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Robusni GARCH model×ARCH model (autoregresivna uslovna heteroskedastičnost)×
OblastEkonometrijaEkonometrija
PorodicaRegression modelRegression model
Godina nastanka1986–20131982
TvoracBoudt, Danielsson & Laurent (robust extensions); Bollerslev (standard GARCH, 1986)Robert F. Engle
TipVolatility modelConditional volatility model
Temeljni izvorBoudt, K., Danielsson, J., & Laurent, S. (2013). Robust forecasting of dynamic conditional correlation GARCH models. International Journal of Forecasting, 29(2), 244–257. DOI ↗Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. DOI ↗
Drugi naziviRobust GARCH, outlier-robust GARCH, heavy-tail GARCH, contamination-robust volatility modelARCH, autoregressive conditional heteroskedasticity, Engle ARCH, conditional variance model
Srodne56
SažetakThe Robust GARCH model extends the classical GARCH framework to handle outliers and heavy-tailed innovations that commonly appear in financial return series. By down-weighting extreme observations through a robust innovation term, it produces more reliable volatility forecasts when data contain jumps, crises, or other anomalies that would otherwise distort standard GARCH estimates.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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ScholarGateUporedite metode: Robust GARCH model · ARCH model. Preuzeto 2026-06-17 sa https://scholargate.app/sr/compare