ba1
14.85%
Ba2
19.95%
Ba3
25.13%
B1
30.79%
B2
37.01%
B3
46.60%
Caa1
62.54%
Caa2
84.09%
Caa3
100.00%
MOODY’S CDOROM™ V2.12 USER GUIDE
38
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
4.3
ABS
4.3.1
TABLE ABS1 – SECTOR CODES, KEY AGENT DEFINITIONS, CORRELATIONS
These tables define the correlation between a pair of ABS assets. The correlation applied by the model is the sum of the add-ons
determined as described below. Table ABS1 is reproduced below for illustration purposes only
Moody's
Sector
Code
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
Sector Name
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
ABS
- Consumer - Cons.ABS - Auto
- Consumer - Cons.ABS - Credit Card and other Consumer Unsecured Lo
- Consumer - Cons.ABS - Student Loans
- Consumer - RMBS - Prime
- Consumer - RMBS - Subprime
- Consumer - RMBS - CDO of RMBS
- Consumer - RMBS - Manufactured Housing
- Consumer - Div.SF.CDO - CDO of SF - Diversified
- Corporate - CRE - REIT - Hotel
- Corporate - CRE - REIT - Multi family
- Corporate - CRE - REIT - Office
- Corporate - CRE - REIT - Retail
- Corporate - CRE - REIT - Industrial
- Corporate - CRE - REIT - Healthcare
- Corporate - CRE - REIT - Self-storage
- Corporate - CRE - REIT - Diversified
- Corporate - CRE - CMBS - Credit Tenant Lease
- Corporate - CRE - CRE CDO
- Corporate - CRE - CMBS - Diversified
- Corporate - CRE - CMBS - Office
- Corporate - CRE - CMBS - Retail
- Corporate - CRE - CMBS - Hotel
- Corporate - CRE - CMBS - Industrial
- Corporate - CRE - CMBS - Nursing Home
- Corporate - CRE - CMBS - Residential/Multi-Family
- Corporate - CRE - CMBS - Warehouse / Self-storage
- Corporate - CRE - CMBS - Healthcare
- Corporate - Specific - Tax Lien
- Corporate - Specific - Mutual Fund Fees
- Corporate - Specific - Structured Settlement
- Corporate - Specific - Utility Stranded Cost
- Corporate - Specific - Big Ticket Lease
- Corporate - Specific - IP (including Entertainment Royalties)
- Corporate - Specific - Dealer's Floorplan
- Corporate - Specific - Tobacco Bonds
- Corporate - Corp.CDO - Market Value CDO & CDO^2
- Corporate - Corp.CDO - CDO exposed to IG
- Corporate - Corp.CDO - CDO exposed to HY
- Corporate - Corp.CDO - CDO exposed to EM
- Corporate - Corp.CDO - ABS or CDO exposured to SME risk
- Corporate - Corp.CDO - CDO - Franchise Loans
ABS
Map to, for
Recovery
correlatio
Cat. (Table
n only
4c)
136
137
138
140
140
140
140
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
1
1
1
2
2
4
2
5
6
6
6
6
6
6
6
6
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
4
5
5
4
5
4
Originator
Originator
Originator
Originator
Originator
Arranger
Originator
Manager/Arranger if static
NA
NA
NA
NA
NA
NA
NA
NA
NA
Manager/Arranger if static
NA
NA
NA
NA
NA
NA
NA
NA
NA
Servicer
Manager
Servicer
NA
Servicer
Originator
Seller
NA
Manager/Arranger if static
Manager/Arranger if static
Manager/Arranger if static
Manager/Arranger if static
Manager / Originator
Originator
Key
Managed
unless
Agent
Penalty specified?
15%
15%
15%
15%
15%
15%
15%
20%
0%
0%
0%
0%
0%
0%
0%
0%
0%
20%
0%
0%
0%
0%
0%
0%
0%
0%
0%
20%
20%
20%
0%
20%
20%
20%
0%
0%
20%
20%
20%
20%
20%
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
TRUE
TRUE
TRUE
TRUE
TRUE
Additional Factors
Correlation 'Tree'
Assum e
Key Agent
Global
Meta
Broad
Narrow
CLO
Real
Estate
Consumer
5.00%
Consumer ABS
5.00%
Same Country
5.00%
RMBS
7.00%
Same Country
5.00%
Div.SF.CDO
5.00%
Same Country
5.00%
5.00%
7%
7%
7%
0%
0%
0%
0%
7%
12%
12%
12%
12%
12%
12%
12%
2%
12%
12%
2%
12%
12%
12%
12%
12%
12%
12%
12%
27%
27%
27%
27%
27%
27%
27%
100%
100%
17%
0%
17%
17%
17%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
17%
0%
17%
0%
0%
0%
0%
0%
0%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
5%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
0%
Same Country
10.00%
from above
3.00%
Corporate Related
5.00%
CRE
5.00%
Same Country
5.00%
Same Country
0.00%
Same region add-on
(regardless of sector)
5.00%
(halved for Global vs.
non-Global exposure)
Specific
0.00%
Same Country
0.00%
Corp. CDO
5.00%
Same Country
5.00%
All exposure pairs start with 3% global correlation (Global column above). This is also the correlation assumption for ABS-corporate
exposure pairs. Pairs of exposures that are in the same region (US, EU or AP) have an additional 5% add-on (same-region add-on). Globalglobal pairs get the full 5% add-on, while global-US and global-EU pairs get half the add-on (2.5%). global-AP pairs get 0% for this add-on.
Exposure pairs that are in the same meta sector (Meta column above) have an additional 5% add-on (consumer or corporate related). If a
pair of consumer meta sector exposures is also in the same country then there is an additional 10% add-on. Global-global pairs get the full
10% add-on and global-non-global pairs get no ”same-country” add-on.
Exposure pairs that are in the same broad sector have an additional correlation given in the Broad column of the table above (e.g. 7% for
RMBS). If the exposures are also in the same country then an additional add-on may apply (e.g. 5% for RMBS). Global-global pairs get the
full same-country add-on but global-non global pairs get no add-on.
Exposure pairs in the same narrow sector have the specified additional correlation (Narrow column in the table above). If the exposures are
also in the same country, then a further 5% correlation is added (the value at the top of the Narrow column). Global-global pairs get the
full same-country add-on but global-non global pairs get no add-on.
MOODY’S CDOROM™ V2.12 USER GUIDE
39
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Key Agent
Exposures in the same broad sector (not specific sector as before) that have the same key agent, as defined in the table above, are given an
additional correlation add-on as shown.
Additional factors
The CLO and real estate factors introduce additional correlation between pairs of assets as specified in the last two columns of the table
above (e.g. RMBS and CRE have an additional 5% correlation).
Vintage Penalty
The second part of Table ABS1 is the Vintage Penalty Add-On table. It is reproduced here for illustrative purposes only.
ABS Vintage Penalty Add-Ons
Sam e Meta
Global
Global
Same Region
Same Country
2%
0%
0%
Sector
Sam e Specific
Sam e Broad Sector
Sector
Cons.ABS
3%
0%
5%
0%
5%
5%
Consumer
0%
0%
5%
Real-Estate
0%
5%
5%
RMBS
Global
Same Region
Same Country
0%
0%
5%
5%
0%
5%
0%
0%
5%
Real-Estate
Div.SF.CDO
0%
0%
5%
Global
Same Region
Same Country
CRE
Same Country
3%
0%
0%
0%
5%
5%
Global
Corporate
0%
10%
5%
Global
Same Region
0%
5%
0%
Corp.CDO
Same Region
Same Country
0%
5%
5%
Specific
Global
Same Region
Same Country
0%
10%
5%
0%
5%
5%
With reference to the table above, the vintage penalty correlation add-on between a pair of exposures is calculated as follows (note that
before adding the vintage penalty add-on to the total pair-wise correlation value, there is an adjustment based on the time difference
between issue dates, as described below).
The vintage penalty add-on is calculated by working through the table above from left to right. Each set of three add-ons is applied
as follows:
»
»
»
the Global add-on is always applied
the Same Region add-on is only applied if the two exposures are in the same region (or both exposures are Global). Global-EU and
Global-US pairs get half the stated same region add-on and Global-AP pairs get no add-on at this level.
the Same Country add-on is only applied if the two exposures are in the same country (or both exposures are Global). Global-non
Global pairs get no add-on at this level.
The Same Meta Sector column specifies the add-ons that apply if the two exposures are in the same meta sector
The Same Broad Sector column specifies the add-ons that apply if the two exposures in the same broad sector
The Same Specific Sector column specifies add-ons that apply (based on the broad sector that the narrow sector belongs to) when the
two exposures are in the same narrow sector.
The Real Estate column specifies add-ons that apply when the two exposures are in any of the real-estate related sectors (CRE +
Div.SF.CDO + RMBS).
MOODY’S CDOROM™ V2.12 USER GUIDE
40
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
The total Vintage Penalty add-on is then multiplied by a factor based on the difference in years between the issue dates of the
two transactions.
Vintage Penalty Roll-Off
Decrease per Year
25.00%
16.67%
Static
Managed
The factor is 1x when the issue dates are the same and reduces linearly by an absolute 25% per year if the transactions are static, or 16.67%
per year if the two transactions are managed. The year difference is capped at four years so that two managed transactions never have less
than 1-4x16.67% = 33.33% of the vintage penalty.
The static/managed attribute of an exposure is based on the sector (as given in the table above) but can be overridden by the user. The
Correlation add-on between a static and a managed transaction is the geometric mean of the add-ons implied by static and managed.
Variation with Rating
The final pair-wise correlation value between a pair of exposures is then modified on the basis of the rating of the exposures.
ABS Correlation variation with rating
Scaling
Aaa-Aa
A
Baa-Ca
100.00%
93.33%
86.67%
The table is not interpolated. The scaling applied to a pair of exposures with different ratings is the geometric mean of the two applicable
scaling factors.
In order to facilitate correct modelling of 100% correlated exposures (same trust or transaction), the highest rating of the 100% correlated
group is used for the purpose of this calculation.
Master Trust Name and Transaction Name
Exposures issued by the same master trust or issued from the same transaction are considered to have 100% correlation. In order to ensure
a consistent correlation framework these exposures must have the same transaction name, closing date, country, key agent and sector.
