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Teori Nilai Extrem (EVT)×Nilai-Risiko Bersyarat (Expected Shortfall)×
BidangKewanganKewangan
KeluargaRegression modelRegression model
Tahun asal20012000
PengasasColes (textbook treatment); McNeil, Frey & EmbrechtsRockafellar & Uryasev (2000); Acerbi & Tasche (2002)
JenisTail / extreme-event modelCoherent tail-risk measure
Sumber perintisColes, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598Rockafellar, R. T. & Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, 2(3), 21-41. DOI ↗
AliasEVT, generalized extreme value, generalized Pareto distribution, peaks over thresholdCVaR, expected shortfall, average value-at-risk, tail VaR
Berkaitan55
RingkasanExtreme 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.Conditional Value-at-Risk (CVaR), also called Expected Shortfall, is a coherent tail-risk measure that quantifies the conditional expectation of losses beyond the Value-at-Risk threshold. It was introduced for optimization by Rockafellar and Uryasev (2000) and shown to be coherent by Acerbi and Tasche (2002), and it has replaced VaR as the regulatory standard under Basel III/IV.
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ScholarGateBandingkan kaedah: Extreme Value Theory · Conditional Value-at-Risk. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare