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http://ssrn.com/abstract=2007484
 
 

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Multivariate Rotated ARCH Models


Diaa Noureldin


University of Oxford - Department of Economics

Neil Shephard


Harvard University

Kevin Sheppard


University of Oxford - Department of Economics; University of Oxford - Oxford-Man Institute of Quantitative Finance

November 5, 2013


Abstract:     
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 fit them using a BEKK-type parameterization of the time-varying covariance whose long-run covariance is the identity matrix. This yields the rotated BEKK (RBEKK) model. The extension to DCC-type parameterizations is given, introducing the rotated DCC (RDCC) model. Inference for these models is computationally attractive, and the asymptotics are standard. The techniques are illustrated using data on the DJIA stocks.

Number of Pages in PDF File: 36

Keywords: RARCH; RBEKK; RDCC; multivariate volatility; covariance targeting; common persistence

JEL Classification: C32, C52, C58

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Date posted: February 19, 2012 ; Last revised: November 19, 2013

Suggested Citation

Noureldin, Diaa and Shephard, Neil and Sheppard, Kevin, Multivariate Rotated ARCH Models (November 5, 2013). Available at SSRN: http://ssrn.com/abstract=2007484 or http://dx.doi.org/10.2139/ssrn.2007484

Contact Information

Diaa Noureldin
University of Oxford - Department of Economics ( email )
Manor Road Building
Manor Road
Oxford, OX1 3UQ
United Kingdom
Neil Shephard
Harvard University ( email )
1875 Cambridge Street
Cambridge, MA 02138
United States
Kevin Keith Sheppard (Contact Author)
University of Oxford - Department of Economics ( email )
Manor Road Building
Manor Road
Oxford, OX1 3BJ
United Kingdom
University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )
Eagle House
Walton Well Road
Oxford, Oxfordshire OX2 6ED
United Kingdom
+44 1865 616 613 (Phone)
HOME PAGE: http://www.oxford-man.ox.ac.uk
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