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Model ARCH odporny na wartości odstające×Model EGARCH (Exponential GARCH)×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania2002–20081991
TwórcaEngle (1982) for ARCH; robust variants developed by Muler, Yohai, and others from the early 2000sDaniel B. Nelson
TypVolatility / conditional heteroscedasticity modelVolatility / conditional variance model
Źródło pierwotneEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. DOI ↗
Inne nazwyrobust ARCH, outlier-robust ARCH, heavy-tailed ARCH, robust conditional volatility modelExponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Pokrewne66
PodsumowanieThe Robust ARCH model extends the classical Autoregressive Conditional Heteroscedasticity framework by replacing the standard maximum-likelihood estimator with robust alternatives that downweight or eliminate the influence of outliers. This makes volatility estimates resistant to extreme observations that frequently contaminate financial and macroeconomic time series.The 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.
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  1. v1
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  3. PUBLISHED

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ScholarGatePorównaj metody: Robust ARCH model · EGARCH model. Pobrano 2026-06-17 z https://scholargate.app/pl/compare