## _wp08206 - References

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---

### I. Introduction
- Purpose of stress testing within IMF work:
  - Identify vulnerabilities across institutions that could undermine financial system stability.
  - Typically performed as part of the Financial Sector Assessment Program (FSAP)—a joint effort by the IMF and the World Bank.
- Coverage and adoption:
  - FSAPs have been or are being carried out for over 120 countries—two-thirds of Fund membership.
  - FSAP reassessments (updates) are also taking place, with more than 40 FSAP Updates completed or underway.
- Expansion of stress testing activity:
  - Article IV teams have started experimenting with stress testing as part of regular consultations.
  - Technical assistance on stress testing has been expanding; authorities often request technical assistance following FSAPs.
  - The IMF cooperates with central banks and supervisory agencies on stress testing projects (examples cited with the European Central Bank and the Deutsche Bundesbank).
- Methodological and cooperative initiatives:
  - Methodological work aims to better account for macro-financial linkages and to use multiple analytical perspectives as cross-checks.
  - The IMF launched the Expert Forum on Advanced Stress Testing Techniques in 2006; it meets approximately every year and a half with participation of supervisory agencies and central banks.
  - Expert Forum meetings mentioned: first in May 2006 at IMF headquarters; second in November 2007 hosted by the Nederlandsche Bank; next scheduled for May 2009 to be hosted by the Deutsche Bundesbank in Berlin.

### II. Background: Overview of the FSAP
- Broad objective:
  - Help strengthen and deepen financial systems and enhance resilience to potential financial crises.
- Scope and focus:
  - Assess stability of financial systems as a whole, rather than individual institutions.
  - Emphasize prevention and mitigation rather than crisis resolution.
  - Take a relatively broad, holistic view of system-level risks, including structural, institutional, and market features and the financial policy framework.
- Tools and complementarities:
  - Use a range of quantitative and qualitative tools, including formal assessments of international standards and codes.
  - Quantitative tools used in FSAPs alongside stress testing:
    - Financial soundness indicators (FSIs).
    - Market-based data (price and volatility measures).
    - Analyses of aggregate balance sheets (macro, sectoral).
    - Early warning systems.

### III. Stress Testing in FSAPs — Principles and Approaches
- Underlying principle:
  - Stress testing is a key tool in FSAPs but is complemented by qualitative analysis and other quantitative analysis. Quotation: “....no single model is ever likely to capture fully the diverse channels through which shocks may affect the financial system. Stress testing models will, therefore, remain a complement to, rather than a substitute for broader macroprudential analysis of potential threats to financial stability.” (Bunn et al. (2005), p.117)
- Expected benefits:
  - Analytical process helps explore potential vulnerabilities.
  - Stimulates dialogue and capacity building among authorities; often has longer lasting effects beyond the FSAP.
- Dimensions of stress testing design:
  - Type of test:
    - Single-factor sensitivity tests (shocks to single risk factors).
    - Multivariate scenario tests (multiple risk factors changing in an internally consistent way).
  - Implementation perspective:
    - Bottom-up: run by individual financial institutions.
    - Top-down: run by central banks, supervisors, or the IMF.
  - Level of aggregation:
    - Bank-by-bank tests (individual institution portfolios).
    - Aggregate system-wide models.
- Design emphasis consistent with IMF comparative advantage:
  - Increasing emphasis on adverse macroeconomic scenarios and their impact on creditworthiness and system stability.
  - Construction of macro scenarios and identification of macro-level risk factors is critical irrespective of bank-by-bank or aggregate application.
- Uniformity and concentration:
  - Same shocks are applied uniformly to all institutions covered within a given stress test.
  - Importance of examining dispersion under aggregates—bank-by-bank testing is critical to reveal concentrations and vulnerabilities hidden under aggregates.
- Calibration principle:
  - Shocks should be “extreme but plausible.”
  - Approaches to calibration cited:
    - Applying the same shock or scenario for different data points in time to show changing risk profiles.
    - Reverse-engineered stress tests, identifying shocks that bring system capitalization to a threshold (example given: a CAR of 8 percent).

### IV. Stress Testing in FSAPs — Experience and Evolution
- General evolution:
  - Stress testing in FSAPs has evolved significantly since program inception; Table 1 (referenced) summarizes changes.
- Key developments highlighted:
  - Single-factor sensitivity analysis:
    - Most FSAPs conduct single-factor sensitivity analysis.
    - Such tests have evolved from central to more supplementary roles—used to approximate partial derivatives associated with broader multi-factor scenarios.
  - Macroeconomic scenario analysis:
    - More recent FSAPs increasingly involve explicit macroeconomic scenario analysis of varying complexity.
  - Involvement of national authorities:
    - Testing increasingly involves national authorities at all levels: methodology design, scenario and shock selection in agreement with FSAP teams, implementation/coordination of tests, and analysis of results (see Appendix Table 2).
- Role of FSAP stress testing in capacity development:
  - Encouraged policymakers to develop in-house capacities and build financial stability assessment functions.
  - Fund technical assistance has at times supported putting models and procedures in place for both FSAP use and regular authority use.
- Cross-checking and model diversification:
  - The FSAP praxis emphasizes not relying on a single model—use of aggregate tests as supplementary cross-checks to bank-by-bank results.

