A comparative analysis of macro stress-testing methodologies with application to Finland

Sorge, Marco M.; Virolainen, Kimmo

doi:10.1016/j.jfs.2005.07.002

Cited by 114 publications

(113 citation statements)

References 73 publications

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“…Sorge and Virolainen [7] have proposed a schematic classification of existing stress testing approaches in finance literature. There are two types of approaches: 1) the piecewise approach, and 2) the integrated approach.…”

Section: Bank Stress Testing Approachesmentioning

confidence: 99%

Ontology-based scenario modeling and analysis for bank stress testing

Yan

Zhao

et al. 2014

Decision Support Systems

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Abstract:The 2008 banking crisis demonstrated that there is a lack of effective methods for modeling and analyzing "exceptional but plausible" risk scenarios in bank stress testing. Existing stress testing practices mainly focus on modeling probability-based risk factors and events in banking systems using historical data. Rare (low probability) risk events that can cause financial crises in banking systems, such as the bankruptcy of Lehman Brothers, are largely ignored due to the lack of appropriate modeling and analysis methods. To address this problem, we propose an approach called Banking Event-driven Scenario-oriented Stress Testing (or simply, BESST) which has two main components: 1) an ontologybased event-driven scenario model (OESM), and 2) two analysis methods based on OESM for scenario recommendation and plausibility checking. The proposed BESST approach provides bank stress testing stakeholders an effective method for modeling and analyzing financial crisis scenarios that are rare but often have significant consequences.

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Section: Bank Stress Testing Approachesmentioning

confidence: 99%

Ontology-based scenario modeling and analysis for bank stress testing

Yan

Zhao

et al. 2014

Decision Support Systems

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“…It is worth mentioning that, although stress test exercises are also oriented to the assessment of solvency from a conditional perspective, Sorge and Virolainen (2006) and Foglia (2009), our approach differ from them significantly. Thus, stress testing usually considers hypothetical, rather than observed, scenarios.…”

Section: Discussionmentioning

confidence: 99%

Conditional Coverage and Its Role in Determining and Assessing Long-Term Capital Requirements

2014

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We define the vector of conditional coverage values generated over the business cycle by a constant capital figure. Using a convenient analytical framework, we explore its properties and propose two applications based on it. For the former, we state a result that links the concepts of conditional and unconditional solvency and offers an alternative interpretation of the unconditional capital. For the latter, we propose using the minimum of the conditional coverage vector in the determination of long-term capital requirements, as well as using its minimum and its standard deviation in the long-term assessment of a given capital figure. Both applications are illustrated empirically. The entire analysis can be understood as an attempt to recognize and incorporate capital cyclicality into the measurement and analysis of default risk. We define the vector of conditional coverage values generated over the business cycle by a constant capital figure. Using a convenient analytical framework, we explore its properties and propose two applications based on it. For the former, we state a result that links the concepts of conditional and unconditional solvency and offers an alternative interpretation of the unconditional capital. For the latter, we propose using the minimum of the conditional coverage vector in the determination of long-term capital requirements, as well as using its minimum and its standard deviation in the long-term assessment of a given capital figure. Both applications are illustrated empirically. The entire analysis can be understood as an attempt to recognize and incorporate capital cyclicality into the measurement and analysis of default risk. J EL

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“…Sorge and Virolainen (2006) focus on credit risk and liquidity risk. The authors present a model for the relationship between the provisions for loan losses and relevant macroeconomic factors.…”

Section: Sample Variables and Methodologymentioning

confidence: 99%

Financial Leading Indicators of Banking Distress: A Micro Prudential Approach - Evidence from Europe

Messai¹,

Gallali²

2015

ASS

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Sovereign and Subprime crises have corrosive effects on European banking system. In this study, we aim to explain and predict the state of distress for 618 European banks for a five year period (2007)(2008)(2009)(2010)(2011). For this purpose, we applied early warning systems using traditional and developed methods: discriminant analysis, logistic regression and the artificial intelligence. Those methods aim to predict bank distress up to a year (two years) before it actually happened. Our study seeks to compare between these three methods and to choose the most appropriate for prediction. The key finding of this study demonstrates that the neural network method outperforms the other models. This result is too much useful for banks and help policy makers to do a better job in terms of regulatory reforms.

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A comparative analysis of macro stress-testing methodologies with application to Finland

Cited by 114 publications

References 73 publications

Ontology-based scenario modeling and analysis for bank stress testing

Ontology-based scenario modeling and analysis for bank stress testing

Conditional Coverage and Its Role in Determining and Assessing Long-Term Capital Requirements

Financial Leading Indicators of Banking Distress: A Micro Prudential Approach - Evidence from Europe

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