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DCC-GARCH (동적 조건부 상관관계)×패널 EGARCH×패널 데이터 고정 효과 모형×
분야재무학계량경제학계량경제학
계열Regression modelRegression modelRegression model
기원 연도20021991 (EGARCH); panel extensions widely used from 2000s2014
창시자Robert F. EngleDaniel B. Nelson (EGARCH); panel extension by applied econometrics literatureHsiao (textbook treatment); within transformation of panel data
유형Multivariate volatility modelVolatility modelPanel data regression
원전Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗
별칭dynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu KorelasyonPanel EGARCH model, panel exponential GARCH, EGARCH for panel data, cross-sectional EGARCHfixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
관련545
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.Panel EGARCH extends Nelson's (1991) Exponential GARCH model to a panel setting, allowing conditional variance to evolve asymmetrically over time for each cross-sectional unit. The log specification ensures non-negative variance without parameter constraints, and the leverage term distinguishes whether negative shocks amplify volatility more than positive ones of equal magnitude.The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).
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ScholarGate방법 비교: DCC-GARCH · Panel EGARCH · Panel Fixed Effects. 2026-06-19에 다음에서 검색함: https://scholargate.app/ko/compare