Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| BEKK-GARCH: Моделирование многомерной условной волатильности× | DCC-GARCH (Dynamic Conditional Correlation)× | |
|---|---|---|
| Область≠ | Эконометрика | Финансы |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1995 | 2002 |
| Автор метода≠ | Robert Engle & Kenneth Kroner | Robert F. Engle |
| Тип≠ | Multivariate conditional volatility model | Multivariate volatility model |
| Основополагающий источник≠ | 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 ↗ |
| Другие названия | BEKK Model, Baba-Engle-Kraft-Kroner GARCH, Multivariate BEKK, BEKK-ÇARCH Modeli | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon |
| Связанные≠ | 3 | 5 |
| Сводка≠ | 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. |
| ScholarGateНабор данных ↗ |
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