Testing Resilience of the Czech
Financial System
Jan Frait
Deputy Head of Economic Research and Financial Stability Department
Smilovice 2009
Stress testing in the CNB
•
•
for assessing resilience of the financial system to shocks other than
liquidity shocks, the CNB conducts stress tests of banking sector since
2003
three (slightly overlapping) stages in development of the stress testing
framework for banks
simple static stress testing/sensitivity analysis (2003-2006)

static stress testing based on (consistent) macroeconomic
scenarios, satellite models and with some interbank contagion
(2005-2009)

dynamic model-based stress testing (2009++)
Macro-stress tests have semi-top-down style, CNB also runs
bottom-up tests with banks

•
•
since 2007, the CNB conducts stress tests of insurance companies (market
risk, insurance-specific risks) and pension funds (market risk)
2
Publication of stress test results
•
•
•
•
the CNB was always very open in communication of stress test results to
the industry and public
traditional means of publication is Financial Stability Report (since FSR
2004 published in January 2005)
results first published in a special feature/article, since FSR 2007 in the
main text (chapter Financial Sector – part „assessment of the financial
sector‘s resilience“)
stress tests conducted nowadays quarterly (for the CNB macrofinancial
panel),

results sometimes published in Bank Board members‘ presentations,

now ready for regular release of results starting from next quarterly
exercise (February 2010)
3
Stress testing in the CNB
Stage I
Simple static stress testing/sensitivity analysis
(2003-2006)
FSR 2004, FSR 2005, FSR 2006
4
Simple static stress testing
• methodology based on the IMF FSAP approach, developed in co-operation
with the IMF
• for testing credit risk and market risk (interest rate risk and FX risk)
• based on „static“ balance sheets of individual banks and assumptions how
balance sheets would change if (a) interest rates, (b) exchange rate, (c)
NPL changed
• impact horizon of 1 year
• suitable for simulations of the impact of
 single shocks (sensitivity analysis) like increase of NPLs by 20%,
 ad hoc scenarios defined as combination of risk factors that have direct
impact on banks‘ balance sheets (interest rate, exchange rate, NPL)
5
Mechanics of the stress test I
Transmission of risk factors:
• impact of a change in NPL: increase in NPL leads to increase in loan loss
provisions (using information about banks‘ provisioning rate)
• impact of a change (increase) in interest rates: change in net interest income
(gap analysis) plus re-pricing of debt securities (duration analysis)
• impact of a change in exchange rate: change in value of FX-denominated assets
and liabilities (using data on net FX position) plus indirect effect on NPL (loans
denominated in FX)
6
Mechanics of the stress test II
Other assumptions:
• in the absence of shocks, banks are assumed to generate profit at the level of the
average of the last 5 years
• profit is used to raise capital to the initial level of capital adequacy (if the profit
is sufficient to counterbalance the impact of shocks), the rest (if any) is
distributed via dividends
• risk-weighted assets (RWA) after shock are calculated as initial RWA minus
80% of the overal impact of shocks
• results of the stress tests are presented in percentage points of the initial capital
adequacy
7
Ad hoc scenarios in the simple stress
test
• the CNB used so-called „historical
scenarios“ I and II, i.e. combination of
shocks that mimic past crisis (1997-1998)
and past volatility of variables (see the
table taken from FSR 2004)
• shocks can be alternatively calibrated for
example as 1 p.p. confidence level
(roughly 3 standard deviations)
• combination of shocks should be
plausible and reflect possible reaction of
authorities and markets (e.g.. central bank
raises interest rates to defend currency
from further depreciation etc.)
8
Presentation of results of an ad hoc
scenario I (FRS 2005, p. 79)
9
Advantages of simple stress tests I
•
•
•
can be used to quickly
assess resilience to
specific risks (sensitivity
analysis)
respond to questions like
„how much would the
interest rates have to
increase to get post-test
capital adequacy equal
to the minimum value of
8 % (see chart from FSR
2005)
served as a necessary
first step in developing
more comprehensive
framework
10
Stress testing in the CNB
Stage II
Static stress testing based on (consistent) macroeconomic
scenarios and satellite models
(2005-2009)
FSR 2005, FSR 2006, FSR 2007, FSR 2008/2009
11
Basic building blocks
•
•
based on the static simple stress testing, i.e.

same risk factors (credit risk, interest rate risk, FX risk)

same transmission channels (impact on net interest income,
revaluation of bonds, FX profit/losses, loan loss provisions)

same horizon of 1Y

same assumptions about profit, CAR etc. (but from FSR 2008/2009,
pre-provision income instead of profits used)
new features

explicit (consistent, i.e. model-generated) macroeconomic scenarios

satellite models to transmit changes in macro variables into risk
factors

a new risk factor – interbank contagion
12
The framework
• QPM model (or since late 2008 G3 DSGE model) generates both baseline
forecast (the official CNB forecast produced quarterly) as well as alternative
„adverse“ macroeconomic scenarios
• satellite models are credit growth model (ECM model of aggregated credit
growth) and credit risk models (corporate, households)
13
Transmission Channels of Credit Risk
14
• dependent variable of credit risk models: 12M default rate (i.e. new bad
loans over initial portfolio)
• 12M default rate is also used by commercial banks; the Basel II „PD“ used
for IRB approach in credit risk should be „a long-run average of default
rates“
• model and explanatory variables
 Corporate Sector
Merton model
macroeconomic shocks (explanatory variables); GDP growth,
exchange rate, inflation, debt
 Households
Merton model + naive econometric models
unemployment rate, real interest rates, GDP
14
Transmission Channels of Credit Risk
15
• other parameters entering the stress tests were derived using sub-models and
expert estimates
• NPL ratio - the ratio of non-performing loans to total loans - was generated
using
 credit risk models
 credit growth model
 expert judgment/assumptions about NPL outflow a
NPL(2)/L(2) = approx. [NPL(1) + L(1)*df - a*NPL(1)]/L(2)
• approximate relationship, because it depends on the time horizon (new loans
can also turn bad)
15
Credit Risk Modeling
16
• Macroeconomic credit risk model for the Czech and Germany corporates
were estimated (Jakubík and Schmieder 2008)
• Czech:
• German:
Variable
df t   (c  b 2 et  2  b 3p t 1  b 4,1 gdpt  b 5 debt t  4  b 6 dumt )
df t   (c  b1irt 1  b 4,1 gdpt  b 4, 2 indprod t 3  b 5 debt t 4 )
Notation
Lag
Czech case
German case
Coefficient Std. error Lag Coefficient Std. error
Constant
-3.060***
0.358
ir
NA
Nominal Interest Rate (b 1 )
e
-2
1.062***
0.323
Real Exchange Rate (b 2 )
-1
-4.850***
0.636
Inflation (b 3 )
p
gdp
0
-4.609***
1.079
GDP (b 4,1 )
indprod
NA
Industry production (b 4,2 )
debt
-4
3.006***
0.246
Credit-to-GDP ratio (b 5 )
dum
0
0.238***
0.043
Dummy variable (b 6 )
Significance level: **: Significant at 5% level; ***: Significant at 1% level;
-1
0
-3
-4
0
-2.6997***
2.2194***
NA
NA
-3.3677***
-0.8215***
1.0871***
0.0400***
0.07141
0.4919
0.328
0.1464
0.1213
0.0125
16
Credit Risk Modeling
17
• Macroeconomic credit risk model for the Czech and German households
were estimated (Jakubík and Schmieder 2008)
• Households models: less successful than for corporates, additional (socioeconomic) indicators may improve modelling
Variable
Notation
Lag
Czech case
German case
Coefficient Std. error Lag Coefficient Std. error
-2.224***
0.071
-5.5656***
0.1072
NA
NA
0
-5.7912***
0.9244
Constant
Household Income (b1)
inc
NA
Credit-to-GDP ratio (b2)
debthouse
NA
NA
NA
-4
5.7186***
0.2788
Unemployment Rate (b3,1)
u
-4
3.695***
0.846
NA
NA
NA
Real Interest Rate (b3,2)
r
-3
1.808**
0.596
NA
NA
NA
Significance level: **: Significant at 5% level; ***: Significant at 1% level;
17
Scenario building
•
•
•
•
•
possible to construct scenarios without a macroeconomic model, but
to achieve the highest possible consistency, using a macro model
(QPM, DSGE, VAR) is of advantage
scenarios should be of a typ „low probability – high impact“, but
plausible and have some „story“ behind
