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Robust TGARCH — Tærskel-GARCH med robust estimering

Robust TGARCH udvider Threshold GARCH-modellen ved at erstatte det konventionelle maximum likelihood-mål med en estimator, der er modstandsdygtig over for innovationer med tunge haler og ekstreme observationer. Den indfanger asymmetriske volatilitetsresponser — hvor negative chok forstørrer variansen mere end positive chok — samtidig med at den forbliver pålidelig, når afkastfordelingen afviger markant fra normalfordelingen.

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Kilder

  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

Sådan citerer du denne side

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

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ScholarGateRobust TGARCH (Robust Threshold Generalized Autoregressive Conditional Heteroscedasticity Model). Hentet 2026-06-15 fra https://scholargate.app/da/econometrics/robust-tgarch · Datasæt: https://doi.org/10.5281/zenodo.20539026