방법 비교

	Fourier EGARCH: 부드러운 구조적 변화를 포함하는 변동성 모델링	일반화 자기회귀 조건부 이분산성 (GARCH)
분야	계량경제학	계량경제학
계열	Regression model	Regression model
기원 연도	2010s	1986
창시자	Extension of Nelson (1991) EGARCH using Fourier approximation frameworks	Tim Bollerslev
유형	Volatility model with smooth structural breaks	Conditional volatility model
원전	Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574-599.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
별칭	Fourier-EGARCH, F-EGARCH, Fourier exponential GARCH, smooth structural break EGARCH	GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli
관련	3	5
요약	Fourier EGARCH extends Nelson's (1991) Exponential GARCH model by embedding Fourier trigonometric terms in the conditional variance equation to capture smooth, gradual shifts in the unconditional variance level over time. This allows the model to handle structural breaks in volatility without requiring prior knowledge of their timing or number.	GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.