Credit Stress LossAlexandre KurthWM&SB Risk Control
22 October, 2009
1
Alphabet of Credit Risk Measures
frequ
ency
of l
osse
s
expectedcredit risk
costs
ExpectedLoss
cost of economic capital directcosts
mean:Expected Loss
amount of loss
Confidence-level ofeconomiccapital
Economic Capital
Standarddeviation
Risk Measure:UnexpectedLoss
Stress Lossesunacceptable risks
Statistical Loss,e.g. Expected Shortfall,CoC
absorbed by revenues absorbed by capital
2
What is Stress Testing About?
♦ Principles for sound stress testing practices and supervision; Basel Committee on Banking Supervision Consultative Document, issued for comment March 13, 2009
♦ Quote: Stress testing is an important risk management tool that is used by banks as part of their internal risk management and, through the Basel II capital adequacy framework, is promoted by supervisors. Stress testing alerts bank management to adverse unexpected outcomes related to a variety of risks and provides an indication of how much capital might be needed to absorb losses should large shocks occur. Moreover, stress testing is a tool that supplements other risk management approaches and measures. It plays a particularly important role in:– providing forward-looking assessments of risk;– overcoming limitations of models and historical data;– supporting internal and external communication;– feeding into capital and liquidity planning procedures;– informing the setting of a banks’ risk tolerance; and– facilitating the development of risk mitigation or contingency plans across a range
of stressed conditions.
3
Overview of Stress LossThree mutually reinforcing Pillars
MINIMUM CAPITALREQUIREMENTS
Combined bank-wide stress test
SUPERVISORY REVIEW OFCAPITAL ADEQUACY
Portfolio specific stress tests
MARKET DISCIPLINE
Reverse stress test
NEW BASEL CAPITAL ACCORDMeasure, monitor
and control risk under stress conditions
Reports, Limits, Planning
4
Credit Stress Testing Landscape
Lombard, Securities FinancingReal Estate Corporate Clients
Credit Portfolio WM&SB
Scenario Analyses
Concentration Analyses
Swiss Real Estate Scenario (Replication 90ies-crisis)
Market risk scenarios (e.g. liquidity and epicenter
scenarios:
Collateral Concentration: (Issuer Group, Hedge Funds, Mutual Funds,
Country)Top Client List: Expected Tail Loss, limit, exposure,
expected Loss
Industry concentrationIndustry concentration
Reverse Stress Testing
Define hypothetical bank-breaking scenarios, e.g. leading to a predefined target loss, not based on PDs, EADs, LGDs, not using a history based model [cf. Principles
for sound stress testing practices and supervision, Par. 9]
Global macro-economic scenariosScenarios: Factor model to forecast
PDs and LGDs
sticky portfolio which is managed in longterm
view
liquid portfolio which can be managed on short-
term basis
majority of portfolio cannot be managed on
short-term basis
5
Applications of EL, Credit VaR, Stress Loss, Loss Forecast
Credit VaRExpected Loss
Risk Measures
Appl
icat
ions
*
Stress Losses
Risk Control
Portfolio Thresholds / Triggers
CLLP
RWA Basel II Capital
Strategy
PricingPerformance Measurement
Basel II ICAAP (Pillar II)Business Plan
*) Applications are not exclusively driven by these measures; but they are influenced; there may be others as well.
…there is no one-size-fits-all measure
General Provisioning
Pool
Influence from risk measures on risk relevant applications…
Actual Loss ForecastNotional
6
Uncertainty of Stress Losses
current EL
stress loss
distribution of credit losses conditional on the
stressed economic situation
♦ The stress loss measure does not suggest the worst possible outcome
♦ Even if the economy turns out to be as assumed in the stress scenario, the loss outcome may significantly vary around the expected value (stress loss) alternative measure for stress loss could be a quantile or ETL of the distribution or confidence interval
ABSCHNITT 1
Lombard Stress
8
Collateral Concentration
♦ Portfolio concentrations of exposures collateralized by marketable assets (e.g. Lombard) are measured by 'single' shocks
10-d
ay p
rice
drop
for s
elec
ted
hist
oric
ev
ents
Proposed shocksMerck
Netscape
Yahoo!
SGX Pharmaceuticals
ABB
Ahold
Parmalat
Worldcom
Enron
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Accounting fraud, June 02
Accounting fraud / insolvency, Dec 03
Grounding, Oct 01
Share price manipulation, Jan 06
Accounting fraud / insolvency, Dec 01
Accounting fraud / CEO resignation, Feb 03
Failed strategy / asbestos risk, Oct 02
Failed clinical trial, Sep 06
Accounting and civil fraud, June 02
Legal issues, July 06
Dot.com bubble, Oct 00
General company crisis, Aug 98
Dot.com bubble, May 00
Accounting problems, Jan 04
Vioxx, Oct 04
Adecco
Qualcomm
Bet and win
Livedoor
Swissair
Tyco
Even without a general market downturn, idiosyncratic, event-driven shocks proved disastrous in the past.
