Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Robust ARCH Model× | Модель GARCH (Прогнозування волатильності)× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2002–2008 | 1986 |
| Автор методу≠ | Engle (1982) for ARCH; robust variants developed by Muler, Yohai, and others from the early 2000s | Tim Bollerslev |
| Тип≠ | Volatility / conditional heteroscedasticity model | Conditional volatility model |
| Основоположне джерело≠ | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗ |
| Інші назви | robust ARCH, outlier-robust ARCH, heavy-tailed ARCH, robust conditional volatility model | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) |
| Пов'язані≠ | 6 | 5 |
| Підсумок≠ | The Robust ARCH model extends the classical Autoregressive Conditional Heteroscedasticity framework by replacing the standard maximum-likelihood estimator with robust alternatives that downweight or eliminate the influence of outliers. This makes volatility estimates resistant to extreme observations that frequently contaminate financial and macroeconomic time series. | 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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