Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Структурный разрыв TGARCH (Threshold GARCH с структурными разрывами)× | Модель EGARCH (Экспоненциальная GARCH)× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1990-1993 | 1991 |
| Автор метода≠ | Lamoureux & Lastrapes (structural breaks in GARCH); Glosten, Jagannathan & Runkle (TGARCH/GJR-GARCH asymmetry) | Daniel B. Nelson |
| Тип≠ | Volatility model | Volatility / conditional variance model |
| Основополагающий источник≠ | Lamoureux, C. G., & Lastrapes, W. D. (1990). Persistence in variance, structural change, and the GARCH model. Journal of Business & Economic Statistics, 8(2), 225-234. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Другие названия | SB-TGARCH, threshold GARCH with structural breaks, GJR-GARCH with structural breaks, break-adjusted TGARCH | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Связанные≠ | 3 | 6 |
| Сводка≠ | Structural Break TGARCH extends the Threshold GARCH (GJR-GARCH) model to accommodate discrete, permanent shifts in the volatility process. By detecting structural breaks and incorporating them — either as regime-specific intercepts or dummy variables — the model separates genuine volatility persistence from spurious persistence induced by ignored regime changes, and preserves the asymmetric leverage effect that characterises equity and financial return data. | 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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