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DCC-GARCH (Dynamic Conditional Correlation)×GJR-GARCH (Asymmetrisches GARCH)×Panel EGARCH×
FachgebietFinanzwirtschaftÖkonometrieÖkonometrie
FamilieRegression modelRegression modelRegression model
Entstehungsjahr200219931991 (EGARCH); panel extensions widely used from 2000s
UrheberRobert F. EngleGlosten, Jagannathan & Runkle (1993); Zakoian (1994)Daniel B. Nelson (EGARCH); panel extension by applied econometrics literature
TypMultivariate volatility modelAsymmetric conditional volatility modelVolatility model
Wegweisende QuelleEngle, 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 ↗Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗
Aliasnamendynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyonasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)Panel EGARCH model, panel exponential GARCH, EGARCH for panel data, cross-sectional EGARCH
Verwandt554
ZusammenfassungDCC-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).Panel EGARCH extends Nelson's (1991) Exponential GARCH model to a panel setting, allowing conditional variance to evolve asymmetrically over time for each cross-sectional unit. The log specification ensures non-negative variance without parameter constraints, and the leverage term distinguishes whether negative shocks amplify volatility more than positive ones of equal magnitude.
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ScholarGateMethoden vergleichen: DCC-GARCH · GJR-GARCH · Panel EGARCH. Abgerufen am 2026-06-19 von https://scholargate.app/de/compare