Sammenlign metoder

	BEKK-GARCH: Modellering av multivariat betinget volatilitet	Vektor Autoregression (VAR)-modell
Fagfelt	Økonometri	Økonometri
Familie	Regression model	Regression model
Opprinnelsesår	1995	2005
Opphavsperson	Robert Engle & Kenneth Kroner	Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
Type	Multivariate conditional volatility model	Multivariate time-series model
Opprinnelig kilde	Engle, R. F., & Kroner, K. F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory, 11(1), 122–150.	Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer.
Alias	BEKK Model, Baba-Engle-Kraft-Kroner GARCH, Multivariate BEKK, BEKK-ÇARCH Modeli	vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Relaterte	3	4
Sammendrag	BEKK-GARCH, proposed by Engle and Kroner (1995), is a multivariate GARCH specification that models the time-varying conditional covariance matrix of a system of financial return series. Named after Baba, Engle, Kraft, and Kroner, it is the dominant framework for quantifying volatility spillovers and dynamic correlations across multiple assets or markets simultaneously, widely adopted by financial economists and risk managers since the mid-1990s.	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).