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On location estimation for LARCH processes

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  • Beran, Jan

Abstract

We consider location estimation when the error process is a stationary LARCH process with long memory in the second moments. The asymptotic distribution of the sample mean and nonlinear M-estimators of the location parameter are derived. Essential assumptions for obtaining asymptotic normality with -rate of convergence are symmetry of the innovation distribution and skew-symmetry of the [psi]-function.

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  • Beran, Jan, 2006. "On location estimation for LARCH processes," Journal of Multivariate Analysis, Elsevier, vol. 97(8), pages 1766-1782, September.
    • Handle: RePEc:eee:jmvana:v:97:y:2006:i:8:p:1766-1782
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    References listed on IDEAS

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    2. Francq, Christian & Zakoïan, Jean-Michel, 2010. "Inconsistency of the MLE and inference based on weighted LS for LARCH models," Journal of Econometrics, Elsevier, vol. 159(1), pages 151-165, November.
    3. Christian FRANCQ & Jean-Michel ZAKOIAN, 2009. "Properties of the QMLE and the Weighted LSE for LARCH(q) Models," Working Papers 2009-19, Center for Research in Economics and Statistics.
    4. Francq, Christian & Zakoian, Jean-Michel, 2009. "Inconsistency of the QMLE and asymptotic normality of the weighted LSE for a class of conditionally heteroscedastic models," MPRA Paper 15147, University Library of Munich, Germany.

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