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DCC-GARCH (동적 조건부 상관관계)×GARCH 모형 (변동성 예측)×
분야재무학계량경제학
계열Regression modelRegression model
기원 연도20021986
창시자Robert F. EngleTim Bollerslev
유형Multivariate volatility modelConditional volatility model
원전Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
별칭dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu KorelasyonGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
관련55
요약DCC-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.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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