ScholarGate
Asistent

Usporedite metode

Pregledajte odabrane metode jednu uz drugu; retci koji se razlikuju su istaknuti.

Model DCC-GARCH (Dinamička uvjetna korelacija)×EGARCH model (eksponencijalni GARCH)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka20021991
TvoracRobert F. EngleDaniel B. Nelson
VrstaMultivariate volatility modelVolatility / conditional variance model
Temeljni izvorEngle, 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 ↗Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗
Drugi naziviDCC-GARCH, Dynamic Conditional Correlation GARCH, Engle DCC model, multivariate DCCExponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Srodne56
SažetakThe 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.The Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets.
ScholarGateSkup podataka
  1. v1
  2. 2 Izvori
  3. PUBLISHED
  1. v1
  2. 2 Izvori
  3. PUBLISHED

Idi na pretraživanje Preuzmi prezentaciju

ScholarGateUsporedite metode: DCC-GARCH model · EGARCH model. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare