Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| DCC-GARCH (Динамична условна корелация)× | Просто и двойно експоненциално изглаждане (SES / Holt)× | |
|---|---|---|
| Област≠ | Финанси | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 2002 | 1957 |
| Създател≠ | Robert F. Engle | Robert G. Brown (SES); Charles C. Holt (linear trend) |
| Тип≠ | Multivariate volatility model | Exponential smoothing forecasting model |
| Основополагащ източник≠ | Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗ | Brown, R. G. (1959). Statistical Forecasting for Inventory Control. McGraw-Hill. link ↗ |
| Други названия | dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon | SES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt) |
| Свързани≠ | 5 | 3 |
| Резюме≠ | DCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step. | 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. |
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