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| Теорія екстремальних значень (ТЕЗ)× | Експоненційне GARCH (EGARCH)× | |
|---|---|---|
| Галузь≠ | Фінанси | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2001 | 1991 |
| Автор методу≠ | Coles (textbook treatment); McNeil, Frey & Embrechts | Nelson |
| Тип≠ | Tail / extreme-event model | Conditional volatility model (asymmetric GARCH variant) |
| Основоположне джерело≠ | Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598 | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ |
| Інші назви≠ | EVT, generalized extreme value, generalized Pareto distribution, peaks over threshold | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH |
| Пов'язані≠ | 5 | 4 |
| 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. | EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance. |
| ScholarGateНабір даних ↗ |
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