36 Pages Posted: 19 Feb 2012 Last revised: 19 Nov 2013
Date Written: November 5, 2013
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.
Keywords: RARCH; RBEKK; RDCC; multivariate volatility; covariance targeting; common persistence
JEL Classification: C32, C52, C58
Suggested Citation: Suggested Citation
Noureldin, Diaa and Shephard, Neil and Sheppard, Kevin, Multivariate Rotated ARCH Models (November 5, 2013). Available at SSRN: https://ssrn.com/abstract=2007484 or http://dx.doi.org/10.2139/ssrn.2007484
By Andrew Ang