- Li Ong
- Published Date:
- December 2014
A Guide to IMF Stress Testing
Methods and Models
Li Lian Ong
©2014 International Monetary Fund
Cover design: IMF Multimedia Services Division
Joint Bank-Fund Library
A guide to IMF stress testing: methods and models / editor, Li Lian Ong. —
Washington, D.C.: International Monetary Fund, 2014.
Includes bibliographical references and index.
1. Financial crises. 2. Banks and banking, International. 3. International Monetary Fund. I. Ong, Li Lian. II. International Monetary Fund.
ISBN: 978-1-48436-858-9 (paper)
ISBN: 978-1-47555-129-7 (web PDF)
Disclaimer: The views expressed in this book are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
Please send orders to:
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Mark W. Swinburne
June 17, 1955–September 3, 2009
Monetary and Capital Markets Department
International Monetary Fund
Manager, mentor, friend
Li Lian Ong • Martin Čihák
Christian Schmieder • Liliana Schumacher
Li Lian Ong • Rodolfo Maino • Nombulelo Duma
Christian Schmieder • Claus Puhr • Maher Hasan
Li Lian Ong • Martin Čihák
Christian Schmieder • Heiko Hesse • Benjamin Neudorfer • Claus Puhr • Stefan W. Schmitz
Theodore Barnhill Jr. • Marcos Souto
Theodore Barnhill Jr. • Liliana Schumacher
Renzo G. Avesani • Kexue Liu • Alin Mirestean • Jean Salvati
Eugenio Cerutti • Anna Ilyina • Yulia Makarova • Christian Schmieder
Marco A. Espinosa-Vega • Juan Solé
Marco A. Espinosa-Vega • Juan Solé
Jorge A. Chan-Lau
Elena Duggar • Srobona Mitra
Jorge A. Chan-Lau • Martin Čihák • Srobona Mitra • Li Lian Ong
Dale F. Gray • Andreas A. Jobst • Cheng Hoon Lim • Yingbin Xiao
Michael T. Gapen • Dale F. Gray • Cheng Hoon Lim • Yingbin Xiao
Dale F. Gray • James P. Walsh
Andreas A. Jobst • Dale F. Gray
Andreas A. Jobst
Andrea M. Maechler
Francisco Vazquez • Benjamin M. Tabak • Marcos Souto
Torsten Wezel • Michel Canta • Manuel Luy
Miguel A. Segoviano • Pablo Padilla
Miguel A. Segoviano • Charles A. E. Goodhart
Geoffrey N. Keim • Andrea M. Maechler
Alexander F. Tieman • Andrea M. Maechler
The files listed below are available on the companion CD and at www.elibrary.imf.org/stress-test-toolkit.
Stress Tester 3.0
Excel Spreadsheet Macro for the Breaking Point Method
Excel Spreadsheet Macro for the Next-Generation Solvency Stress Test
Excel Spreadsheet Macro for the Market and Funding Liquidity Stress Test
Excel Spreadsheet Macro for the Next-Generation Systemwide Liquidity Stress Test
Excel Add-in for the CreditRisk+ Model
Excel Spreadsheet Macro for Stress Testing Defined Benefit Pension Plans
Excel-based Program for Bank Network Analysis
Example Eviews Program Codes: External Linkages
Example Eviews Program Codes: International Banking System
Excel Spreadsheet for the Balance Sheet Risk Analysis
Excel Spreadsheet Macro for Forward-Looking Macroprudential Stress Test
The global financial crisis has placed a spotlight on the stress testing of financial systems. Although weaknesses in stress tests were exposed by the crisis, the recent experience of several countries has conversely provided a stark illustration of their potential benefit in examining the resilience of bank balance sheets when performed credibly and transparently. Nonetheless, the large menu of stress testing approaches, methods, and models raises questions about their appropriate application under different situations and, consequently, the comparability and reliability of the associated analyses.
