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ARCH-model (Autoregressiv Betinget Heteroskedasticitet)×DCC-GARCH-model (Dynamisk Betinget Korrelation)×
FagområdeØkonometriØkonometri
FamilieRegression modelRegression model
Oprindelsesår19822002
OphavspersonRobert F. EngleRobert F. Engle
TypeConditional volatility modelMultivariate volatility model
Oprindelig kildeEngle, 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 ↗
AliasserARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelDCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Relaterede65
ResuméThe 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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ScholarGateSammenlign metoder: ARCH model · DCC-GARCH model. Hentet 2026-06-17 fra https://scholargate.app/da/compare