World Economic and
Financial Surveys
Global Financial
Stability Report
Responding to the
Financial Crisis and Measuring Systemic Risks
(all reports)
(A Report by the Monetary and Capital Markets Department
on Market Developments and Issues)
April 2009 - International
Monetary Fund - Washington DC
Cover - Contents - Preface
Joint Foreword to the World
Economic Outlook and
the Global Financial
Stability Report
Executive Summary
The global financial system remains under severe stress as the crisis broadens to include households,
corporations, and the banking sectors in both advanced and emerging market countries.
Shrinking economic activity has put further pressure on banks’ balance sheets as asset values
continue to degrade, threatening their capital adequacy and further discouraging fresh lending.
Thus, credit growth is slowing, and even turning negative, adding more downward pressure on
economic activity. Substantial private sector adjustment and public support packages are already
being implemented and are contributing to some early signs of stabilization. Even so, further decisive
and effective policy actions and international coordination are needed to sustain this improvement,
to restore public confidence in financial institutions, and to normalize conditions in markets.
The key challenge is to break the downward spiral between the financial system and the global
economy. Promising efforts are already under way for the redesign of the global financial system
that should provide a more stable and resilient platform for sustained economic growth.
Chapter 1. Stabilizing the Global Financial System and
Mitigating Spillover Risks
Summary
A. Global Financial Stability Map
B. Global Deleveraging and Its Consequences
C. The Crisis Has Engulfed Emerging Markets
D. The Deteriorating Outlook for Household and Corporate
Defaults in Mature Markets and
Implications for the Financial System
E. Stability Risks and the Effectiveness of the Policy Response
F. Costs of Official Support, Potential Spillovers, and Policy
Risks
Annex 1.1. Global Financial Stability Map: Construction and
Methodology
Annex 1.2. Predicting Private “Other Investment” Flows and
Credit Growth in
Emerging Markets
Annex 1.3. Spillovers Between Foreign Banks and Emerging Market
Sovereigns
Annex 1.4. Debt Restructuring in Systemic Crises
Annex 1.5. Methodology for Estimating Potential Writedowns
References
Systemic risks remain high and the adverse feedback loop between the financial system
and the real economy has yet to be arrested, despite the wide range of policy actions and
some limited improvement in market functioning. Further effective government action—
particularly geared toward cleansing balance sheets and strengthening institutions—will
be required to stabilize the global financial system and to provide the foundation for a sustainable
economic recovery. The banking system needs additional equity to absorb further writedowns as
credit deteriorates, and risks are broadening to encompass nonbank institutions. The crisis has
spread to emerging markets with the collapse of international financing, posing challenges to
corporates, households, and banks as well as raising sovereign risk. The global policy response,
including the IMF’s enhanced lending framework, should help to mitigate crisis risks. There
remains considerable scope for further public commitments in larger economies, but extensive
provision of financing and the transfer of balance sheet risk from the private to the public sector
have increased tail risks for certain mature market sovereigns.
Against this backdrop, Chapter 1 first outlines the key financial stability risks that have materialized
since the October 2008 Global Financial Stability Report. Then, it examines the deleveraging
process and its effects on the real economy. The following section assesses the vulnerability of
emerging markets to global stress, especially focusing on the refinancing risks facing corporates.
The outlook for global credit markets is then evaluated, along with IMF staff estimates of potential
global financial writedowns. The stability risks facing financial institutions are assessed and the
effectiveness of the policy response evaluated. The chapter concludes with a discussion on sovereign
risks.
Box 1.1 summarizes the key financial stability challenges and policy priorities detailed in the
chapter.
