Robust TGARCH
Robust TGARCH extends the Threshold GARCH model by replacing the conventional maximum likelihood objective with an estimator that is resistant to heavy-tailed innovations and outlying observations. It captures asymmetric volatility responses — where negative shocks amplify variance more than positive shocks — while remaining reliable when the return distribution deviates strongly from normality.
Source record
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- 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
- Preminger, A., & Storti, G. (2017). Least squares estimation for GARCH (1,1) model with heavy tailed errors. The Econometrics Journal, 20(1), 221–258. · URL
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