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Робастная модель ARCH×Квантильная регрессия×
ОбластьЭконометрикаЭконометрика
СемействоRegression modelRegression model
Год появления2002–20081978
Автор методаEngle (1982) for ARCH; robust variants developed by Muler, Yohai, and others from the early 2000sKoenker & Bassett
ТипVolatility / conditional heteroscedasticity modelConditional quantile regression
Основополагающий источникEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Другие названияrobust ARCH, outlier-robust ARCH, heavy-tailed ARCH, robust conditional volatility modelconditional quantile regression, regression quantiles, Kantil Regresyon
Связанные65
СводкаThe 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.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Robust ARCH model · Quantile Regression. Получено 2026-06-15 из https://scholargate.app/ru/compare