Journal
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
Volume 52, Issue 4, Pages 1490-1503Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/03610918.2021.1884877
Keywords
Laplace quasi-maximum likelihood estimator; Strong consistency; Asymptotic normality; GARCH processes
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This paper proposes a consistent estimator for the noise mean of the GARCH process based on Laplace errors. It also proves the consistency and asymptotic normality of the Quasi-Maximum Likelihood Estimator of the GARCH model based on Laplace residuals with any mean value. Numerical simulations confirm the accuracy of the estimators.
We propose a consistent estimator for the noise mean m of the GARCH process based on Laplace (m,1) errors. Also, we prove the consistency and asymptotic normality for the Quasi-Maximum Likelihood Estimator of the GARCH model based on the Laplace residuals with any mean value for the residuals. Numerical simulations confirm the accuracy of the estimators.
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