Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| BEKK-GARCH: Daudzdimensiju nosacītās mainīguma modelēšana× | DCC-GARCH (dinamiskā nosacītā korelācija)× | |
|---|---|---|
| Nozare≠ | Ekonometrija | Finanses |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1995 | 2002 |
| Autors≠ | Robert Engle & Kenneth Kroner | Robert F. Engle |
| Tips≠ | Multivariate conditional volatility model | Multivariate volatility model |
| Pirmavots≠ | Engle, R. F., & Kroner, K. F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory, 11(1), 122–150. DOI ↗ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗ |
| Citi nosaukumi | BEKK Model, Baba-Engle-Kraft-Kroner GARCH, Multivariate BEKK, BEKK-ÇARCH Modeli | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon |
| Saistītās≠ | 3 | 5 |
| 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. | DCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step. |
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