قارن الطرق

	نموذج GARCH (التنبؤ بالتقلب)	نموذج هار-آر في للتقلب المحقق
المجال	الاقتصاد القياسي	التمويل
العائلة	Regression model	Regression model
سنة النشأة	1986	2009
صاحب الطريقة	Tim Bollerslev	Fulvio Corsi
النوع	Conditional volatility model	Linear time-series regression for volatility
المصدر التأسيسي	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.	Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174–196.
الأسماء البديلة	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)	HAR-RV, heterogeneous autoregressive realized volatility, Corsi HAR model, HAR-RV Modeli (Heterogeneous Autoregressive Realized Volatility)
ذات صلة	5	5
الملخص	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.	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.