Boxes
1.1 Near-Term Financial Stability Challenges and Policy
Priorities
1.2 Cross-Border Exposures and Financial Interlinkages within
Europe
1.3 Effects of the Global Financial Crisis on Trade Finance: The
Case of Sub-Saharan Africa
1.4 Enhanced IMF Lending Capabilities and Implications for
Emerging Markets
1.5 Modeling Corporate Bond Spreads: A Capital Flows Framework
1.6 Recent Unconventional Measures of Selected Major Central
Banks
1.7 Forecasts for Charge-Offs on U.S. Bank Loans
Tables
1.1 Macro and Financial Indicators in Selected Emerging Market
Countries
1.2 Potential Writedowns and Capital Needs for Emerging Market
Banks by Region
1.3 Estimates of Financial Sector Potential Writedowns (2007–10)
by Geographic Origin of
Assets as of April 2009
1.4 Bank Equity Requirement Analysis
1.5 Policy Measures and Effectiveness
1.6 Tentative Easing in Credit Conditions
1.7 Bank Wholesale Financing and Public Funding Support
1.8 Public Debt and Stabilization Costs
1.9 Mature Market Sovereign Credit Default Swap Spreads and Debt
Outstanding
1.10 Announced Sovereign Guaranteed Bank Debt
1.11 Changes in Risks and Conditions Since the October 2008 Global
Financial Stability Report
1.12 Distress Dependence Matrices: Sovereigns and Banks
1.13 Estimated Bank Portfolio Composition by Type of Asset
1.14 Estimated Bank Portfolio Composition by Origin of Assets
1.15 Estimated Distribution of Writedowns by Bank Domicile and
Cumulative Loss Rates
Figures
1.1 Global Financial Stability Map
1.2 Heat Map: Developments in Systemic Asset Classes
1.3 Ratio of Debt to GDP Among Selected Advanced Economies
1.4 Bank Credit to the Private Sector
1.5 Private Sector Credit Growth
1.6 Bank for International Settlements Reporting Banks:
Cross-Border Liabilities, Exchange-Rate- Adjusted Changes
1.7 Bank for International Settlements Reporting Countries:
Cross-Border Assets as a Proportion of Total Assets
1.8 Emerging Market Net Private Capital Flows
1.9 Net Foreign Equity Investment in Emerging Economies
1.10 Emerging Market Hedge Funds: Estimated Assets and Net Asset
Flows
1.11 Heat Map: Developments in Emerging Market Systemic Asset
Classes
1.12 Emerging Europe: Real Credit Growth to the Private Sector
and Output
1.13 Emerging Market Performance of Credit Default Swap Spreads
and Equity Prices
1.14 Cross-Currency Basis Swap Spreads
1.15 Emerging Market Real Credit Growth
1.16 External Debt Refinancing Needs
1.17 Emerging Market External Corporate Bond Spreads
1.18 Aggregate Emerging Markets Bond Index Global Spread
1.19 Distress Dependence between Emerging Market Sovereigns and Advanced Country Banks
1.20 U.S. Loan Charge-Off Rates: Baseline
1.21 Delinquency Rate of U.S. Residential Mortgage Loans
1.22 Spreads on Commercial Mortgage-Backed Securities
1.23 Spreads on Consumer Credit Asset-Backed Securities
1.24 Global Corporate Default Rates
1.25 Average Recovery Rates on Defaulted U.S. Bonds
1.26 Corporate Credit Default Swap Spreads
1.27 Estimates of Economic Growth and Financial Sector
Writedowns
1.28 U.S. and European Bank and Insurance Company Market
Capitalization, Writedowns, and Capital Infusions
1.29 U.S. and European (including U.K.) Bank Earnings and
Writedowns
1.30 Commercial Bank Loan Charge-Offs
1.31 European Securitization Gross Issuance
1.32 Refinancing Gap of Global Banks
1.33 Pension Funds of Large U.S. and European Companies:
Estimated Funding Levels
1.34 Insurance Sector Credit Default Swap Spreads
1.35 Large Economy Credit Default Swap Spreads
1.36 Benchmark Five-Year Government Bonds
1.37 Swap Spreads of Government-Guaranteed Bonds
1.38 Global Financial Stability Map: Monetary and Financial
Conditions
1.39 Global Financial Stability Map: Risk Appetite
1.40 Global Financial Stability Map: Macroeconomic Risks