### Evolution of Stress Testing Methodologies in European FSAPs
- Key high-level adoption statistics (in percent of all FSAPs initiated in the period):
  - Scenario analysis: 2000–02: 64; 2003–05: 95; 2006–07: 82
  - Contagion analysis 1/: 2000–02: 11; 2003–05: 38; 2006–07: 55
  - Insurance sector stress testing: 2000–02: 25; 2003–05: 37; 2006–07: 9
  - 1/ Includes cross-border and interbank contagion.
  - Note: 2/ Includes a high proportion of less advanced countries.
- Implementation trends:
  - Increasing direct involvement of financial institutions, especially in relatively advanced systems.
  - Institution-by-institution implementation often uses banks’ own models, analyses, and judgments.
  - Interbank contagion increasingly integrated via mutual exposure matrices in domestic interbank markets.
  - Nonbank financial institutions increasingly covered, mainly insurance companies and to a lesser degree pension funds; nonbanks typically tested separately, but some cross-sectoral conglomerates tested at group level.

### Risks Addressed in FSAP Stress Tests
- Risk categories covered:
  - Credit risk; market risk (interest rate, exchange rate, volatility, equity, real estate and other asset price risks); liquidity risk; contagion risk.

- Credit risk — findings and approaches:
  - Credit risk remains the main overall source of risk for banks in many countries.
  - Early and simpler approaches: mechanical exercises shocking NPLs or provisions directly (single-factor sensitivity tests); NPL migration and loan reclassification remain essential.
  - More advanced approaches: loan performance regressions (single equation, structural, vector autoregression); PDs and LGDs analyses.
  - Typical advanced practice: model NPLs or loan-loss provisions as functions of macroeconomic variables; use stressed default rates for top-down stress tests or as bank inputs for bottom-up internal-model calculations.
  - IMF-highlighted methodologies:
    - Portfolio credit risk model based on CreditRisk+ complemented with PD and LGD models linked to macro-financial factors (input data aligned with Basel II IRB).
    - Nonparametric framework combining CoPoD, CIMDO, and CIMDO-copula to address short time series and default dependence; used to quantify impacts on individual banks’ economic capital and system economic capital (examples: Denmark, Lithuania).
  - Microeconomic linkage approaches (using corporate and household borrower characteristics) exist but limited use due to data and time requirements.

- Market risk — findings and approaches:
  - Generally smaller effects observed in FSAPs, partly due to shorter horizon and stronger bank management of market risk.
  - Interest rate risk methods used: repricing/maturity gaps, duration, VaR.
  - Exchange rate risk methods used: net open position sensitivity, VaR.
  - Shocks calibrated ad hoc, hypothetical, or historical; interest rate shocks include parallel shifts, steepening/flattening, and specific basis-point shocks; exchange rate shocks include ad-hoc devaluations and historical large changes.
  - Other market risks tested include equity price, real estate price, commodity price, credit spread risk, and competition risk.

- Liquidity risk — findings and approaches:
  - Liquidity stress tests now essential in recent FSAPs.
  - Typical shocks: deposit and wholesale funding runs; cross-border scenario where foreign investors/parent banks stop funding domestic banks.
  - Some FSAPs also stress market liquidity via haircuts on quasi-liquid assets.
  - Calibration: historical data when available (e.g., Croatia, France); often ad hoc otherwise (e.g., Austria).
  - Reporting metrics: changes to a liquidity ratio (regulatory or ad hoc) or days until banks become illiquid; some quantify CAR effects from market liquidity shocks.

- Contagion risk — findings and approaches:
  - Contagion stress testing increasingly common.
  - “Pure” contagion tests assess whether a random bank failure causes deterioration in capital adequacy of other banks via net domestic uncollateralized interbank exposures and are typically iterative.
  - Macro-linked contagion analyses use outcomes of system-wide stress tests as inputs to quantify knock-on effects and account for the likelihood of trigger failures (examples: Poland, Russia, Austria).

### FSAP Stress Testing Going Forward — Methodological Agenda
- Credit risk modeling priorities:
  - Continue development of distributions for PDs and LGDs and correlations between banks and portfolios to reflect system-level credit risk.
- Liquidity and joint risk analysis:
  - Expand work on funding and market liquidity risk, including off-balance-sheet concentration risk (excessive credit lines).
  - Strengthen joint analysis of market, credit, and liquidity risks; examine correlations and avoid simple additive capital aggregation where VaR measures are used.
  - Consider wider scenarios that include funding or market liquidity stresses alongside macro shocks (“perfect storm” scenarios).
- Contagion stress testing enhancements:
  - Examine mutual exposures in payment and settlement systems.
  - Consider liquidity contagion and apply extreme value theory (EVT) to explore correlations between institutions for contagion matrices.
  - Improve coverage of cross-border transmission channels and cross-border contagion between financial institutions.
- Scenario and alternative frameworks:
  - Consider contingent-claims approach (CCA) to link balance-sheet and market information via factor models to connect macro shocks to credit risk indicators; applicable when institutions issue securities in sufficiently deep markets.
- Behavioral and structural challenges:
  - Address modeling of behavioral responses of institutions under stress (monetary policy reactions are sometimes included; financial institution reaction functions—herding, fire-sales—pose systemic risks).
  - Account for potential nonlinearities and structural breaks that reduce stress-test reliability (example: limited past exchange rate volatility in hard-currency peg countries).
  - Incorporate second-round feedback effects from the financial sector back to the macroeconomy, acknowledging complexity.

### FSAP Process and Policy Recommendations
- Integration and data:
  - Improve integration of stress testing with other quantitative analysis; continue to improve availability and benchmarking of Financial Soundness Indicators (FSIs).
  - Greater use of market-based indicators as complementary modes and where feasible, integrate them into stress tests.
- Standardization vs. flexibility:
  - Debate on standardizing FSAP stress testing — consensus that strict standardization of shocks and sizes across countries could be misleading given structural differences.
  - Scope to standardize broader good practices within a flexible framework; initial steps and an adaptable template for smaller/less complex systems have been developed.
- Resource trade-offs:
  - Balance between analytical rigor (multiple approaches, consistency checks) and resource, computational, and data constraints.
  - Some costs are startup in nature; growing community of practitioners has eased the trade-off, but it remains a key consideration.
- Stakeholder engagement:
  - Maintain close dialogue with policymakers and academics to manage methodological evolution and resource allocation.

### Appendix — Coverage and Methodological Patterns in European FSAPs (selected tabulated findings)
- FSAP coverage (FSAPs initiated between 2000 and 2007) — examples of FSAPs and Updates:
  - Austria: FSAP 2003; Update 2007
  - Croatia: FSAP 2001; Update 2007
  - Ireland: FSAP 2000; Update 2006
  - Russia: FSAP 2002; Update 2007
  - Switzerland: FSAP 2001; Update 2006
- Who conducted calculations (selected patterns):
  - Supervisory agency/central bank executed calculations in jurisdictions including Austria (2003, 2007), Belgium (2004), Denmark (2005), Germany (2003), Ireland (2000, 2006), Russia (2007), Spain (2005), United Kingdom (2002).
  - FSAP team calculations in jurisdictions including Belarus (2004), Croatia (2001, 2007), Lithuania (2001, 2007), Moldova (2004, 2007), Poland (2000, 2006), Romania (2003), Ukraine (2002).
  - Financial institutions participated in calculations in jurisdictions including Austria (2007), Belgium (2004), Denmark (2005), Greece (2005), Ireland (2000, 2006), Italy (2004), Russia (2007), United Kingdom (2002).
- Institutions covered (selected):
  - All banks (bank by bank) in Belarus (2004), Croatia (2007), Latvia (2007), Lithuania (2001), Poland (2006), Russia (2007), Slovakia (2007), Switzerland (2006), Ukraine (2002).
  - Large/systemically important banks (bank by bank) in Austria (2003, 2007), Belgium (2004), Denmark (2005), France (2004), Germany (2003), Ireland (2000, 2006), Italy (2004), Russia (2002, 2007), United Kingdom (2002).
  - Insurance companies tested in Belgium (2004), Denmark (2005), Finland (2001), France (2004), Italy (2004), Netherlands (2003), Norway (2004), Portugal (2005), Spain (2005), Sweden (2001), Switzerland (2006), United Kingdom (2002).
  - Pension funds covered in Netherlands (2003), United Kingdom (2002).
- Approaches to credit risk modeling (selected):
  - NPLs/provisions via historical or macro-regressions: Austria (2003), Czech Republic (2000), France (2004), Iceland (2000), Ireland (2006), Israel (2000), Romania (2003), Russia (2002), Sweden (2001).
  - NPLs/provisions via ad hoc approaches: Belarus (2004), Bulgaria (2001), Croatia (2001, 2007), Hungary (2000, 2005), Latvia (2001, 2007), Moldova (2004, 2007), Poland (2000, 2006), Slovakia (2002, 2007), Switzerland (2001).
  - Shocks to PDs based on historical observations/regressions: Austria (2003, 2007), Belgium (2004), Denmark (2005), Greece (2005), Lithuania (2007), Luxembourg (2001), Russia (2002), Spain (2005).
  - Ad hoc shocks to PDs: Germany (2003), Italy (2004), Netherlands (2003), Norway (2004), United Kingdom (2002).
  - Explicit analyses: cross-border lending (Austria 2003, 2007; Spain 2005); foreign exchange lending (Austria 2003, 2007; Croatia 2001, 2007); loan concentration (Greece 2005; Latvia 2007; Netherlands 2003; Russia 2002, 2007).
- Interest rate and exchange rate shock practices (selected examples):
  - Interest rate shock examples: 3 standard deviations of 3-month changes; 50%-100% increase; three-fold increase in nominal rate; 100 basis point shock to interest rates; 100 basis point shock to dollar rates and concomitant 300 basis point shock to local rates; 300 basis point increase; +500, +200, +0 (+0, +200, +500) basis point increases by maturity bands.
  - Exchange rate shock examples: 20%-50% devaluation; 30% devaluation; 10% depreciation; 20% depreciation/appreciation; 40% depreciation/appreciation of Euro/Dollar exchange rate.
- Liquidity and contagion modeling (selected):
  - Liquidity risk (ad-hoc decline) applied in Austria (2003, 2007), Belgium (2004), Croatia (2007), Greece (2005), Ireland (2006), Italy (2004), Netherlands (2003), Poland (2006), Russia (2002, 2007), Spain (2005), Switzerland (2006), United Kingdom (2002).
  - Liquidity risk (historical shock) observed in Croatia (2001), France (2004), Lithuania (2007), Moldova (2007).
  - Interbank contagion applied in Austria (2003, 2007), Belgium (2004), Croatia (2007), Greece (2005), Luxembourg (2001), Netherlands (2003), Romania (2003), United Kingdom (2002).

