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푸리에 ARCH 모형×GARCH 모형 (변동성 예측)×
분야계량경제학계량경제학
계열Regression modelRegression model
기원 연도2010s1986
창시자Extends Engle (1982) ARCH framework with Fourier terms following Enders & Lee (2012)Tim Bollerslev
유형Volatility model with smooth structural changeConditional volatility model
원전Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
별칭Fourier-ARCH, F-ARCH, ARCH with Fourier terms, Fourier smooth transition ARCHGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
관련65
요약The 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 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.
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