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DCC-GARCH (dinamička uvjetna korelacija)×Model GARCH (Prognoziranje volatilnosti)×
PodručjeFinancijeEkonometrija
ObiteljRegression modelRegression model
Godina nastanka20021986
TvoracRobert F. EngleTim Bollerslev
VrstaMultivariate volatility modelConditional volatility model
Temeljni izvorEngle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
Drugi nazividynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu KorelasyonGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Srodne55
SažetakDCC-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.The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.
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ScholarGateUsporedite metode: DCC-GARCH · GARCH Model. Preuzeto 2026-06-19 s https://scholargate.app/hr/compare