100% Correlated Sectors (Tobacco, MV CDO)
In order to permit 100% correlation to be assumed within these sectors, exposures in them are assumed to have the following attributes »
Issue date = today
»
»
»
Key agent = none
Country = global
Managed = false
»
Transaction name = “100% Correlated Sector X”
Emerging Market Methodology
Although the methodology for emerging market ABS is not defined, CDOROM applies the Emerging Market Methodology consistently to
the entire correlation matrix, including correlations between and with ABS exposures, to ensure that the correlation matrix is positive
definite and describes a consistent correlation framework.
4.3.2
TABLE ABS2 – RESECURITISATION STRESS
The resecuritisation stress factor implied by the region, country and rating of the exposure as per the data in this table.
MOODY’S CDOROM™ V2.12 USER GUIDE
41
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Summary of the ABS Exposure Default Probability Calculation
The SU/RO rating input is first notched by the whole number of notches input in the Notching column, then it is converted to an expected
loss (EL) using the idealised expected loss tables and the weighted average life (WAL) of the exposure.
The exposure default probability (DP) is then calculated as DP = EL * DP_Factor * (1 + DP_Stress) / (1 – Theo_RR)
Where,
»
DP_Factor is the resecuritisation stress factor implied by the region, country and rating of the exposure as per the Resecuritization
Stress table in the RefData sheet.
»
»
DP_Stress are additional DP stresses entered by the user using the Add DP Stress column
Theo_RR is the recovery rate mean derived using the recovery categorisation, the initial size % of the exposure and the initial rating of
the ABS exposure. An initial rating of Ca or C implies a zero Theo_RR recovery rate.
Fractional Notching column values are applied by logarithmically interpolating the implied DP that would be obtained using the ratings
above and below the exact notching required.
4.3.3
TABLE ABS3 - ABS RECOVERY RATES
Table ABS3 contains the list of the ABS recovery rates, which depend on:
1)
the SF category
2)
the initial or current rating
3) the % of the tranche in the Initial deal.
MOODY’S CDOROM™ V2.12 USER GUIDE
42
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
The recovery rate mean is then derived using this categorisation, the initial size % of the exposure, and the current rating of the ABS
exposure. A current rating of Ca or C implies a zero mean recovery rate.
The recovery rate standard deviation is then calculated as StdDev = sqrt ( RR mean * ( 1 - RR Mean) ) * 70%
Note that the 70% factor can be modified in CDOROM. Recovery rates specified by the user using the RR inputs on the Portfolio(s) sheet
will override these assumptions.
The structured finance recovery rates can be applied by enabling the Use ABS Recovery Rates option in the RefData worksheet, Table 4d.
Use Current Rating to determ ine RR for calculation of DP
Use Current Rating to determ ine Recovery Rate
ABS Recovery Rate Standard Deviation Factor
ABS Recovery Rate Process
Use Alternative Recovery Rates?
4.3.4
FALSE
TRUE
70%
StdDev = sqrt ( RR mean * ( 1 - RR Mean) ) * Factor
Single Factor
FALSE
TABLE ABS4 – ABS WRAPPER / GUARANTOR LIST
Exposures with non-blank text in the Guarantor column are treated as corporate exposures to that insurance company, with no credit
event stresses applied. When specifying that an ABS exposure is wrapped or has a guarantor (see Section 3.3.3 for more details), the
wrapper/guarantor must be defined in this table so that the exposure can be correctly modeled as an insurance sector corporate exposure
on the wrapper/guarantor itself.
Table 7
Guarantor / Wrapper Name
ACA Financial Guaranty Corporation
Ambac Assurance Corporation
Radian Group Inc.
Financial Guaranty Insurance Company
Financial Security Assurance Inc.
MBIA Inc.
Assured Guaranty Corp
AXA
XL Capital Assurance Inc.
XL Financial Assurance Ltd.
Country
United States
United States
United States
United States
United States
United States
United States
France
United States
Bermuda
>Back to top
Parent Entity
AMERICAN CAPITAL ACCESS HOLD
AMBAC FINANCIAL GROUP, INC.
RADIAN GROUP INC.
FGIC ADVISORS, INC.
DEXIA GROUP (THE)
MBIA INC.
ASSURED GUARANTY LTD (BERMU
FINAXA
XL CAPITAL LTD
XL CAPITAL LTD
N.B. The name of the wrapper must exactly match the name of any other exposures in the portfolio that refer to the same entity
If the wrapper/guarantor is not listed in Table ABS4, additional entries may be specified using the empty rows in the table. If the
information for an existing entry is incorrect, please contact Moody’s.
MOODY’S CDOROM™ V2.12 USER GUIDE
43
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
4.4
US TRUST PREFERRED SECURITIES (TRUPS)
4.4.1
TABLE TRUP1 – REGIONAL CORRELATIONSS MATRIX
This table provides the intra-Regional correlation along the main diagonal, and the inter-Regional correlation elsewhere in the table:
Table TRUP1: Sector Codes, Correlations
1
2
3
>Back to top
4
5
6
7
8
9
10
11
12
1
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
2
3
10.00%
10.00%
45.00%
10.00%
10.00%
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
10.00%
10.00%
10.00%
45.00%
10.00%
10.00%
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
10.00%
4
10.00%
10.00%
10.00%
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
45.00%
10.00%
10.00%
5
10.00%
10.00%
10.00%
10.00%
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
45.00%
10.00%
6
10.00%
10.00%
10.00%
10.00%
10.00%
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
45.00%
7
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
8
10.00%
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
45.00%
10.00%
10.00%
10.00%
10.00%
9
10.00%
10.00%
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
45.00%
10.00%
10.00%
10.00%
10
10.00%
10.00%
10.00%
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
45.00%
10.00%
10.00%
11
10.00%
10.00%
10.00%
10.00%
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
45.00%
10.00%
12
10.00%
10.00%
10.00%
10.00%
10.00%
45.00%
10.00%
10.00%
10.00%
10.00%
10.00%
45.00%
e.g. two TruPS exposures in two different Regions (e.g. Region 1 and 2) would have 10% correlation. TwoTruPS exposures in the same
Region (e.g. RegionS RegionS 3) would have 45% correlation.
4.4.2
TABLE TRUP2 – RECOVERY RATES AND CORRELATIONS
This table defines the mean and standard deviation parameters for the recovery rate beta distribution for TruPS exposures.The same
recovery correlation figure used for corporate is also applied to the TruPS recovery processes.
4.5
US MUNICIPAL (MUNI)
These tables are used to implement assumptions to model municipal assets in Moody’s CDOROM. Table MUNI1 is used to store the
categorization of municipal assets into different sectors, the associated asset correlation assumptions, and recovery rates. Table MUNI2 is
used to store the expected uplift in public finance ratings based on the sector’s loss given default expectation.
MOODY’S CDOROM™ V2.12 USER GUIDE
44
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
MOODY’S CDOROM™ V2.12 USER GUIDE
45
MOODY’S INVESTORS SERVICE
MOOD
5
Structured Finance Group
Output Data: ‘Portfolio Summary’
5.1
GENERAL
This sheet summarises key information on the assets. The data is updated automatically when the Run Simulation, Show Data,
Regenerate Matrix or Update buttons are pressed.
MOODY'S CDOROM™: Portfolio Summary
Update
Table 1: Attributes
Table 2 and 3: CDO^1 Overlaps (Not available)
Table 4: Ratings (Graph and Data)
Table 5: Tiers (Graph and Data)
Table 6: Regions (Graph and Data)
Table 7: Industries (Graph and Data)
The picture above depicts the Portfolio Summary menu. Click on the hyperlinks to access each of the tables. On each table there will be a
Back to top hyperlink to go back to the menu and access other information.
5.2
ATTRIBUTES
Table 1: Attributes
All obligations (includes Ca/C/D)
WAEL (net)
- Implied Rating / Moody's Metric
Defaulted Obligations (rating = Ca/C/D)
Defaulted %
WARR of Defaulted
BET
Performing obligations (excludes Ca/C/D)
10y WARF (of Rating input only, excl. stresses & WAL)
- Implied Rating / Moody's Metric
WAEL (net of all stresses)
WAL
Implied Rating (From WAEL,WAL)
Diversity Score (Corp)
WADP (net of all stresses)
Implied WARF (From WADP, WAL)
Portfolio RR Mean (net of haircuts)
Portfolio RR Std Dev
Portfolio RR Systematic Risk
Average Pairwise Correlation
Largest Corp Issuer (% Corp)
- Issuer Parent Entity Name
ABS % (excludes w rapped ABS)
Caa %
Stresses
WA Credit Event DP Stress
WA Total DP Stress
WA Credit Event RR Haircut
WA Total RR Haircut
Portfolio(s)
2.9308%
Ba2 / 11.02
0.00%
0.00%
360.00
Baa2 / 9.00
2.9308%
5.00
Ba2 / 11.02
0.0000
3.7832%
722.85
23.20%
30.58%
7.13%
25.10%
0.00%
100.00%
0.00%
0.00%
142.40%
0.00%
0.00%
For each portfolio read by the model the following statistics are calculated. Each output is described in turn. Negative (short) exposures are
excluded from all calculations.
MOODY’S CDOROM™ V2.12 USER GUIDE
46
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
ALL OBLIGATIONS (INCLUDES CA/C/D)
WAEL (net)
This is the amount-weighted average of the net expected loss (EL) of all exposures in the portfolio (including defaulted exposures). It should
give the same EL as the undiscounted EL of a 0-100% tranche (subject to Monte Carlo convergence)
It may be defined as the amount-weighted average for all exposures of:
Exposure_Default_Probability * (1 – Exposure_Recovery_Mean * (1 – Exposure_Recovery_Haircut))
Implied Rating / Moody's Metric
Using a weighted-average life (WAL) calculated using all the exposures (not just the performing ones as for the WAL below), the WAEL (net)
above is converted into a rating.
DEFAULTED OBLIGATIONS (RATING = CA/C/D)
Note that exposures may have 100% default probability but not be rated Ca/C/D range (e.g. a Caa3 ABS exposure where the
resecuritization stress takes the DP to 100%). These are not considered “defaulted obligations” for the purpose of the calculations in this
section. A “defaulted obligation” simply has a rating input (after whole-number application of the notching column) of Ca, C, D or default.
