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Whittle estimation of ARCH models

Author

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  • Giraitis, Liudas
  • Robinson, Peter M.

Abstract

For a class of parametric ARCH models, Whittle estimation based on squared observations is shown to be inconsistent and asymptotically normal. Our conditions require the squares to have short memory autocorrelation, by comparison with the work of Zaffaroni (1999), who established the same properties on the basis of an alternative class of models with martingale difference levels and long memory autocorrelated squares.

Suggested Citation

  • Giraitis, Liudas & Robinson, Peter M., 2000. "Whittle estimation of ARCH models," LSE Research Online Documents on Economics 2277, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:2277
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    File URL: http://eprints.lse.ac.uk/2277/
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    Citations

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    Cited by:

    1. Wai Leong Ng & Chun Yip Yau, 2018. "Test for the existence of finite moments via bootstrap," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 28-48, January.
    2. Mikosch, Thomas & Straumann, Daniel, 0. "Whittle estimation in a heavy-tailed GARCH(1,1) model," Stochastic Processes and their Applications, Elsevier, vol. 100(1-2), pages 187-222, July.
    3. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.

    More about this item

    Keywords

    ARCH models; Whittle estimation;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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