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Whittle estimation of ARCH models

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Keywords
  • Hb Economic Theory
Disciplines
  • Economics
  • Mathematics

Abstract

LSE Research Online Article (refereed) Whittle estimation of ARCH models Liudas Giraitis & Peter M. Robinson LSE has developed LSE Research Online so that users may access research output of the School. Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Users may download and/or print one copy of any article(s) in LSE Research Online to facilitate their private study or for non-commercial research. You may not engage in further distribution of the material or use it for any profit-making activities or any commercial gain. You may freely distribute the URL (http://eprints.lse.ac.uk) of the LSE Research Online website. You may cite this version as: Giraitis, L. & Robinson, P.M. (2001). Whittle estimation of ARCH models [online]. London: LSE Research Online. Available at: http://eprints.lse.ac.uk/archive/00000316 This is an electronic version of an Article published in Econometric theory, 17 (3). pp. 608-631 © 2001 Cambridge University Press. http://uk.cambridge.org/journals/ect/ http://eprints.lse.ac.uk Contact LSE Research Online at: [email protected] WHITTLE ESTIMATION OF ARCH MODELS LIIIUUUDDDAAASSS GIIIRRRAAAIIITTTIIISSS AAANNNDDD PEEETTTEEERRR M. ROOOBBBIIINNNSSSOOONNN London School of Economics For a class of parametric ARCH models, Whittle estimation based on squared observations is shown to be !n-consistent and asymptotically normal+ Our con- ditions require the squares to have short memory autocorrelation, by comparison with the work of Zaffaroni ~1999, “Gaussian Inference on Certain Long-Range Dependent Volatility Models,” Preprint!, who established the same properties on the basis of an alternative class of models with martingale difference levels and long memory autocorrelated squares+ 1. INTRODUCTION Conditional heteroskedasticity arises in much analysis of economic and finan- cial time series da

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