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Modelo EGARCH (GARCH Exponencial)×Modelo ARCH (Autoregressive Conditional Heteroskedasticity)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem19911982
Autor originalDaniel B. NelsonRobert F. Engle
TipoVolatility / conditional variance modelConditional volatility model
Fonte seminalNelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
Outros nomesExponential GARCH, EGARCH, Nelson EGARCH, log-GARCHARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Relacionados66
ResumoThe 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 ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.
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  1. v1
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ScholarGateComparar métodos: EGARCH model · ARCH model. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare