Open Access
2017 Asymptotic behavior of the Laplacian quasi-maximum likelihood estimator of affine causal processes
Jean-Marc Bardet, Yakoub Boularouk, Khedidja Djaballah
Electron. J. Statist. 11(1): 452-479 (2017). DOI: 10.1214/17-EJS1241

Abstract

We prove the consistency and asymptotic normality of the Laplacian Quasi-Maximum Likelihood Estimator (QMLE) for a general class of causal time series including ARMA, AR($\infty$), GARCH, ARCH($\infty$), ARMA-GARCH, APARCH, ARMA-APARCH,..., processes. We notably exhibit the advantages (moment order and robustness) of this estimator compared to the classical Gaussian QMLE. Numerical simulations confirms the accuracy of this estimator.

Citation

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Jean-Marc Bardet. Yakoub Boularouk. Khedidja Djaballah. "Asymptotic behavior of the Laplacian quasi-maximum likelihood estimator of affine causal processes." Electron. J. Statist. 11 (1) 452 - 479, 2017. https://doi.org/10.1214/17-EJS1241

Information

Received: 1 April 2016; Published: 2017
First available in Project Euclid: 2 March 2017

zbMATH: 06702351
MathSciNet: MR3619313
Digital Object Identifier: 10.1214/17-EJS1241

Subjects:
Primary: 62M10 , 62M10
Secondary: 60G10

Keywords: ARMA-ARCH processes , asymptotic normality , Laplacian quasi-maximum likelihood estimator , strong consistency

Vol.11 • No. 1 • 2017
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