Is early warning against systemic risk feasible? The ECBs newly - - PowerPoint PPT Presentation

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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
• f 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-

• ver 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

• wn 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
• f 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

• f 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
• nwards 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-11

Source: 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

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

32 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

• r 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

• utbreak of the financial crisis
• Probability of a simultaneous default
• f two or more large euro area

banks very low

33 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

• n 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.

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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

• n “best practices”, and on structural patterns rather

than on market based indicators.