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Bayesov TGARCH (Pragljeni GARCH s Bayesovom procjenom)×Model DCC-GARCH (Dinamička uvjetna korelacija)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka1994 / 20082002
TvoracZakoian (1994) for TGARCH; Bayesian estimation formalized by Ardia (2008)Robert F. Engle
VrstaVolatility model with asymmetric threshold and Bayesian inferenceMultivariate volatility model
Temeljni izvorZakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955. 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 naziviBayesian TGARCH, Bayesian GJR-GARCH, Threshold GARCH with Bayesian estimation, TGARCH-BDCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Srodne65
SažetakBayesian TGARCH combines the Threshold GARCH volatility model — which captures the asymmetric response of volatility to positive versus negative shocks — with full Bayesian inference via Markov Chain Monte Carlo sampling. The result is a principled, uncertainty-aware framework for modeling leverage effects and fat-tailed financial returns.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: Bayesian TGARCH · DCC-GARCH model. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare