Asymptotic behavior of the Laplacian quasi-maximum likelihood estimator of affine causal processes

Jean Marc Bardet, Yakoub Boularouk, Khedidja Djaballah

Research output: Contribution to journalArticlepeer-review

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(∞), GARCH, ARCH(∞), 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.

Original languageEnglish
Pages (from-to)452-479
Number of pages28
JournalElectronic Journal of Statistics
Volume11
Issue number1
DOIs
Publication statusPublished - 1 Jan 2017
Externally publishedYes

Keywords

  • ARMA-ARCH processes
  • Asymptotic normality
  • Laplacian quasi-maximum likelihood estimator
  • Strong consistency

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