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Uogólniona warunkowa heteroskedastyczność z autoregresją (GARCH)×DCC-GARCH (Dynamic Conditional Correlation)×
DziedzinaEkonometriaFinanse
RodzinaRegression modelRegression model
Rok powstania19862002
TwórcaTim BollerslevRobert F. Engle
TypConditional volatility modelMultivariate volatility model
Źródło pierwotneBollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗
Inne nazwyGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modelidynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon
Pokrewne55
PodsumowanieGARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.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.
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ScholarGatePorównaj metody: GARCH · DCC-GARCH. Pobrano 2026-06-17 z https://scholargate.app/pl/compare