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Medidas de Risco de Cauda (Expected Shortfall, Espectral, Expectil)×Teoria do Valor Extremo (EVT)×
ÁreaFinançasFinanças
FamíliaRegression modelRegression model
Ano de origem19992001
Autor originalArtzner, Delbaen, Eber & Heath (coherent risk axioms); Acerbi & Tasche (Expected Shortfall)Coles (textbook treatment); McNeil, Frey & Embrechts
TipoCoherent tail risk measureTail / extreme-event model
Fonte seminalArtzner, P., Delbaen, F., Eber, J.-M. & Heath, D. (1999). Coherent Measures of Risk. Mathematical Finance, 9(3), 203–228. DOI ↗Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598
Outros nomesexpected shortfall, conditional value at risk, CVaR, spectral risk measureEVT, generalized extreme value, generalized Pareto distribution, peaks over threshold
Relacionados55
ResumoTail risk measures quantify the loss distribution beyond Value-at-Risk (VaR). Expected Shortfall — the expected loss given that VaR is exceeded — is the leading coherent risk measure, formalised by Artzner, Delbaen, Eber and Heath (1999) and shown to be coherent by Acerbi and Tasche (2002). Spectral and expectile-based measures generalise it.Extreme Value Theory is a statistical framework for modelling the rare events that live in the tail of a probability distribution. As developed in Coles (2001) and applied to risk by McNeil, Frey & Embrechts (2005), it offers two standard routes: the Generalized Extreme Value (GEV) distribution for block maxima and the Generalized Pareto Distribution (GPD), used in the peaks-over-threshold approach, for exceedances above a high threshold.
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ScholarGateComparar métodos: Tail Risk Measures · Extreme Value Theory. Recuperado em 2026-06-19 de https://scholargate.app/pt/compare