방법 비교

	DCC-GARCH (동적 조건부 상관관계)	GJR-GARCH (비대칭 GARCH)	패널 EGARCH
분야	재무학	계량경제학	계량경제학
계열	Regression model	Regression model	Regression model
기원 연도	2002	1993	1991 (EGARCH); panel extensions widely used from 2000s
창시자	Robert F. Engle	Glosten, Jagannathan & Runkle (1993); Zakoian (1994)	Daniel B. Nelson (EGARCH); panel extension by applied econometrics literature
유형	Multivariate volatility model	Asymmetric conditional volatility model	Volatility model
원전	Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350.	Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801.	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.
별칭	dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon	asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)	Panel EGARCH model, panel exponential GARCH, EGARCH for panel data, cross-sectional EGARCH
관련	5	5	4
요약	DCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step.	GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994).	Panel EGARCH extends Nelson's (1991) Exponential GARCH model to a panel setting, allowing conditional variance to evolve asymmetrically over time for each cross-sectional unit. The log specification ensures non-negative variance without parameter constraints, and the leverage term distinguishes whether negative shocks amplify volatility more than positive ones of equal magnitude.