Defaulted %
This is the percentage (by exposure amount) of the defaulted obligations in the portfolio.
WARR of Defaulted
The weighted average of the net recovery rate mean of the defaulted exposures i.e. for each exposure:
Exposure_Recovery_Mean * (1 – Exposure_Recovery_Haircut)
PERFORMING OBLIGATIONS (EXCLUDES CA/C/D)
The following calculations are performed across all the exposures that are not defaulted as per the above definition (rating =
Ca/C/D/Default). These are called “performing obligations.”.
10-year WARF (of rating input only, excl. stresses & WAL)
This is an exposure weighted average of the 10-year rating factors of the rating input for performing obligations. The 10-year rating factor is
the 10-year idealized expected loss associated with the rating divided by the 10-year idealized expected loss of the Aaa rating.
»
Implied Rating / Moody's Metric
These rating & Moody’s Metric outputs reflect the expected loss obtained by simply taking the 10-year WARF (immediately above) and
multiplying it by 0.0055% (10-year Aaa EL).
WAEL (net of all stresses)
This is the exposure weighted average of the net expected loss for the performing exposures. i.e. for each exposure:
Exposure_Default_Probability * (1 – Exposure_Recovery_Mean * (1 – Exposure_Recovery_Haircut))
WAL
This is the amount-weighted average across all performing exposures of the Exposure_Maturity values.
Implied Rating (from WAEL,WAL)
This is a rating calculated using the performing WAL and WAEL values above
BET MEASURES
The following measures serve as inputs into Moody’s BET model.
MOODY’S CDOROM™ V2.12 USER GUIDE
47
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Diversity Score (Corp)
This is the diversity score calculated as per “Moody’s Approach to Rating Collateralized Loan Obligations” in Appendix 4.
WADP (net of all stresses)
This is the exposure-weighted average of the net default probability of the performing exposures.
Implied WARF (from WADP, WAL)
This WARF is intended for use in CLO cash-flow models that take a WARF input (as opposed to pool DP) so that when the model converts
the WARF into a DP, the DP will be exactly the same as the performing WADP calculated above.
The algorithm for calculating this WARF is as follows:
»
»
Convert WADP to an EL by multiplying by 55%.
Convert the EL & WAL to a Moody’s Metric.
»
Solve for the 10-year EL such that the Moody’s Metric of this EL (assuming maturity of 10 years) equals the Moody’s Metric from the
previous step.
Convert this 10 year EL to a WARF by dividing by 0.0055%.
»
Portfolio RR Mean (net of haircuts)
This is the exposure-weighted average of the recovery rate mean (net of haircuts) of the performing assets.
Portfolio RR Standard Deviation
This calculation gives an aggregate standard deviation using the approach in the Recovery Rate Toolkit. It is not a weighted average of the
exposure recovery rate standard deviations. An additional term in the calculation captures the additional variance due to variation in the
mean of the assets that defaulted. The formula is:


σ = ∑ σ x + ∑ µ x −  ∑ µ i xi 
i
i
 i

2
i i
2
2
i i
Where σ i is the standard deviation of each exposure’s recovery rate process and μ i is the mean of each exposure’s recovery rate process. x i
gives the percentage exposure to each name as a fraction of the total performing exposure.
Portfolio RR Systematic Risk
The systematic risk is 25% of the square root of the weighted average of the exposure recovery rate variance values.
σ = 0.25 ×
∑σ
i
2
i i
x
OTHER MEASURES
Average Pairwise Correlation
Considering a portfolio where all 100% correlated exposures are aggregated into one, this value gives the weighted average of the pairwise
correlation values excluding the main diagonal.
If the exposures to each asset are s i and the correlation between a pair of assets is p ij then the average pairwise correlation is the sum for all
i and all j excluding i=j of s i s j p ij , divided by the sum for all i and all j excluding i=j of s i s j .
Largest Corp Issuer (% Corp)
Considering all exposures with matching parent entity names to be aggregated into one, this gives the percentage concentration, across the
corporate component of the portfolio only, of the largest exposure.
MOODY’S CDOROM™ V2.12 USER GUIDE
48
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Issuer Parent Entity Name
This is the name of the issuer that has the largest exposure (given above). If up to four issuers are equally in first place, their names will be
shown separated by slashes (/). If there are more than four issuers, then only the number of issuers will be displayed.
ABS % (excludes wrapped ABS)
This is the percentage of the performing portfolio that are ABS, excluding ABS exposures with non-blank guarantor/wrapper inputs, which
are modelled as insurance sector exposures.
Caa %
This is the percentage of the performing portfolio that has ratings (after whole number notching) in the Caa range.
Stresses
These calculations are performed across the entire portfolio (Performing + Defaulted).
WA Credit Event DP Stress
This is the exposure-weighted average across the entire portfolio of the credit event-related DP stresses (ABS and corporate).
WA Total DP Stress
This is the exposure- weighted average of the total DP stress. This stress is applied to the raw DP obtained from the idealized expected loss
and theoretical exposure recovery rate table. It includes DP stresses due to fractional notching, built-in stresses and any manually supplied
DP stresses.
WA Credit Event RR Haircut
This is the weighted average of the credit event type-related recovery rate haircut values of the exposures.
WA Total RR Haircut
This is the weighted average of the net recovery rate haircuts (credit event type + user supplied).
MOODY’S CDOROM™ V2.12 USER GUIDE
49
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
5.3
RATINGS (GRAPH AND DATA)
On the menu described in Section 5.1 above, click on Table 4: Ratings (Graph and Data).
The figure below charts the aggregate portfolio breakdown by rating. The table provides breakdowns by each inner CDO and rating.
Ratings Distribution
% of All Notional Exposures
0%
5%
10%
15%
CDO 1
20%
25%
30%
Aaa
Aa1
Aa2
Aa3
A1
A2
A3
Baa1
Baa2
Baa3
Ba1
Ba2
Ba3
B1
B2
B3
Caa1
Caa2
Caa3
Ca
C
>Back to top
Ratings
Aaa
Aa1
Aa2
Aa3
A1
A2
A3
Baa1
Baa2
Baa3
Ba1
Ba2
Ba3
B1
B2
B3
Caa1
Caa2
Caa3
Ca
C
Total
CDO 2
CDO 3
CDO 4
CDO 5
CDO 6
Total
MOODY’S CDOROM™ V2.12 USER GUIDE
0.50%
0.67%
2.00%
4.17%
7.67%
10.67%
19.00%
19.33%
25.00%
8.67%
1.33%
0.50%
0.50%
100.00%
CDO 1
0.17%
0.50%
0.67%
1.17%
1.67%
2.83%
4.17%
3.33%
1.50%
0.50%
0.17%
16.67%
CDO 2
0.17%
0.33%
0.33%
0.83%
1.50%
1.50%
3.17%
2.17%
5.00%
1.33%
0.17%
0.17%
16.67%
CDO 3
0.17%
0.17%
1.00%
1.67%
1.33%
2.83%
2.83%
4.67%
1.67%
0.33%
16.67%
CDO 4
0.17%
0.50%
0.50%
1.17%
2.17%
3.83%
2.33%
3.83%
2.00%
0.17%
16.67%
CDO 5
CDO 6
0.17%
0.33%
1.00%
1.17%
1.67%
3.50%
3.67%
3.67%
1.17%
0.17%
0.17%
0.17%
0.17%
0.17%
1.00%
2.33%
2.83%
4.17%
4.50%
1.00%
0.17%
16.67%
16.67%
CDO 7
CDO 8
CDO 9
0.17%
50
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
5.4
TIERS (GRAPH AND DATA)
On the menu described in Section 5.1 above, click on Table 5: Tiers (Graph and Data).
The figure below charts the aggregate portfolio breakdown by recovery rate tier. The table provides breakdowns by each inner CDO and
recovery rate tier. 1
Tiers Distribution
% of All Notional Exposures
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
CDO 1
US
C
CDO 2
A
CDO 3
B
D
CDO 4
A <Baa2
CDO 5
JP
E
>Back to top
Tiers
US
C
A
B
D
A <Baa2
JP
E
F
G
ABS
Total
1
CDO 6
Total
39.67%
19.17%
16.50%
12.17%
7.50%
2.17%
1.83%
1.00%
100.00%
CDO 1
6.50%
3.00%
3.33%
2.00%
1.00%
CDO 3
6.83%
3.00%
2.83%
1.33%
1.33%
1.00%
0.33%
CDO 4
6.50%
3.33%
2.00%
2.00%
1.33%
0.67%
0.50%
0.33%
CDO 5
6.67%
3.17%
2.83%
2.50%
1.33%
0.67%
0.17%
CDO 2
6.67%
4.00%
2.50%
1.83%
1.17%
0.17%
0.17%
0.17%
16.67%
16.67%
16.67%
16.67%
16.67%
0.17%
CDO 6
6.50%
2.67%
3.00%
2.50%
1.33%
0.33%
CDO 7
CDO 8
0.33%
16.67%
For more details on Moody’s Recovery Rates, please refer to the special report, “Modelling Recovery Rates in European CDOs”.
MOODY’S CDOROM™ V2.12 USER GUIDE
51
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
5.5
REGIONS (GRAPH AND DATA)
On the menu described in Section 5.1 above, click on Table 6: Regions (Graph and Data).
The figure below charts the aggregate portfolio breakdown by region. The table provides breakdowns by each inner CDO and region.
Regions Distribution
% of All Notional Exposures
0%
10%
20%
30%
40%
50%
EUROPE
CDO 1
CDO 2
NORTH AMERICA
CDO 3
NON EM ASIA
CDO 4
EAST ASIA
CENTRAL AMERICA
CDO 5
CENTRAL EUROPE
>Back to top
Regions
EUROPE
NORTH AMERICA
NON EM ASIA
EAST ASIA
CENTRAL AMERICA
CENTRAL EUROPE
Total
MOODY’S CDOROM™ V2.12 USER GUIDE
CDO 6
46.33%
39.67%
11.67%
1.33%
0.50%
0.50%
CDO 1
7.83%
6.50%
2.00%
0.17%
0.17%
CDO 2
7.83%
6.67%
1.50%
0.50%
0.17%
CDO 3
7.33%
6.83%
2.17%
0.33%
CDO 4
7.67%
6.50%
2.00%
0.17%
0.17%
0.17%
CDO 5
8.17%
6.67%
1.67%
0.17%
CDO 6
7.50%
6.50%
2.33%
CDO 7
CDO 8
0.17%
0.17%
52
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
5.6
INDUSTRIES (GRAPH AND DATA)
On the menu described in Section 5.1 above, click on Table 7: Industries (Graph and Data).
The figure below charts the aggregate portfolio breakdown by industry. The table provides breakdowns by each inner CDO and Industry.
This information is also available for portfolios of ABS.
Industries Distribution
0%
% of All Notional Exposures
2%
4%
6%
CDO 1
8%
10%
12%
Telecommunications
Banking
Utilities
Insurance
Automobile
Buildings and Real Estate
Printing and Publishing
Oil and Gas
Chemicals, Plastics and Rubber
Retail Stores
Beverage, Food and Tobacco
Personal Transportation
Grocery
Finance
Electronics
Aerospace and Defense
Mining, Steel, Iron and Non Precious Metals
Broadcasting & Entertainment
Diversified/Conglomerate Service
Healthcare, Education and Childcare
Hotels, Motels, Inns and Gaming
Sovereign & Supranational
Containers, Packaging and Glass
Cargo Transport
Diversified/Conglomerate Manufacturing
Personal,
Food and Miscellaneous
Home and Office Furnishings,
Housewares,
and Durable
Consumer
Products
Leisure, Amusement,
Entertainment
Diversified Natural
Resources, Precious
Machinery (Non-Agriculture,
Non-Construction,
NonElectronic)
Farming
and Agriculture
Personal and Non
Durable
Consumer
Products
CDO 2
CDO 3
CDO 4
CDO 5
CDO 6
(Manufacturing
Only)and Leather
Textiles
>Back to top
Industries
Telecommunications
Banking
Utilities
Insurance
Automobile
Buildings and Real Estate
Printing and Publishing
Oil and Gas
Chemicals, Plastics and Rubber
Retail Stores
Beverage, Food and Tobacco
Personal Transportation
Grocery
Finance
Electronics
Aerospace and Defense
Mining, Steel, Iron and Non Prec
Broadcasting & Entertainment
Diversified/Conglomerate Service
Healthcare, Education and Child
Hotels, Motels, Inns and Gaming
Sovereign & Supranational
Containers, Packaging and Glas
Cargo Transport
Diversified/Conglomerate Manufa
Personal, Food and Miscellaneo
Home and Office Furnishings, Ho
Leisure, Amusement, Entertainm
Diversified Natural Resources, P
Machinery (Non-Agriculture, Non
Farming and Agriculture
Personal and Non Durable Consu
Textiles and Leather
Ecological
Total
MOODY’S CDOROM™ V2.12 USER GUIDE
10.83%
9.50%
8.33%
6.67%
5.33%
5.33%
4.83%
4.50%
4.00%
3.83%
3.83%
3.00%
2.83%
2.83%
2.83%
2.33%
2.17%
2.17%
2.00%
2.00%
1.67%
1.67%
1.50%
1.17%
1.00%
0.83%
0.67%
0.67%
0.50%
0.50%
0.33%
0.17%
0.17%
CDO 1
2.00%
1.33%
1.50%
0.83%
1.33%
0.67%
0.67%
0.83%
0.17%
0.83%
0.33%
0.67%
0.50%
0.67%
0.67%
0.33%
0.17%
0.50%
0.33%
0.67%
0.33%
0.17%
CDO 2
2.00%
1.67%
1.33%
1.50%
0.83%
0.33%
0.17%
0.17%
0.17%
0.17%
0.17%
0.17%
0.17%
0.33%
0.17%
0.50%
1.17%
0.33%
0.50%
0.67%
0.50%
0.67%
0.50%
0.83%
0.50%
0.50%
0.67%
0.17%
0.50%
0.17%
0.17%
CDO 3
1.67%
2.17%
1.33%
1.33%
0.67%
0.67%
1.00%
0.50%
0.67%
0.33%
0.50%
0.83%
0.50%
0.83%
0.33%
0.33%
0.50%
0.33%
0.50%
0.33%
0.33%
0.17%
0.17%
0.17%
0.17%
0.17%
0.17%
0.17%
CDO 4
1.67%
1.67%
2.17%
0.83%
0.33%
0.33%
1.17%
1.00%
0.67%
0.83%
0.67%
0.50%
0.67%
0.50%
0.50%
0.17%
0.33%
0.33%
0.17%
0.17%
0.50%
0.50%
0.17%
0.17%
0.17%
0.17%
0.17%
0.17%
CDO 5
2.00%
1.83%
1.00%
0.83%
1.00%
2.00%
1.00%
0.33%
0.67%
0.67%
0.17%
0.33%
0.17%
0.17%
0.83%
0.50%
0.67%
0.17%
0.50%
0.17%
0.33%
0.50%
0.17%
0.17%
0.17%
0.17%
CDO 6
1.50%
0.83%
1.00%
1.33%
1.17%
1.67%
0.50%
0.67%
1.50%
0.67%
1.50%
0.17%
0.33%
0.33%
0.33%
0.17%
0.17%
0.33%
0.17%
0.17%
0.33%
0.33%
0.50%
0.17%
0.17%
CDO 7
CDO 8
0.17%
0.17%
0.33%
0.17%
53
MOODY’S INVESTORS SERVICE
MOOD
6
Structured Finance Group
Model Outputs: ‘OutputData’
6.1
GENERAL
This section describes possible additional Excel output from the simulation besides the standard expected loss (EL), variance and frequency
available on the Calculation sheet.
6.2
TABLE 1: LOSS DISTRIBUTION DATA
MOODY'S CDOROM™: Output Data
Table 1: Loss Distribution Data
Table 2: CDO Default Correlation (Not available)
Table 3: CDO Tranche Recoveries (Not available)
Loss Distribution Data
Loss Rate
0.0%
0.1%
0.2%
0.3%
0.4%
0.5%
0.6%
0.7%
0.8%
0.9%
1.0%
1.1%
1.2%
1.3%
1.4%
1.5%
1.6%
1.7%
1.8%
1.9%
2.0%
2.1%
>Back to top
Probabilities
80.3156%
0.0000%
0.0000%
0.0000%
0.0000%
0.0000%
9.4033%
0.0000%
0.0000%
0.0000%
0.0000%
0.0000%
3.5461%
0.0000%
0.0000%
0.0000%
0.0000%
1.9344%
0.0000%
0.0000%
0.0000%
0.0000%
Loss Probability Distribution
Number of10%
bins in Loss Distribution
1001
9%
8%
Probabilities
Table 1:
7%
6%
5%
4%
3%
2%
1%
0%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Size of Loss
The loss distribution data represents the loss of the portfolio entered on the Portfolio(s) sheet. The Loss Rate field indicates the upper limit
(inclusive) of the bucket in which the probabilities have been aggregated; i.e., the 0% bucket represents the probability of scenarios with
loss of 0% exactly. The 0.1% bucket represents scenarios where the loss is > 0% and <= 0.1%, etc.
There is a cell below the loss distribution graph that can be used to change the number of buckets in the loss distribution. Note that in this
case the loss rate levels will not be updated.
MOODY’S CDOROM™ V2.12 USER GUIDE
54
MOODY’S INVESTORS SERVICE
MOOD
7
Structured Finance Group
Additional Model Inputs: ’Asset Correl Matrix’
7.1
THE MULTIFACTOR MODEL AND THE CORRELATION MATRIX
By default Moody’s CDOROM is configured to use a multi-factor model with stochastic global correlation levels. This is required for the
corporate methodology implementation. In this configuration, the asset correlation matrix may only be viewed and cannot be used as an
input by the model.
The correlations displayed on the Asset Correlation Matrix worksheet will be the average values weighted by the stochastic correlation
probabilities provided in the corporate methodology reference data tables – see Section 4.2.1 for a description of the reference data tables
where these values are recorded.
Note also that assets with 100% correlation may be represented by only a single entry in the correlation matrix, as they are modelled using
the same variate in the multi-factor model framework. The row and column headers will reflect the parent entity name in the case of
corporate exposures, or the transaction name in the case of ABS exposures.
7.2
MANUALLY MODIFY THE CORRELATION MATRIX
Tick the View/Modify Correlation Matrix option on the Calculation sheet (in Table 3, “Monte Carlo Parameters”) to enable the Asset
Correl Matrix worksheet, on which the pair-wise correlation values can be viewed and/or modified. Once the portfolio information has
been entered, go to the Asset Correl Matrix sheet and press the Regenerate the Matrix button to build the correlation matrix. If using
the correlation matrix model, please contact Moody’s to discuss the parameters.
MOODY'S CDOROM™: Asset Correlation Matrix
Regenerate the Matrix
Dump to file instead:
ref1
ref2
ref3
ref4
ref5
ref6
ref7
ref8
ref9
ref10
Make the Matrix Positive Definite
Max Columns
254
ref1
ref2
ref3
ref4
ref5
ref6
ref7
ref8
ref9
ref10
ref11
ref12
ref13
ref14
ref15
ref16
100.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
100.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
100.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
100.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00% 100.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00% 100.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00% 100.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00% 100.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00% 100.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00% 100.00%
45.00%
45.00%
45.00%
45.00%
45.00%
45.00%
Any modifications made to the correlation matrix are included in the model the next time that the simulation is run. It is important to
remember to regenerate the correlation matrix if it is enabled and the portfolio information has changed. To help ensure that this is
observed, the simulation code will check to ensure that the entity names in the correlation matrix headers match the entity names in the
portfolio before the simulation is started.
7.3
MAKING THE MATRIX POSITIVE DEFINITE
In order to be able to generate random variables for the Monte Carlo simulation, the correlation matrix must be positive definite. If for
some reason the correlation matrix is not positive definite, there is the facility to use an iterative algorithm to attempt to transform the
matrix into a positive definite one by using the Make the Matrix Positive button.
7.4
DUMP TO FILE INSTEAD
If a filename is specified in this field, then Regenerate the Matrix will output the matrix to the specified CSV file instead of the Excel
workbook. This can be useful when the number of exposures exceeds Excel’s column limit.
7.5
MAX COLUMNS
This field should auto-detect the number of columns supported by the version of Excel being used and indicates to the CDOROM engine
the maximum number of columns that it should attempt to output to the worksheet. To enable more than 254 columns save the file in
XLSM or XLSB format, close it and re-open it.
