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	बेयसियन टीजीएआरसीएच (बेयसियन अनुमान के साथ थ्रेशोल्ड जीएआरसीएच)	डीसीसी-गार्ग मॉडल (डायनामिक कंडीशनल कोरिलेशन)
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1994 / 2008	2002
प्रवर्तक	Zakoian (1994) for TGARCH; Bayesian estimation formalized by Ardia (2008)	Robert F. Engle
प्रकार	Volatility model with asymmetric threshold and Bayesian inference	Multivariate volatility model
मौलिक स्रोत	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.
उपनाम	Bayesian TGARCH, Bayesian GJR-GARCH, Threshold GARCH with Bayesian estimation, TGARCH-B	DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
संबंधित	6	5
सारांश	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.