Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| DCC-GARCH (Dynamic Conditional Correlation)× | Théorie des Valeurs Extrêmes (TVE)× | |
|---|---|---|
| Domaine | Finance | Finance |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 2002 | 2001 |
| Auteur d'origine≠ | Robert F. Engle | Coles (textbook treatment); McNeil, Frey & Embrechts |
| Type≠ | Multivariate volatility model | Tail / extreme-event model |
| Source fondatrice≠ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗ | Coles, S. (2001). An Introduction to Statistical Modeling of Extreme Values. Springer. ISBN: 978-1852334598 |
| Alias≠ | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon | EVT, generalized extreme value, generalized Pareto distribution, peaks over threshold |
| Apparentées | 5 | 5 |
| Résumé≠ | DCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step. | 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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