From value at risk to stress testing: The extreme value approach

Longin, François

doi:10.1016/s0378-4266(99)00077-1

Cited by 406 publications

(266 citation statements)

References 27 publications

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“…For example, the plausibility is defined as the distance from the scenario to the present state of the market in a probability perspective [17,18]. Statistical methods (e.g., extreme value approach [19], Monte Carlo simulation [20]) are used to design scenarios. As criticized by Quagliariello [11], these numerical and statistical methods are not practical and have the significant drawback that the risk factors may not behave as they did in the past, because these methods assume that there is no structural change over the entire period.…”

Section: Scenario Design and Scenario Plausibilitymentioning

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: Scenario Design and Scenario Plausibilitymentioning

confidence: 99%

Ontology-based scenario modeling and analysis for bank stress testing

Yan

Zhao

et al. 2014

Decision Support Systems

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“…While the number of univariate contributions increases steadily, multivariate finance applications are also beginning to appear. Longin and Solnik (2000) explore the use of multivariate extreme value methods for stock market returns, which Longin (2000) uses to demonstrate how VaR of a position can be derived. Stȃricȃ (2000) finds a high level of dependence between the extreme movements of most of the currencies in the EU.…”

Section: Introductionmentioning

confidence: 99%

Modelling Extreme-Value Dependence in International Stock Markets

2002

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In the finance literature, cross-sectional dependence in extreme returns of risky assets is often modelled implicitly assuming an asymptotically dependent structure. If the true dependence structure is asymptotically independent then current modelling approaches will lead to an over-estimation of the risk of simultaneous extreme events. We use two simple nonparametric measures to identify and quantify the tail dependence among stock returns in five international stock markets. We show that there is strong evidence in favour of asymptotically independent models for the tail structure of stock market returns, and that most of the extremal dependence is due to heteroskedasticity in stock returns processes. Using a range of volatility filters, we find that tail index and tail dependence can be partially captured by models for heteroskedasticity. We find there is no clear reason to prefer one volatility filter over another.

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“…EVT provides a solid framework to formally study the behavior of extreme observations. It focuses directly on the tails of the sample distribution and could, therefore, potentially perform better than other approaches in terms of predicting unexpected extreme changes (see for exemple, Dacorogna et al, 1995;Longin, 2000). However, none of these studies has reflected the current volatility background.…”

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confidence: 99%