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Quantile Regression Estimator for GARCH Models
Author(s) -
LEE SANGYEOL,
NOH JUNGSIK
Publication year - 2013
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/j.1467-9469.2011.00759.x
Subject(s) - quantile regression , mathematics , estimator , quantile , econometrics , statistics , autoregressive conditional heteroskedasticity , regression analysis , regression , volatility (finance)
. 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.