방법 비교

	BEKK-GARCH: 다변량 조건부 변동성 모형화	Vector Autoregression (VAR) Model
분야	계량경제학	계량경제학
계열	Regression model	Regression model
기원 연도	1995	2005
창시자	Robert Engle & Kenneth Kroner	Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
유형	Multivariate conditional volatility model	Multivariate time-series model
원전	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.
별칭	BEKK Model, Baba-Engle-Kraft-Kroner GARCH, Multivariate BEKK, BEKK-ÇARCH Modeli	vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
관련	3	4
요약	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).