Quasi-maximum likelihood estimation of periodic GARCH processes
Statistics Theory
2007-09-20 v1 Probability
Methodology
Statistics Theory
Abstract
This paper establishes the strong consistency and asymptotic normality of the quasi-maximum likelihood estimator (QMLE) for a GARCH process with periodically time-varying parameters. We first give a necessary and sufficient condition for the existence of a strictly periodically stationary solution for the periodic GARCH (P-GARCH) equation. As a result, it is shown that the moment of some positive order of the P-GARCH solution is finite, under which we prove the strong consistency and asymptotic normality (CAN) of the QMLE without any condition on the moments of the underlying process.
Cite
@article{arxiv.0709.2982,
title = {Quasi-maximum likelihood estimation of periodic GARCH processes},
author = {Abdehakim Aknouche and Abdelouhab Bibi},
journal= {arXiv preprint arXiv:0709.2982},
year = {2007}
}
Comments
19 pages