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Modèle EGARCH à rupture structurelle×Modèle DCC-GARCH (Corrélation Conditionnelle Dynamique)×
DomaineÉconométrieÉconométrie
FamilleRegression modelRegression model
Année d'origine1990–19912002
Auteur d'origineNelson (1991) for EGARCH; Lamoureux and Lastrapes (1990) for break-augmented GARCH variantsRobert F. Engle
TypeVolatility model with structural breaksMultivariate volatility model
Source fondatriceNelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. DOI ↗
AliasSB-EGARCH, EGARCH with regime shifts, break-adjusted EGARCH, structural change EGARCHDCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Apparentées55
RésuméStructural Break EGARCH combines Nelson's Exponential GARCH framework with explicit allowance for one or more structural breaks in the volatility process. By letting the intercept and persistence parameters of the log-variance equation shift at detected break dates, the model avoids the spurious long-memory and inflated persistence that standard EGARCH suffers when the data contain regime changes.The DCC-GARCH model, introduced by Engle (2002), extends univariate GARCH to capture time-varying correlations between multiple financial time series. It decomposes the multivariate conditional covariance matrix into individual volatility processes and a dynamic correlation matrix, allowing correlations to fluctuate over time while remaining computationally tractable even with many series.
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ScholarGateComparer des méthodes: Structural Break EGARCH · DCC-GARCH model. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare