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Model ARCH odporny na wartości odstające×Model GARCH (Prognozowanie zmienności)×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania2002–20081986
TwórcaEngle (1982) for ARCH; robust variants developed by Muler, Yohai, and others from the early 2000sTim Bollerslev
TypVolatility / conditional heteroscedasticity modelConditional volatility model
Źródło pierwotneEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
Inne nazwyrobust ARCH, outlier-robust ARCH, heavy-tailed ARCH, robust conditional volatility modelGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Pokrewne65
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 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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ScholarGatePorównaj metody: Robust ARCH model · GARCH Model. Pobrano 2026-06-17 z https://scholargate.app/pl/compare