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| 损失分布模型× | 极值理论 (EVT)× | |
|---|---|---|
| 领域≠ | 精算学 | 金融学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2012 | 2001 |
| 提出者≠ | Klugman, Panjer & Willmot | Coles (textbook treatment); McNeil, Frey & Embrechts |
| 类型≠ | Parametric probability model | Tail / extreme-event model |
| 开创性文献≠ | 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 |
| 别名≠ | Severity-Frequency Model, Aggregate Loss Model, Claim Size Distribution Model, Hasar Dağılımı Modeli | EVT, generalized extreme value, generalized Pareto distribution, peaks over threshold |
| 相关≠ | 3 | 5 |
| 摘要≠ | 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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