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Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.

Model ARCH (Autoregresivní podmíněná heteroskedasticita)×Model ARIMA (Autoregressive Integrated Moving Average)×Model GARCH (Predikce volatility)×
OborEkonometrieEkonometrieEkonometrie
RodinaRegression modelRegression modelRegression model
Rok vzniku198219701986
TvůrceRobert F. EngleGeorge Box and Gwilym JenkinsTim Bollerslev
TypConditional volatility modelTime series forecasting modelConditional volatility model
Původní zdrojEngle, 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 ↗Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗
Další názvyARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance modelARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Příbuzné665
ShrnutíThe 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 ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics.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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ScholarGatePorovnat metody: ARCH model · ARIMA model · GARCH Model. Získáno 2026-06-19 z https://scholargate.app/cs/compare