Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Modelo EGARCH de Parâmetros Variantes no Tempo× | Modelo GARCH (Previsão de Volatilidade)× | |
|---|---|---|
| Área | Econometria | Econometria |
| Família | Regression model | Regression model |
| Ano de origem≠ | 1991–2000s | 1986 |
| Autor original≠ | Nelson (1991) for EGARCH; TVP extension developed across the 1990s–2000s literature (e.g., Harvey, Engle and co-authors) | Tim Bollerslev |
| Tipo | Conditional volatility model | Conditional volatility model |
| Fonte seminal≠ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ | Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗ |
| Outros nomes | TVP-EGARCH, time-varying EGARCH, EGARCH with time-varying parameters, dynamic parameter EGARCH | GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini) |
| Relacionados≠ | 3 | 5 |
| Resumo≠ | The TVP-EGARCH model extends Nelson's (1991) Exponential GARCH by allowing the volatility equation's parameters — including the leverage effect coefficient — to drift continuously over time. This makes it possible to capture structural change and regime evolution in financial return volatility without imposing a fixed break date. | The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series. |
| ScholarGateConjunto de dados ↗ |
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