Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Экспоненциальный GARCH (EGARCH)× | Теория экстремальных значений (Extreme Value Theory, EVT)× | |
|---|---|---|
| Область≠ | Эконометрика | Финансы |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1991 | 2001 |
| Автор метода≠ | Nelson | Coles (textbook treatment); McNeil, Frey & Embrechts |
| Тип≠ | Conditional volatility model (asymmetric GARCH variant) | Tail / extreme-event model |
| Основополагающий источник≠ | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ | Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598 |
| Другие названия≠ | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH | EVT, generalized extreme value, generalized Pareto distribution, peaks over threshold |
| Связанные≠ | 4 | 5 |
| Сводка≠ | 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. | 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. |
| ScholarGateНабор данных ↗ |
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