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نموذج GARCH (التنبؤ بالتقلب)×نموذج SARIMA×
المجالالاقتصاد القياسيالاقتصاد القياسي
العائلةRegression modelRegression model
سنة النشأة19861970 (first edition); 1976 (revised)
صاحب الطريقةTim BollerslevBox, Jenkins, and Reinsel
النوعConditional volatility modelSeasonal time series model
المصدر التأسيسيBollerslev, 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
الأسماء البديلةGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component
ذات صلة55
الملخصThe 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.
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ScholarGateقارن الطرق: GARCH Model · SARIMA model. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare