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BEKK-GARCH: Multivariat modellering av betingad volatilitet×Vektorautoregressionsmodell (VAR)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår19952005
UpphovspersonRobert Engle & Kenneth KronerLütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
TypMultivariate conditional volatility modelMultivariate time-series model
UrsprungskällaEngle, R. F., & Kroner, K. F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory, 11(1), 122–150. DOI ↗Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
AliasBEKK Model, Baba-Engle-Kraft-Kroner GARCH, Multivariate BEKK, BEKK-ÇARCH Modelivector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Närliggande34
SammanfattningBEKK-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).
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ScholarGateJämför metoder: BEKK-GARCH · VAR Model. Hämtad 2026-06-18 från https://scholargate.app/sv/compare