1.41 Global Financial Stability Map: Emerging Market Risks
1.42 Global Financial Stability Map: Credit Risks
1.43 Global Financial Stability Map: Market and Liquidity Risks
1.44 Impulse Responses
1.45 Net Private Other Investment Flows to Emerging Markets
1.46 Emerging Market Real Credit Growth
1.47 Emerging Market GDP Growth
1.48 Default Probabilities Implied by Credit Default Swap
Pricing
1.49 Distress Dependence
Chapter 2. Assessing the Systemic Implications of Financial
Linkages
Summary
Four Methods of Assessing Systemic Linkages
How Regulators Assess Systemic Linkages
Policy Reflections
Annex 2.1. Default Intensity Model Estimation
References
The rise in the complexity and globalization of financial services has contributed to stronger
interconnections or linkages. While more extensive linkages contribute to economic
growth by smoothing credit allocation and allowing greater risk diversification, they also
increase the potential for disruptions to spread swiftly across markets and borders. In
addition, financial complexity has enabled risk transfers that were not fully recognized by financial
regulators or by institutions themselves, complicating the assessment of counterparty risk, risk
management, and policy responses. Thus the importance of assessing the systemic implications of
financial linkages.
The current crisis has highlighted how systemic linkages can arise not just from financial institutions’
solvency concerns but also from liquidity squeezes and other stress events. This chapter
illustrates the type of methodologies that can provide some prospective metrics to facilitate discussions
on systemic linkages and, specifically, the “too-connected-to-fail” problem, thereby contributing
to enhanced systemically focused surveillance and regulation. By contrast, Chapter 3 presents
other methodologies that examine systemic risk by looking at the conditions under which financial
institutions experience simultaneous stressful events.
This chapter presents four complementary approaches to assess direct and indirect financial sector
systemic linkages:
• The network approach, which tracks the reverberation of a credit event or liquidity squeeze
throughout the banking system via direct linkages in the interbank market;
• The co-risk model, which exploits market data to assess systemic linkages among financial
institutions under extreme events;
• The distress dependence matrix, which examines pairs of institutions’ probabilities of distress,
taking into account a set of other institutions; and
• The default intensity model, which measures the probability of failures of a large fraction of
financial institutions due to both direct and indirect systemic linkages.
The chapter argues that, although each approach by itself has its limitations, together they represent
a set of valuable surveillance tools and can form the basis for policies to address the tooconnected-
to-fail problem. More specifically, this chapter assists policymakers in two areas under
current discussion:
• Perimeter of regulation. To maintain an effective perimeter of prudential regulation without
stifling innovation, the tools provided in the chapter could help address questions such
as whether to limit an institution’s exposures, the desirability of capital surcharges based on
systemic linkages, and the merits of additional liquidity regulations.
• Information gaps. The chapter also discusses the importance of filling existing information
gaps on cross-market, cross-currency, and cross-country linkages to refine analyses of systemic
linkages. Closing information gaps would require improved data collection procedures and
impose additional demands on financial institutions, but would be a far better alternative to
waiting until a crisis ensues to obtain information as events unfold.
