Сравнение на методи

	Robust ARCH Модел	Квантилна регресия
Област	Иконометрия	Иконометрия
Семейство	Regression model	Regression model
Година на възникване	2002–2008	1978
Създател	Engle (1982) for ARCH; robust variants developed by Muler, Yohai, and others from the early 2000s	Koenker & Bassett
Тип	Volatility / conditional heteroscedasticity model	Conditional quantile regression
Основополагащ източник	Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Други названия	robust ARCH, outlier-robust ARCH, heavy-tailed ARCH, robust conditional volatility model	conditional quantile regression, regression quantiles, Kantil Regresyon
Свързани	6	5
Резюме	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.	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.