방법 비교

	일반화 자기회귀 조건부 이분산성 (GARCH)	DCC-GARCH (동적 조건부 상관관계)	단순 및 이중 지수 평활법 (SES / Holt)
분야	계량경제학	재무학	계량경제학
계열	Regression model	Regression model	Regression model
기원 연도	1986	2002	1957
창시자	Tim Bollerslev	Robert F. Engle	Robert G. Brown (SES); Charles C. Holt (linear trend)
유형	Conditional volatility model	Multivariate volatility model	Exponential smoothing forecasting model
원전	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327.	Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350.	Brown, R. G. (1959). Statistical Forecasting for Inventory Control. McGraw-Hill.
별칭	GARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeli	dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu Korelasyon	SES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt)
관련	5	5	3
요약	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.	DCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step.	Exponential smoothing is a family of basic time-series forecasting models in which each new observation updates a smoothed estimate by a weighting parameter. Simple exponential smoothing (SES), introduced by Robert G. Brown in 1959, forecasts series with a stable level, while Holt's double exponential smoothing, introduced by Charles C. Holt in 1957, adds a trend term using the parameters alpha and beta.