Economic Capital - Moody`s Analytics

Estimating Multiple Risk Measurements for Internal
and External Audiences Using a Manageable
Approach: Stress Testing Structured Portfolios
YANIV GERSHON, STATE STREET
JUAN CARLOS CALCAGNO, MOODY’S ANALYTICS
Outline
» Discuss project aimed to stress test State Street structured portfolio
o Describe standard modeling approach for diverse assets and regions
o Explain economic stress testing framework and assumptions
o Internal and external applications for
 Credit risk economic capital
 Reserve requirements
 Research, development, and investment
Overview of Project
Model
Macro Forecast
Estimation
Assumptions
Deal-Level
Behavioral
Assumptions
Collateral
Performance
Security-Level
Different uses
Cash-flows
at State Street
CDR
ECAP
Default Vector
Severity
CreditCycle –
Behavioral
Model
Choose your
Macro Scenario
Cash-Flow
Engine
Severity Vector
CPR
Economic
Parameters (GDP,
HPI, employment
Prepayment Vector
Principal and
interest
payments
OTTI Process
Loss
Estimation
Stress Test
Program
DATA, MODELS AND ESTIMATION
Moody's Performance Data Service (PDS)
Our data and modeling team collects, normalizes and stores data
Scrubbing, validation &
standardization
Data collection
Accessible Data
Data warehousing
4.7199998
5.4699998
5.6399999
6.25
6.7122302
7.3008995
8.136611
8.6848841
9.2574759
9.1450596
8.7279348
8.2612009
7.8519301
4.7199998
5.4699998
5.6399999
6.25
6.6847372
7.1676712
7.7857828
7.9900608
8.0914431
7.4228692
6.5703249
5.9571881
5.603909
4.9333301
5.3666701
6.0666699
6.8666701
8.0736609
8.6520376
9.1786413
9.4953976
9.7242556
9.7663956
9.6879368
9.386632
8.9864655
4.7199998
5.4699998
5.6399999
6.25
6.7122302
7.3008995
8.136611
8.6848841
9.2574759
9.1450596
8.7279348
8.2612009
7.8519301
4.7199998
5.4699998
5.6399999
6.25
6.6847372
7.1676712
7.7857828
7.9900608
8.0914431
7.4228692
6.5703249
5.9571881
5.603909
4.9333301
5.3666701
6.0666699
6.8666701
8.0736609
8.6520376
9.1786413
9.4953976
9.7242556
9.7663956
9.6879368
9.386632
8.9864655
Software Suite
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10
8
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6
4
0000000000000
2
0
000000000000000000000000
00000000000000000000000
0000000000000000000000
00000000000000000000
0000000000000
4.7199998
5.4699998
5.6399999
6.25
6.7122302
7.3008995
8.136611
8.6848841
9.2574759
9.1450596
8.7279348
8.2612009
7.8519301
1
4.7199998
5.4699998
5.6399999
6.25
6.6847372
7.1676712
7.7857828
7.9900608
8.0914431
7.4228692
6.5703249
5.9571881
5.603909
4.9333301
5.3666701
6.0666699
6.8666701
8.0736609
8.6520376
9.1786413
9.4953976
9.7242556
9.7663956
9.6879368
9.386632
8.9864655
4.7199998
5.4699998
5.6399999
6.25
6.7122302
7.3008995
8.136611
8.6848841
9.2574759
9.1450596
8.7279348
8.2612009
7.8519301
4.7199998
5.4699998
5.6399999
6.25
6.6847372
7.1676712
7.7857828
7.9900608
8.0914431
7.4228692
6.5703249
5.9571881
5.603909
4.9333301
5.3666701
6.0666699
6.8666701
8.0736609
8.6520376
9.1786413
9.4953976
9.7242556
9.7663956
9.6879368
9.386632
8.9864655
Collect pool, deal, tranche and
loan level data from originators,
servicers and rating agencies.
