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| Lossz eloszlás modell× | Szélsőérték-elmélet (EVT)× | |
|---|---|---|
| Tudományterület≠ | Biztosításmatematika | Pénzügy |
| Módszercsalád | Regression model | Regression model |
| Keletkezés éve≠ | 2012 | 2001 |
| Megalkotó≠ | Klugman, Panjer & Willmot | Coles (textbook treatment); McNeil, Frey & Embrechts |
| Típus≠ | Parametric probability model | Tail / extreme-event model |
| Alapmű≠ | Klugman, S. A., Panjer, H. H., & Willmot, G. E. (2012). Loss Models: From Data to Decisions (4th ed.). Wiley. ISBN: 978-1-118-31532-3 | Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598 |
| Alternatív nevek≠ | Severity-Frequency Model, Aggregate Loss Model, Claim Size Distribution Model, Hasar Dağılımı Modeli | EVT, generalized extreme value, generalized Pareto distribution, peaks over threshold |
| Kapcsolódó≠ | 3 | 5 |
| Összefoglaló≠ | A 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. |
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