Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| BEKK-GARCH: Daudzdimensiju nosacītās mainīguma modelēšana× | Vektora autoregresijas (VAR) modelis× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1995 | 2005 |
| Autors≠ | Robert Engle & Kenneth Kroner | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Tips≠ | Multivariate conditional volatility model | Multivariate time-series model |
| Pirmavots≠ | 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 ↗ |
| Citi nosaukumi | BEKK Model, Baba-Engle-Kraft-Kroner GARCH, Multivariate BEKK, BEKK-ÇARCH Modeli | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| Saistītās≠ | 3 | 4 |
| Kopsavilkums≠ | 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). |
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