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Εκθετικό GARCH (EGARCH)×Μοντέλο ARIMA (Autoregressive Integrated Moving Average)×Γενικευμένη Αυτοπαλίνδρομη Υπό Συνθήκη Ετεροσκεδαστικότητα (GARCH)×GJR-GARCH (Ασύμμετρο GARCH)×
ΠεδίοΟικονομετρίαΟικονομετρίαΟικονομετρίαΟικονομετρία
ΟικογένειαRegression modelRegression modelRegression modelRegression model
Έτος προέλευσης1991201519861993
ΔημιουργόςNelsonBox & Jenkins (Box-Jenkins methodology)Tim BollerslevGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
ΤύποςConditional volatility model (asymmetric GARCH variant)Univariate time-series modelConditional volatility modelAsymmetric conditional volatility model
Θεμελιώδης πηγήNelson, 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: 978-1118675021Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327. DOI ↗Glosten, L. R., Jagannathan, R. & Runkle, D. E. (1993). On the Relation Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779-1801. DOI ↗
Εναλλακτικές ονομασίεςexponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCHBox-Jenkins model, ARIMA(p,d,q), ARIMA ModeliGARCH(1,1), generalized ARCH, conditional volatility model, GARCH Modeliasymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
Συναφείς4555
ΣύνοψηEGARCH 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).GARCH is an econometric model for the time-varying volatility of financial time series, introduced by Tim Bollerslev in 1986 as a generalisation of Engle's ARCH model. It treats the conditional variance as a function of past squared shocks and past variances, capturing the volatility clustering seen in returns.GJR-GARCH is a variant of the GARCH conditional-volatility model that captures the asymmetric effect of negative shocks on volatility using an indicator variable. It was introduced by Glosten, Jagannathan and Runkle (1993), with a closely related threshold formulation by Zakoian (1994).
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ScholarGateΣύγκριση μεθόδων: EGARCH · ARIMA · GARCH · GJR-GARCH. Ανακτήθηκε στις 2026-06-20 από https://scholargate.app/el/compare