Linganisha mbinu

	Muundo wa Wastani wa Kusonga Usio na Mfumo (NMA)	Modeli wa GARCH (Utabiri wa Msukosuko)
Nyanja	Ekonometriki	Ekonometriki
Familia	Regression model	Regression model
Mwaka wa asili	1978	1986
Mwanzilishi	Granger & Andersen (bilinear/NMA framework); Tong (nonlinear time series theory)	Tim Bollerslev
Aina	Nonlinear time series model	Conditional volatility model
Chanzo asilia	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.
Majina mbadala	NMA model, nonlinear moving average, NLMA model, nonlinear MA	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Zinazohusiana	4	5
Muhtasari	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.