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مدل GARCH (پیش‌بینی نوسانات)×مدل خودرگرسیون برداری (VAR)×
حوزهاقتصادسنجیاقتصادسنجی
خانوادهRegression modelRegression model
سال پیدایش19862005
پدیدآورTim BollerslevLütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
نوعConditional volatility modelMultivariate time-series model
منبع بنیادینBollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI ↗Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
نام‌های دیگرGARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
مرتبط54
خلاصهThe 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.Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).
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ScholarGateمقایسهٔ روش‌ها: GARCH Model · VAR Model. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare