手法を比較

	ベイジアンTGARCH（閾値GARCHとベイジアン推定）	DCC-GARCHモデル（動学的条件付き相関）
分野	計量経済学	計量経済学
系統	Regression model	Regression model
提唱年	1994 / 2008	2002
提唱者	Zakoian (1994) for TGARCH; Bayesian estimation formalized by Ardia (2008)	Robert F. Engle
種類	Volatility model with asymmetric threshold and Bayesian inference	Multivariate volatility model
原典	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.	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.
別名	Bayesian TGARCH, Bayesian GJR-GARCH, Threshold GARCH with Bayesian estimation, TGARCH-B	DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
関連	6	5
概要	Bayesian 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.