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Ikke-lineær EGARCH-model×GARCH-model (volatilitetsprognoser)×
FagområdeØkonometriØkonometri
FamilieRegression modelRegression model
Oprindelsesår19911986
OphavspersonDaniel B. NelsonTim Bollerslev
TypeConditional volatility modelConditional volatility model
Oprindelig kildeNelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
AliasserNL-EGARCH, nonlinear exponential GARCH, asymmetric EGARCH, NEGARCHGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Relaterede55
ResuméThe Nonlinear EGARCH model extends Nelson's (1991) Exponential GARCH by allowing the news impact function to take a flexible nonlinear form, capturing asymmetric and nonlinear responses of conditional volatility to past shocks. It is widely used in financial econometrics to model leverage effects and complex volatility dynamics in asset returns.The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, introduced by Tim Bollerslev in 1986, models the time-varying conditional variance of a financial time series. It captures volatility clustering and the ARCH effect, and is the standard tool for estimating risk and volatility in return series.
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ScholarGateSammenlign metoder: Nonlinear EGARCH model · GARCH Model. Hentet 2026-06-17 fra https://scholargate.app/da/compare