Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель EGARCH с меняющимися во времени параметрами× | Модель EGARCH (Экспоненциальная GARCH)× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1991–2000s | 1991 |
| Автор метода≠ | Nelson (1991) for EGARCH; TVP extension developed across the 1990s–2000s literature (e.g., Harvey, Engle and co-authors) | Daniel B. Nelson |
| Тип≠ | Conditional volatility model | Volatility / conditional variance model |
| Основополагающий источник | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Другие названия | TVP-EGARCH, time-varying EGARCH, EGARCH with time-varying parameters, dynamic parameter EGARCH | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Связанные≠ | 3 | 6 |
| Сводка≠ | The TVP-EGARCH model extends Nelson's (1991) Exponential GARCH by allowing the volatility equation's parameters — including the leverage effect coefficient — to drift continuously over time. This makes it possible to capture structural change and regime evolution in financial return volatility without imposing a fixed break date. | The Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets. |
| ScholarGateНабор данных ↗ |
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