Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Модель EGARCH (Експоненційна GARCH)× | Модель GARCH (Прогнозування волатильності)× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1991 | 1986 |
| Автор методу≠ | Daniel B. Nelson | Tim Bollerslev |
| Тип≠ | Volatility / conditional variance model | Conditional volatility model |
| Основоположне джерело≠ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗ |
| Інші назви | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) |
| Пов'язані≠ | 6 | 5 |
| Підсумок≠ | 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. | The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series. |
| ScholarGateНабір даних ↗ |
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