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Model EGARCH z przerwami strukturalnymi×Model DCC-GARCH (Dynamic Conditional Correlation)×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania1990–19912002
TwórcaNelson (1991) for EGARCH; Lamoureux and Lastrapes (1990) for break-augmented GARCH variantsRobert F. Engle
TypVolatility model with structural breaksMultivariate volatility model
Źródło pierwotneNelson, 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 ↗
Inne nazwySB-EGARCH, EGARCH with regime shifts, break-adjusted EGARCH, structural change EGARCHDCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Pokrewne55
PodsumowanieStructural 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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ScholarGatePorównaj metody: Structural Break EGARCH · DCC-GARCH model. Pobrano 2026-06-17 z https://scholargate.app/pl/compare