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Model DCC-GARCH (Dynamic Conditional Correlation)×Autoregresi Vektor (VAR)×
BidangEkonometrikaEkonometrika
KeluargaRegression modelRegression model
Tahun asal20021980
PencetusRobert F. EngleChristopher A. Sims
TipeMultivariate volatility modelMultivariate time-series model
Sumber perintisEngle, 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 ↗Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗
AliasDCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCCVAR, VAR model, vector autoregressive model, multivariate autoregression
Terkait55
RingkasanThe 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.Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.
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ScholarGateBandingkan metode: DCC-GARCH model · Vector Autoregression. Diakses 2026-06-17 dari https://scholargate.app/id/compare