should react to risks identified in risk assessment; in case of doublesided risk, opposite scenarios can be built (e.g.
appreciation/depreciation, increase/decrease in interest rates)
the story can be reflected in the name of the scenario (makes it easier
to remember); „sexy“ names are of advantage
use baseline scenario (official forecast) as benchmark; however,
problems with interpreting the results if the stress testing
model/models calibrated conservatively
18
Example FSR 2007: stress test scenarios
19
• Three alternative model-consistent scenarios in FSR 2007 (scenarios for the
year 2008
 A - safe haven (appreciation of currency)
 B - property market crisis (internal shock with direct impact on banks)
 C - loss of confidence (external shock – increase in risk aversion)
Calibration of baseline and alternative scenarios
(2008 averages)
Baseline Scenario A Scenario B Scenario C
Real GDP growth (%; y-o-y)
4.1
2.4
0.3
2.8
Inflation rate - CPI (%; y-o-y)
6.2
7.0
5.3
8.0
Unemployment rate (%)
6.0
6.3
6.7
6.3
1Y PRIBOR (%)
3.8
2.8
1.5
8.7
1)
...
CZK/EUR exchange rate
25.6
27.0
30.5
Source: CNB
Note: 1) In 2008, the baseline expects an correction of the record values initially and then a slight appreciation
19
FSR 2007: Impact of Alternative Scenarios on
the Banking Sector
21
• Example of presentation of
Baseline Scenario A Scenario B Scenario C
the results
Scenario type
2007
2007
2007
2007
11.5
11.5
11.5
11.5
Capital adequacy (CAR)
• The results were interpreted
Results for chosen scenario type
-2.1
-2.8
-3.0
-6.3
Overall impact of shocks (p.p. CAR)
as follows:
0.2
0.1
0.6
-2.6
Interest rate shock
-0.1
-0.2
0.0
0.5
Exchange rate shock
 The banking sector
-2.0
-2.4
-3.3
-3.6
Credit shock
-0.5
-0.5
-0.5
-0.5
… households
seems to be resilient to a
-1.0
-1.5
-2.0
-0.6
… non-financial corporations
-0.2
-0.2
-0.2
-0.7
Interbank contagion
wide range of risks
9.4
8.7
8.5
5.2
CAR before profit allocation
1.8
2.3
2.2
2.8
Profit allocation (p.p. CAR)
 Only an extreme
Post-shock CAR
11.3
11.0
10.8
8.1
0.0
0.1
0.1
1.1
macroeconomic scenario
Capital injection (% of GDP)
0.0
0.0
0.0
14.9
Share of banks with negative capital after shock
would necessitate
Notes:
1) CAR means the capital adequacy ratio defined in accordance with the relevant CNB regulations (in particular those
capital injections to
governing the capital adequacy of banks and other prudential business rules).
2) Test integrated with interbank contagion and expected level of loss given default (LGD) 100%
maintain sufficient
and chosen probability of the banks' failure (default) on the basis of the CAR.
3) The scenarios assume that in the absence of shocks each bank would generate profit (or loss) equal to the average for the previous five
capitalization
years and that it would use any profit (income) as a first line of defence against a declining CAR.
Results of bank stress tests
(capital adequacy; % and p.p.)
1)
2)
3)
4)
5)
4) The capital needed to ensure that each bank has a post-shock CAR of at least 8%.
5) Market share of banks with negative capital after the impact of the assumed shocks (as a percentage of total assets).
21
FSR 2007: Impact of Alternative Scenarios on
the Banking Sector
• alternative –
graphic –
presentation of the
results
• scenario C would
have the strongest
impact on banking
sector
26
24
Baseline
Scenario A
Scenario B
Scenario C
Growth of total loans
(%)
22
20
22
____
____
____
____
18
16
14
Capital adequacy
(%)
12
10
8
6
4
Share of default loans
(%)
2
0
2006
2007
2008
Source: CNB
Note: Growth in total loans is defined as the average annual rate of growth. The share of new
non-performing loans (NPLs) relates to the estimation of the loan volume at the end of 2007.
22
Example FSR 2008/2009: macroeconomic
scenarios
23
• Three scenarios reflecting the risks from the global financial
crisis



Europe in recession (= baseline prediction)
Nervousness of the markets (a la „loss of confidence“, i.e.
increase in risk aversion)
Economic depression (very large decline in GDP)
Stress-Test Scenarios
in CNB's Financial Stability Report (June 2009)
Europe in
recession
Development of key macroeconomic variables in 2009
Real GDP (%, y-o-y)
-2.4
Inflation (%, y-o-y)
1.2
Interest rate 1Y PRIBOR (%)
2.4
Exchange rate CZK/EUR
26.6
Nervousness of
markets
-3.9
1.7
4.6
28.8
Economic
depression
-6.2
1.3
2.6
27.8
23
FSR 2008/2009: capital adequacy looks
satisfactory even in large depression
Results of stress testing scenarios
(%; banking sector)
16
14
Capital adequacy development
(%)
12
10
8
6
Share of non-performing loans (%)
4
2
0
06/2007
12/2007
06/2008
12/2008
Europa in recession
Nervousness of markets
Economic depression
Source: CNB
06/2009
12/2009
• Horizon of stress tests is
just one year.
• In a longer horizon, the
NPL share continues to
grow and capital
adequacy deteriorates
further.
• Still, unless recession is
very long and very deep,
the banks should manage
without public funds.
24
FSR 2008/2009: presentation of the
results
Results of bank stress tests
(capital adequacy; % and p.p.)
Scenario type
Europe in
recession
Capital adequacy (CAR) at the end 2008
Overall impact of shocks (p.p. CAR)
Interest rate shock
Exchange rate shock
Credit shock
… households
… non-financial corporations
Interbank contagion
Income allocation 2/
Post-shock CAR
Capital injection (CZK billions) 3/
Capital injection (% of GDP) 3/
Number of banks (CAR below 8 %) 4/
Share of banks (CAR below 8 %) 4/
Number of banks with negative capital
Share of banks with negative capital 5/
5/
1/
Nervousness of
markets
Economic
depression
12.3
12.3
12.3
-3.2
1.3
0.0
-4.4
-1.3
-3.0
-0.1
2.2
11.3
8.0
0.2
4
8.2
0
0.0
-5.4
0.0
0.1
-5.4
-1.5
-3.1
-0.1
3.1
10.0
15.7
0.4
8
21.8
0
0.0
-5.0
1.2
0.1
-6.2
-1.8
-3.9
-0.1
2.4
9.7
15.5
0.4
4
5.0
1
5.2
1/ CAR means the capital adequacy ratio defined in accordance with the relevant CNB regulations
(in particular those governing the capital adequacy of banks and other prudential business rules).
2/ We assume that banks would generate income in all adverse scenarios which would be used to
strengthen the capital. The level of income for individual banks is estimated using the past
development of income and parameters of the scenario. Every bank allocates the income to reach
the starting CAR level.
3/ The capital needed to ensure that each bank has a post-shock CAR of at least 8%.
4/ Banks with post-shock CAR 0 - 8 %.
5/ Banks with post-shock negative capital.
• same style of presentation
• information about the
capital injections needed
25
Stress testing in the CNB
Stage III
Dynamic model-based stress testing
(2009++)
FSR 2008/2009
26
Problems with static stress testing
•
Existing framework limited as regards its ability to

analyze the impact of shocks in a longer horizon than a one-year
horizon (up to two to three years),

capture the effects of credit, interest and currency shocks over
time in a more dynamic way,

estimate the pre-provision income as a function of both the
macroeconomic development and a bank’s business model,

be expressed in the variables used in current regulatory
framework (PD, LGD) and thus mimick the stress testing done
by individual banks within Pillar II of Basel II

capture pro-cyclical nature of current Basel II regulation,

integrate fully the funding liquidity shock within the
macroeconomic stress testing framework,

link the interbank contagion and second-round liquidity shocks
to development of the individual bank’s capital and liquidity
conditions in a non-linear way, and

capture potential two-way interaction between the banking
system and the macroeconomic environment (feedback effect).
27
Example of the „time“ problem:
market vs credit risk
•
difference in time horizon between the effects of market
and credit risks


