Сравнение методов

	Робастная модель ARCH	Модель EGARCH (Экспоненциальная GARCH)
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	2002–2008	1991
Автор метода	Engle (1982) for ARCH; robust variants developed by Muler, Yohai, and others from the early 2000s	Daniel B. Nelson
Тип	Volatility / conditional heteroscedasticity model	Volatility / conditional variance model
Основополагающий источник	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370.
Другие названия	robust ARCH, outlier-robust ARCH, heavy-tailed ARCH, robust conditional volatility model	Exponential GARCH, EGARCH, Nelson EGARCH, log-GARCH
Связанные	6	6
Сводка	The Robust ARCH model extends the classical Autoregressive Conditional Heteroscedasticity framework by replacing the standard maximum-likelihood estimator with robust alternatives that downweight or eliminate the influence of outliers. This makes volatility estimates resistant to extreme observations that frequently contaminate financial and macroeconomic time series.	The Exponential GARCH (EGARCH) model, introduced by Nelson (1991), extends the standard GARCH framework by modelling the logarithm of conditional variance. This ensures variance is always positive without parameter constraints and, crucially, allows negative and positive shocks to have asymmetric effects on volatility — capturing the well-known leverage effect in financial markets.