Regression modelEconometrics / time series

Robusni GARCH model

Robusni GARCH model proširuje klasični GARCH okvir za obradu ekstremnih vrednosti (outliera) i inovacija sa teškim repovima koje se često javljaju u finansijskim serijama prinosa. Smanjenjem uticaja ekstremnih opservacija putem robusnog inovacionog člana, on proizvodi pouzdanije prognoze volatilnosti kada podaci sadrže skokove, krize ili druge anomalije koje bi inače iskrivile standardne GARCH procene.

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Izvori

  1. Boudt, K., Danielsson, J., & Laurent, S. (2013). Robust forecasting of dynamic conditional correlation GARCH models. International Journal of Forecasting, 29(2), 244–257. DOI: 10.1016/j.ijforecast.2012.06.003
  2. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327. DOI: 10.1016/0304-4076(86)90063-1

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Robust Generalized Autoregressive Conditional Heteroscedasticity Model. ScholarGate. https://scholargate.app/sr/econometrics/robust-garch-model

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ScholarGateRobust GARCH model (Robust Generalized Autoregressive Conditional Heteroscedasticity Model). Preuzeto 2026-06-15 sa https://scholargate.app/sr/econometrics/robust-garch-model · Skup podataka: https://doi.org/10.5281/zenodo.20539026