Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Modelo ARCH Não Linear (NARCH)× | Modelo EGARCH (GARCH Exponencial)× | |
|---|---|---|
| Área | Econometria | Econometria |
| Família | Regression model | Regression model |
| Ano de origem≠ | 1992 | 1991 |
| Autor original≠ | Higgins & Bera | Daniel B. Nelson |
| Tipo≠ | Volatility model | Volatility / conditional variance model |
| Fonte seminal≠ | Higgins, M. L., & Bera, A. K. (1992). A class of nonlinear ARCH models. International Economic Review, 33(1), 137-158. DOI ↗ | Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗ |
| Outros nomes | NARCH, Nonlinear ARCH, nonlinear conditional heteroscedasticity model, NARCH model | Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH |
| Relacionados≠ | 4 | 6 |
| Resumo≠ | The Nonlinear ARCH (NARCH) model, introduced by Higgins and Bera (1992), extends Engle's original ARCH framework by allowing the power transformation of volatility to be estimated from the data rather than fixed at two. This flexibility captures a broader class of volatility dynamics observed in financial and macroeconomic time series. | The Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets. |
| ScholarGateConjunto de dados ↗ |
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