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Робастная модель ARCH×Модель ARCH (авторегрессионная условная гетероскедастичность)×
ОбластьЭконометрикаЭконометрика
СемействоRegression modelRegression model
Год появления2002–20081982
Автор методаEngle (1982) for ARCH; robust variants developed by Muler, Yohai, and others from the early 2000sRobert F. Engle
ТипVolatility / conditional heteroscedasticity modelConditional volatility model
Основополагающий источникEngle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
Другие названияrobust ARCH, outlier-robust ARCH, heavy-tailed ARCH, robust conditional volatility modelARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Связанные66
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.The ARCH model, introduced by Robert Engle in 1982, captures time-varying volatility in financial and macroeconomic time series. It models the conditional variance of today's error as a function of past squared errors, explaining why volatile periods cluster together — a phenomenon known as volatility clustering.
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 · ARCH model. Получено 2026-06-17 из https://scholargate.app/ru/compare