Boxes
2.1 Network Simulations of Credit and Liquidity Shocks
2.2 Quantile Analysis
2.3 Default Intensity Model Specification
2.4 Basics of Over-the-Counter Counterparty Credit Risk
Mitigation
2.5 A Central Counterparty as a Mitigant to Counterparty Risk in
the Credit Default Swap Markets
Tables
2.1 Taxonomy of Financial Linkages Models
2.2 Simulation 1 Results (Credit Channel)
2.3 Post-Simulation 1 Capital Losses
2.4 Simulation 2 Results (Credit and Funding Channel)
2.5 Post-Simulation 2 Capital Losses
2.6 Conditional Co-Risk Estimates, March 2008
2.7 Conditional Co-Risk Estimates, September 2008
2.8 Distress Dependence Matrix
2.9 Summary of Various Methodologies: Limitations and Policy
Implications
Figures
2.1 Network Analysis: A Diagrammatic Representation of Systemic
Interbank Exposures
2.2 Network Analysis: Number of Induced Failures
2.3 Network Analysis: Country-by-Country Vulnerability Level
2.4 Network Analysis: Contagion Path Triggered by the U.K.
Failure
2.5 AIG and Lehman Brothers Default Risk Codependence
2.6 A Diagrammatic Depiction of Co-Risk Feedbacks
2.7 U.S. and European Banks: Tail-Risk Dependence Devised from
Equity Option Implied Volatility, 2006–08
2.8 Legend of Trivariate Dependence Simplex
2.9 Annual Number of Corporate and Banking Defaults
2.10 Actual and Fitted Economy Default Rates
2.11 Default Rate Probability and Number of Defaults
2.12 Quarterly One-Year-Ahead Forecast Value-at-Risk at 95
Percent Level
2.13 Capital Adequacy Ratios After Hypothetical Credit Shocks
2.14 Basic Structure of the Systemic Risk Monitor Model
2.15 RAMSI Framework
Chapter 3. Detecting Systemic Risk
Summary
What Constitutes “Systemic” Risk?
“Fundamental” Characteristics of Intervened and
Nonintervened Financial Institutions
Market Perceptions of Risk of Financial Institutions
Identifying Systemic Risks Through Regime Shifts
Role of Global Market Conditions During Episodes of Stress
Policy Implications
Conclusions
Annex 3.1. Financial Soundness Indicators
Annex 3.2. Groups of Selected Financial Institutions
Annex 3.3. List of Intervened Financial Institutions
References
The current crisis demonstrates the need for tools to detect systemic risks. Given that
there are many facets and causes of such risks, this chapter presents a range of measures
that can be used to discern when events become systemic. The chapter first
reviews the standard financial soundness indicators’ ability to highlight those financial
institutions (FIs) that proved to be vulnerable in the current crisis. For the sample of global FIs
examined, leverage ratios and return-on-assets proved the most reliable indicators, while capital
asset ratios and nonperforming loan data lacked predictive power.
The chapter then proceeds to examine several techniques to analyze forward-looking market
data for groups of FIs in order to detect whether and when systemic risks became apparent.
Market-based measures that are able to capture tail risks seem to have given forward indications
of impending stress for the overall financial system. Chapter 2 provides a slightly different
approach to systemic risk by examining interlinkages, both direct and indirect, between
selected FIs.
Finally, proxies for “market conditions” that influence (and reflect) the risks facing FIs are
examined to capture other key factors, such as investors’ risk appetite. The signaling capacity
of these indicators is examined by detecting whether and when they moved from low, to
medium, and to high volatility states, with the high state associated with systemic crisis. Several
measures signaled periods during which the financial system suffered a systemic crisis.
The various techniques clearly identify major stress events, such as those associated with the
merger of Bear Stearns and the failure of Lehman Brothers, as systemic. Some indicators, as
early as February 2007, also signaled rising systemic pressures. However, advance notice of
systemic stress was relatively brief and the extent to which some markets remained in high volatility
states was somewhat short-lived. Hence, the use of a number of market-based indicators
provides a more holistic picture.
Being able to identify systemic events at an early stage enhances policymakers’ ability to take
necessary exceptional steps to contain the crisis. In this regard, the chapter suggests enhancing
stress tests and capital requirements to take account of the buildup of systemic risks. Some of
the analysis presented could be a starting point to calibrate the risk contribution of FIs to overall
systemic risk, thereby prompting additional regulatory capital and enhanced supervision to
discourage practices that increase systemic risk.
In sum, although systemic events are difficult to predict, and may only become apparent concurrently
in some cases, policymakers should monitor a wide range of market indicators tuned
to systemic risk, and have comprehensive crisis plans in place to be implemented quickly if
needed.
