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| Eteroschedasticità Condizionale Autoregressiva Generalizzata (GARCH)× | DCC-GARCH (Correlazione Condizionale Dinamica)× | Smorzamento Esponenziale Semplice e Doppio (SES / Holt)× | |
|---|---|---|---|
| Campo≠ | Econometria | Finanza | Econometria |
| Famiglia | Regression model | Regression model | Regression model |
| Anno di origine≠ | 1986 | 2002 | 1957 |
| Ideatore≠ | Tim Bollerslev | Robert F. Engle | Robert G. Brown (SES); Charles C. Holt (linear trend) |
| Tipo≠ | Conditional volatility model | Multivariate volatility model | Exponential smoothing forecasting model |
| Fonte seminale≠ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗ | 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 ↗ |
| Alias | GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli | 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) |
| Correlati≠ | 5 | 5 | 3 |
| Sintesi≠ | 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. | 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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