Is early warning against systemic risk feasible? · 5 5 The ECB definitions of financial stability...
Transcript of Is early warning against systemic risk feasible? · 5 5 The ECB definitions of financial stability...
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Zürich, 13 September 2012
Is early warning against systemic risk feasible?
The ECB’s newly developed analytical
support to the European Systemic Risk Board
Latsis Symposium 2012
“Economics on the Move”
Carsten Detken Head, Financial Stability Surveillance Division
Directorate General Financial Stability
European Central Bank
Any opinions expressed are only the presenter’s own and should not be regarded as opinions of the European Central Bank or the
Eurosystem.
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Introduction
• Since the Lehman collapse in September 2008
- World went through the largest recession since the 1930s
- Fiscal deficits increased in all countries
- Sovereign debt crisis in Europe
- Financial markets talk about redomination risk in the euro area
• These events were a direct consequence of the financial crisis and they provide a clear motivation for a continuous efforts to improve frameworks for financial stability analysis and policy
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1. Institutional set up, definitions and the process regarding
systemic risk identification
2. Some indicators of systemic risk and early warning
models used in the ECB’s financial stability analysis
3. Is “early warning” against systemic risks feasible? The
example of 2007
4. Do we need an interdisciplinary approach?
a) political economy: the fundamental issues regarding
the long-term viability of EMU
b) science of uncertainty: the process of risk
identification
5. Conclusions
Outline
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The new EU supervisory architecture
European Banking Authority
European Insurance and Occupational
Pensions Authority
Proposed: ECB (with national supervisors) ECB
National
Supervisors
(non-voting) National
central banks
European
Supervisory
Authorities
European
Commission
Macro-prudential oversight Micro-prudential supervision
European Systemic Risk Board European System of Financial
Supervision
President of the
Economic and
Financial
Committee
(non-voting)
European Securities
and Markets Authority
Issue risk warnings and, if necessary,
Macro-prudential recommendations
Ensure EU-wide technical supervisory standards
Coordination of supervisors (also in crises)
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The ECB definitions of financial stability and systemic risk
“Financial stability can be defined as a condition in which the financial system –
comprising of financial intermediaries, markets and market infrastructures – is
capable of withstanding shocks and the unravelling of financial imbalances, thereby
mitigating the likelihood of disruptions in the financial intermediation process which
are severe enough to significantly impair the allocation of savings to profitable
investment opportunities.” (ECB, Financial Stability Review, preface)
Systemic risk:
The risk that financial instability becomes so widespread that it impairs the functioning of a financial system to the point where economic growth and welfare suffer materially.
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Time series dimension of systemic risk …
• Short-run buildup may occur when measured risk is low • buildup may be linked to financial sector growth, underwriting standards, degree
of monitoring, risk management of market participants
=> Challenge to build forward looking measures (Early Warning
Models).
…versus cross sectional dimension of systemic risk:
• Interlinkages may enable risk sharing but also cause risk propagation • Fire sale externality: deleveraging spills across institutions due to market
illiquidity.
• Hoarding externality: institutions hoard lending capacity.
• Runs: e.g. on the shadow banking system
• Network externality: counterparty credit risk
=> Systemic Risk indicators
Economics of systemic risk
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Focus on: Macroprudential oversight process
Potential sources of
systemic risk
Risk
identification
Risk
assessment Communication
Policy
response Detection of
vulnerabilities, potential
triggers, likelihood of
risks materialising
Selected tools:
•Set of financial stability
indicators and early
warning models
• Market intelligence
•Expert judgement
Assessment of
propagation channels,
potential severity of
risks identified and
system’s ability to
absorb shocks
Selected tools:
• Assessing propagation
channels (including
contagion and spill-
over models)
• Macro stress-testing
Vulnera-
bility
Material
risk
Yes
No
Yes
No
Possible macro-
prudential policy
action by
responsible
authorities (not
ECB)
Monitoring follow-up of recommendations and assessing policy impact
Feedback to risk monitoring and analysis
Financial
Stability Reports
ESRB Risk
warnings
Price stability at
risk in the long
run? Possible
monetary policy
response (l-a-w)
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Six Origins of vulnerabilities: Aim to find robust early warning models
and systemic risk indicators and implement Early Warning System
1. Macro (risk) Business cycle, global imbalances
2. Credit (risk) Households, non-financial corporations, public finances
3. Market (risk) Risk premia, asset price disequilibria
4. Liquidity and
funding
Liquidity conditions, funding strategy and activity
5. Interlinkages and
Imbalances
Operation linkages, counterparty interconnectedness,
business models
6. Profitability and
Solvency
Financial performance, profitability outlook and risks
Regulatory capital, financial gearing
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1. Institutional set up, definitions and the process regarding
