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Robustni EGARCH model×Robusni GARCH model×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka20081986–2013
TvoracNelson (1991) for EGARCH; robust adaptation via Muler & Yohai (2008) and related authorsBoudt, Danielsson & Laurent (robust extensions); Bollerslev (standard GARCH, 1986)
VrstaRobust volatility modelVolatility model
Temeljni izvorMuler, N., & Yohai, V. J. (2008). Robust estimates for GARCH models. Journal of Statistical Planning and Inference, 138(10), 2918–2940. DOI ↗Boudt, K., Danielsson, J., & Laurent, S. (2013). Robust forecasting of dynamic conditional correlation GARCH models. International Journal of Forecasting, 29(2), 244–257. DOI ↗
Drugi naziviRobust EGARCH model, outlier-robust EGARCH, robust exponential GARCH, REGARCHRobust GARCH, outlier-robust GARCH, heavy-tail GARCH, contamination-robust volatility model
Srodne65
SažetakRobust EGARCH extends Nelson's (1991) Exponential GARCH model by replacing standard quasi-maximum likelihood estimation with outlier-resistant procedures — typically bounded-influence or M-estimation — so that a small fraction of extreme observations or data errors cannot distort the estimated volatility dynamics or the leverage effect.The 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.
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ScholarGateUsporedite metode: Robust EGARCH · Robust GARCH model. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare