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Robustais ARCH modelis×Autoregresīvās nosacītās heteroskedastiskuma (ARCH) modelis×
NozareEkonometrijaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads2002–20081982
AutorsEngle (1982) for ARCH; robust variants developed by Muler, Yohai, and others from the early 2000sRobert F. Engle
TipsVolatility / conditional heteroscedasticity modelConditional volatility model
PirmavotsEngle, 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 ↗
Citi nosaukumirobust ARCH, outlier-robust ARCH, heavy-tailed ARCH, robust conditional volatility modelARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Saistītās66
KopsavilkumsThe 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.
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ScholarGateSalīdzināt metodes: Robust ARCH model · ARCH model. Izgūts 2026-06-17 no https://scholargate.app/lv/compare