So sánh phương pháp

	Mô hình GARCH phi tuyến	Mô hình ARCH (Autoregressive Conditional Heteroskedasticity)
Lĩnh vực	Kinh tế lượng	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	1991-1993	1982
Người khởi xướng	Glosten, Jagannathan & Runkle; Nelson (1991) for EGARCH	Robert F. Engle
Loại	Volatility model	Conditional volatility model
Công trình gốc	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.
Tên gọi khác	NL-GARCH, asymmetric GARCH, GJR-GARCH, nonlinear volatility model	ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Liên quan	6	6
Tóm tắt	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.