systemic risk identification
2. Some indicators of systemic risk and early warning
models used in the ECB’s financial stability analysis
3. Is “early warning” against systemic risks feasible? The
example of 2007
4. Do we need an interdisciplinary approach?
a) political economy: the fundamental issues regarding
the long-term viability of EMU
b) science of uncertainty: the process of risk
identification
5. Conclusions
Outline
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Indicators of financial stress (Probability of a simultaneous default of two or more large EA banks)
Sources: Thomson Reuters and ECB calculations
(Oct.2008 – 10 Sep 2012; probability in percentages)
LTROs
Draghi's
speech
Greek fiscal problems gain
media attention
EU summit
21 Jul
Second PSI for Greece
agreed
OMT
0%
5%
10%
15%
20%
25%
30%
Oct-08 Apr-09 Oct-09 Apr-10 Oct-10 Apr-11 Oct-11 Apr-12
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Indicators of financial stress (Composite indicator of systemic stress (CISS) for the euro area) (Jan. 1999 – Aug. 2012)
Sources: ECB and ECB calculations.
-0.5
-0.3
0.0
0.3
0.5
0.8
1.0
1999 2001 2003 2005 2007 2009 2011
equity market contribution
forex market contribution
bond market contribution
financial sector contribution
money market contribution
correlation contribution
CISS
8 Jun 8 Jul 8 Aug
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Equity market (non-financials): realised volatility of equity returns; CMAX;
stock/bond correlation
Money market: realised volatility of 3 month Euribor; spread Euribor/T-bill (3 month maturity); recourse to the marginal lending facility at the ECB.
Bond Market: realised volatility of 10y bund; spread corporate AAA versus government bonds; 10y interest rate swap spread.
Financial intermediaries: realised volatility of excess returns of the banking index; spread A rated financials/non-financials; CMAX interacted with book-
price ratio for the financial sector equity index.
Foreign exchange: realised volatility of US/EUR, JPY/EUR, GBP/EUR.
Market segments and indicators of CISS
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Degree of interconnectedness of banks (Centrality of Eurosystem banks based on their cross-holding of securities)
(Oct. 2008 – Aug. 2012; average of normalised number of weighted shortest paths)
Source: ECB.
Notes: A decrease denotes a general fall of the centrality of banks in the system, and
therefore a more resilient banking system as a whole.
second PSI
for Greece
agreed
LTROs
Greece’s economic
programme Draghi's Speech
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
Oct-08 Apr-09 Oct-09 Apr-10 Oct-10 Apr-11 Oct-11 Apr-12
EU summit
July 21
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Evolution of tail dependence network for European
banks
Source: Betz, F. and Peltonen, T. , 2012, Tail dependence and Systemic Risk in European Banking, ECB
mimeo. Note: estimation method quantile-Lasso as in Hautsch et al. (2012).
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Evolution of tail dependence network for European
banks, when conditioning with sovereign yields
Source: Betz, F. and Peltonen, T. , 2012, Tail dependence and Systemic Risk in European Banking, ECB
mimeo. Note: estimation method quantile-Lasso as in Hautsch et al. (2012).
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Tail dependence network: Focus on Spain 2007-2010
Source: Betz, F. and Peltonen, T. , 2012, Tail dependence and Systemic Risk in European Banking, ECB
mimeo. Note: estimation method quantile-Lasso as in Hautsch et al. (2012).
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Tail dependence network: Focus on Spain 2010-2012
Source: Betz, F. and Peltonen, T. , 2012, Tail dependence and Systemic Risk in European Banking, ECB
mimeo. Note: estimation method quantile-Lasso as in Hautsch et al. (2012).
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Identification of bank distress
• Bankruptcies, liquidations and defaults
• Government aid (capital injection, asset protection or asset guarantees)
• Mergers in distress
Potential vulnerabilities
• Bank-specific balance-sheet indicators (CAMELS)
• Country-specific banking sector indicators (MFI balance-sheet data)
• Country-specific macro-financial indicators (EU MIP)
Early Warning Signal
• Out of sample prediction of bank being in distress within the next 1-12 quarters
• Signal evaluation taking into account policymarkers‘ preference between Type 1 and 2 errors
Tail Dependence
Network
• Estimate tail dependence network of banks
• Use this information to identify banks that are vulnerable for contagion given the signal of a distressed bank
Identification of vulnerable
banks
• List of banks that are vulnerable either through their own balance sheet issues, banking sector issues or macro-financial vulnerabilities
• List of banks that are vulnerable for contagion given the above identified banks
Purpose:
1. Predict individual bank distress in the EU
2. Identify potential for contagion
3. Understand determinants of banking sector fragility in Europe
Key Features:
Estimation sample: 439 EU banks with at least EUR 1 bln in assets
Model calibrated for out-of-sample prediction of bank distress 2 years ahead
European Bank Early Warning System (EB-EWS) (Betz, Oprica, Peltonen, Sarlin (2012): “Predicting Bank Distress and Identifying Interdependencies among
European Banks”), ECB, mimeo.
