Template-type: ReDIF-Paper 1.0
Author-Name: Diaa Noureldin
Author-Email: diaa.noureldin@economics.ox.ac.uk
Author-Workplace-Name: Dept of Economics and Oxford-Man Institute of Quantitative Finance, University of Oxford
Author-Name: Neil Shephard
Author-Email: neil.shephard@economics.ox.ac.uk
Author-Workplace-Name: Dept of Economics and Oxford-Man Institute of Quantitative Finance, University of Oxford.
Author-Name: Kevin Sheppard
Author-Email: kevin.sheppard@economics.ox.ac.uk
Author-Workplace-Name: Dept of Economics and Oxford-Man Institute of Quantitative Finance, University of Oxford.
Title: Multivariate Rotated ARCH Models
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 ?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.
Keywords: RARCH; RCC; multivariate volatility; covariance targeting; common persistence; empirical Bayes; predictive likelihood.
Classification-JEL: C32; C52; C58.
Length: 34 pages
Creation-Date: 2012-02-18
Number: 2012-W01
File-URL: http://www.nuffield.ox.ac.uk/economics/papers/2012/covtar_bekk_v3.pdf
File-Format: application/pdf
Handle: RePEc:nuf:econwp:1201