The International Monetary Fund (IMF) has had a long and unique involvement in the stress testing of financial systems. Since the introduction of the Financial Sector Assessment Program (FSAP) more than a decade ago, IMF staff has conducted stress tests of banking sectors in over 120 countries, typically in close collaboration with country authorities. Stress testing is also playing an increasingly important role in the IMF’s multilateral surveillance, through the analysis in our Global Financial Stability Report. Separately, member countries are increasingly requesting IMF technical assistance in stress testing as they develop their own expertise in this area. As a result, our staff has amassed a wealth of hands-on experience with stress testing techniques and their practical application.
This book represents a compendium of stress testing methods, models, and tools developed or adapted by IMF staff over the years. Almost all the methods and models that are included in this volume have, at one time or another, been applied in our surveillance of, or our technical assistance to, member countries. To guide users, each chapter offers a summary describing the application of a method or model, its strengths and weaknesses, and the data requirements. Where available, the stress testing tools or program codes are also provided for wider public use.
Although I trust that this volume will provide a valuable resource for policymakers, supervisors, academics, and private sector participants alike, caveats still apply. The crisis has underscored that stress tests, irrespective of their level of sophistication, are not fail-safe, stand-alone diagnostic tools. Assessments of the soundness of any financial system cannot and should not be based solely on a “model” and must be complemented by other quantitative analyses, qualitative information, and, most important, expert judgment. Especially in light of evolving market practices, risks, and regulatory requirements, stress testing will necessarily continue to be art rather than science.
IMF staff is continually working to strengthen the analytical underpinnings of its stress testing, in ways that will help bolster its consistency and comparability and hence its credibility. Key areas of focus include extending the analysis to better cover nonbank financial institutions and infrastructures; to take account of spillovers between institutions and across borders; to consider the interaction between liquidity and solvency risks; and to address data gaps. In addition, IMF staff is developing the policy-related aspects of stress testing, namely, “best practice” principles, concepts, and frameworks, to complement and strengthen the application of the models. These efforts represent a challenging and exciting part of the IMF’s broader support of global efforts to improve financial surveillance and promote sound macroprudential frameworks.
Financial Counsellor and Director
Monetary and Capital Markets Department
International Monetary Fund
I am grateful to the many contributing authors of this book. The papers that make up the many chapters of this volume are the result of collaboration among internal colleagues and external experts, and have benefited from comments from IMF staff, academics, market participants, and policymakers, as well as journal editors and referees.
This project would not have been possible without the backing of José Viñals. And my heartfelt thanks to my colleague, friend, and sometime co-author, Martin Čihák, for his support and sage advice throughout this venture.
The book has also benefited greatly since its inception from the professionalism and expertise of colleagues in the Communications Department, specifically, Sean Culhane, Patricia Loo, and Joanne Johnson.
Last but not least, I would like to thank Margarita Aguilar for her indispensable and patient assistance in the preparation of the manuscript; and James Morsink and Srobona Mitra for back-stopping me during the publication process.
accrued benefit obligationABS
Allied Irish Banks PLCAIG
American International GroupAIRB
Advanced Internal Ratings BasedAnglo IB
Anglo Irish Bank Corp. PLCARCH
autoregressive conditional heteroskedasticityASF
available stable fundingBBVA
Banco Bilbao Vizcaya ArgentariaBCBS
Basel Committee on Banking SupervisionBCCH
Central Bank of Chile/Banco Central de ChileBCP
Basel Core Principles for Banking SupervisionBHC
bank holding companyBIS
Bank for International SettlementsBoE
Bank of EnglandBoI
Bank of IrelandBSI
Banking Stability IndexBSM
banking stability measureBSMD
Banking System’s (portfolio) Multivariate DensityBSoM
capital asset pricing modelCAR
capital adequacy ratio (regulatory capital to risk-weighted assets)CCA
contingent claims analysisCCP
Copula Choice ProblemCDO
collateralized debt obligationCDS
credit default swapCEBS
Committee of European Banking SupervisorsCEDF
cumulative expected default frequencyCESE
Central, Eastern, and Southern EuropeC&I
commercial and industrialCIMDO
Consistent Information Multivariate Density OptimizingCN
Croatian National BankCoPoD
Conditional Probability of DefaultCPI
consumer price indexCRE
commercial real estateCRI
credit risk indicatorCRT
credit risk transferCSFP
Credit Suisse Financial ProductsDAX
Deutscher Aktien IndeXDB
dynamic conditional correlationDD
distance to defaultDiDe
Distress Dependence MatrixDNB
De Nederlandsche BankDSI
debt service-to-income ratioDTA
deferred tax assetsDtD
distance to distressEAD
exposure at defaultEC
European Central BankEDF
expected default frequencyEL
Emerging Market Bond IndexEMBIG
Emerging Market Bond Index GlobalES
extreme value theoryFFT
fast Fourier transformFIRB
Foundation Internal Ratings BasedFME
Financial Supervisory Authority/FjármálaeftirlitsinsFMI
financial market infrastructureFSAP
Financial Sector Assessment ProgramFSB
Financial Stability BoardFSC
Financial Services CenterFSI
financial soundness indicatorFSR
Financial Stability ReportFVCDS
fair value CDSFVOAS
fair value option adjusted spreadFX
generalized autoregressive conditional heteroskedasticityGEV
generalized extreme valueGFSR
Global Financial Stability ReportGMM
Generalized Method of MomentsGOB
Government of BrazilHBOS
Halifax Bank of ScotlandHHI
Hongkong and Shanghai Banking CorporationIBB
immediate borrower basisICR
interest coverage ratioIFRS
International Financial Reporting StandardsIFS
International Financial StatisticsIMACEC
Indicador Mensual de Actividad EconómicaIPSA
Indice de Precios Selectivo de AccionesIRB
Internal Ratings BasedIRF
impulse response functionISEQ
Irish Stock Exchange Overall IndexIT
joint probability of distressKMV
Kealhofer, McQuown, and Vasicek (a part of Moody’s Analytics)LCR
liquidity coverage ratioLGD
loss given defaultLHS
London Interbank Offered RateLLR
loan loss reserveLS
Long Term Capital ManagementLTV
market-implied capital adequacy ratioMES
marginal expected shortfallMfRisk
moment generating functionMIDP
market implied default probabilitiesMKMV
macroprudential policy and surveillanceMSCI
Morgan Stanley Capital InternationalMSE
mean squared errorMXED
minimum cross-entropy distributionNASDAQ
National Association of Securities Dealers Automated QuotationsNBB
National Bank of BankistanNBFI
nonbank financial institutionNFI
net foreign investmentNPL
net stable funding ratioOBS
Austrian National Bank/Oesterreichische NationalbankOIS
overnight indexed swapOLS
ordinary least squaresOOM
probability that at least one bank becomes distressedPBO
projected benefit obligationPBOcd
projected benefit obligation constant dollarPCA
principal component analysisPD
probability of defaultPGF
probability generating functionPIT
Probability Integral TransformationPLD
profit and loss distributionPMD
portfolio multivariate distributionPoD
probability of distressQIRB
quasi-Internal Ratings BasedQIS
Quantitative Impact StudyRAMSI
Risk Assessment Model for Systemic InstitutionsRHS
retirement benefit obligationRBS
Royal Bank of ScotlandRNDP
risk-neutral default probabilityRNS
risk-neutral credit spreadROA
return on assetsRRE
residential real estateRSF
required stable fundingRWA
Banking Supervisory Agency/Superintendencia de Bancos e Instituciones FinancierasSCAP
Supervisory Capital Assessment ProgramSELIC
Sistema Especial de Liquidação e CustodiaSLOOS
Senior Loan Officer Opinion Survey of Bank Lending PracticesSME
small-and medium-sized enterpriseS&P
Standard and Poor’sSPD
Systemic Risk-Adjusted LiquiditySRM
Systemic Risk MonitorStA
sovereign wealth fundTARP
Troubled Asset Relief ProgramTBTF
ultimate risk basisVaR
value at riskVAR
implied volatility of the Deutscher Aktien IndeX (DAX)VIX
Chicago Board Options Exchange Market Volatility Index (implied volatility of the S&P 500 index)WaMu
World Economic Outlook
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The views expressed in this volume are those of the authors and do not necessarily represent those of their respective institutions.