### References (selected bibliographic entries)
- Avesani, Renzo, Kexue Liu, Alin Mirestean, and Jean Salvati, 2006, “Review and Implementation of Credit Risk Models of the Financial Sector Assessment Program,” IMF Working Papers 06/134 (Washington: International Monetary Fund).
- Aspachs-Bracons, Oriol, and others, 2006, “Searching for a Metric for Financial Stability,” Financial Markets Group, London School of Economics, Special Paper Series, 167.
- Goodhart, Charles, Boris Hofmann, and Miguel Segoviano, 2008a, “Bank Regulation and Macroeconomic Fluctuations”, in Handbook of European Financial Markets and Institutions, edited by X. Freixas, P. Hartmann, and C. Mayer, pp. 690–720.
- Goodhart, Charles, Miguel Segoviano, and D. Tsomocos, 2008b, “Measuring Financial Stability,” IMF Working Papers (forthcoming).
- Blaschke, Winfrid, Matthew T. Jones, Giovanni Majnoni, and Soledad Martinez Peria, 2001, “Stress Testing of Financial Systems: An Overview of Issues, Methodologies, and FSAP Experiences,” IMF Working Papers 01/88 (Washington: International Monetary Fund).
- Bunn, Philip, Alastair Cunningham, and Mathias Drehmann, 2005, “Stress Testing as a Tool for Assessing Systemic Risks,” Bank of England Financial Stability Review, June, pp. 116–26.
- Chan-Lau, Jorge A., Srobona Mitra, and Li Lian Ong, 2007, “Contagion Risk in the International Banking System and Implications for London as a Global Financial Center,” IMF Working Papers 07/74 (Washington: International Monetary Fund).
- Čihák, Martin, 2006, “How Do Central Banks Write on Financial Stability?” IMF Working Papers 06/163 (Washington: International Monetary Fund).
- Čihák, Martin, 2007, “Introduction to Applied Stress Testing,” IMF, Working Papers 07/59 (Washington: International Monetary Fund).
- Čihák, Martin, and Li Lian Ong, 2007, “Estimating Spillover Risk Among Large EU Banks,” IMF, Working Papers 07/267 (Washington: International Monetary Fund).
- Committee on the Global Financial System, 2000, “Stress Testing by Large Financial Institutions: Current Practice and Aggregation Issues.”
- Committee on the Global Financial System, 2005, “Stress Testing at Major Financial Institutions: Survey Results and Practice.”
- Drehman, M., 2005, “A Market Based Macro Stress Test for the Corporate Credit Exposures of UK Banks,” Paper presented at the Basel Committee Workshop on Banking and Financial Stability, Vienna, April, www.bis.org/bcbs/events.
- Gonzalez-Hermosillo, Brenda, and Miguel Segoviano, 2008, “Global Financial Stability and Macro-Financial Linkages,” IMF, Working Papers (forthcoming).
- Gray, Dale, and James P. Walsh, 2008, “Model for Stress-testing with a Contingent Claims Model of the Chilean Banking System,” IMF, Working Papers 08/89 (Washington: International Monetary Fund).
- Independent Evaluation Office, 2006, “Report on the Evaluation of the Financial Sector Assessment Program”, www.imf.org.
- International Monetary Fund and the World Bank, 2005, “Financial Sector Assessment: A Handbook,” www.imf.org.
- Jones, Matthew T., Paul Hilbers, and Graham Slack, 2004, “Stress Testing Financial Systems: What to Do When the Governor Calls,” IMF Working Papers 04/127 (Washington: International Monetary Fund).
- Maechler, Andrea, and Alexander Tieman, 2008, “The Real Effects of Financial Sector Risk,” IMF, Working Papers (forthcoming).
- Segoviano, Miguel, (2006a), “The Conditional Probability of Default Methodology,” Financial Markets Group, London School of Economics, Discussion Papers, no. 558.
- Segoviano, Miguel, (2006b), “The Consistent Information Multivariate Density Optimizing Methodology,” Financial Markets Group, London School of Economics, Discussion Papers, no. 557.
- Segoviano, Miguel, (2008), “CIMDO-Copula: Robust Estimation of Default Dependence with Data Restrictions,” IMF Working Papers (forthcoming).
- Segoviano, Miguel, and Charles Goodhart, 2008, “Banking Stability Index,” IMF Working Papers (forthcoming).
- Segoviano, Miguel, Charles Goodhart, and Boris Hofmann, 2006, “Default, Credit Growth, and Asset Prices,” IMF Working Papers 06/223 (Washington: International Monetary Fund).
- Segoviano, Miguel, and Pablo Basurto, 2006, “Portfolio Credit Risk and Macroeconomic Shocks: Applications to Stress Testing Under Data-Restricted Environments,” IMF Working Papers 06/283 (Washington: International Monetary Fund).
- Sorge, M., 2004, “Stress-Testing Financial Systems: An Overview of Current Methodologies,” BIS, Working Papers, 165.

*Source: _wp08206 - References*

### References..............................................................................................................

### _wp08206 - References

### I. Introduction
- Purpose of stress testing within IMF work:
  - Identify vulnerabilities across institutions that could undermine financial system stability.
  - Typically performed as part of the Financial Sector Assessment Program (FSAP)—a joint effort by the IMF and the World Bank.
- Coverage and adoption:
  - FSAPs have been or are being carried out for over 120 countries—two-thirds of Fund membership.
  - FSAP reassessments (updates) are also taking place, with more than 40 FSAP Updates completed or underway.
- Expansion of stress testing activity:
  - Article IV teams have started experimenting with stress testing as part of regular consultations.
  - Technical assistance on stress testing has been expanding; authorities often request technical assistance following FSAPs.
  - The IMF cooperates with central banks and supervisory agencies on stress testing projects (examples cited with the European Central Bank and the Deutsche Bundesbank).
- Methodological and cooperative initiatives:
  - Methodological work aims to better account for macro-financial linkages and to use multiple analytical perspectives as cross-checks.
  - The IMF launched the Expert Forum on Advanced Stress Testing Techniques in 2006; it meets approximately every year and a half with participation of supervisory agencies and central banks.
  - Expert Forum meetings mentioned: first in May 2006 at IMF headquarters; second in November 2007 hosted by the Nederlandsche Bank; next scheduled for May 2009 to be hosted by the Deutsche Bundesbank in Berlin.

### II. Background: Overview of the FSAP
- Broad objective:
  - Help strengthen and deepen financial systems and enhance resilience to potential financial crises.
- Scope and focus:
  - Assess stability of financial systems as a whole, rather than individual institutions.
  - Emphasize prevention and mitigation rather than crisis resolution.
  - Take a relatively broad, holistic view of system-level risks, including structural, institutional, and market features and the financial policy framework.
- Tools and complementarities:
  - Use a range of quantitative and qualitative tools, including formal assessments of international standards and codes.
  - Quantitative tools used in FSAPs alongside stress testing:
    - Financial soundness indicators (FSIs).
    - Market-based data (price and volatility measures).
    - Analyses of aggregate balance sheets (macro, sectoral).
    - Early warning systems.

### III. Stress Testing in FSAPs — Principles and Approaches
- Underlying principle:
  - Stress testing is a key tool in FSAPs but is complemented by qualitative analysis and other quantitative analysis. Quotation: “....no single model is ever likely to capture fully the diverse channels through which shocks may affect the financial system. Stress testing models will, therefore, remain a complement to, rather than a substitute for broader macroprudential analysis of potential threats to financial stability.” (Bunn et al. (2005), p.117)
- Expected benefits:
  - Analytical process helps explore potential vulnerabilities.
  - Stimulates dialogue and capacity building among authorities; often has longer lasting effects beyond the FSAP.
- Dimensions of stress testing design:
  - Type of test:
    - Single-factor sensitivity tests (shocks to single risk factors).
    - Multivariate scenario tests (multiple risk factors changing in an internally consistent way).
  - Implementation perspective:
    - Bottom-up: run by individual financial institutions.
    - Top-down: run by central banks, supervisors, or the IMF.
  - Level of aggregation:
    - Bank-by-bank tests (individual institution portfolios).
    - Aggregate system-wide models.
- Design emphasis consistent with IMF comparative advantage:
  - Increasing emphasis on adverse macroeconomic scenarios and their impact on creditworthiness and system stability.
  - Construction of macro scenarios and identification of macro-level risk factors is critical irrespective of bank-by-bank or aggregate application.
- Uniformity and concentration:
  - Same shocks are applied uniformly to all institutions covered within a given stress test.
  - Importance of examining dispersion under aggregates—bank-by-bank testing is critical to reveal concentrations and vulnerabilities hidden under aggregates.
- Calibration principle:
  - Shocks should be “extreme but plausible.”
  - Approaches to calibration cited:
    - Applying the same shock or scenario for different data points in time to show changing risk profiles.
    - Reverse-engineered stress tests, identifying shocks that bring system capitalization to a threshold (example given: a CAR of 8 percent).

### IV. Stress Testing in FSAPs — Experience and Evolution
- General evolution:
  - Stress testing in FSAPs has evolved significantly since program inception; Table 1 (referenced) summarizes changes.
- Key developments highlighted:
  - Single-factor sensitivity analysis:
    - Most FSAPs conduct single-factor sensitivity analysis.
    - Such tests have evolved from central to more supplementary roles—used to approximate partial derivatives associated with broader multi-factor scenarios.
  - Macroeconomic scenario analysis:
    - More recent FSAPs increasingly involve explicit macroeconomic scenario analysis of varying complexity.
  - Involvement of national authorities:
    - Testing increasingly involves national authorities at all levels: methodology design, scenario and shock selection in agreement with FSAP teams, implementation/coordination of tests, and analysis of results (see Appendix Table 2).
- Role of FSAP stress testing in capacity development:
  - Encouraged policymakers to develop in-house capacities and build financial stability assessment functions.
  - Fund technical assistance has at times supported putting models and procedures in place for both FSAP use and regular authority use.
- Cross-checking and model diversification:
  - The FSAP praxis emphasizes not relying on a single model—use of aggregate tests as supplementary cross-checks to bank-by-bank results.

*Source: _wp08206 - References*

### Appendix Table 1 lists the European countries whose FSAPs are covered in this survey. The survey focuses on

### _wp08206 - Appendix Table 1 lists the European countries whose FSAPs are covered in this survey. The survey focuses on

### Evolution of Stress Testing Methodologies in European FSAPs
- Key high-level adoption statistics (in percent of all FSAPs initiated in the period):
  - Scenario analysis: 2000–02: 64; 2003–05: 95; 2006–07: 82
  - Contagion analysis 1/: 2000–02: 11; 2003–05: 38; 2006–07: 55
  - Insurance sector stress testing: 2000–02: 25; 2003–05: 37; 2006–07: 9
  - 1/ Includes cross-border and interbank contagion.
  - Note: 2/ Includes a high proportion of less advanced countries.

- Implementation trends:
  - Increasing direct involvement of financial institutions, especially in relatively advanced systems.
  - Institution-by-institution implementation often uses banks’ own models, analyses, and judgments.
  - Interbank contagion increasingly integrated via mutual exposure matrices in domestic interbank markets.
  - Nonbank financial institutions increasingly covered, mainly insurance companies and to a lesser degree pension funds; nonbanks typically tested separately, but some cross-sectoral conglomerates tested at group level.

### Risks Addressed in FSAP Stress Tests
- Risk categories covered:
  - Credit risk; market risk (interest rate, exchange rate, volatility, equity, real estate and other asset price risks); liquidity risk; contagion risk.

- Credit risk — findings and approaches:
  - Credit risk remains the main overall source of risk for banks in many countries.
  - Early and simpler approaches: mechanical exercises shocking NPLs or provisions directly (single-factor sensitivity tests); NPL migration and loan reclassification remain essential.
  - More advanced approaches: loan performance regressions (single equation, structural, vector autoregression); PDs and LGDs analyses.
  - Typical advanced practice: model NPLs or loan-loss provisions as functions of macroeconomic variables; use stressed default rates for top-down stress tests or as bank inputs for bottom-up internal-model calculations.
  - IMF-highlighted methodologies:
    - Portfolio credit risk model based on CreditRisk+ complemented with PD and LGD models linked to macro-financial factors (input data aligned with Basel II IRB).
    - Nonparametric framework combining CoPoD, CIMDO, and CIMDO-copula to address short time series and default dependence; used to quantify impacts on individual banks’ economic capital and system economic capital (examples: Denmark, Lithuania).
  - Microeconomic linkage approaches (using corporate and household borrower characteristics) exist but limited use due to data and time requirements.

- Market risk — findings and approaches:
  - Generally smaller effects observed in FSAPs, partly due to shorter horizon and stronger bank management of market risk.
  - Interest rate risk methods used: repricing/maturity gaps, duration, VaR.
  - Exchange rate risk methods used: net open position sensitivity, VaR.
  - Shocks calibrated ad hoc, hypothetical, or historical; interest rate shocks include parallel shifts, steepening/flattening, and specific basis-point shocks; exchange rate shocks include ad-hoc devaluations and historical large changes.
  - Other market risks tested include equity price, real estate price, commodity price, credit spread risk, and competition risk.

- Liquidity risk — findings and approaches:
  - Liquidity stress tests now essential in recent FSAPs.
  - Typical shocks: deposit and wholesale funding runs; cross-border scenario where foreign investors/parent banks stop funding domestic banks.
  - Some FSAPs also stress market liquidity via haircuts on quasi-liquid assets.
  - Calibration: historical data when available (e.g., Croatia, France); often ad hoc otherwise (e.g., Austria).
  - Reporting metrics: changes to a liquidity ratio (regulatory or ad hoc) or days until banks become illiquid; some quantify CAR effects from market liquidity shocks.

- Contagion risk — findings and approaches:
  - Contagion stress testing increasingly common.
  - “Pure” contagion tests assess whether a random bank failure causes deterioration in capital adequacy of other banks via net domestic uncollateralized interbank exposures and are typically iterative.
  - Macro-linked contagion analyses use outcomes of system-wide stress tests as inputs to quantify knock-on effects and account for the likelihood of trigger failures (examples: Poland, Russia, Austria).

### FSAP Stress Testing Going Forward — Methodological Agenda
- Credit risk modeling priorities:
  - Continue development of distributions for PDs and LGDs and correlations between banks and portfolios to reflect system-level credit risk.
- Liquidity and joint risk analysis:
  - Expand work on funding and market liquidity risk, including off-balance-sheet concentration risk (excessive credit lines).
  - Strengthen joint analysis of market, credit, and liquidity risks; examine correlations and avoid simple additive capital aggregation where VaR measures are used.
  - Consider wider scenarios that include funding or market liquidity stresses alongside macro shocks (“perfect storm” scenarios).
- Contagion stress testing enhancements:
  - Examine mutual exposures in payment and settlement systems.
  - Consider liquidity contagion and apply extreme value theory (EVT) to explore correlations between institutions for contagion matrices.
  - Improve coverage of cross-border transmission channels and cross-border contagion between financial institutions.
- Scenario and alternative frameworks:
  - Consider contingent-claims approach (CCA) to link balance-sheet and market information via factor models to connect macro shocks to credit risk indicators; applicable when institutions issue securities in sufficiently deep markets.
- Behavioral and structural challenges:
  - Address modeling of behavioral responses of institutions under stress (monetary policy reactions are sometimes included; financial institution reaction functions—herding, fire-sales—pose systemic risks).
  - Account for potential nonlinearities and structural breaks that reduce stress-test reliability (example: limited past exchange rate volatility in hard-currency peg countries).
  - Incorporate second-round feedback effects from the financial sector back to the macroeconomy, acknowledging complexity.

### FSAP Process and Policy Recommendations
- Integration and data:
  - Improve integration of stress testing with other quantitative analysis; continue to improve availability and benchmarking of Financial Soundness Indicators (FSIs).
  - Greater use of market-based indicators as complementary modes and where feasible, integrate them into stress tests.
- Standardization vs. flexibility:
  - Debate on standardizing FSAP stress testing — consensus that strict standardization of shocks and sizes across countries could be misleading given structural differences.
  - Scope to standardize broader good practices within a flexible framework; initial steps and an adaptable template for smaller/less complex systems have been developed.
- Resource trade-offs:
  - Balance between analytical rigor (multiple approaches, consistency checks) and resource, computational, and data constraints.
  - Some costs are startup in nature; growing community of practitioners has eased the trade-off, but it remains a key consideration.
- Stakeholder engagement:
  - Maintain close dialogue with policymakers and academics to manage methodological evolution and resource allocation.

### Appendix — Coverage and Methodological Patterns in European FSAPs (selected tabulated findings)
- FSAP coverage (FSAPs initiated between 2000 and 2007) — examples of FSAPs and Updates:
  - Austria: FSAP 2003; Update 2007
  - Croatia: FSAP 2001; Update 2007
  - Ireland: FSAP 2000; Update 2006
  - Russia: FSAP 2002; Update 2007
  - Switzerland: FSAP 2001; Update 2006
  - (Appendix lists full set of European FSAPs covered in the survey.)

- Who conducted calculations (selected patterns):
  - Supervisory agency/central bank executed calculations in jurisdictions including Austria (2003, 2007), Belgium (2004), Denmark (2005), Germany (2003), Ireland (2000, 2006), Russia (2007), Spain (2005), United Kingdom (2002).
  - FSAP team calculations in jurisdictions including Belarus (2004), Croatia (2001, 2007), Lithuania (2001, 2007), Moldova (2004, 2007), Poland (2000, 2006), Romania (2003), Ukraine (2002).
  - Financial institutions participated in calculations in jurisdictions including Austria (2007), Belgium (2004), Denmark (2005), Greece (2005), Ireland (2000, 2006), Italy (2004), Russia (2007), United Kingdom (2002).

- Institutions covered (selected):
  - All banks (bank by bank) in Belarus (2004), Croatia (2007), Latvia (2007), Lithuania (2001), Poland (2006), Russia (2007), Slovakia (2007), Switzerland (2006), Ukraine (2002).
  - Large/systemically important banks (bank by bank) in Austria (2003, 2007), Belgium (2004), Denmark (2005), France (2004), Germany (2003), Ireland (2000, 2006), Italy (2004), Russia (2002, 2007), United Kingdom (2002).
  - Insurance companies tested in Belgium (2004), Denmark (2005), Finland (2001), France (2004), Italy (2004), Netherlands (2003), Norway (2004), Portugal (2005), Spain (2005), Sweden (2001), Switzerland (2006), United Kingdom (2002).
  - Pension funds covered in Netherlands (2003), United Kingdom (2002).

- Approaches to credit risk modeling (selected):
  - NPLs/provisions via historical or macro-regressions: Austria (2003), Czech Republic (2000), France (2004), Iceland (2000), Ireland (2006), Israel (2000), Romania (2003), Russia (2002), Sweden (2001).
  - NPLs/provisions via ad hoc approaches: Belarus (2004), Bulgaria (2001), Croatia (2001, 2007), Hungary (2000, 2005), Latvia (2001, 2007), Moldova (2004, 2007), Poland (2000, 2006), Slovakia (2002, 2007), Switzerland (2001).
  - Shocks to PDs based on historical observations/regressions: Austria (2003, 2007), Belgium (2004), Denmark (2005), Greece (2005), Lithuania (2007), Luxembourg (2001), Russia (2002), Spain (2005).
  - Ad hoc shocks to PDs: Germany (2003), Italy (2004), Netherlands (2003), Norway (2004), United Kingdom (2002).
  - Explicit analyses: cross-border lending (Austria 2003, 2007; Spain 2005); foreign exchange lending (Austria 2003, 2007; Croatia 2001, 2007); loan concentration (Greece 2005; Latvia 2007; Netherlands 2003; Russia 2002, 2007).

- Interest rate and exchange rate shock practices (selected examples):
  - Interest rate shock examples: 3 standard deviations of 3-month changes; 50%-100% increase; three-fold increase in nominal rate; 100 basis point shock to interest rates; 100 basis point shock to dollar rates and concomitant 300 basis point shock to local rates; 300 basis point increase; +500, +200, +0 (+0, +200, +500) basis point increases by maturity bands.
  - Exchange rate shock examples: 20%-50% devaluation; 30% devaluation; 10% depreciation; 20% depreciation/appreciation; 40% depreciation/appreciation of Euro/Dollar exchange rate.

- Liquidity and contagion modeling (selected):
  - Liquidity risk (ad-hoc decline) applied in Austria (2003, 2007), Belgium (2004), Croatia (2007), Greece (2005), Ireland (2006), Italy (2004), Netherlands (2003), Poland (2006), Russia (2002, 2007), Spain (2005), Switzerland (2006), United Kingdom (2002).
  - Liquidity risk (historical shock) observed in Croatia (2001), France (2004), Lithuania (2007), Moldova (2007).
  - Interbank contagion applied in Austria (2003, 2007), Belgium (2004), Croatia (2007), Greece (2005), Luxembourg (2001), Netherlands (2003), Romania (2003), United Kingdom (2002).

