Regression modelEconometrics / time series

Robusni TGARCH — Prag GARCH sa robusnom procenom

Robusni TGARCH proširuje model praga GARCH zamenom konvencionalnog cilja maksimalne verodostojnosti proceniteljem koji je otporan na inovacije sa teškim repovima i izuzetne opservacije. On obuhvata asimetrične odgovore volatilnosti — gde negativni šokovi pojačavaju varijansu više nego pozitivni šokovi — dok ostaje pouzdan kada se distribucija prinosa značajno udaljava od normalnosti.

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Izvori

  1. Zakoian, J.-M. (1994). Threshold heteroskedastic models. Journal of Economic Dynamics and Control, 18(5), 931–955. DOI: 10.1016/0165-1889(94)90039-6
  2. Preminger, A., & Storti, G. (2017). Least squares estimation for GARCH (1,1) model with heavy tailed errors. The Econometrics Journal, 20(1), 221–258. link

Kako citirati ovu stranicu

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

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Citirana u

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