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Модель распределения убытков×Теория экстремальных значений (Extreme Value Theory, EVT)×
ОбластьАктуарная наукаФинансы
СемействоRegression modelRegression model
Год появления20122001
Автор методаKlugman, Panjer & WillmotColes (textbook treatment); McNeil, Frey & Embrechts
ТипParametric probability modelTail / extreme-event model
Основополагающий источникKlugman, S. A., Panjer, H. H., & Willmot, G. E. (2012). Loss Models: From Data to Decisions (4th ed.). Wiley. ISBN: 978-1-118-31532-3Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598
Другие названияSeverity-Frequency Model, Aggregate Loss Model, Claim Size Distribution Model, Hasar Dağılımı ModeliEVT, generalized extreme value, generalized Pareto distribution, peaks over threshold
Связанные35
СводкаA Loss Distribution Model is a parametric statistical framework used in actuarial science to characterise the probabilistic behaviour of insurance claim amounts and frequencies. Developed comprehensively by Klugman, Panjer, and Willmot in their foundational text Loss Models: From Data to Decisions (first edition 1998, fourth edition 2012), these models underpin premium rating, reserving, reinsurance pricing, and regulatory capital calculations across the insurance and risk-management industries.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.
ScholarGateНабор данных
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ScholarGateСравнение методов: Loss Distribution Model · Extreme Value Theory. Получено 2026-06-18 из https://scholargate.app/ru/compare