Сравнение на методи
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| Robust ARCH Модел× | Модел EGARCH (Експоненциален GARCH)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 2002–2008 | 1991 |
| Създател≠ | Engle (1982) for ARCH; robust variants developed by Muler, Yohai, and others from the early 2000s | Daniel B. Nelson |
| Тип≠ | Volatility / conditional heteroscedasticity model | Volatility / conditional variance model |
| Основополагащ източник≠ | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Други названия | robust ARCH, outlier-robust ARCH, heavy-tailed ARCH, robust conditional volatility model | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Свързани | 6 | 6 |
| Резюме≠ | 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 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 от данни ↗ |
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