Downside Risks to the Macro Outlook: Retail Credit Risk Implications
-
Upload
moodys-analytics -
Category
Economy & Finance
-
view
550 -
download
0
description
Transcript of Downside Risks to the Macro Outlook: Retail Credit Risk Implications
Dr. Juan M. Licari, Head of Economic & Credit Analytics – EMEA, Moody’s AnalyticsOriginally presented at the EFMA Retail Credit Conference | June 20, 2013 | Amsterdam, The Netherlands
Downside Risks to the Macro OutlookRetail Credit Risk Implications
2
Today’s Agenda
- How to anticipate downside risks & identify different potential scenariosExamples: (i) currency wars, (ii) eurozone breakdown, (iii) US fiscal situation, (iv) emerging markets hard landing, (v) oil price shock and stagflation
- Translation of macro scenarios to retail credit portfolios:Stress Testing Challenges
- UK mortgages case study:A vintage approach to modelling risk
3
Macro Modelling & Scenario Analysis
Simulation-Based Scenarios
4
Weaker Economy
Healthier Economy
Baseline:Recession
S3:Double
Dip
1-in-10
S4:Severe
Double Dip1-in-25
Alternative Economic Scenarios
S2:Mild
Double Dip
1-in-4
S1:Stronger Recovery
1-in-4
Simulation-Based
1:100 1:25 1:20 1:10 1:4 Forecast 1:4
4
S6:Stagflation
1-in-15
S5:Global
Slowdown
1-in-7
Current Economic Cycle
5
Expansion
In recessionAt riskRecovery
May 2013
Source: Moody’s Analytics
Baseline Outlook
6
12 13 14 15 16 12 13 14 15 16 12 13 14 15 16 12 13 14 15 1695
100
105
110
115
120
125
Euro zone
Real GDP, 2008Q1=100
World
U.K.
U.S.
Source: National Statistical Offices, Moody’s Analytics
Baseline Outlook
7
12 13 14 15 16 12 13 14 15 16 12 13 14 15 16 12 13 14 15 160
2
4
6
8
10
Rus-sia
Real GDP growth
China
Brazil
India
Source: National Statistical Offices, Moody’s Analytics
Quantitative Models for Scenario Analysis
-3
-2
-1
0
1
2
3
4
5
2006 2007 2008 2009 2010 (E) 2011 (F) 2012 (F) 2013 (F) 2014 (F)
8
Inflation Rate, History & Forecasts,
Euro-Zone Level
Inflation Rate Distribution, Euro-
Zone Level
Inflation Rate Distribution, Euro-
Zone Level
Developed Markets: GDP Growth
Euro Zone Japan Germany Spain UK US-8
-6
-4
-2
0
2
4
6BL 2013Q2 - 2014Q4 S4 (s-t-t) S6 (s-t-t)
14Q4
14Q3
14Q414Q3
14Q4 14Q4
Source: National Statistical Offices, Moody’s Analytics
9
Developed Markets: Inflation Rate% change on the previous year
Source: National Statistical Offices, Moody’s Analytics
Euro Zone Japan Germany Spain UK US-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.52014Q4 baseline 2014Q4 S4 2014Q4 S6
10
11
Event-driven Scenarios
Event-Driven vs. Simulation-Based Scenarios
12
Weaker Economy
Healthier Economy
Baseline:Recession
S3:Double
Dip
1-in-10
S4:Severe
Double Dip1-in-25
S2:Mild
Double Dip
1-in-4
S1:Stronger Recovery
1-in-4
Simulation-Based
1:100 1:25 1:20 1:10 1:4 Forecast 1:4
12
S6:Stagflation
1-in-15
S5:Global
Slowdown
1-in-7
EmergingMarkets
Hard Landing
SovereignDefaultShock
In line withRegulatoryGuidelines
Event-Driven
13
Alternative Macroeconomic Scenarios
Stronger Near-Term ReboundS1
S2 Mild Second Recession
S3 Deeper Second Recession
Protracted SlumpS4
Baseline (most likely)BL
Standard
Below Trend, Long-Term GrowthS5
Oil Price ShockS6
Fed BaselineFB
Fed AdverseFA
EBA BaselineEB
EBA AdverseES
Regulatory-Driven
Fed Severely AdverseFS
Custom
Euro Zone BreakupEB
StagflationSF
14
GDP at Market Prices, (Bil. 2000 EUR, SA) EU Harmonised Unemployment Rate, (%, NSA)
Average Nominal House Price: Total (EUR)Interest Rate: 10-year Bond Yield, %
Event-Driven Scenario: Italy Exit - Effect on Europe
Source: Moody’s Analytics
GDP at Market Prices, (Bil. 2008 £, SAAR) UK Unemployment Rate, (%, SA)
Halifax Average Nominal House Price, (£, SA)Interest Rate: 10-year Bond Yield, %
Source: Moody’s Analytics
Event-Driven Scenario: Italy Exit - Effect on UK
15
16
Stress Testing Retail Credit Portfolios
• Key Discussion Topics:
1- Dynamic vs. Static Approach to Stress Testing, 2- Partial vs. General Equilibrium,
3- Top-down vs. Bottom-up,4- Modelling Methodologies: Stress Testing vs.
Forecasting/Scoring,
Historic and predicted default rates (baseline), % of balance at originationConsolidated portfolio, vintages over time
Performance of Future Loans
Forecasted Performance of Existing LoansPerformance History
17
Stress Testing: 1- Dynamic vs. Static Approach
18
Historic and predicted default rates (severe scenario), % of balance at originationConsolidated portfolio, vintages over time
Performance of Future Loans
Forecasted Performance of Existing LoansPerformance History
Stress Testing: 1- Dynamic vs. Static Approach
19
Stress Testing: 2- Partial vs. General Equilibrium
Examples of collateral type for RMBS/ABS deals
» Interest rates
» Unemployment rates
» Income growth
» Profits (National Accounts)
» Share market
Small Business Loans
» Interest rates
» Unemployment rate
» Commodity/oil prices
» Price index for used cars
Auto-Equipment Loan/Lease
Illustrative
» Mortgage rate difference from origination
» Unemployment rate
» Employment growth
» Income growth
» House price growth
» Home equity
RMBS
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
Baseline
S3
S4
DD
0
10
20
30
40
50
60
70
80
90
100
2009
M06
2009
M11
2010
M04
2010
M09
2011
M02
2011
M07
2011
M12
2012
M05
2012
M10
2013
M03
2013
M08
2014
M01
2014
M06
2014
M11
2015
M04
2015
M09
Baseline
S3
S4
DD
PD term-structure
LGD curves
20
Stress Testing: 3- Top-down vs. Bottom-up
Issue: Loan level model can miss correlations and feedback effects
» Individual performance depends on other loans
» Difficult to model individuals within a system
Risk models could miss the forest for the trees– Why not model the forest, model the trees and then make
sure the tree model agrees with forest projections?