000000000000000000000000
00000000000000000000000
0000000000000000000000
00000000000000000000
2
An automated program sorts
and cleans the data, then a
team of specialists manually
validates and scrub key fields
3
Data warehouse is constructed
4
from scrubbed data, and is made
available for use in the software
or accessible via direct download
Direct Download
4.7199998
5.4699998
5.6399999
6.25
6.7122302
7.3008995
8.136611
8.6848841
9.2574759
9.1450596
8.7279348
8.2612009
7.8519301
4.7199998
5.4699998
5.6399999
6.25
6.6847372
7.1676712
7.7857828
7.9900608
8.0914431
7.4228692
6.5703249
5.9571881
5.603909
4.9333301
5.3666701
6.0666699
6.8666701
8.0736609
8.6520376
9.1786413
9.4953976
9.7242556
9.7663956
9.6879368
9.386632
8.9864655
Data sets, performance
reports and indexes would
be available to end users
Over 13,000 deals back to 1980s
and over 50 performance metrics
5
Data Coverage ABS/RMBS Deals
Asset Class
Product Line
Number of Unique
Pools
Asset Class
Product Line
Market as Feb 2011
11,689
USA RMBS
3,530
4,562
2,327
507
1
762
Subprime
Alt-A
Jumbo
Other
Prime Conforming
Option Arms
275
USA HEL
Australia
Greece
Ireland
Italy
Netherlands
Portugal
Russia
Spain
UK
TOTAL
Market as Feb 2011
136
9
22
92
107
30
12
226
141
12,739
251
Auto
176
17
58
Prime
Marginal
Subprime
Motorcycles
49
Credit Cards
37
24
2
6
Bank
Charge
Retail
212
63
HELOC
Home Equity/Closed End
Number of Unique
Pools
348
Student Loans
238
79
31
FFELP
Private
Mixed
TOTAL
685
6
Highlights of credit risk models
» A comprehensive approach based on a series of econometric models, each
designed to capture a specific component of pool behaviour – pipeline,
prepayment, default and severity
» Model generates correlations between performance and macroeconomic data
» Correlations are estimated using ALL active and inactive deals in the market
» Time series includes data covering a full business cycle
» Based on multiple regression analysis, deal specific vectors are generated under
alternative economic scenarios
» Standardized pool-level data and similar econometric framework is used for ALL
ASSETS AND COUNTRIES
Econometric Model: Dynamic Panel Data
Lifecycle component
» Takes into account the shape of the performance curve over pools’ life
Business cycle exposure component
Pool performance
time series
(e.g., CPR, CDR, LGD
Vectors)
=
f
» Explicit connection between pool performance and macroeconomic drivers
provides the ability to stress test holdings and run “what-if” scenarios
Pool & Loan-level
components
Pool-specific
quality
component
» Attributes (LTV, collateral type, region, etc) define quality across pools
» Early delinquencies also serve as proxies for underlying pool quality
» Economic conditions at origination matter for pool quality
» Econometric technique accounts for other unobserved effects
Different subsets of macroeconomic variables are used
for each vector and asset type
RMBS/HEL
»
»
»
»
»
»
»
Home Prices
Existing Home Sales
Refinancing Activity
Unemployment Rate
Real GDP
Disposable Income and Wages
Fed Funds and Mortgage Composite Rates
AUTO/MOTO LOANS & LEASES
»
»
»
»
»
»
»
STUDENT LOANS
CREDIT CARDS
»
»
»
»
Wages and Disposable Income
Employment ,Unemployment Rate-UI Claims
Real GDP
Interest Rate – Bank Prime Rate
Unemployment Rate-UI Claims
CPI New and Used Cars
Vehicles Sales & Car Registrations
Disposable Income
Real GDP
Personal Bankruptcy Rates
Interest Rate – Bank Prime Rate
»
»
»
»
Labor Market Indicators
Avg. Hourly Wages and Disposable Income
Net Worth and Debt Service Ratio
Interest Rate – Fed Funds
US Auto Loans, Leases, Motorcycle, RVs and Boats: Summary of model inputs
Vector
Economic
Conditions at
Origination
Origination
Conditions
Group
Variable
Current Economic Conditions
60 day
delinquency
90+ day
delinquency
CDR
Repossession Net Chargeoff
CPR
Principal
Weighted Average Coupon (WAC)
X
Weighted Average Maturity (WAM)
X
Loan Type
X
X
X
X
X
X
Unemployment Rate
X
X
X
X
X
X
Prime Rate
Used Car Prices
X
X
X
X
X
New Car Prices
GDP
Pipeline
connections
30 day
delinquency
X
X
X
X
X
X
t, t-3
t, t-3
t, t-3
t, t-3
t, t-3
t, t-3
t, t-3
Unemployment Rate
t
t
t
t
t
t
t
Relative Unemployment Rate
t
t
t
t
t
t
t
Relative Prime Rate
t
Used Car Prices
t
t
t
t
t
Relative Used Car Prices
t
t
t
t
t
Relative New Car Prices
t
t
Automobile Sales
t
Automobile Registrations
t
t
t
t
t
t
Personal Bankruptcies
t
t
t
t
t
t
Mortgage Loan-to-Value Ratio
t
t
t
t
t
t
30 day delinquency
60 day delinquency
90+ day delinquency
t
t
t
t
t
t
Notes: All models include nonlinear terms for the lifecycle (age in months), and seasonality factors (month)
X
Example: USA Alt-A RMBS Deal (2006 vintage)
Constant Default Rate (annualized %)
You can ask: “What would happen to my deal’s CDR under the 5 different
scenarios given by Chief Economist Mark Zandi?”
