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Autoregressiv modell för betingad heteroskedasticitet (ARCH-modell)×GARCH-modellen (prognostisering av volatilitet)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår19821986
UpphovspersonRobert F. EngleTim Bollerslev
TypConditional volatility 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 ↗
AliasARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Närliggande65
SammanfattningThe 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.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: ARCH model · GARCH Model. Hämtad 2026-06-17 från https://scholargate.app/sv/compare