≠
21
Stress Testing: 4- Modelling Methodologies
Table 1 Average probabilities (1983M1 - 2007M1)
Aaa Aa A Baa Ba B Caa-c Def Aaa 92.10% 7.52% 0.33% 0.00% 0.04% 0.00% 0.00% 0.00% Aa 0.99% 90.49% 8.07% 0.37% 0.04% 0.03% 0.00% 0.02% A 0.07% 2.76% 90.65% 5.67% 0.65% 0.15% 0.03% 0.02% Baa 0.05% 0.24% 5.51% 87.91% 4.75% 1.14% 0.23% 0.17% Ba 0.01% 0.07% 0.47% 6.35% 82.56% 8.60% 0.60% 1.33% B 0.01% 0.05% 0.18% 0.52% 5.52% 82.90% 4.74% 6.08% Caa-c 0.00% 0.02% 0.10% 1.20% 1.19% 7.12% 69.42% 20.96%
Table 2 Average probabilities (2007M6 - 2009M10)
Aaa Aa A Baa Ba B Caa-c Def Aaa 78.15% 21.71% 0.04% 0.11% 0.00% 0.00% 0.00% 0.00% Aa 0.05% 82.65% 16.03% 0.99% 0.11% 0.02% 0.07% 0.09% A 0.00% 0.88% 89.58% 8.24% 0.44% 0.30% 0.15% 0.41% Baa 0.01% 0.14% 2.20% 91.95% 4.40% 0.72% 0.20% 0.38% Ba 0.00% 0.00% 0.04% 5.10% 81.25% 10.46% 1.83% 1.32% B 0.00% 0.00% 0.07% 0.17% 3.35% 78.31% 13.55% 4.55% Caa-c 0.00% 0.00% 0.00% 0.14% 0.23% 5.74% 71.19% 22.70%
22
Stress Testing: 4- Modelling Methodologies
Figure I: Bi-Modal Nature of Credit Transitions Bi-Modal Distribution of Baa to Ba Credit Migrations (Bar Chart) vs. a Normal, Symmetric Distribution (Green Solid Line)
01
02
03
04
0D
ensi
ty
0 .02 .04 .06 .08 .1baa_ba
First Mode: Around Normal/Good Credit
Conditions
Second Mode: Around Stressed Credit Conditions
23
Stress Testing: 4- Modelling Methodologies0
.2.4
.6.8
1T
ran
sitio
n %
2000m1 2002m1 2004m1 2006m1 2008m1 2010m1 2012m1Month of Transition
Binary_Probit_Regression O_1_Median_Variable
0.2
.4.6
.81
Tra
nsitio
n %
2000m1 2002m1 2004m1 2006m1 2008m1 2010m1 2012m1Month of Transition
Binary_Probit_Regression O_1_Median_Variable
Binary (Probit) Model Downgrade
0.1
.2.3
.4T
rans
ition
%
2000m1 2002m1 2004m1 2006m1 2008m1 2010m1 2012m1 2014m1 2016m1Month of Transition
Actuals BaselineFSA Scenario4Custom
0.0
2.0
4.0
6.0
8T
rans
ition
%
2000m1 2002m1 2004m1 2006m1 2008m1 2010m1 2012m1 2014m1 2016m1Month of Transition
Actuals BaselineFSA Scenario4Custom
CaaC to DefaultBaa to A
Binary (Probit) Model Upgrade
24
Case Study: UK Mortgage Market
Econometric model – Dynamic Panel Data Techniques
Time series performance for a given vintage and
segment
= f
Lifecycle component
» Dynamic evolution of vintages as they mature
» Nonlinear model against “age"
(1) Lifecycle component
Pool-specific quality component
» Vintage attributes (LTV, asset class/collateral type, geography,
etc.) define heterogeneity across cohorts
» Early arrears serve as proxies for underlying vintage quality
» Economic conditions at origination matter
» Econometric technique accounts for time-constant,
unobserved effect
(2) Vintage-quality component
Business cycle exposure component
» Sensitivity of performance to the evolution of
macroeconomic and credit series
(3) Business cycle exposure component
25
Lifecycle ComponentLifecycle Component
Modelling Approach
Consumer Credit Forecasting
Total delinquency rate (% of out. £) against months-on-book
26
Vintage-QualityVintage-QualityModelling Approach
Consumer Credit Forecasting
Vintage quality index (left) and Disposable Income Growth (right) against vintages
27
- Baseline Scenario- Stressed Scenario
Exposure to theBusiness CycleExposure to theBusiness Cycle
Modelling Approach
Consumer Credit Forecasting
Total delinquency rate (% of out. £) under different economic scenarios
28
© 2013 Moody’s Analytics, Inc. and/or its licensors and affiliates (collectively, “MOODY’S”). All rights reserved. ALL INFORMATION CONTAINED HEREIN IS PROTECTED BY 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 WRITTEN CONSENT. All information contained herein is obtained by MOODY’S from Fuentes 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. 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. 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. Each rating or other opinion must be weighed solely as one factor in any investment decision made by or on behalf of any user of the information contained herein, and each such user must accordingly make its own study and evaluation of each security and of each issuer and guarantor of, and each provider of credit support for, each security that it may consider purchasing, holding, or selling.