9
Example of Collateral Concentration
Title MV LV exposureTitle A 15 6Title B 2 1.2Title C 3 1.8Total 20 9 6
All figures in CHF Mio
5 3
Loss: CHF 1 Mio
XX X
X Total
10
Collateral Concentration Analysis ResultsCollateral concentration of issuer groups
illustrative figures
CHF mio Volatility Adtv McapIssuer Group Issuer Rating May09 Feb09
1 (1) Issuer A 100 105 86 [1664]
Equity 25% 315 86'716 26
Debt A1 8
Fiduciary 67
Structured products 0
2 (2) Issuer B 65 90 1 [314]
Equity 28% 384 112'354 65
Debt Aa2 0
Fiduciary
Structured products 0
3 (4) Issuer C 27 28 1 [99]
Equity 46% 753 37'946 27
Debt A2 0
Fiduciary
Structured products 0
95% ShockStress exposure Eff [actual]
# stress exp.
11
Market Scenario Stress Testing in Credit
TradedProducts
Client relationship
Collateralmarket value
BankingProducts
Equities
Fixed Income
Precious Metals
Cash
Hedge FundsMutual FundsStruct.
Products
other
Exposure
Before stress event
Stress ex.
Additional unsecured exposure following a market stress event
Exposure
TradedProducts
BankingProducts
Collateralmarket value
EquitiesFixed Inc.P. Metals
Cash
H. FundsM. Funds
St. Prod.
other
Stress exposure
After stress event
Scenarios / market stress events
10-day risk factor shocks for ♦ Equity indices ♦ FX rates ♦ Interest rates ♦ Country spreads♦ Credit spreads
Shock transmission
♦ Risk factor shocks are translated into product-specific shocks
♦ Exposure side only receives FX shock to account for currency mismatches
12
Stress Test Scenario Description for Securities FinancingThe scenario suite consists of selected Group market stress as well as portfolio-specific scenarios
Equ
ity in
dex
shoc
ksC
urre
ncy
shoc
ks
vs. C
HF
Libo
r rat
e sh
ocks
in b
p
Note that the above charts only contain the most relevant risk factors.
Scenario 1All markets down
Scenario 2EM crisis (pegs break)
Scenario 3Credit crunch
Scenario 4FX shocks only
Scenario 5specific scenario
Scenario 6specific scenario
Market Risk Stress Test Scenario Portfolio specific Scenarios
EU
RG
BP
GB
P
HK
DS
GD
RU
BB
RL
US
DE
UR
GB
PJP
YH
KD
SG
DR
UB
BR
L
EU
RG
BP
JPY
HK
DS
GD
RU
BB
RL
EU
R
JPY
US
D
US
D
US
DE
UR
JPY
HK
DS
GDR
UB
BR
L
US
D
GB
P
HK
DS
GD
RU
BB
RL
JPY
EUR
US
D
GB
PJP
YH
KD
SG
D
BR
LR
UB
CH
FE
UR
US
DG
BP
JPY
HK
DS
GD
CH
FE
UR
US
DG
BP
JPY
HK
DS
GD
SG
DH
KD
JPYG
BPUSDEURC
HF
SG
DH
KD
JPY
US
D
CH
FEUR
GBP
SG
DH
KD
JPY
GBP
USDEURCHF
SG
DH
KD
JPY
GB
PU
SD
EU
RC
HF
SM
IS
&P
500FTS
E 100
DA
XC
AC
Topix
CA
CD
AX
FTSE
100S
&P
500S
MI
Topix
CA
CD
AX
FTSE
100S
&P
500S
MI
CA
CD
AX
S&
P500
SM
I
SM
IS
&P
500FTS
E 100
DA
XC
AC
Topix
Topix
Hang S
eng
Hang S
eng
TopixH
ang Seng
CA
C
FTSE
100
Hang S
eng
Hang S
eng
Hang S
engTopix
SM
IS
&P
500FTS
E 100
DA
X
13
Stress Scenario Results
♦ Stress results show portfolio exposition against a scenario
♦ Stress results are not a forecast
♦ Significant increase of Stress Exposure during the subprime crisis until November 2008
♦ Continuous decrease of Stress Exposure since November 2008
Total Stress Exposure
1.001.78
0.87 0.82 1.27 1.33 1.712.54
3.31 3.02 3.24 3.412.37 2.18
1.45 1.39 1.26
4.81
0
1
2
3
4
5
6
Mar06
May06
Aug06
Nov06
Feb07
May07
Aug07
Nov07
Feb08
May08
Aug08
Nov08
Feb09
Mar09
Apr09
May09
Jun09
Jul09
Stre
ss E
xpos
ure
in C
HF
mill
ion
(inde
xed
Mar
06)
illustrative figures
ABSCHNITT 2
Macro-economic Stress Testing
15
SensitivitiesDrivers
Use sensitivities to forecast future PDs and LGDs for stress scenarios defined in terms of drivers, e.g. PD=f(IR, GDP growth, RE prices,…)
Identify macroeconomic factors for each segment which impact the default rate, i.e. Interest Rate IR, GDP growth, RE prices, FX rate EUR/CHF
Sensitivities Analyse historic time series to estimate how a change in a driver impacts the default rate resp. LGD, e.g. IR up 1% => PD up by x%, i.e. default rate for services (1.00%) changes by 1.00%*39% to 1.39%, if IR goes up by 1%
Forecast
Sensitivities for various economic drivers are estimated on portfolio relevant segmentation:
e.g.Energy intensiveFinancial ServicesManufacturingServicesReal Estate ConstructionRestaurant Hotels…
Lombard, Securities FinancingReal Estate Corporate Clients
private mortgagesIPRE
private clientsmarket stress
16
Macro-economic Stress Testing Methodology Explained♦ Sensitivities to macroeconomic variables estimated based on internal history of
impairment data Main drivers: GDP growth, interest rates, FX rate EUR/CHF, House Price changes
♦ Application to given macroeconomic scenario
02
46
8%
1995
q1
1996
q1
1997
q1
1998
q1
1999
q1
2000
q1
2001
q1
2002
q1
2003
q1
2004
q1
2005
q1
2006
q1
2007
q1
2008
q1
2009
q1
2010
q1
time
Illustrative example
Upper confidence bound
Lower confidence bound
Fitted Values / Forecasts under stress scenario
2008
q1
2009
q1
2010
q1
Current Average
PD in Portfolio segment
Application
Stressed Default Rate Levels
Future stress scenario, specifying GDP, interest rates, FX-rates, etc.
Past time-series of default rates, used to derive sensitivities to macro-variables like GDP, interest rates … 20
09q1
2010
q1
2011
q1
εββββ +++++= KKVolatilitytesInterestRaGDPgrowthPD ...22110
ABSCHNITT 3
Real Estate Stress
18
A New Swiss Real Estate Crisis
♦ Starting point: favorable economic environment in Swiss real estate market
♦ Inflation picks up throughout the country
Loss RateBankruptcy RateBooked Losses
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004Replication of the Swiss real estate bubble from the 90ies
♦ Property prices go up, too, resulting in a general bubble
♦ SNB is forced to react and raises interest rates sharply
♦ The economy markedly slows down, unemployment starts to grow, the property markets show first signs of correction
♦ A widespread fall of property prices follows
Illustration –sample figures
19
Credit Risk Drivers in Real Estate Portfolio
Affordability
Equi
ty
Portfolio Slice along LtV and Affordability for private mortgages
Affordability = _____________________________costs (mortgage, maintenance)
income (corrected by 2nd homes)
Loan-to-Value
LGD
Default
Red AreaLosses expected due to- limited equity buffer- stressed affordability
Orange AreaNo losses expected because of - very good affordability and - limited or missing loss potential
20
Impact of Scenarios
Affordability
Equi
ty Shift to upper areas
Real Estate Price Decline
Interest Rate Increase
Unemployment Rate Increase
Shift to right area
0.1% 0.35%
Increase of Default Rates
21
Market Activity Map for Swiss Owner-occupied Properties
Market activity map is based on Swiss real estate market variables such as prices, construction activity; and macro-economic variables such as unemployment rate, tax rates and population (change, forecast)
Market activity map for Swiss Owner-occupied Properties based on MS segmentation (mobilité spaciale)
22
Real Estate Scenario Cockpit
♦ Price forecast of price index per MS region (mobilité spaciale) auf Basis based on macro-economic parameters and scenarios
♦ Forecasts per MS-Region for– SFH– Condominiums– MFH– Office Buildings ♦ The Real Estate Scenario Cockpit supports
– the visualization of the (long-term) sensitivity of the Swiss real estate market based on normal scenarios
– stress loss calcuation based on various stress scenarios
Real Estate Scenario Cockpit
ABSCHNITT 4
Reverse Stress Testing
24
The "Reverse" part of Stress Testing Current scenarios ask "what happens if" whereas reverse stress testing asks "what needs to happen that we lose x"
Define scenario mainly based on history in terms of macroeconomic variables, e.g. GDP, IR, etc.
Apply model based on internal risk measures parameters and historic time series
Obtain stress loss figures, usually in a severe but not (necessarily) bank breaking dimension
Define outcomes which threaten the viability of the whole firm, e.g. target loss breaking regulatory capital ratios
Find hypothetic trigger events which could cause such an effect
Find out which (sub-) portfolio would be affected to which extent, NOT on the basis of historic time series
Conventional stress test
Reverse stress test
Principles for sound stress testing practices and supervision; Basel Committee on Banking Supervision Consultative Document, issued for comment March 13, 2009 (cf. Principle 9, p.18)
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