Сравнение на методи

	Устойчив EGARCH модел	Модел GARCH (Прогнозиране на волатилността)
Област	Иконометрия	Иконометрия
Семейство	Regression model	Regression model
Година на възникване	2008	1986
Създател	Nelson (1991) for EGARCH; robust adaptation via Muler & Yohai (2008) and related authors	Tim Bollerslev
Тип	Robust volatility model	Conditional volatility model
Основополагащ източник	Muler, N., & Yohai, V. J. (2008). Robust estimates for GARCH models. Journal of Statistical Planning and Inference, 138(10), 2918–2940.	Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307–327.
Други названия	Robust EGARCH model, outlier-robust EGARCH, robust exponential GARCH, REGARCH	GARCH, GARCH(1,1), conditional volatility model, GARCH Modeli (Oynaklık Tahmini)
Свързани	6	5
Резюме	Robust EGARCH extends Nelson's (1991) Exponential GARCH model by replacing standard quasi-maximum likelihood estimation with outlier-resistant procedures — typically bounded-influence or M-estimation — so that a small fraction of extreme observations or data errors cannot distort the estimated volatility dynamics or the leverage effect.	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.