ScholarGate
Asistent

Uporedite metode

Pregledajte izabrane metode jednu pored druge; redovi koji se razlikuju su istaknuti.

ARIMA model (Autoregresivni integrisani model pokretnih proseka)×GARCH model (predviđanje volatilnosti)×SARIMA model×
OblastEkonometrijaEkonometrijaEkonometrija
PorodicaRegression modelRegression modelRegression model
Godina nastanka197019861970 (first edition); 1976 (revised)
TvoracGeorge Box and Gwilym JenkinsTim BollerslevBox, Jenkins, and Reinsel
TipTime series forecasting modelConditional volatility modelSeasonal time series model
Temeljni izvorBox, 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 ↗Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744
Drugi naziviARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component
Srodne655
SažetakThe 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.SARIMA extends ARIMA by adding seasonal autoregressive and moving-average operators to capture repeating patterns at fixed intervals — such as monthly, quarterly, or annual cycles. Denoted SARIMA(p,d,q)(P,D,Q)s, it is the standard workhorse for univariate seasonal time series forecasting in econometrics, economics, and official statistics.
ScholarGateSkup podataka
  1. v1
  2. 2 Izvori
  3. PUBLISHED
  1. v1
  2. 1 Izvori
  3. PUBLISHED
  1. v1
  2. 2 Izvori
  3. PUBLISHED

Idi na pretragu Preuzmi slajdove

ScholarGateUporedite metode: ARIMA model · GARCH Model · SARIMA model. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare