방법 비교

	TGARCH 모형 (Threshold GARCH)	Vector Autoregression (VAR)
분야	계량경제학	계량경제학
계열	Regression model	Regression model
기원 연도	1993-1994	1980
창시자	Zakoian (1994); Glosten, Jagannathan & Runkle (1993)	Christopher A. Sims
유형	Asymmetric volatility model	Multivariate time-series model
원전	Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931-955.	Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.
별칭	Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH	VAR, VAR model, vector autoregressive model, multivariate autoregression
관련	6	5
요약	The Threshold GARCH (TGARCH) model extends the standard GARCH framework by allowing positive and negative return shocks to have asymmetric effects on conditional variance. Negative shocks — bad news — typically amplify volatility more than positive shocks of the same magnitude, a stylised fact known as the leverage effect. TGARCH captures this asymmetry through a threshold indicator that switches on when the previous period's shock was negative.	Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.