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Tidsvarierande parameter-DCC-GARCH-modell×DCC-GARCH-modellen (Dynamic Conditional Correlation)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår2002 (DCC-GARCH); TVP extension 2010s2002
UpphovspersonRobert F. Engle (DCC-GARCH); TVP extension developed in applied finance literatureRobert F. Engle
TypMultivariate volatility model with time-varying correlationMultivariate volatility model
UrsprungskällaEngle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. DOI ↗Engle, R. F. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. DOI ↗
AliasTVP-DCC-GARCH, time-varying DCC-GARCH, dynamic conditional correlation GARCH with TVP, TVP dynamic conditional correlation modelDCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCC
Närliggande45
SammanfattningThe TVP-DCC-GARCH model extends the Dynamic Conditional Correlation GARCH framework by allowing not only the pairwise correlations but also the underlying model parameters to evolve continuously over time. It captures structural shifts in volatility dynamics and cross-asset dependence, making it essential for financial risk modelling in non-stationary environments.The DCC-GARCH model, introduced by Engle (2002), extends univariate GARCH to capture time-varying correlations between multiple financial time series. It decomposes the multivariate conditional covariance matrix into individual volatility processes and a dynamic correlation matrix, allowing correlations to fluctuate over time while remaining computationally tractable even with many series.
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ScholarGateJämför metoder: Time-varying parameter DCC-GARCH model · DCC-GARCH model. Hämtad 2026-06-18 från https://scholargate.app/sv/compare