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Model EGARCH (GARCH exponencial)×Model GARCH (Previsió de la Volatilitat)×
CampEconometriaEconometria
FamíliaRegression modelRegression model
Any d'origen19911986
Autor originalDaniel B. NelsonTim Bollerslev
TipusVolatility / conditional variance modelConditional volatility model
Font seminalNelson, 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 ↗
ÀliesExponential GARCH, EGARCH, Nelson EGARCH, log-GARCHGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Relacionats65
ResumThe 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.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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ScholarGateCompara mètodes: EGARCH model · GARCH Model. Recuperat el 2026-06-17 de https://scholargate.app/ca/compare