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ARCH model (Autoregressive Conditional Heteroskedasticity)×Model DCC-GARCH (Dinamička uvjetna korelacija)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka19822002
TvoracRobert F. EngleRobert F. Engle
VrstaConditional volatility modelMultivariate volatility model
Temeljni izvorEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. 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 ↗
Drugi naziviARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelDCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Srodne65
SažetakThe ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.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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ScholarGateUsporedite metode: ARCH model · DCC-GARCH model. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare