ScholarGate
Asistent

Usporedite metode

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

EGARCH (Exponential GARCH)×Model ARIMA (Autoregresivni integrirani pokretni prosjek)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka19912015
TvoracNelsonBox & Jenkins (Box-Jenkins methodology)
VrstaConditional volatility model (asymmetric GARCH variant)Univariate time-series model
Temeljni izvorNelson, D. B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59(2), 347-370. 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
Drugi naziviexponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCHBox-Jenkins model, ARIMA(p,d,q), ARIMA Modeli
Srodne45
SažetakEGARCH 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.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).
ScholarGateSkup podataka
  1. v1
  2. 2 Izvori
  3. PUBLISHED
  1. v1
  2. 1 Izvori
  3. PUBLISHED

Idi na pretraživanje Preuzmi prezentaciju

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