•
•
impact of a change in interest rates or other market
variables (the exchange rate or stock prices) on the balance
sheets of financial institutions is virtually immediate
(revaluation of securities)
credit risk accumulates over a longer time frame (one to
three years) as loans gradually shift into the NPL category
existing CNB stress testing framework was addressing
this discrepancy with a compromise assuming an impact
horizon of one year
macro variables of the projected year were averaged to
produce the „shock“ as the difference between initial and
average future value = underestimates peaks in possible
crisis (Lehman September 2008)
28
Example of the evolution of the
impact of shocks
•
•
•
„experimental“ dynamic stress test in FSR 2008/2009
scenario „nervousness of markets“ assumes losses due to
unfavourable interest rate changes in some quarters, but these losses
are fully reversed in the following periods
this dynamics of the directional changes in the shocks over time
generates stress situations in the financial sector that cannot be
captured by the standard stress tests using averages for the entire test
period.
29
Bringing the stress tests in line with
Basel II
•
Pillar I: change in credit risk terminology/risk factors



•
explicit PD (probabilities of default, proxied by default
rates), LGD (loss given default), EL (expected loss)
loan segments very close to Basel II segments (corporate,
retail, other)
for banks in IRB approach, application of Basel II formula
to determine capital requirements
Pillar II: exchange of views with banks on stress testing
methodology


adjustments in interest rate impact (use of derivatives,
interest rate sensitivity of current accounts etc.)
explicit (expert) modelling of yield curve and interest rate
risk
30
Interest rate shock revised
• The new framework for assessing the impact of interest rate
shock
 partially set following the research of banks practices
regarding interest risk management
 assumption that only on some part (cca 20 %) of short-term
liabilities (mostly sight deposits) banks adjust client rates
according to the money market
 the change in value of bonds is muted for banks using
hedging via IRS
 revaluation of long-term bonds is calculated with a forecast
of 5Y rate which is linked to 1Y rate, 5Y Bund rate and
assumption on risk premium (spread between 5Y euro rate
and 5Y CZK rate)
31
Regular cross-check of the stress
testing framework
•
•
regular consultations with commercial banks on stress testing
methodology
verification of the models and assumptions (over time, banking
sector changes thus the stress testing framework should react as
well - Basel II, use of derivatives etc.)

how to assess results of verification?

use baselines, but assymetric assessment needed (better to
overestimate risks than underestimate)

in crisis periods, alternatives might be better benchmarks than
baselines

conservative calibration of models and/or additional expert‘s
adjustments are needed
32
Stress testing in the CNB
Last Stress Testing Exercise – Assumptions and Results
33
Basic framework of CNB‘s stress tests
• This part will focus on methodology and some results of stress
tests of the Czech banking sector.
• CNB now performs stress tests with every new quarterly
macroeconomic forecasts (i.e. 4 times a year)


alternative macro scenarios: one scenario reflects actual CNB‘s
macroeconomist forecast, one or two adverse scenarios run in
DSGE model are outlined by the financial stability team
together with modelling division experts (14 variables used),
the horizon is set to 8 quarters - actual (internal) stress tests
performed on mid-2009 portfolios with July 2009 forecasts
focusing on horizon 3Q2009 – 2Q2011.
• The results presented below are taken from July 2009 exercise
(to some extent „work in progress“ as a part of dynamic stress
34
testing methodology development.
34
Two macroeconomic scenarios
• The July bank stress test worked with two scenarios:
 Scenario A: “baseline” reflects the CNB’s July forecast
 Scenario B: “protracted recession” expects a greater and
longer decline in GDP compared to the baseline scenario
• These scenarios were updates to the scenarios published in the
Financial Stability Report in June 2009
Scenario
Baseline
2009
2010
Real GDP growth (%, y-o-y)
Inflation (%, y-o-y)
Interest rate 3M PRIBOR (%)
-3,8
1,2
2,1
26,6
Exchange rate CZK/EUR
0,8
1,1
1,8
25,7
Protracted recession
2009
2010
-5,2
1,2
2,3
27,0
-1,1
1,2
2,0
27,0
35
Two macroeconomic scenarios
Alternative scenarios: inflation rate
(in %)
Alternative scenarios: real GDP growth
(in %)
8
6
4
2
0
-2
-4
-6
-8
-10
06/07
36
8
7
6
5
4
3
2
1
12/07
06/08
12/08
06/09
12/09
06/10
12/10
06/11
0
06/07
12/07
06/08
12/08
06/09
12/09
Baseline
Baseline
Protracted recession
06/10
12/10
06/11
Protracted recession
Alternative scenarios: exchange rate
(CZK/EUR)
Alternative scenarios: 3M Pribor rate
(in %)
31
30
6
29
5
28
4
27
3
26
25
2
24
1
0
06/07
23
06/07
12/07
06/08
Baseline
12/08
06/09
12/09
06/10
12/10
Protracted recession
06/11
12/07
06/08
Baseline
12/08
06/09
12/09
06/10
12/10
Protracted recession
06/11
36
Credit risk in CNB‘s stress tests
37
• Credit risk and credit growth assumptions: outputs of satellite
models utilizing macro scenarios (4 separate loan portfolios
modelled).
• Dependent variable of credit risk models: 12M default rate
(i.e. new bad loans over initial portfolio).
• 12M default rate is also used by commercial banks; the Basel
II „PD“ used for IRB approach in credit risk should be „a
long-run average of default rates“
• NPL ratio - the ratio of non-performing loans to total loans generated using expert judgment/assumptions about NPL
outflow (15% in a quarter):

NPL(2)/L(2) = approx. [NPL(1) + L(1)*df - a*NPL(1)]/L(2)
37
Dynamic features of CNB‘s stress
tests
38
• Credit growth is estimated for each portfolio via simple
macroeconomic model.
• Forecast of default rates and credit dynamics are transformed
to predictions of main balance sheet and flow variables of
banks.
• Four key risks are tested then (credit, interest rate, currency
and interbank contagion).
• Tests are set as dynamic – for every item in assets, liabilities,
income and costs there is an initial state to which the impact
of shocks is added in one quarter and the results serve as the
initial state for following quarter – this is repeated in next 8
quarters for which the prediction is generated.
38
Credit developments in two
scenarios
Alternative scenarios: corporate default rate developments
(in %)
39
Alternative scenarios: household default rate developments
(in %)
19
11
17
10
15
9
13
8
11
7
9
6
7
5
5
03/09
06/09
09/09 12/09
baseline
03/10
06/10
09/10 12/10
03/11
06/11
protracted recession
4
03/09
06/09
09/09
12/09
baseline
Alternative scenarios: corporate credit growth rate
(in %)
10
03/10
06/10
09/10
12/10
03/11
06/11
protracted recession
Alternative scenarios: household credit growth rate
(in %)
20
5
15
0
10
-5
5
-10
0
-15
-5
-20
03/09 06/09 09/09 12/09 03/10 06/10 09/10 12/10 03/11 06/11
baseline
protracted recession
-10
03/09 06/09
09/09 12/09 03/10
baseline
06/10 09/10 12/10
protracted recession
39 06/11
03/11
NPLs in current stress tests
40
• NPLs in major segments (corporates, households) higher relative to FSR
2008/2009...
• ... due to higher predicted default rates
 corporates - 2009/20010 - baseline 11,8/11,1 % - adverse 13,4/11,6 %
 households - 2009/2010 - baseline 5,7/6 % - adverse 7/9 %
NPLs in corporate sector
(in %)
NPLs in household sector
(in %)
16
16
14
14
12
12
10
10
8
8
6
6
4
4
2
2
0
0
06/07
06/07
12/07
06/08
Baseline
12/08
06/09
12/09
Protracted recession
06/10
12/10
06/11
Baseline May 2009
12/07
Baseline
06/08
12/08
06/09
12/09
Protracted recession
06/10
12/10
06/11
Baseline May 2009
How we work with pre-provision
income, profits and capital
•
Assumptions regarding behaviour of net income, profits and
regulatory capital

•

•
pre-provision income is expertly set at x % of average of past 2 years
(x < 100%, thus additional stress applied in the sense of lower
intermediation activity).
Profit/loss is generated using the pre-provision income and the
impact of shocks

•
41
in current accounting period pre-provision income serves as a first line
„buffer“ against the impact of shocks,
only after the „buffer“ is exhausted, the impacts are deducted from the
capital.
Regulatory capital is adjusted every 2nd Q of calendar year to
get back to initial CAR, if there are sufficient profits generated
in previous accounting year ...
... thus, a P/L account and balance sheet of all banks generated
every quarter = possible to cross-check with reality later on.
Net income, P/L and capital
adequacy: an example
•
•
42
For final evaluation of banks‘ resilience capital adequacy
is estimated.
Link between shocks impact and capital adequacy must
reflect


(net) income generated by banks even under stress,
asymmetric treatment of profits in calculation of regulatory
capital,
Initial state
Estimate of P&L over quarter
Final state
Regulatory
capital
RWA
CAR
Loss from
shock impact
Net
income
P/L
Regulatory
capital
RWA
CAR
Example 1
100
1000
10.0%
20
30
+10
100
1020
9.8%
Example 2
100
1000
10.0%
40
30
-10
90
1020
8.8%

topping up of regulatory capital in 2nd Q.
Current ST results in detail
43
Detailed results of stress tests
Scenario
Baseline
2Q2009
2Q2010
Capital adequacy (CAR)
Protracted recession
2Q2010
2Q2011
2Q2009
2Q2010
2Q2010
2Q2011
13,5
13,1
13,5
12,9
-2,8
-2,1
-4,3
-2,6
-0,1
-0,1
-0,2
0,0
0,0
0,0
0,0
0,0
Credit shock
-2,5
-1,9
-4,1
-2,5
… non-financial corporations
-1,9
-1,5
-2,7
-1,5
… households - housing loans
-0,2
-0,1
-0,5
-0,4
… households - consumer loans
-0,3
-0,2
-0,7
-0,5
Interbank contagion
-0,1
-0,1
-0,1
0,0
2,4
1,9
3,7
2,5
13,1
12,9
12,9
12,8
Capital injection (CZK billions)
0,0
0,0
0,0
0,0
Capital injection (% of GDP)
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
Overall impact of shocks (p.p. CAR)
Interest rate shock
Exchange rate shock
Income allocation
Post-test CAR
No. of banks with CAR between 0% and 8%
Share of banks with CAR between 0% and 8% in total assets
No. of banks with negative capital
Share of banks with negative capital in total assets
(capital adequacy in %, and p.p.)
• Strong
resilience
confirmed
despite
recessionary
scenarios.
• CAR higher
than at the
end of 2008
(effect of
high capital
buffer +
relatively
strong
income
generation
capacity)
Current ST: capital adequacy
Capital ratio: model-based (negative) credit growth
(in %)
16
15
14
13
12
11
10
9
8
06/07
12/07
06/08
12/08
06/09
Baseline
12/09
06/10
12/10
06/11
Protracted recession
Capital ratio: 8% credit growth assumption
(in %)
16
15
14
13
12
11
10
9
8
06/07
12/07
06/08
12/08
Baseline
06/09
12/09
06/10
Protracted recession
12/10
06/11
44
• Banks remain stable in both
scenarios.
• Net income (profit prior to
shocks): 90 (70) % of previous
2Y average in baseline (in
protracted recession).
• Potential „deleveraging“ leads
to higher CAR in protracted
recession.
• For comparison a scenario with
credit growth constructed too:
negative impact on CAR
confirmed.
…. the banking sector remains
strong … so far
45
• The Czech banking sector has remained profitable and the
profits have not shown a tendency to decline thus far.
• Capital adequacy went up as banks retained a large part of
generated profit as a buffer against the expected increase in
credit risk.
Net profits in the Czech banking sector
(bil. CZK)
Capital and capital requirements for the banking risks
(CZK billions; %)
2 2
250
0
0
1
14
1
70
200
60
150
50
100
40
50
30
0
13
12
11
10
9
8
XII
III
VI
IX
XII
III
VI
IX
XII
III
VI
2006 2007 2007 2007 2007 2008 2008 2008 2008 2009 2009
20
10
Regulatory capital
0
IV
-0
5
VI
I-0
5
X05
I-0
6
IV
-0
6
VI
I-0
6
X06
I-0
7
IV
-0
7
VI
I-0
7
X07
I-0
8
IV
-0
8
VI
I-0
8
X08
I-0
9
IV
-0
9
VI
I-0
9
Credit risk
Market risks
Operational and other risks
net profit (last 3M annualized)
net profit (last 1M annualized)
Capital adequacy (%, right-hang scale)
Source: CNB
Capital adequacy Tier I (%, right-hang scale)
Source: CNB
Thank You for Your Attention!
Contact:
Jan Frait
Czech National Bank
Na Prikope 28
CZ-11503 Prague
Tel.: +420 224 414 430
E-mail: jan.frait@cnb.cz
Financial Stability Team in the CNB
financial.stability@cnb.cz
46