Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Експоненциален GARCH (EGARCH)× | Просто и двойно експоненциално изглаждане (SES / Holt)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1991 | 1957 |
| Създател≠ | Nelson | Robert G. Brown (SES); Charles C. Holt (linear trend) |
| Тип≠ | Conditional volatility model (asymmetric GARCH variant) | Exponential smoothing forecasting model |
| Основополагащ източник≠ | Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗ | Brown, R. G. (1959). Statistical Forecasting for Inventory Control. McGraw-Hill. link ↗ |
| Други названия | exponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH | SES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt) |
| Свързани≠ | 4 | 3 |
| Резюме≠ | EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance. | Exponential smoothing is a family of basic time-series forecasting models in which each new observation updates a smoothed estimate by a weighting parameter. Simple exponential smoothing (SES), introduced by Robert G. Brown in 1959, forecasts series with a stable level, while Holt's double exponential smoothing, introduced by Charles C. Holt in 1957, adds a trend term using the parameters alpha and beta. |
| ScholarGateНабор от данни ↗ |
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