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Multivariate Rotated ARCH Models

Listed author(s):
  • Diaa Noureldin

    ()

    (Dept of Economics and Oxford-Man Institute of Quantitative Finance, University of Oxford)

  • Neil Shephard

    ()

    (Dept of Economics and Oxford-Man Institute of Quantitative Finance, University of Oxford.)

  • Kevin Sheppard

    ()

    (Dept of Economics and Oxford-Man Institute of Quantitative Finance, University of Oxford.)

This paper introduces a new class of multivariate volatility models which is easy to estimate using covariance targeting, even with rich dynamics. We call them rotated ARCH (RARCH) models. The basic structure is to rotate the returns and then to ?t them using a BEKK-type parameterization of the time-varying covariance whose long-run covariance is the identity matrix. The extension to DCC-type parameterizations is given, introducing the rotated conditional correlation (RCC) model. Inference for these models is computationally attractive, and the asymptotics are standard. The techniques are illustrated using data on some DJIA stocks.

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File URL: http://www.nuffield.ox.ac.uk/economics/papers/2012/covtar_bekk_v3.pdf
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Paper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number 2012-W01.

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Length: 34 pages
Date of creation: 18 Feb 2012
Handle: RePEc:nuf:econwp:1201
Contact details of provider: Web page: https://www.nuffield.ox.ac.uk/economics/

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