Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Netezire Exponențială Simplă și Dublă (SES / Holt)× | Autoregresivul Condiționat Generalizat cu Heteroscedasticitate (GARCH)× | |
|---|---|---|
| Domeniu | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 1957 | 1986 |
| Autorul original≠ | Robert G. Brown (SES); Charles C. Holt (linear trend) | Tim Bollerslev |
| Tip≠ | Exponential smoothing forecasting model | Conditional volatility model |
| Sursa seminală≠ | Brown, R. G. (1959). Statistical Forecasting for Inventory Control. McGraw-Hill. link ↗ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗ |
| Denumiri alternative | SES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt) | GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli |
| Înrudite≠ | 3 | 5 |
| Rezumat≠ | 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. | GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns. |
| ScholarGateSet de date ↗ |
|
|