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Robust ARCH-modell×GARCH-modellen (prognostisering av volatilitet)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår2002–20081986
UpphovspersonEngle (1982) for ARCH; robust variants developed by Muler, Yohai, and others from the early 2000sTim Bollerslev
TypVolatility / conditional heteroscedasticity modelConditional volatility model
UrsprungskällaEngle, 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 ↗
Aliasrobust ARCH, outlier-robust ARCH, heavy-tailed ARCH, robust conditional volatility modelGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Närliggande65
SammanfattningThe 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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ScholarGateJämför metoder: Robust ARCH model · GARCH Model. Hämtad 2026-06-17 från https://scholargate.app/sv/compare