Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| BEKK-GARCH: Багатовимірне моделювання умовної волатильності× | Модель векторної авторегресії (VAR)× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1995 | 2005 |
| Автор методу≠ | Robert Engle & Kenneth Kroner | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Тип≠ | Multivariate conditional volatility model | Multivariate time-series model |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви | BEKK Model, Baba-Engle-Kraft-Kroner GARCH, Multivariate BEKK, BEKK-ÇARCH Modeli | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| Пов'язані≠ | 3 | 4 |
| Підсумок≠ | 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). |
| ScholarGateНабір даних ↗ |
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