विधियों की तुलना करें

	गार्छ मॉडल (अस्थिरता पूर्वानुमान)	वेक्टर ऑटोरिग्रेशन (VAR) मॉडल
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1986	2005
प्रवर्तक	Tim Bollerslev	Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
प्रकार	Conditional volatility model	Multivariate time-series model
मौलिक स्रोत	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.	Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer.
उपनाम	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)	vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
संबंधित	5	4
सारांश	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.	Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).