*Source: IMF staff survey and calculations as reported in the provided FSAP review content.*

### References

### References

### Bibliographic entries
- Avesani, Renzo, Kexue Liu, Alin Mirestean, and Jean Salvati, 2006, “Review and Implementation of Credit Risk Models of the Financial Sector Assessment Program,” IMF Working Papers 06/134 (Washington: International Monetary Fund).
- Aspachs-Bracons, Oriol, and others, 2006, “Searching for a Metric for Financial Stability,” Financial Markets Group, London School of Economics, Special Paper Series, 167.
- Goodhart, Charles, Boris Hofmann, and Miguel Segoviano, 2008a, “Bank Regulation and Macroeconomic Fluctuations”, in Handbook of European Financial Markets and Institutions, edited by X. Freixas, P. Hartmann, and C. Mayer, pp. 690–720.
- Goodhart, Charles, Miguel Segoviano, and D. Tsomocos, 2008b, “Measuring Financial Stability,” IMF Working Papers (forthcoming).
- Blaschke, Winfrid, Matthew T. Jones, Giovanni Majnoni, and Soledad Martinez Peria, 2001, “Stress Testing of Financial Systems: An Overview of Issues, Methodologies, and FSAP Experiences,” IMF Working Papers 01/88 (Washington: International Monetary Fund).
- Bunn, Philip, Alastair Cunningham, and Mathias Drehmann, 2005, “Stress Testing as a Tool for Assessing Systemic Risks,” Bank of England Financial Stability Review, June, pp. 116–26.
- Chan-Lau, Jorge A., Srobona Mitra, and Li Lian Ong, 2007, “Contagion Risk in the International Banking System and Implications for London as a Global Financial Center,” IMF Working Papers 07/74 (Washington: International Monetary Fund).
- Čihák, Martin, 2006, “How Do Central Banks Write on Financial Stability?” IMF Working Papers 06/163 (Washington: International Monetary Fund).
- Čihák, Martin, 2007, “Introduction to Applied Stress Testing,” IMF, Working Papers 07/59 (Washington: International Monetary Fund).
- Čihák, Martin, and Li Lian Ong, 2007, “Estimating Spillover Risk Among Large EU Banks,” IMF, Working Papers 07/267 (Washington: International Monetary Fund).
- Committee on the Global Financial System, 2000, “Stress Testing by Large Financial Institutions: Current Practice and Aggregation Issues.”
- Committee on the Global Financial System, 2005, “Stress Testing at Major Financial Institutions: Survey Results and Practice.”
- Drehman, M., 2005, “A Market Based Macro Stress Test for the Corporate Credit Exposures of UK Banks,” Paper presented at the Basel Committee Workshop on Banking and Financial Stability, Vienna, April, www.bis.org/bcbs/events.
- Gonzalez-Hermosillo, Brenda, and Miguel Segoviano, 2008, “Global Financial Stability and Macro-Financial Linkages,” IMF, Working Papers (forthcoming).
- Gray, Dale, and James P. Walsh, 2008, “Model for Stress-testing with a Contingent Claims Model of the Chilean Banking System,” IMF, Working Papers 08/89 (Washington: International Monetary Fund).
- Independent Evaluation Office, 2006, “Report on the Evaluation of the Financial Sector Assessment Program”, www.imf.org.
- International Monetary Fund and the World Bank, 2005, “Financial Sector Assessment: A Handbook,” www.imf.org.
- Jones, Matthew T., Paul Hilbers, and Graham Slack, 2004, “Stress Testing Financial Systems: What to Do When the Governor Calls,” IMF Working Papers 04/127 (Washington: International Monetary Fund).
- Maechler, Andrea, and Alexander Tieman, 2008, “The Real Effects of Financial Sector Risk,” IMF, Working Papers (forthcoming).
- Segoviano, Miguel, (2006a), “The Conditional Probability of Default Methodology,” Financial Markets Group, London School of Economics, Discussion Papers, no. 558.
- Segoviano, Miguel, (2006b), “The Consistent Information Multivariate Density Optimizing Methodology,” Financial Markets Group, London School of Economics, Discussion Papers, no. 557.
- Segoviano, Miguel, (2008), “CIMDO-Copula: Robust Estimation of Default Dependence with Data Restrictions,” IMF Working Papers (forthcoming).
- Segoviano, Miguel, and Charles Goodhart, 2008, “Banking Stability Index,” IMF Working Papers (forthcoming).
- Segoviano, Miguel, Charles Goodhart, and Boris Hofmann, 2006, “Default, Credit Growth, and Asset Prices,” IMF Working Papers 06/223 (Washington: International Monetary Fund).
- Segoviano, Miguel, and Pablo Basurto, 2006, “Portfolio Credit Risk and Macroeconomic Shocks: Applications to Stress Testing Under Data-Restricted Environments,” IMF Working Papers 06/283 (Washington: International Monetary Fund).
- Sorge, M., 2004, “Stress-Testing Financial Systems: An Overview of Current Methodologies,” BIS, Working Papers, 165.

*Source: _wp08206 - References*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2008/_wp08206.pdf_