Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| BEKK-GARCH: Modelado de Volatilidad Condicional Multivariante× | Modelo de Vectores Autorregresivos (VAR)× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1995 | 2005 |
| Autor original≠ | Robert Engle & Kenneth Kroner | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Tipo≠ | Multivariate conditional volatility model | Multivariate time-series model |
| Fuente seminal≠ | Engle, 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 ↗ |
| Alias | BEKK Model, Baba-Engle-Kraft-Kroner GARCH, Multivariate BEKK, BEKK-ÇARCH Modeli | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| Relacionados≠ | 3 | 4 |
| Resumen≠ | 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). |
| ScholarGateConjunto de datos ↗ |
|
|