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DCC-GARCH (Dynamic Conditional Correlation)×GJR-GARCH (Asymetryczny GARCH)×
DziedzinaFinanseEkonometria
RodzinaRegression modelRegression model
Rok powstania20021993
TwórcaRobert F. EngleGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
TypMultivariate volatility modelAsymmetric conditional volatility model
Źródło pierwotneEngle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. DOI ↗
Inne nazwydynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyonasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
Pokrewne55
PodsumowanieDCC-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.GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994).
ScholarGateZbiór danych
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  1. v1
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  3. PUBLISHED

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ScholarGatePorównaj metody: DCC-GARCH · GJR-GARCH. Pobrano 2026-06-19 z https://scholargate.app/pl/compare