Võrdle meetodeid

	Bayes'i autoregressiivse tinglikult heteroskedastilisuse (ARCH) mudel	Bayesian TGARCH (Bayes' meetodiga lähendatud lävepakkega GARCH)
Valdkond	Ökonomeetria	Ökonomeetria
Perekond	Regression model	Regression model
Tekkeaasta	1982 (ARCH); 1989 (Bayesian estimation)	1994 / 2008
Looja	Robert F. Engle (ARCH, 1982); Bayesian treatment: John Geweke (1989)	Zakoian (1994) for TGARCH; Bayesian estimation formalized by Ardia (2008)
Tüüp	Volatility model with Bayesian inference	Volatility model with asymmetric threshold and Bayesian inference
Algallikas	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.
Rööpnimetused	Bayesian ARCH, ARCH with Bayesian estimation, Bayesian conditional heteroskedasticity model, B-ARCH	Bayesian TGARCH, Bayesian GJR-GARCH, Threshold GARCH with Bayesian estimation, TGARCH-B
Seotud	6	6
Kokkuvõte	The Bayesian ARCH model estimates Engle's Autoregressive Conditional Heteroskedasticity specification within a Bayesian framework. Instead of maximising a likelihood, it combines a prior distribution over the volatility parameters with the data likelihood to obtain a full posterior distribution, providing richer uncertainty quantification than classical maximum-likelihood ARCH.	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.