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गार्छ मॉडल (अस्थिरता पूर्वानुमान)×SARIMA मॉडल×
क्षेत्रअर्थमितिअर्थमिति
परिवारRegression modelRegression model
उद्भव वर्ष19861970 (first edition); 1976 (revised)
प्रवर्तकTim BollerslevBox, Jenkins, and Reinsel
प्रकारConditional volatility modelSeasonal time series model
मौलिक स्रोतBollerslev, 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
उपनामGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component
संबंधित55
सारांशThe 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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