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Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.

DCC-GARCH (Dynamic Conditional Correlation)×Modelul ARIMA (Autoregresiv Integrat cu Medii Mobile)×GARCH Exponențial (EGARCH)×
DomeniuFinanțeEconometrieEconometrie
FamilieRegression modelRegression modelRegression model
Anul apariției200220151991
Autorul originalRobert F. EngleBox & Jenkins (Box-Jenkins methodology)Nelson
TipMultivariate volatility modelUnivariate time-series modelConditional volatility model (asymmetric GARCH variant)
Sursa seminalăEngle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business & Economic Statistics, 20(3), 339-350. DOI ↗Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Nelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. DOI ↗
Denumiri alternativedynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu KorelasyonBox-Jenkins model, ARIMA(p,d,q), ARIMA Modeliexponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCH
Înrudite554
RezumatDCC-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.ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).EGARCH is an asymmetric GARCH variant, introduced by Nelson in 1991, that models the leverage effect in which bad news raises volatility more than good news of the same size. It captures the negative-shock asymmetry of financial return series by modelling the logarithm of the conditional variance.
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ScholarGateCompară metode: DCC-GARCH · ARIMA · EGARCH. Preluat la 2026-06-19 de pe https://scholargate.app/ro/compare