MOODY’S CDOROM™ V2.12 USER GUIDE
55
MOODY’S INVESTORS SERVICE
MOOD
8
Structured Finance Group
Additional Model Control: ‘Scenario Analysis’
A simple yet powerful Scenario Analysis feature is built into CDOROM in order to allow multiple runs of the model to be made without user
intervention.
Unhide the Scenario Analysis sheet using Format->Unhide->Sheet within the Calculation sheet.
The Scenario Analysis worksheet looks something like this:
Each column from E onwards towards the right represents a scenario to test. Set the Enable Scenario? cells to a non-zero value in order to
enable that column as a scenario to be run
When you press the Run Scenarios button, CDOROM will perform the following steps:
»
Write values for the inputs specified in the scenario analysis sheet to the CDOROM workbook.
»
»
Emulate clicking the Run Simulation button.
Read values by the outputs list and store them in the scenario analysis sheet.
Each row from the 7th onwards defines either an input or an output.
Inputs are cells that are listed in column B (by range name or address). The value to use for each scenario is given in each scenario’s
column. e.g. the AssetSingleMat.Calc text in B8 refers to the maturity input on the calculation page (through its named range). In Scenario
1, it will be set to one year, in Scenario 2 it will be set to two years, etc.
Outputs are cells listed in Column C. After the simulation has been run for each scenario, the values in the output cells will be copied to
the Scenario Analysis sheet in the column for that scenario. In the example above, when Scenario 1 has finished, the expected loss (EL) of T1
in the calculation page (CDO2.EL.Pf) will be copied to cell E11.
The Check column will show #REF! if the input range or output range specification seems invalid.
MOODY’S CDOROM™ V2.12 USER GUIDE
56
MOODY’S INVESTORS SERVICE
MOOD
9
Structured Finance Group
Appendix: Technical Information About CDOROM
This section contains technical information about the CDOROM model.
9.1
THE MONTE CARLO SIMULATION FRAMEWORK
Within a given methodology (i.e. default probabilities, recovery rate distributions and correlation structure), the accuracy of the results
provided by a Monte-Carlo simulation is related to the number of simulations that are run. As for any Monte-Carlo simulation, results differ
depending on the number of simulations: results after 10,000 runs will be different from results after 10,000,000 runs.
The higher the number of simulations, the higher the level of convergence – to a point where the results have converged sufficiently close to
the hypothetically exact value and there is no significant added value in additional simulations. The number of simulations typically needed
to reach an acceptable level of convergence depends on the simulation engine that is used – even with the most sophisticated lowdiscrepancy random generators or quasi-random numbers. 2, several million simulations are needed to arrive at acceptable confidence
intervals (particularly when the true dimension of the problem is high).
It is worth noting that this “required” number of runs increases with the targeted rating and with the rating of the underlying assets. This
can be understood by considering that there will be very low number of occurrences that would “hit” a Aaa tranche or asset (1 in 10,000 for
a 10 year horizon).
As a rough estimate, Moody’s recommends using CDOROM with the following number of simulations:
» 10 million if the target rating is Aaa or if the rating of the reference portfolio is Aaa.
» 5 million in all other cases.
Moody’s uses a 99% confidence interval in order to determine the final expected loss of a tranche. To assist users in assessing the level of
convergence, a “Moody’s Metric Confidence Interval” is provided in the model showing the size of the confidence interval on the Moody’s
Metric scale.
9.2
DESCRIPTION OF THE CDOROM MODELLING APPROACH
The computation of the expected loss mean and variance of synthetic CDO tranches in CDOROM is based on a Monte Carlo simulation.
In each Monte Carlo trial, defaults and recovery rates are simulated for each reference entity. Losses on the CDO tranches, either rated
tranches or intermediary tranches, are then computed. By repeating this process and averaging over a large number of simulations, an
estimate of the expected loss borne by each tranche is derived.
9.3
THE UNDERLYING CREDIT UNIVERSE
Each asset is associated with certain characteristics:
Default Probability
The default probability (“DP”) of each asset is generally determined by the rating and maturity of the exposure. See the specific sections
below for the DP calculation for various asset types as described in Chapter 4.
Dependency / Correlation
Moody’s currently uses a standard normal or Gaussian dependency structure, as is widely accepted and used by market participants to
price credit derivatives structures. Moody’s defines a set of assumptions for pair-wise asset correlations generally using information such
as the sector and geography of an asset. See the specific sections in Chapter 4 above for more information. Note that the correlation may
be implemented using a correlation matrix or a multi-factor model approach, subject to the setting in RefData’s Table 6 – Link Settings
and Advanced Options. The multi-factor model supports multiple regimes for the global and industry factor weights which are
simulated stochastically. If using the correlation matrix model, please contact Moody’s to discuss the parameters.
2
Moody’s is using a Mersenne Twister generator in the CDOROMv2.5 tool. This generator has a periodicity of 2^19937-1 and a proven
equidistribution property in 623-dimensions.
MOODY’S CDOROM™ V2.12 USER GUIDE
57
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Recovery
In the context of a Monte Carlo simulation, the previous two points determine for each simulation the assets that have defaulted. The last
step is to determine the recovery (and the loss) resulting from that default.
If random recoveries are being used for an asset, its recovery value is generated randomly using a beta distribution whose parameters alpha
and beta are calculated so as to match the desired mean and standard deviation of the recovery rate distribution 3. These two parameters
would typically vary and depend on the country of incorporation and the bankruptcy regime in this country. In the context of a synthetic
transaction, the recovery rate would also be decreased by cheapest-to-deliver haircuts. See the specific sections below for the recovery
assumptions for various asset types.
When the recovery rate of an asset is known in advance (fixed recovery), all the defaults of this asset will result in the same loss.
9.4
THE CAPITAL STRUCTURE
Once the underlying credit universe has been properly defined and simulated, the behaviour of the tranches (either an inner tranche, an
outer tranche or a CDO^1 tranche) is fully known. As for the underlying credit universe, certain key characteristics for any CDO tranches
should be defined to compute the losses, if any.
»
The CDO composition: This is where the corporate names and their sizes are allocated in each CDO. This allocation of the underlying
credits to the different CDOs creates the dependency structure between the CDO tranches, through name overlap and industry
overlap.
»
The tranche’s characteristics: These sizes and subordination levels of the tranches that are extracted from each CDO and the size and
subordination of the tranches of the CDO^2 (if any).
Losses on the assets are passed through the structure (i.e.,, a “look-through approach”) and may or may not result in losses at the rated
tranche level. By repeating this process and averaging over the number of simulations, an estimate of the expected loss borne by each class
of notes is derived. That notion of averaging over a random sample is what defines the Monte Carlo methodology.
9.5
RANDOM RECOVERY: USE OF THE BETA DISTRIBUTION AND CORRELATION STRUCTURE
When the model simulates random recoveries, these recoveries follow beta distributions with means and standard deviations determined
either through the geography, type and seniority (corporate exposures) or the entity’s rating and initial size (ABS exposures). These beta
distributions are normally modelled with a 10% global correlation within a Gaussian copula.The process of simulating recoveries can be
described in three steps.
3
It can be shown that the mean and standard deviation of a beta distribution are functions of these two parameters
µ=
a
a+b
and
MOODY’S CDOROM™ V2.12 USER GUIDE
σ2 =
a.b
(a + b + 1).(a + b) 2
58
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
1) Construct an inverse cumulative beta distribution. Starting from the theoretical mean and standard deviation, calculate the appropriate
Alpha and Beta parameters 4 of the Beta distribution. Then, construct a discrete inverse cumulative beta distribution (CDOROM uses
1% increments).
2)
Generate uniform variables in the [0,1] range exhibiting a 10% correlation. This can be achieved as follows
»
Let 𝑅𝑅𝐺 be the global recovery factor, which follows a standard normal distribution.
»
»
Let 𝜌𝐺 equal 10%, the recovery rate correlation.
The standard normal variable 𝑋𝑖 describing the recovery of asset the is:
Xi =
ρ G * RR G + 1 − ρ G * ε i
Where 𝜀𝑖 is the idiosyncratic RR factor specific to recovery i.
Using the cumulative normal standard distribution, the 𝑋𝑖 values are transformed into uniform variables 𝑈𝑖 in the [0,1] range.
3) Apply the discrete inverse cumulative beta distribution pre-calculated in 1) above to convert 𝑈𝑖 into a recovery rate exhibiting the
desired beta distribution.
Numerical Example:
Assume a senior unsecured debt issued by a US entity with recovery rate mean = 45%, stdev = 35%
Random numbers: RRG = -0.5 and 𝜀𝑖 =1.5
Beta parameters: Alpha = 0.4592 and Beta = 0.5612.
1)
Using an approximation algorithm, we then determine the Inverse Cumulative Discrete Beta Function for this asset. (see
the graph below).
2)
Given the random numbers drawn and the correlation hypotheses, the modeled value 𝑋𝑖 is:
X i = 0.1 * (−0.5) + 0.9 * 1.5 = 1.264911
3)
4)
4
CumNorm(𝑋𝑖 ) = 𝑈𝑖 = 0.8970
Looking up the uniform variable 𝑈𝑖 in the (linearly interpolated discrete) inverse cumulative beta distribution, we get the
recovery achieved: 95.4%. This step is also described in the graph below.
Alpha = (𝑀𝑒𝑎𝑛) �
(𝑀𝑒𝑎𝑛)(1−𝑀𝑒𝑎𝑛)
Beta = (1 − 𝑀𝑒𝑎𝑛) �
− 1�
𝑆𝑡𝐷2
(𝑀𝑒𝑎𝑛)(1−𝑀𝑒𝑎𝑛)
𝑆𝑡𝐷2
MOODY’S CDOROM™ V2.12 USER GUIDE
− 1�
59
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Inverse Cumulative Beta Distribution (45% Mean, 35% StD)
Recovery Achieved = 95.4%
100.0%
90.0%
Recovery Achieved
80.0%
70.0%
60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
Uniform Variable Drawn = 0.897
8%
12
%
16
%
20
%
24
%
28
%
32
%
36
%
40
%
44
%
48
%
52
%
56
%
60
%
64
%
68
%
72
%
76
%
80
%
84
%
88
%
92
%
96
%
10
0%
4%
0%
0.0%
Uniform Variable in the [0,1] range
9.6
PARENT SECTOR/REGION RULES
When two or more entities in the portfolio have the same parent company, the following rules are used to determine a single parent sector,
parent region, and parent country to be used for all the affiliated entities when determining the correlation matrix.
For the sectorand region values:
»
»
»
»
If one particular sector/region is represented by more exposure than any other, amongst the entities that have matching parent
company values, then that sector/region is used.
If the exposure to each sector/region is the same, within the set of entities with the same parent company, then the sector/region
associated with the lowest-rated entity is used (i.e., highest EL @ 10-year maturity).
If there are two or more entities that have the same, lowest, rating, then the sector/region that has the most total exposure in the
portfolio is used.
If there is still a tie between two or more sector/regions, they are sorted in alphabetical order and the sector/region at the end of the
list is chosen. (e.g. the US will be chosen over Europe, which will be chosen over Asia Pacific).
In order to determine a parent country the same process as above is followed except that only countries from the region that was selected
as the parent region are considered.
9.7
SHORT EXPOSURES
9.7.1
SHORT EXPOSURES IN THE PORTFOLIO
To model a portfolio with short exposures, negative values can be used in the Amount column or matrix in the Portfolio(s) sheet.
In this case, the notional size of a tranche will only be the sum of the positive exposures.
The short exposures will be taken into account in the simulation to reduce the loss on the positive exposures. Thus, the total loss is the sum
of the losses on the positive exposures minus the sum of the losses on the negative exposures. The total loss is capped at zero (there can’t
be any gain).
9.7.2
1.
SHORT CDO TRANCHES
To short CDO tranches, negative values can be input in the Inclusion input of a tranche exposure (see Section 3.9.3).
MOODY’S CDOROM™ V2.12 USER GUIDE
60
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
9.8
THE CORRELATED BINOMIAL METHODOLOGY
In the context of deals rated using the Correlated Binomial Methodology (typically cash CDO of ABS), CDOROM is used to calculate the
Moody’s Asset Correlation (MAC) figure for a portfolio. This section describes how to calculate the MAC and how to use the CDOROM addin to generate a CBM distribution for use in a cash flow model.
9.9
TO CALCULATE THE MAC OF A CDO^1
To calculate a Moody’s Asset Correlation figure for a CDO^1 portfolio, select Correlated Binomial Methodology from the Deal Type
drop-down in the Calculation sheet. This configures CDOROM to hide the Capital Structure Table and enable the CBET outputs.
MOODY'S CDOROMv2.5™
Choose Fields ...
1. Transaction Information
Deal Type
2
Correlated Binomial Methodology
As-Of Date
09/06/2006
Maturity (years or Date)
5
Run Simulation
Import
Export
Clean Inputs
Email to Monitoring
3. Monte Carlo Parameters
Nb Simulations
View/Modify Correlation Matrix
Simulation Time:
1,000,000
FALSE
0h 0m 7s
7a. Correlated Binomial Data
Number of Assets (N)
WARR
Default Prob (DP)
100
42.00%
0.0583%
MAC (Asset Correlation for Default Dist)
24.9342%
Asset Correlation for Loss Distribution
21.2340%
These fields may also be enabled by selecting Correlated Binomial (CBET) from the Choose Fields button.
Note that CDOROM will have set the Credit Events enabled option to ”false”, since the CBET is normally applied to deals for which credit
event stresses are not appropriate. This can be changed by selecting the Credit Event table through the Choose Fields button.
Number of Assets (N)
The number of assets to assume when calculating the MAC is not necessarily the same as the number of assets in the portfolio and is to be
specified using this input. For more information consult Moody’s methodology papers on the Correlated Binomial Methodology.
WARR
This output indicates the average recovery rate of the pool. It can be changed into an input by clicking the Input Fixed “WARR” Value
option in RefData Table 6.
Advanced CBET Options
Input Fixed "N" Value?
Input Fixed "WARR" Value?
MOODY’S CDOROM™ V2.12 USER GUIDE
TRUE
FALSE
61
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Populate the Portfolio(s) sheet as normal. After running the simulation, the MAC results are displayed in the Correlated Binomial
Data Table.
Default Prob (DP)
This is the implied average default probability of the pool, based on the pool’s average expected loss and WARR.
MAC (Asset Correlation for Default Dist)
This is the traditional Moody’s Asset Correlation output as used in the Correlated Binomial Methodology.
Asset Correlation for Loss Distribution
This is the asset correlation obtained by matching “N” units of loss (with no recovery) to the simulated loss distribution. It is equivalent to
running the MAC calculation assuming a pool WARR of 0%. Use only if specifically instructed to do so.
9.9.1
ADDITIONAL CBET OUTPUTS
These fields, accessible through the Choose Fields button on the Calculation worksheet, enable the Pool Third Moment and Default
Correlation outputs in the Correlated Binomial Data Table.
9.10
THE EXCEL CDOROM ADD-IN
CDOROM includes an add-in for Excel that provides additional functions to be used when modelling transactions with the Correlated
Binomial Methodology. The add-in is automatically installed with CDOROM.
9.10.1
MANUALLY INSTALLING THE ADD-IN
The CDOROM add-in is a file called CDOROM.XLL that is normally placed in C:\Program Files\Moodys\CDOROM. To manually register
the add-in in Excel, select Tools->Add-ins, then press Browse and go to the CDOROM.XLL file. Office 2007 users will find the add-in
manager by clicking the Office button on the top left of the Excel window, then clicking Excel Options, Add-Ins and with “Excel Add-ins”
selected clicking the Go button.
9.10.2
USING THE CDOROM ADD-IN
The add-in provides a mathematical function that can be used in Excel formulas as described below
CBETMAC(nAssets, avgProbability, Mac)
The CBETMAC function calculates the Correlated Binomial Distribution. It returns an array of (nAssets + 1) probabilities, giving the
probabilities of 0 to n defaults in the pool of assets. The input parameters are as follows:
PARAMETER
DESCRIPTION
NAssets
Number of assets in the collateral pool.
avgProbability
Average default probability among all the assets.
MAC
Moody’s Asset Correlation.
In order to use the formula, select a column of (nAssets + 1) cells and enter the function’s name in the formula box. Enter values or cell
references for the three inputs, and then press {Ctrl + Shift + Enter} to save the formula as a ”Range Formula.”
MOODY’S CDOROM™ V2.12 USER GUIDE
62
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
9.11
THE GETRATING ADD-IN
Moody’s analysis of CDO transactions that have combination notes (combo-notes) utilizes a specific benchmarking methodology described
in Moody’s Rating Methodology, “Using the Structured Note Methodology to Rate CDO Combo-Notes”, 26 February 2004..
CDOROM’s GetRating add-In provides an implementation of this benchmarking methodology.
9.12
INSTALLING THE GETRATING ADD-IN
The GetRating add-in is a file called GetRating.XLL that is normally placed in C:\Program Files\Moodys\CDOROM. To manually register
the add-in in Excel select Tools->Add-ins, then press Browse and go to the GetRating.XLL file. Office 2007 users will find the add-in
manager by clicking the Office button on the top left of the Excel window, then clicking Excel Options, Add-Ins and with “Excel Add-ins”
selected clicking the Go button.
9.13
USING THE GETRATING ADD-IN
The add-in provides a mathematical function that can be used in Excel formulas as described below.
GETRATING(ExpectedLoss, Exposure, RecoveryRate, ForwardRates [PeriodsPerYear, DefaultTime, LookupType, ReturnStyle])
This function returns the indicative modeled rating corresponding to the expected loss and exposure of the target security
PARAMETER
DESCRIPTION
ExpectedLoss
A number that represents the expected loss for the target security, either with respect to par, the present value
of the promise, or the present value of the risk cash-flows, depending on the lookup_type.
A number that represents either the average life of the target security, the duration of the promise or the
default-adjusted duration of the cash-flows, depending on the lookup type.
A number between 0 and 1
A vector of annualized risk-free forward rates for discounting the benchmark bond cash flows, one for each
period. If the calculation requires more periods than forward rates in the vector, use the final rate for all
subsequent missing values.
Exposure
RecoveryRate
ForwardRates
Optional Parameters:
PeriodsPerYear
DefaultTime
LookupType
ReturnStyle
Values of 1, 2, or 4, representing annual, semi-annual or quarterly payments. If blank, the default value is 1.
Takes a value between 0 and 1. It represents when in the period the default event occurs, and therefore the
amount of accrued interest included in the recovery. If blank, the default value is 0 (default at the beginning of
the period).
Takes the values 0, 1, or 2. If 0 or blank, returns the traditional look up method (EL w.r.t. par). If 1, returns the
structured note method w.r.t. the promise. If 2, returns the structured note method w.r.t. the risky cashflows..
Takes the values 0 or 1. If 0 or blank, returns the rating characters (“Aaa”, “Aa1”, etc.). If 1, returns the ratings
mapped to a continuous scale (where Aaa < 1.00, 1.00 <= Aa1 < 2.00, etc.).
MOODY’S CDOROM™ V2.12 USER GUIDE
63
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
9.14
PER-ASSET DEFAULT TIMING GENERATION
Exact default timing for individual assets within the simulation is required when performing Ith to default analysis or generating full data
text/binary output data (Section 2.5.8). Per-asset default timing is not used to calculate the present value of losses. CDOROM remains a
single-period model. Per-asset default timing is determined as follows:
Let EL(t) be the cumulative expected loss for the asset as given in Moody’s Idealised Expected Loss Table, given the asset’s rating. Linear
interpolation is used to determine EL(t) when t is not a whole number of years.
Let RR be the theoretical recovery rate for the asset. For corporate exposures it is 45%. For ABS it is determined from the RR tables based
on the initial size and initial or current rating of the asset.
The cumulative probability of default is –
P(t) = EL(t)/(1-RR)
-1
The asset defaults when its correlated asset value “X” is less than the asset threshold. The asset threshold is in fact Φ. .(P(T)), where T = the
-1
maturity (WAL) of the asset, and Φ. is the inverse cumulative normal function. The asset defaults when:
-1.
