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DCC-GARCH (Uhusiano Unaobadilika wa Masharti)×Mfumo wa ARIMA (Autoregressive Integrated Moving Average)×
NyanjaFedhaEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili20022015
MwanzilishiRobert F. EngleBox & Jenkins (Box-Jenkins methodology)
AinaMultivariate volatility modelUnivariate time-series model
Chanzo asiliaEngle, 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: 978-1118675021
Majina mbadaladynamic conditional correlation, Engle DCC, multivariate GARCH, DCC-GARCH — Dinamik Koşullu KorelasyonBox-Jenkins model, ARIMA(p,d,q), ARIMA Modeli
Zinazohusiana55
MuhtasariDCC-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).
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  3. PUBLISHED

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ScholarGateLinganisha mbinu: DCC-GARCH · ARIMA. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare