手法を比較

	非線形移動平均（NMA）モデル	GARCHモデル（ボラティリティ予測）
分野	計量経済学	計量経済学
系統	Regression model	Regression model
提唱年	1978	1986
提唱者	Granger & Andersen (bilinear/NMA framework); Tong (nonlinear time series theory)	Tim Bollerslev
種類	Nonlinear time series model	Conditional volatility model
原典	Granger, C. W. J., & Andersen, A. P. (1978). An Introduction to Bilinear Time Series Models. Vandenhoeck and Ruprecht, Gottingen.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
別名	NMA model, nonlinear moving average, NLMA model, nonlinear MA	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
関連	4	5
概要	The Nonlinear Moving Average (NMA) model extends the classical linear MA model by allowing the current observation to depend on past innovations through a nonlinear function rather than a simple weighted sum. It is used in time series analysis when error shocks transmit to outcomes in an asymmetric or state-dependent fashion.	The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.