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Robusni GARCH model×Kvantilna regresija×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka1986–20131978
TvoracBoudt, Danielsson & Laurent (robust extensions); Bollerslev (standard GARCH, 1986)Koenker & Bassett
VrstaVolatility modelConditional quantile regression
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 ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Drugi naziviRobust GARCH, outlier-robust GARCH, heavy-tail GARCH, contamination-robust volatility modelconditional quantile regression, regression quantiles, Kantil Regresyon
Srodne55
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.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.
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ScholarGateUsporedite metode: Robust GARCH model · Quantile Regression. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare