পদ্ধতির তুলনা করুন

	বেয়েশীয় টিজিএআরসিএইচ (সীমাযুক্ত জিএআরসিএইচ সহ বেয়েশীয় প্রাক্কলন)	ইগার্চ মডেল (এক্সপোনেনশিয়াল GARCH)
ক্ষেত্র	অর্থমিতি	অর্থমিতি
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1994 / 2008	1991
প্রবর্তক	Zakoian (1994) for TGARCH; Bayesian estimation formalized by Ardia (2008)	Daniel B. Nelson
ধরন	Volatility model with asymmetric threshold and Bayesian inference	Volatility / conditional variance model
মৌলিক উৎস	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.
অপর নাম	Bayesian TGARCH, Bayesian GJR-GARCH, Threshold GARCH with Bayesian estimation, TGARCH-B	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
সম্পর্কিত	6	6
সারসংক্ষেপ	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.