手法を比較

	ベイズEGARCHモデル	EGARCHモデル（指数型GARCH）
分野	計量経済学	計量経済学
系統	Regression model	Regression model
提唱年	1991 (EGARCH); 2000s (Bayesian estimation)	1991
提唱者	Nelson (1991) for EGARCH; Bayesian inference via MCMC developed from early 2000s	Daniel B. Nelson
種類	Volatility model with Bayesian inference	Volatility / conditional variance model
原典	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.
別名	Bayesian EGARCH model, Bayesian Exponential GARCH, EGARCH with Bayesian estimation, B-EGARCH	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
関連	6	6
概要	The Bayesian EGARCH model combines Nelson's (1991) Exponential GARCH specification — which models the log of conditional variance and captures the leverage effect — with Bayesian posterior inference via Markov Chain Monte Carlo (MCMC). This allows full uncertainty quantification of all volatility parameters, including the asymmetry coefficient, without requiring large-sample normality of the estimates.	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.