X < Φ. (P(T))
The default time, 𝑡𝑑 is determined by searching for the exact value of t for which the following equality is satisfied when:
-1
X = Φ. .(P(t d. ))
In other words, CDOROM searches for the maturity at which an asset of the given rating and asset value “X” would only just have
defaulted.
9.15
CDOROM - TECHNICAL CHARACTERISTICS
This section provides information about the CDOROM implementation, which is useful if building a model to mimic the CDOROM analysis.
»
»
Random numbers are drawn using the Mersenne Twister random number generator.
The inverse cumulative normal function is used to convert uniform variates into normally distributed variates. The numerical
approximation used is an extension of Moro’s algorithm.
»
The beta distribution used for generating random recoveries is discretized using 101 points. During the simulation a linear interpolation
is used.
»
If assets have different recovery rate distributions but are 100% correlated, then the same underlying variate will be used to generate
the recovery rate values. It will be mapped to the specific distribution of each asset using the inverse cumulative function of the asset’s
specific beta distribution.
9.16
TECHNICAL INFORMATION ABOUT THE CDOROM DATA FEED FILE
9.16.1
INFORMATION ABOUT MOODY’S CDOROM DATA FEED FOR IT ADMINISTRATORS
CDOROM attempts to connect to the feed using the FTP protocol. It uses the “URLMON” component in Windows which should ensure
that the same proxy settings used by Internet Explorer to access an FTP site will be used by CDOROM.
The Use alternative download method option engages alternative code that instead automates Excel’s WebQuery feature to attempt to
download the data. This has been used successfully in some environments where for some reason the URLMON component fails to work.
MOODY’S CDOROM™ V2.12 USER GUIDE
64
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
If neither of the above methods succeed, or if for other reasons it is not desirable for CDOROM to access the internet directly, the feed files
may be downloaded to a location on the Intranet and CDOROM configured to access the feed from this source by placing an UNC style
path for the ID in the Configure Feed screen, e.g. .\\InternalServer01\Moodys\CDOROMFeed\. The trailing slash is required.
The CDOROM Feed ID supplied by Moody’s contains the username and password required to connect to the Moody’s FTP site to download
the feed. For information about the contents of the feed files themselves, please see section 9.16.2.
MOODY’S CDOROM™ V2.12 USER GUIDE
65
MOODY’S INVESTORS SERVICE
MOOD
9.16.2
Structured Finance Group
DESCRIPTION OF FIELDS IN THE FEED FILE
FIELD NAME
DESCRIPTION [FORMAT, LENGTH]
ENTITY_CUSIP
ORG_NUM
ORG_NAME
PAR_ORG_NAME
NOTCHED_RATING
The CUSIP of the entity [String,6]
Moody's Org Number of the entity [32 bit integer (ignore any decimal)]
Moody's name of the entity [String,45]
Moody's name of the ultimate parent entity [String,50]
This is the rating after any applicable notching has been applied,
e.g. if it was a Corporate Family Rating notched down by one then this is the final notched rating
whereas the "RATING" column will contain the un-notched CFR rating. Note that this rating is NOT
notched for UPG/DNG REVIEW status [String,10]
DNG if on watch for downgrade, UPG if on watch for upgrade [String,5]
Take the first three characters only. NEG means Negative Outlook, POS means Positive Outlook. Other
values have other meanings that aren’t used in CDO analysis. [String,10]
The country input to use when modeling in CDOROM [String,20]
The industry number to use when modeling in CDOROM [Integer 1-34]
Note that this column was used by CDOROMv2.4 only. See IND_NUM_35
The name of the industry (informational only - not used by CDOROM) [String,66].
Note that this field is being removed from the feed.
This is the CDS implied rating 1 = Aaa, 2 = Aa1, etc [Integer]
The MarkIt long name of the entity [String,128]
The MarkIt short name for the entity [String,100]
The 6 digit RED Code of the entity [String,6]
The 9 digit RED code of the Preferred Reference Obligation [String,9]
The CUSIP of the Preferred Reference Obligation [String,9]
The ISIN of the Preferred Reference Obligation [String,12]
The seniority of the Preferred Reference Obligation
SNRFOR = SU
SUBLT2 = SB
FG = Financial Guarantee (e.g. Monoline) [String,6]
The number of the rule employed to derive the rating
1) A specific debt was identified by Moody's Analysts to use
2,3) An SU rating was identified
5) LT Deposit
11) IFS
12) Corporate Family Rating
13) Senior Subordinated
14) Subordinated
15) Junior Subordinated
16) Senior Secured
17) Corporate Family Rating of Ultimate Parent
18) SU of guaranteed debt in same corporate family
19) IFS of subsidiary [Integer]
This column is added to the Feed_Cache.xls file by CDOROM. It is the NOTCHED_RATING with the
UPG/DNG notching applied as per REVIEW. [String,10]. Note that this column is not used by
CDOROMv2.5 and later
The new 101-135 sector code applied by CDOROMv2.5 & later. [Integer 101-135]
This applies the CDOROM notching algorithm, where ratings on review for downgrade are notched down
by 2 notches, and ratings with negative outlook are notched down by 1 notch. Until such time as the
CDOROM Data Feed contains this column, CDOROM will automatically add it [String,10]
REVIEW
RATING_OUTLOOK
DOMICILE
IND_NUM
IND_NAME
CDS_IMP_RATING
MARKIT_ENTITY_NAME
MARKIT_SHORT_NAME
ENTITY_CLIP
RO_CLIP
RO_CUSIP
RO_ISIN
RO_SENIORITY
RULE_NUM
FINAL_RATING
IND_NUM_35 (see notes)
FINAL_RATING_FWD (see notes)
MOODY’S CDOROM™ V2.12 USER GUIDE
66
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
9.16.3
DIRECTLY ACCESSING TO THE FEED DATA
Check with your Moody’s representative whether you are licensed to access the feed data directly.
The CDOROM Feed Data is accessed via FTP. The FTP folder given by the client ID contains a list of feed files named
cdorom_service_levelX_MMDDYYYY.csv, where MM = the month, DD = the day, YYYY = the year and X = 2 or 3 depending on the service
level of access. CDOROM takes the latest file when downloading from the server.
The files themselves are Pipe Separated Text format with the first row containing the names of the columns. There are no quotes used for
string fields and the number/date formats are US.
Please ignore additional fields in the feed that are not described in the table above - these had meaning in earlier internal versions of the
feed only and are now deprecated.
9.16.4
OVERRIDING THE FEED DATA FOR SPECIFIC ENTITIES
It is possible to supply an additional .xls file to override data for specific entities in the CDOROM Data Feed, for example to allow for Credit
Estimates or Notched Ratings from other agencies to be automatically updated when the Update with Feed function is used.
In order to create an override file
»
Press Open Feed in CDOROM to open the most recent data feed file
»
»
Delete all the rows of data on the RM worksheet except for the names for which you want to override the ratings
In the FINAL_RATING column, enter the rating overrides required
» Save this Feed_Cache.xls file with a different name, in a central location on your file system
e.g. \\IntranetServer\CDOROM\Feed\Overrides.xls
»
In CDOROM (edit the master copy so that this change is kept) go to the RefData worksheet
»
»
Unhide the rows in Table 6 below “Path and Filename for temporary CDOROM Feed file”
A new input should appear labelled “Path and Filename for ABS RefMaster import (for internal use only)”
»
Enter the path to the Overrides.xls file in this input, e.g.
When the Update with Feed button is pressed, CDOROM will first update the portfolio using the normal feed file and then subsequently do
another pass through the portfolio updating it with any issuer information from the Overrides.xls file
MOODY’S CDOROM™ V2.12 USER GUIDE
67
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
9.17
CORPORATE SECTOR CODE DESCRIPTIONS
101
Aerospace & Defense: Aircraft & Aerospace Equipment, Parts and Services; Defense Equipment and Services
102
Automotive: Passenger Vehicles; Commercial Vehicles; Farm Equipment, Parts; Wholesale and Retail Vehicles and Parts
103
Banking: Banks; Bank Holding Companies; Credit Unions; Thrifts
104
Beverage, Food & Tobacco: Packaged Beverage (including Alcohol); Packaged Food; Packaged Tobacco products; Agriculture,
Protein and Tobacco Processing
105
Capital Equipment: Heavy Machinery; Finished Products; Component Equipment; Transportation Equipment (Rail & Maritime)
106
Chemicals, Plastics & Rubber: Commodity Chemicals; Specialty Chemicals; Agricultural Chemicals
107
Construction & Building: Building Materials; Commercial and Residential Construction and Engineering Services
108
Consumer Goods: Durable: Durable Consumer Goods
109
Consumer Goods: Non-durable: Apparel & Shoes; Household & Personal Care; Textiles
110
Containers, Packaging & Glass: Glass, Metal and Plastic Packaging
111
Energy: Electricity: Non-utility Electricity Production; Merchant Energy; Propane
112
Energy: Oil & Gas: Non-utility Oil & Gas Exploration and Production; Integrated Oil companies; Oil Refining and Marketing;
Pipelines; Oil Services; Gas
113
Environmental Industries: Environmental Services and Waste Management
114
FIRE: Finance: Asset Management; Investment Management; Trading Companies; Leasing, Securities Companies
115
FIRE: Insurance: Financial Guarantors; Insurance Brokerage; Life & Health; Property & Casualty; Mortgage; Title
116
FIRE: Real Estate: REITs and REOCs
117
Forest Products & Paper: Paper Packaging; Pulp & Paper; Wood Products
118
Healthcare & Pharmaceuticals: Hospitals; Long-Term Care Facilities; Outpatient Facilities; Medical Devices; General and
Specialty Pharmaceuticals
119
High Tech Industries: General Services; IT Services; Component Equipment; Hardware; Software; Consumer Electronics; Contract
Manufacturing; Semiconductors
120
Hotel, Gaming & Leisure: Casinos; Amusement Parks; Cruise Lines; Movie Theaters; Ski Resorts; Sports Enterprises; Lodging;
Family Dining; Fast Food
121
Media: Advertising, Printing & Publishing: Publishing (Books, Newspapers, Magazines); Advertising Agencies; Printing
122
Media: Broadcast & Subscription: Broadcast TV & Radio; Subscription TV & Radio; Cable TV; Television Networks
123
Media: Diversified & Production: Diversified Media; Media Services; Theatrical, Music & TV Production
124
Metals & Mining: Coal; Aluminum; Steel; Metal Recycling; Metal Mining
MOODY’S CDOROM™ V2.12 USER GUIDE
68
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
125
Retail: Department Stores; Drug Stores; Food & Grocery; General Merchandise; Specialty Merchandise
126
Services: Business: Business Services; Rental Services
127
Services: Consumer: Consumer Services
128
Sovereign & Public Finance: Non-Defense Government Services; Higher Education; Government Agency; Public Sector Agency;
Regional and Local Government; Toll Roads; All Government Related Issuers, regardless of sector (except regulated utilities)
129
Telecommunications: Equipment; Towers; Satellite Equipment and Services; Wireless; Wireline; Integrated Telecommunications
130
Transportation: Cargo: Equipment Leasing; Air Freight; Maritime; Rail; Trucking
131
Transportation: Consumer: Airline; Airports; Commuter Services
132
Utilities: Electric: Integrated Electric Utilities; Electricity Transmission and Distribution; Electricity Production
133
Utilities: Oil & Gas: Gas Distribution; Gas Transmission
134
Utilities: Water: Water Utilities
135
Wholesale: Building Materials; Business Products; Consumer Products; Industrial Products; Food and Grocery; Healthcare;
Internet; Metals; Technology Equipment and Components; Telecommunications Equipment
9.18
MOODY’S METRICS
Moody’s ratings – Aaa, Aa1, Aa2, etc.— are alphanumeric and reflect the expected loss associated with the rated instrument. Moody’s
Metrics (MM) are numerical mappings of such a rating. MMs are continuous and range between zero to 20, where zero represents the upper
limit of a Aaa rating and 20 representing the lower limit of a Ca rating. Each integer value corresponds to the boundary of the expected loss
for a given rating. A logarithmic interpolation is applied to interval values, except for those with an MM in the (0,1] range, where linear
interpolation is applied.
