Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo ARCH de Fourier× | Modelo ARCH (Heterocedasticidad Autoregresiva Condicional)× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 2010s | 1982 |
| Autor original≠ | Extends Engle (1982) ARCH framework with Fourier terms following Enders & Lee (2012) | Robert F. Engle |
| Tipo≠ | Volatility model with smooth structural change | Conditional volatility model |
| Fuente seminal | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ | Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗ |
| Alias | Fourier-ARCH, F-ARCH, ARCH with Fourier terms, Fourier smooth transition ARCH | ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model |
| Relacionados | 6 | 6 |
| Resumen≠ | The Fourier ARCH model extends the classical ARCH framework by incorporating trigonometric (Fourier) terms into the conditional variance equation. This allows the model to capture smooth, gradual shifts in volatility dynamics over time without assuming abrupt structural breaks, making it well-suited for long financial or macroeconomic time series subject to slowly evolving regime changes. | 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 datos ↗ |
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