방법 비교

	비선형 GARCH 모형	ARCH 모형 (자기회귀 조건부 이분산성)
분야	계량경제학	계량경제학
계열	Regression model	Regression model
기원 연도	1991-1993	1982
창시자	Glosten, Jagannathan & Runkle; Nelson (1991) for EGARCH	Robert F. Engle
유형	Volatility model	Conditional volatility model
원전	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. Journal of Finance, 48(5), 1779-1801.	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.
별칭	NL-GARCH, asymmetric GARCH, GJR-GARCH, nonlinear volatility model	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
관련	6	6
요약	The Nonlinear GARCH model extends the standard GARCH framework to capture asymmetric and nonlinear responses of conditional volatility to past shocks. It allows negative returns (bad news) to amplify volatility more than positive returns of equal magnitude, a phenomenon known as the leverage effect, which is empirically pervasive in financial markets.	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.