For example, let’s consider a tranche with an expected loss of 1% with a 5-year maturity. The expected loss is between the 5-year Baa2 and
Baa3 EL limits of 0.8690% (MM=9) and 1.6775% (MM=10) respectively. The MM of this tranche is calculated as follows:
MM = 9 + [ ln(1.00%) – ln(0.8690%)] / [ ln(1.6775%) – ln(0.8690%)] = 9.21
The expected loss limit may vary with maturity, but, by construction, the MM stays constant.
For example, if the expected loss of a tranche with a tenor of five years is 0.2569%, then the corresponding MM is six, equivalent to A2. If
one year later the expected loss of the tranche is 0.1898%, then the MM remains unchanged at six, equivalent to A2.
Moody's
Rating
Aaa
Aa1
Aa2
Aa3
A1
A2
A3
Baa1
Baa2
Baa3
Ba1
Moody's Metric
Upper
Limit
Lower Limit
(exclusive)
(inclusive)
0
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
MOODY’S CDOROM™ V2.12 USER GUIDE
69
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
Ba2
Ba3
B1
B2
B3
Caa1
Caa2
Caa3
Ca
11
12
13
14
15
16
17
18
19
MOODY’S CDOROM™ V2.12 USER GUIDE
12
13
14
15
16
17
18
19
20
70
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
SP25283
© 2013 Moody’s Investors Service, Inc. and/or its licensors and affiliates (collectively, “MOODY’S”). All rights reserved.
CREDIT RATINGS ISSUED BY MOODY'S INVESTORS SERVICE, INC. (“MIS”) AND ITS AFFILIATES ARE MOODY’S CURRENT OPINIONS OF
THE RELATIVE FUTURE CREDIT RISK OF ENTITIES, CREDIT COMMITMENTS, OR DEBT OR DEBT-LIKE SECURITIES, AND CREDIT RATINGS
AND RESEARCH PUBLICATIONS PUBLISHED BY MOODY’S (“MOODY’S PUBLICATIONS”) MAY INCLUDE MOODY’S CURRENT OPINIONS
OF THE RELATIVE FUTURE CREDIT RISK OF ENTITIES, CREDIT COMMITMENTS, OR DEBT OR DEBT-LIKE SECURITIES. MOODY’S DEFINES
CREDIT RISK AS THE RISK THAT AN ENTITY MAY NOT MEET ITS CONTRACTUAL, FINANCIAL OBLIGATIONS AS THEY COME DUE AND
ANY ESTIMATED FINANCIAL LOSS IN THE EVENT OF DEFAULT. CREDIT RATINGS DO NOT ADDRESS ANY OTHER RISK, INCLUDING BUT
NOT LIMITED TO: LIQUIDITY RISK, MARKET VALUE RISK, OR PRICE VOLATILITY. CREDIT RATINGS AND MOODY’S OPINIONS INCLUDED
IN MOODY’S PUBLICATIONS ARE NOT STATEMENTS OF CURRENT OR HISTORICAL FACT. CREDIT RATINGS AND MOODY’S
PUBLICATIONS DO NOT CONSTITUTE OR PROVIDE INVESTMENT OR FINANCIAL ADVICE, AND CREDIT RATINGS AND MOODY’S
PUBLICATIONS ARE NOT AND DO NOT PROVIDE RECOMMENDATIONS TO PURCHASE, SELL, OR HOLD PARTICULAR SECURITIES.
NEITHER CREDIT RATINGS NOR MOODY’S PUBLICATIONS COMMENT ON THE SUITABILITY OF AN INVESTMENT FOR ANY
PARTICULAR INVESTOR. MOODY’S ISSUES ITS CREDIT RATINGS AND PUBLISHES MOODY’S PUBLICATIONS WITH THE EXPECTATION
AND UNDERSTANDING THAT EACH INVESTOR WILL MAKE ITS OWN STUDY AND EVALUATION OF EACH SECURITY THAT IS UNDER
CONSIDERATION FOR PURCHASE, HOLDING, OR SALE.
ALL INFORMATION CONTAINED HEREIN IS PROTECTED BY LAW, INCLUDING BUT NOT LIMITED TO, COPYRIGHT LAW, AND NONE OF
SUCH INFORMATION MAY BE COPIED OR OTHERWISE REPRODUCED, REPACKAGED, FURTHER TRANSMITTED, TRANSFERRED,
DISSEMINATED, REDISTRIBUTED OR RESOLD, OR STORED FOR SUBSEQUENT USE FOR ANY SUCH PURPOSE, IN WHOLE OR IN PART,
IN ANY FORM OR MANNER OR BY ANY MEANS WHATSOEVER, BY ANY PERSON WITHOUT MOODY’S PRIOR WRITTENCONSENT.
All information contained herein is obtained by MOODY’S from sources believed by it to be accurate and reliable. Because of the possibility
of human or mechanical error as well as other factors, however, all information contained herein is provided “AS IS” without warranty of
any kind. MOODY'S adopts all necessary measures so that the information it uses in assigning a credit rating is of sufficient quality and from
sources MOODY'S considers to be reliable including, when appropriate, independent third-party sources. However, MOODY’S is not an
auditor and cannot in every instance independently verify or validate information received in the rating process. Under no circumstances
shall MOODY’S have any liability to any person or entity for (a) any loss or damage in whole or in part caused by, resulting from, or relating
to, any error (negligent or otherwise) or other circumstance or contingency within or outside the control of MOODY’S or any of its
directors, officers, employees or agents in connection with the procurement, collection, compilation, analysis, interpretation,
communication, publication or delivery of any such information, or (b) any direct, indirect, special, consequential, compensatory or
incidental damages whatsoever (including without limitation, lost profits), even if MOODY’S is advised in advance of the possibility of such
damages, resulting from the use of or inability to use, any such information. The ratings, financial reporting analysis, projections, and other
observations, if any, constituting part of the information contained herein are, and must be construed solely as, statements of opinion and
not statements of fact or recommendations to purchase, sell or hold any securities. Each user of the information contained herein must
make its own study and evaluation of each security it may consider purchasing, holding or selling.
NO WARRANTY, EXPRESS OR IMPLIED, AS TO THE ACCURACY, TIMELINESS, COMPLETENESS, MERCHANTABILITY OR FITNESS FOR ANY
PARTICULAR PURPOSE OF ANY SUCH RATING OR OTHER OPINION OR INFORMATION IS GIVEN OR MADE BY MOODY’S IN ANY
FORM OR MANNER WHATSOEVER.
MIS, a wholly-owned credit rating agency subsidiary of Moody’s Corporation (“MCO”), hereby discloses that most issuers of debt securities
(including corporate and municipal bonds, debentures, notes and commercial paper) and preferred stock rated by MIS have, prior to
assignment of any rating, agreed to pay to MIS for appraisal and rating services rendered by it fees ranging from $1,500 to approximately
$2,500,000. MCO and MIS also maintain policies and procedures to address the independence of MIS’s ratings and rating processes.
Information regarding certain affiliations that may exist between directors of MCO and rated entities, and between entities who hold
ratings from MIS and have also publicly reported to the SEC an ownership interest in MCO of more than 5%, is posted annually at
www.moodys.com under the heading “Shareholder Relations — Corporate Governance — Director and Shareholder Affiliation Policy.”
For Australia only: Any publication into Australia of this document is pursuant to the Australian Financial Services License of MOODY’S
affiliate, Moody’s Investors Service Pty Limited ABN 61 003 399 657AFSL 336969 and/or Moody’s Analytics Australia Pty Ltd ABN 94 105
136 972 AFSL 383569 (as applicable). This document is intended to be provided only to “wholesale clients” within the meaning of section
761G of the Corporations Act 2001. By continuing to access this document from within Australia, you represent to MOODY’S that you are,
or are accessing the document as a representative of, a “wholesale client” and that neither you nor the entity you represent will directly or
MOODY’S CDOROM™ V2.12 USER GUIDE
71
MOODY’S INVESTORS SERVICE
Structured Finance Group
MOOD
indirectly disseminate this document or its contents to “retail clients” within the meaning of section 761G of the Corporations Act 2001.
MOODY’S credit rating is an opinion as to the creditworthiness of a debt obligation of the issuer, not on the equity securities of the issuer
or any form of security that is available to retail clients. It would be dangerous for retail clients to make any investment decision based on
MOODY’S credit rating. If in doubt you should contact your financial or other professional adviser.
.
MOODY’S CDOROM™ V2.12 USER GUIDE
72