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EB-EWS – case studies: predicted crisis probabilities
for Dexia and Bank of Ireland from 2007Q1-2011Q4
Absolute distress probabilities
Percentile distress probabilities
Early warning signals
Dexia SA
2007 Q1 2007 Q3 2008 Q1 2008 Q3 2009 Q1 2009 Q3 2010 Q1 2010 Q3 2011 Q1 2011 Q3
0.0
0.2
0.4
0.6
0.8
1.0
Pre-distress event Distress event
Absolute distress probabilities
Percentile distress probabilities
Early warning signals
Bank of Ireland
2007 Q1 2007 Q3 2008 Q1 2008 Q3 2009 Q1 2009 Q3 2010 Q1 2010 Q3 2011 Q1 2011 Q3
0.0
0.2
0.4
0.6
0.8
1.0
Pre-distress event Distress event
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EB-EWS: identifying banks potential for contagion
given and early warning signal
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ING
BANK
NV
CREDIT
AGRICOLE
SA
BARCLAYS
PLC
COMMERZBANK
AG
DEUTSCHE
BANK
AG-REGISTERED
DEXIA
SA
SOCIETE
GENERALE
HSBC
HOLDINGS
PLC
LLOYDS
BANKING
GROUP
PLC
NORDEA
BANK
AB
ROYAL
BANK
OF
SCOTLAND
GROUP
BANCO
SANTANDER
SA
UNICREDIT
SPA
0.0
0.1
0.2
0.3
0.4
0.5
Bank-specific
BSI
Macro-financials
EB-EWS: current distress probabilities for European
GSIFIs (and contributing factors)
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1. Institutional set up, definitions and the process regarding
systemic risk identification
2. Some indicators of systemic risk and early warning
models used in the ECB’s financial stability analysis
3. Is “early warning” against systemic risks feasible? The
example of 2007
4. Do we need an interdisciplinary approach?
a) political economy: the fundamental issues regarding
the long-term viability of EMU
b) science of uncertainty: the process of risk
identification
5. Conclusions
Outline
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Challenges – risk surveillance: Interpretation of
indicators varies with circumstances
• Many indicators of vulnerabilities have two interpretations:
– High bank solvency: improved shock absorption capacity or foregone lending opportunities?
– Narrow spreads: risks are low or mispriced?
– High loan to deposit ratios: efficient banking sector or funding vulnerability?
– Cross border market integration: risk sharing or contagion channel?
– High return on equity: profitable business model or excessive risk taking and leverage?
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Is Early Warning Feasible?
• Majority of academics very critical: out-of-sample failure (!) (in sample overfitting, variable selection bias), reduced-form exercise (fundamental trend vs. growing imbalances?)
• Majority of policy makers (at least until crisis) dominated by fear of type II errors (false alarms)
• Goodhart’s Law: “Any observed statistical regularity will tend to
collapse once pressure is placed upon it for control purposes.”
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Is Early Warning Feasible? Some careful optimism…
• Preference shift from type I to type II errors might be significant due to depth of crisis (more balanced preferences increase usefulness, see Alessi/Detken, 2009)
• Easier to predict imbalances than crises (IMF/FSB EWE, ECB surveillance process)
• Application of (under explored) suitable methodologies, e.g. Classification and Regression Trees (simple but robust, conditional rules of thumb, Manasse/Roubini, 2008; also Ghosh and Ghosh, 2003)
• Data availability (housing prices; large data sets; FoF, cross-country exposures, individual bank balance sheet data)
• Important issues like out-of-sample validation, overfitting risk can be dealt with
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Systemic risk surveillance - can we predict the
financial cycle?
Some indicators did (would have) predict(ed) the last financial cycle !
In terms of performance there are three types of indicators:
1. Early Warning Models with structural indicators e.g. global credit gap: would have predicted financial crisis like many other past crises (caveat: also significant number of false alarms)
2. Structural indicators not (yet) subject to early warning evaluation (mainly due to lack of time series) e.g. leverage, house price valuation models: would have predicted crisis with hindsight – difficult to decide on threshold value – how much is too much? (typical question: financial development and catching up versus growing imbalances?)
3. Market based indicators e.g. based on price volatilities: not useful as early warning. These are thermometers not barometers.
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Early Warning Indicators: A “global” credit gap
- Some early warning indicators currently used by the ECB identified growing imbalances before the crisis
- Global credit gap rising from 2002 onwards and above threshold Q3 2005 - Q2 2009
- Real time performance since 1970: 82% correct warnings 32% false alarms 95% of costly asset price booms predicted in at least one of 6 preceding quarters
Global credit gap and optimal early warning threshold (Q1 1980 – Q1 2012; percentages)
Source: Alessi, L. and Detken, D. “Quasi real time early warning
indicators for costly asset price boom/bust cycles: A role for global
liquidity”, European Journal of Political Economy, 27(3), 520-533,
September 2011.
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Rising leverage and unstable funding
Banks leveraging up and more reliant on wholesale funding before the financial crisis
Loan to deposit ratios for euro area and UK banks (Jan. 1999 – Dec. 2011; percentages)
120
140
160
180
200
220
240
1999 2001 2003 2005 2007
euro area UK
Jun-07 Jun-09 Jun-11Source: ECB (MFI balance sheet items). Source: ECB (MFI balance sheet items).
Leverage ratio for euro area and UK banks (Jan. 2003 – Dec. 2011; total assets/capital and reserves)
11
12
13
14
15
16
17
18
19
2003 2004 2005 2006 2007
euro area UK
Jun-07 Jun-09 Jun-11
29
10
14
18
22
26
50
55
60
65
70
1999 2001 2003 2005 2007
loans to MFIs (left-hand scale)
holdings of MFI debt securities
(right-hand scale)
Jun-07Jun-09Jun-11
Increasing interconnectedness of banks
- Higher debt levels within the financial sector were accompanied by increased interbank lending and cross-holdings of debt securities among banks
- The banking sector had become more interconnected
Euro area monetary financial institutions’ (MFIs) lending to other MFIs and holdings of MFI debt securities (Q1 1999 – Q3 2011; percentage of GDP)
Source: ECB (MFI balance sheet items).
30
80
90
100
110
120
130
140
150
160
170
2003 2004 2005 2006 2007
Spain
Ireland
UK
US
Netherlands
Germany
Jun-07 Jun-09 Jun-11
Asset price “disequilibria”
- Euro area residential property prices increased sharply in many countries before the crisis
- Developments were very disperse across countries
Residential property prices (Q1 2004 – Q4 2011; index: Q1 2004 = 100)
Sources: ECB and Bloomberg.
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Examples of asset price “disequilibria”
- Commercial property markets in several euro area countries showed clear signs of overvaluation in 2007, when comparing with fundamentals
Value misalignment indicators for prime commercial property in selected euro area countries (Q1 2007; percentage deviation from average values from Q1 1997 to Q1 2007)
Source: Jones Lange LaSalle, ECB and ECB calculations.
Note: For detail see Box 6 in the December 2011 ECB Financial
Stability Review.
-10
0
10
20
30
40
50
60
70
80
IE ES FR NL IT FI euro
area
BE PT AT DE GR
capital value-to-GDP ratio
capital value-to-private consumption ratio
capital value-to-employment ratio
capital value-to-rent ratio
yield
average
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0%
5%
10%
15%
20%
25%
30%
Jan-07 Apr-07 Jul-07 Jul-08 Jul-09 Jul-10 Jul-11
Market price based indicator (1)
Probability of a simultaneous default of two or more large euro area banks within two years (Jan. 2007 – Mar. 2012; probability; percentages)
Source: Bloomberg and ECB calculations.
Notes: For further details of the indicator, see Box 16 in ECB,
Financial Stability Review, December 2007.
- Financial market stress and risk aversion indicators were at historically low levels before the outbreak of the financial crisis
- Probability of a simultaneous default of two or more large euro area banks very low
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0.0
0.2
0.4
0.6
0.8
1999 2001 2003 2005 2007 Jul-07 Jul-09 Jul-11
Market price based indicator (2)
- Composite financial market stress indicator had been more or less flat from 1999 until August 2007
Composite indicator of stress (CISS) for the euro area (Jan. 1999 – Mar. 2012)
Source: D. Hollo, M. Kremer and M. Lo Duca, “CISS - a composite
indicator of systemic stress in the financial system”, ECB Working
Paper, No 1426, March 2012.
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1. Institutional set up, definitions and the process regarding
systemic risk identification
2. Some indicators of systemic risk and early warning
models used in the ECB’s financial stability analysis
3. Is “early warning” against systemic risks feasible? The
example of 2007
4. Do we need an interdisciplinary approach?
a) political economy: the fundamental issues regarding
the long-term viability of EMU
b) science of uncertainty: the process of risk
identification
5. Conclusions
Outline
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1. Deficit Bias (especially forceful in a monetary union); e.g. Detken,
Gaspar, Winkler (2004), ECB WP No. 420.
SGP => Six Pack + Two Pack + Fiscal Compact => Fiscal Union
2. Productivity gaps: Is EMU an optimal currency area? “Theory of
endogenous optimal currency areas”, adjustment not strong
enough in first decade; e.g. Frankel and Rose (1998).
Six Pack (MIP/EIP) + Compact for Growth and Jobs + European
Semester + national structural reforms
3. (Partial) failure of (micro and macro-) supervisory process =>
excessive risk taking in financial sector; e.g. Padoa Schioppa (1999).
Single Supervisory Mechanism => Banking Union + ESRB + reg. reforms
e.g. Basel III
The three most fundamental issues regarding the
long-term viability of EMU
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Many critical issues are being addressed …
… but challenges remain, including:
1. Giving up national sovereignty versus mutual insurance of liabilities:
does an equilibrium exist ?
2. Feasible pace of change fast enough to regain investor confidence ?
=> Political sciences / political economy key
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1. Institutional set up, definitions and the process regarding
systemic risk identification
2. Some indicators of systemic risk and early warning
models used in the ECB’s financial stability analysis
3. Is “early warning” against systemic risks feasible? The
example of 2007
4. Do we need an interdisciplinary approach?
a) political economy: the fundamental issues regarding
the long-term viability of EMU
b) science of uncertainty: the process of risk
identification
5. Conclusions
Outline
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Ludic Fallacy (Nassim Taleb, The Black Swan):
Studying chance in narrow model of games and dice and
ignoring uncertainty about rules of the game in real life
Halo effect / judgement heuristics (Daniel Kahneman,
Thinking Fast and Slow)
- Excessive weight of first impression
- System 1 dominating System 2
(System 1 infers and invents cause and intentions, neglects
ambiguity, focuses on existing evidence and ignores absent
evidence: intuitive story wins)
Science of Uncertainty / Psychology
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This is nearly a rhetoric question, as deficiencies of
mainstream economics have become so evident. So the
answer is YES
From a practitioneers perspective:
We need (even) more attention to
a) political economy / public choice issues. The main systemic
risks materialising in the crisis could possibly have been contained
with closer attention to polit-economic arguments in the design of
the system (EMU). These issues are currently dealt with and corrected
in a painful process.
b) the science of uncertainty / psychology in order to avoid
fallacies in the systemic risk identification process (e.g. ludic fallacy,
halo effect, judgement heuristics of system 1).
Do we need an interdisciplinary approach?
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1. The current macro-prudential surveillance process requires the ECB to supply the ESRB with regular risk analysis. An Early Warning System is being established – work in progress.
2. Work on micro-prudential supervisory processes also has a bright future at the ECB - since yesterday.
3. A careful optimism that early warning against systemic risk is feasible in principle seems defendable, once best practices are adhered to, the improving data landscape and methodological progress (e.g. avoiding variable selection bias) and due to relatively simple key patterns of financial crises.
4. A “real life risk surveillance process” does benefit from interdisciplinary approaches. Behavioural patterns of “supervisors” and public choice logic in institutional design are key areas to focus on to mitigate and/or identify systemic risk.
Conclusions
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Thank you for your attention!
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Zürich, 13 September 2012
Is early warning against systemic risk feasible?
The ECB’s newly developed analytical
support to the European Systemic Risk Board
Latsis Symposium 2012
“Economics on the Move”
Carsten Detken Head, Financial Stability Surveillance Division
Directorate General Financial Stability
European Central Bank
Any opinions expressed are only the presenter’s own and should not be regarded as opinions of the European Central Bank or the
Eurosystem.
43
Systemic Risk: Are there lessons to be
learned?
1.(Partial) failure of (micro- and macro-) supervisory
processes allowed a build up of systemic risk in the
financial sector. The new European supervisory
architecture has potential to correct the relevant
deficiencies.
2. Current progress with early warning systems
suggests that “early warning” is feasible, by focusing
on “best practices”, and on structural patterns rather
than on market based indicators.