방법 비교

	ARCH 모형 (자기회귀 조건부 이분산성)	TGARCH 모형 (Threshold GARCH)
분야	계량경제학	계량경제학
계열	Regression model	Regression model
기원 연도	1982	1993-1994
창시자	Robert F. Engle	Zakoian (1994); Glosten, Jagannathan & Runkle (1993)
유형	Conditional volatility model	Asymmetric volatility model
원전	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.
별칭	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model	Threshold GARCH, TGARCH, GJR-GARCH, asymmetric GARCH
관련	6	6
요약	The ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.	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.