Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| DCC-GARCH (Dynamic Conditional Correlation)× | Экспоненциальный GARCH (EGARCH)× | |
|---|---|---|
| Область≠ | Финансы | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 2002 | 1991 |
| Автор метода≠ | Robert F. Engle | Nelson |
| Тип≠ | Multivariate volatility model | Conditional volatility model (asymmetric GARCH variant) |
| Основополагающий источник≠ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗ | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ |
| Другие названия | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH |
| Связанные≠ | 5 | 4 |
| Сводка≠ | 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. | EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance. |
| ScholarGateНабор данных ↗ |
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