Worst Case
Scenario
USE OF MODELS AT
STATE STREET
Overview
Model
Macro Forecast
Estimation
Assumptions
Deal-Level
Behavioral
Assumptions
Collateral
Performance
Security-Level
Different uses
Cash-flows
at State Street
CDR
ECAP
Default Vector
Severity
CreditCycle –
Behavioral
Model
Choose your
Macro Scenario
Cash-Flow
Engine
Severity Vector
CPR
Economic
Parameters (GDP,
HPI, employment
Prepayment Vector
Principal and
interest
payments
OTTI Process
Loss
Estimation
Stress Test
Program
Overview
» Several functions within State Street are interested in analyzing
Structured Assets performance
o Global Treasury – responsible for investment decisions and the Other Than
Temporary Impairment (OTTI) process
o Finance – responsible for State Street’s stress test program and the Fed
Comprehensive Capital Analysis and Review (CCAR) program
o Enterprise Risk Management - in its role of business units risk management
and Credit Risk Economic Capital
Internal macroeconomic scenarios
» State Street developed a process for a
firm wide macroeconomic scenarios
that are used throughout the bank
o The scenarios are developed by a
macroeconomic forecasting firm with
inputs from State Street’s Economics
Team
o The scenarios are reviewed and approved
by a Scenario Review Board with
members from different areas of the bank
o The scenarios are used for budgeting and
analysis purposes.
Global Treasury
» Global Treasury is responsible for State Street’s Investment Portfolio (IP).
» In this capacity, it makes decisions on purchase and sell of structured assets bonds
» Global Treasury Risk, analyses the bonds on an ongoing basis and go through a
very robust OTTI process on a quarterly basis (as prescribed by SFAS 115-2).
o Review of the full portfolio and
identification process for deep
dive bonds
o Deep dive analysis on selected
bonds taking CreditCycle vectors
as inputs
o Waterfall cashflows based on
CreditCycle vectors with analyst
adjustments
Finance
» State Street Finance has been
designated to develop and deploy
a stress test program for the bank.
» The Stress Test team conducts
tests on a quarterly basis. The test
maybe on a macroeconomic level
or specific to State Street either as
a whole or specific business units.
» State Street’s Stress Testing
Advisory Committee prioritizes the
tests to be conducted
CreditCycles
Models
Economic Capital
» For credit Economic Capital (ECap) purposes State Street divides its portfolio into
two portions: Credit ECap for Securitized Assets (CESA) and Credit ECap for NonSecuritized Assets (CENSA)
» For CENSA we currently use a Multi-Factor Merton model approach
» For CESA we use the CreditCycles models
Capital Charge by Sub-Asset Type
o Estimation is done on historical data
o Forecasts are calculated based on the Economic Capital
scenario approved by the Scenario Review Board
o Model outputs (CDR, CPR, and Severity) are then entered
into a cashflow engine (INTEX) for principal writedowns and
interest shortfalls
o ECap is defined as Total lifetime Losses – OTTI
o Extremely helpful in identifying capital “Hogs” and manage
holdings accordingly
Aug-10
Aug-11
Sample results for the alternative scenarios
» Below are example of a US RMBS Prime deal “GSR Mortgage Loan Trust 20056F”. Under the alternative scenarios the deal suffers different levels of losses.
o Under the Base case the deal does not suffer losses and therefore no OTTI charges.
o Under Stress Test and ECap the deal suffers a 1% and 3.4% loss respectively.
30
25
20
15
10
5
20
70
18
60
16
14
50
12
40
10
30
8
20
6
4
10
2
0
Severity (%)
Constant Prepayment Rate (%)
Constant Default Rate (%)
0
0
Base
Stress
ECap
Advantages of using the models
» Same models used for different functions within the bank
» Very transparent and intuitive
» Easley used for loss allocation
» Same econometric methodology across asset types increases speed of
implementation and makes it easier to explain to Senior Management
» Easley modified for special projects arise or when alternative scenarios are
considered
o European stress test
o Oil shock scenario
o Foreclosure crisis of 2010