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Mierky rizika chvosta (očakávaný nedostatok, spektrálne, expektilné)×Teória extrémnych hodnôt (EVT)×
OdborFinancieFinancie
RodinaRegression modelRegression model
Rok vzniku19992001
TvorcaArtzner, Delbaen, Eber & Heath (coherent risk axioms); Acerbi & Tasche (Expected Shortfall)Coles (textbook treatment); McNeil, Frey & Embrechts
TypCoherent tail risk measureTail / extreme-event model
Pôvodný zdrojArtzner, 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
Ďalšie názvyexpected shortfall, conditional value at risk, CVaR, spectral risk measureEVT, generalized extreme value, generalized Pareto distribution, peaks over threshold
Príbuzné55
ZhrnutieTail 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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ScholarGatePorovnať metódy: Tail Risk Measures · Extreme Value Theory. Získané 2026-06-19 z https://scholargate.app/sk/compare