方法对比
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| 简单和双指数平滑 (SES / Holt)× | 广义自回归条件异方差模型 (GARCH)× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1957 | 1986 |
| 提出者≠ | Robert G. Brown (SES); Charles C. Holt (linear trend) | Tim Bollerslev |
| 类型≠ | Exponential smoothing forecasting model | Conditional volatility model |
| 开创性文献≠ | 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 ↗ |
| 别名 | 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 |
| 相关≠ | 3 | 5 |
| 摘要≠ | 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. |
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