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Whittle Estimation of ARCH Models

Author

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  • Liudas Giraitis
  • Peter M Robinson

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

  • Liudas Giraitis & Peter M Robinson, 2000. "Whittle Estimation of ARCH Models," STICERD - Econometrics Paper Series 406, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Handle: RePEc:cep:stiecm:406
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    File URL: https://sticerd.lse.ac.uk/dps/em/em406.pdf
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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. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    3. 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.

    More about this item

    Keywords

    ARCH models; Whittle estimation.;

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