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Quantile Regression Estimator for GARCH Models |
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| Authors: | SANGYEOL LEE JUNGSIK NOH |
| Affiliation: | Department of Statistics, Seoul National University |
| Abstract: | Abstract. In this article, we study the quantile regression estimator for GARCH models. We formulate the quantile regression problem by a reparametrization method and verify that the obtained quantile regression estimator is strongly consistent and asymptotically normal under certain regularity conditions. We also present our simulation results and a real data analysis for illustration. |
| Keywords: | argmin sequence asymptotic normality bracketing method GARCH models non‐convex optimization quantile regression reparametrization method strong consistency value at risk |