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| 傅里叶自回归条件异方差模型 (Fourier ARCH Model)× | 自回归条件异方差 (ARCH) 模型× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2010s | 1982 |
| 提出者≠ | Extends Engle (1982) ARCH framework with Fourier terms following Enders & Lee (2012) | Robert F. Engle |
| 类型≠ | Volatility model with smooth structural change | Conditional volatility model |
| 开创性文献 | 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 ↗ |
| 别名 | Fourier-ARCH, F-ARCH, ARCH with Fourier terms, Fourier smooth transition ARCH | ARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model |
| 相关 | 6 | 6 |
| 摘要≠ | 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. |
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