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Model ARCH (Autoregresywna Heteroskedastyczność Warunkowa)×Model ARMA (Autoregresyjny Model Średniej Ruchomej)×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania19821970
TwórcaRobert F. EngleGeorge E. P. Box and Gwilym M. Jenkins
TypConditional volatility modelTime series model
Źródło pierwotneEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗
Inne nazwyARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
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 ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a moving average part that accounts for past q error terms. It is the foundational framework of the Box-Jenkins methodology for univariate time series modelling and short-run forecasting.
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  3. PUBLISHED

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