Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Теория экстремальных значений (Extreme Value Theory, EVT)× | Value at Risk (VaR)× | |
|---|---|---|
| Область | Финансы | Финансы |
| Семейство | Regression model | Regression model |
| Год появления≠ | 2001 | 2007 |
| Автор метода≠ | Coles (textbook treatment); McNeil, Frey & Embrechts | Jorion (textbook benchmark); popularised by RiskMetrics / J.P. Morgan |
| Тип≠ | Tail / extreme-event model | Financial risk measure |
| Основополагающий источник≠ | Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598 | Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk (3rd ed.). McGraw-Hill. ISBN: 978-0071464956 |
| Другие названия | EVT, generalized extreme value, generalized Pareto distribution, peaks over threshold | VaR, value-at-risk, delta-normal VaR, historical simulation VaR |
| Связанные | 5 | 5 |
| Сводка≠ | 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. | Value at Risk is a financial risk measure that estimates the maximum loss a position or portfolio could suffer over a fixed holding period at a given confidence level. It is the standard benchmark in risk management and regulatory capital calculations, developed in the textbook tradition of Jorion (2007) and the Basel market-risk framework. |
| ScholarGateНабор данных ↗ |
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