Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Теорія екстремальних значень (ТЕЗ)× | Value at Risk (VaR)× | |
|---|---|---|
| Галузь | Фінанси | Фінанси |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2001 | 2007 |
| Автор методу≠ | Coles (textbook treatment); McNeil, Frey & Embrechts | Jorion (textbook benchmark); popularised by RiskMetrics / J.P. Morgan |
| Тип≠ | Tail / extreme-event model | Financial risk measure |
| Основоположне джерело≠ | 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 |
| Інші назви | EVT, generalized extreme value, generalized Pareto distribution, peaks over threshold | VaR, value-at-risk, delta-normal VaR, historical simulation VaR |
| Пов'язані | 5 | 5 |
| Підсумок≠ | 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. |
| ScholarGateНабір даних ↗ |
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