Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Exponential GARCH (EGARCH)× | Théorie des Valeurs Extrêmes (TVE)× | |
|---|---|---|
| Domaine≠ | Économétrie | Finance |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1991 | 2001 |
| Auteur d'origine≠ | Nelson | Coles (textbook treatment); McNeil, Frey & Embrechts |
| Type≠ | Conditional volatility model (asymmetric GARCH variant) | Tail / extreme-event model |
| Source fondatrice≠ | 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 |
| Alias≠ | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH | EVT, generalized extreme value, generalized Pareto distribution, peaks over threshold |
| Apparentées≠ | 4 | 5 |
| Résumé≠ | 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. |
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