Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Modelo ARCH Não Linear (NARCH)× | Modelo ARCH (Autoregressive Conditional Heteroskedasticity)× | |
|---|---|---|
| Área | Econometria | Econometria |
| Família | Regression model | Regression model |
| Ano de origem≠ | 1992 | 1982 |
| Autor original≠ | Higgins & Bera | Robert F. Engle |
| Tipo≠ | Volatility model | Conditional volatility model |
| Fonte seminal≠ | Higgins, M. L., & Bera, A. K. (1992). A class of nonlinear ARCH models. International Economic Review, 33(1), 137-158. DOI ↗ | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ |
| Outros nomes | NARCH, Nonlinear ARCH, nonlinear conditional heteroscedasticity model, NARCH model | ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model |
| 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 ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering. |
| ScholarGateConjunto de dados ↗ |
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