SEARCH

SEARCH BY CITATION

Keywords:

  • argmin sequence;
  • asymptotic normality;
  • bracketing method;
  • GARCH models;
  • non-convex optimization;
  • quantile regression;
  • reparametrization method;
  • strong consistency;
  • value at risk

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.