So sánh phương pháp

	Mô hình HAR-RV của Biến động Thực hiện	Mô hình GARCH (Dự báo Biến động)
Lĩnh vực	Tài chính	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	2009	1986
Người khởi xướng	Fulvio Corsi	Tim Bollerslev
Loại	Linear time-series regression for volatility	Conditional volatility model
Công trình gốc	Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174–196.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
Tên gọi khác	HAR-RV, heterogeneous autoregressive realized volatility, Corsi HAR model, HAR-RV Modeli (Heterogeneous Autoregressive Realized Volatility)	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Liên quan	5	5
Tóm tắt	The HAR-RV model, introduced by Fulvio Corsi in 2009, forecasts realized volatility by decomposing it into daily, weekly, and monthly components. It is a simple linear regression that mirrors how market participants with different investment horizons react to volatility, and it naturally captures the long-memory behaviour of volatility.	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.