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	बेयसियन टीजीएआरसीएच (बेयसियन अनुमान के साथ थ्रेशोल्ड जीएआरसीएच)	EGARCH मॉडल (घातीय GARCH)
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1994 / 2008	1991
प्रवर्तक	Zakoian (1994) for TGARCH; Bayesian estimation formalized by Ardia (2008)	Daniel B. Nelson
प्रकार	Volatility model with asymmetric threshold and Bayesian inference	Volatility / conditional variance model
मौलिक स्रोत	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.
उपनाम	Bayesian TGARCH, Bayesian GJR-GARCH, Threshold GARCH with Bayesian estimation, TGARCH-B	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
संबंधित	6	6
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 Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets.