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Robust Dynamic Conditional Correlation GARCH (Robust DCC-GARCH)×Vektorautoregression (VAR)×
FagområdeØkonometriØkonometri
FamilieRegression modelRegression model
Oprindelsesår2002–20211980
OphavspersonEngle (2002) for DCC; robust extensions by Pakel, Shephard, Sheppard, and Engle (2021)Christopher A. Sims
TypeMultivariate volatility model with robust estimationMultivariate time-series model
Oprindelig kildeEngle, 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 ↗
Aliasserrobust DCC-GARCH, robust dynamic conditional correlation, outlier-robust DCC, composite-likelihood DCC-GARCHVAR, VAR model, vector autoregressive model, multivariate autoregression
Relaterede65
ResuméThe Robust DCC-GARCH model extends Engle's (2002) Dynamic Conditional Correlation framework by replacing standard quasi-maximum likelihood estimation with outlier-resistant or composite-likelihood techniques. This preserves accurate time-varying correlation estimation even when financial return data contain extreme observations, heavy tails, or structural irregularities.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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ScholarGateSammenlign metoder: Robust DCC-GARCH · Vector Autoregression. Hentet 2026-06-17 fra https://scholargate.app/da/compare