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Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Exponential GARCH (EGARCH)×Modelo GARCH (Previsão de Volatilidade)×GJR-GARCH (GARCH Assimétrico)×
ÁreaEconometriaEconometriaEconometria
FamíliaRegression modelRegression modelRegression model
Ano de origem199119861993
Autor originalNelsonTim BollerslevGlosten, Jagannathan & Runkle (1993); Zakoian (1994)
TipoConditional volatility model (asymmetric GARCH variant)Conditional volatility modelAsymmetric conditional volatility model
Fonte 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 ↗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 ↗
Outros nomesexponential GARCH, Nelson's EGARCH, asymmetric GARCH, EGARCH — Üstel GARCHGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)asymmetric GARCH, leverage GARCH, TGARCH, GJR-GARCH — Asimetrik GARCH (Glosten-Jagannathan-Runkle)
Relacionados455
ResumoEGARCH 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.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.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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ScholarGateComparar métodos: EGARCH · GARCH Model · GJR-GARCH. Recuperado em 2026-06-19 de https://scholargate.app/pt/compare