Boxes
3.1 Modeling Risk-Adjusted Balance Sheets: The Contingent Claims
Approach
3.2 Option-iPoD
Measures of Risk Across Financial Institutions
3.3 Higher Moments and Multivariate Dependence of Implied
Volatilities from Equity Options as Measures of Systemic Risk
3.4 The Consistent Information Multivariate Density Optimizing
Approach
3.5 Spillovers to Emerging Markets: A Multivariate GARCH
Analysis
3.6 The Transformation of Bank Risk into Sovereign Risk—The
Tale of Credit Default Swaps
Tables
3.1 Selected Indicators on Fundamental Characteristics in
Financial Institutions
3.2 Taxonomy of Credit Risk Models
3.3 Correlations Among 45 Financial Institutions During
Different Stress Periods
3.4 Cluster Analysis
3.5 Summary of Various Methodologies: Limitations and Policy
Implications
Figures
3.1 Capital-to-Assets Ratio
3.2 Ratio of Short-Term Debt to Total Debt
3.3 Return on Assets
3.4 Dendrogram
3.5 U.S. and European Banks: Joint Tail Risk of Implied
Volatilities
3.6 Higher Moments and Multivariate Dependence of Implied Equity
Volatility
3.7 Joint Probability of Distress and Banking Stability Index:
Core 2 Group
3.8 Joint Probability of Distress and Banking Stability Index:
By Geographic Region
3.9 Daily Percentage Change: Joint and Average Probability of
Distress, Core 2 Group
3.10 Probability of Cascade Effects
3.11 Markov-Regime Switching ARCH Model: Joint Probability of
Distress and Banking Stability Index
3.12 Euro-Dollar Forex Swap
3.13 Markov-Switching ARCH Model of VIX
3.14 Markov-Switching ARCH Model of TED Spread
3.15 Markov-Switching ARCH Model of VIX, TED Spread, and Core 2
Banking Stability Index
Glossary
Annex: Summing Up by the Acting Chair
Statistical Appendix
This statistical appendix presents data
on financial developments in key
financial centers and emerging markets.
It is designed to complement the
analysis in the text by providing additional data
that describe key aspects of financial market
developments.
These data are derived from a
number of sources external to the IMF, including
banks, commercial data providers, and
official sources, and are presented for information
purposes only; the IMF does not, however,
guarantee the accuracy of the data from external
sources.
Presenting financial market data in one
location
and in a fixed set of tables and
charts, in this and future issues of the GFSR,
is intended to give the reader an overview of
developments
in global financial markets.
Unless otherwise noted, the statistical appendix
reflects information available up to February
25, 2009.
Mirroring the structure of the chapters of the
report, the appendix presents data separately
for key financial centers and emerging market
countries. Specifically, it is organized into three
sections:
• Figures 1–14 and Tables 1–9 contain information
on market developments in key financial
centers. This includes data on global capital
flows, and on markets for foreign exchange,
bonds, equities, and derivatives as well as sectoral
balance sheet data for the United States,
Japan, and Europe.
• Figures 15 and 16, and Tables 10–21 present
information on financial developments in
emerging markets, including data on equity,
foreign exchange, and bond markets, as well
as data on emerging market financing flows.
• Tables 22–27 report key financial soundness
indicators for selected countries, including
bank profitability, asset quality, and capital
adequacy.
The following symbols have been used throughout this volume:
. . . to indicate that data are not available;
— to indicate that the figure is zero or less than half the
final digit shown, or that the item does not exist;
– between years or months (for example, 1997–99 or January–June)
to indicate the years or months covered, including the beginning and ending
years or months;
/ between years (for example, 1998/99) to indicate a fiscal or
financial year.
“Billion” means a thousand million; “trillion” means a
thousand billion.
“Basis points” refer to hundredths of 1 percentage point
(for example, 25 basis points are equivalent to 1/4 of 1 percentage point).
“n.a.” means not applicable.
Minor discrepancies between constituent figures and totals are
due to rounding.
As used in this volume the term “country” does not in all
cases refer to a territorial entity that is a state as understood by international law and
practice. As used here, the term also covers some territorial entities that are not states
but for which statistical data are maintained on a separate and independent basis.
|