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Model ARCH (Autoregresywna Heteroskedastyczność Warunkowa)×Model GARCH (Prognozowanie zmienności)×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania19821986
TwórcaRobert F. EngleTim Bollerslev
TypConditional volatility 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 nazwyARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Pokrewne65
PodsumowanieThe 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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ScholarGatePorównaj metody: ARCH model · GARCH Model. Pobrano 2026-06-17 z https://scholargate.app/pl/compare