NM-QELE for ARMA-GARCH models with non-Gaussian innovations

Jeongcheol Ha and Taewook Lee

Statistics & Probability Letters, 2011, vol. 81, issue 6, 694-703

Abstract: Although the quasi maximum likelihood estimator based on Gaussian density (Gaussian-QMLE) is widely used to estimate parameters in ARMA models with GARCH innovations (ARMA-GARCH models), it does not perform successfully when error distribution of ARMA-GARCH models is either skewed or leptokurtic. In order to circumvent such defects, Lee and Lee (submitted for publication) proposed the quasi maximum estimated-likelihood estimator using Gaussian mixture-based likelihood (NM-QELE) for GARCH models. In this paper, we adopt the NM-QELE method for estimating parameters in ARMA-GARCH models and demonstrate the validity of NM-QELE by verifying its consistency.

Keywords: ARMA-GARCH; model; Consistency; Gaussian; mixture; model; QMLE; Quasi-maximum; estimated-likelihood; estimator (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (1)

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