Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель EGARCH со структурными разрывами× | Модель DCC-GARCH (динамическая условная корреляция)× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1990–1991 | 2002 |
| Автор метода≠ | Nelson (1991) for EGARCH; Lamoureux and Lastrapes (1990) for break-augmented GARCH variants | Robert F. Engle |
| Тип≠ | Volatility model with structural breaks | Multivariate volatility model |
| Основополагающий источник≠ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ | Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. DOI ↗ |
| Другие названия | SB-EGARCH, EGARCH with regime shifts, break-adjusted EGARCH, structural change EGARCH | DCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC |
| Связанные | 5 | 5 |
| Сводка≠ | Structural Break EGARCH combines Nelson's Exponential GARCH framework with explicit allowance for one or more structural breaks in the volatility process. By letting the intercept and persistence parameters of the log-variance equation shift at detected break dates, the model avoids the spurious long-memory and inflated persistence that standard EGARCH suffers when the data contain regime changes. | The DCC-GARCH model, introduced by Engle (2002), extends univariate GARCH to capture time-varying correlations between multiple financial time series. It decomposes the multivariate conditional covariance matrix into individual volatility processes and a dynamic correlation matrix, allowing correlations to fluctuate over time while remaining computationally tractable even with many series. |
| ScholarGateНабор данных ↗ |
|
|