Multivariate Rotated ARCH Models

Diaa Noureldin, Neil Shephard () and Kevin Sheppard ()

No 2012-W01, Economics Papers from Economics Group, Nuffield College, University of Oxford

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. (search for similar items in EconPapers)
JEL-codes: C32 C52 C58 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2012-02-18
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

Downloads: (external link)
http://www.nuffield.ox.ac.uk/economics/papers/2012/covtar_bekk_v3.pdf (application/pdf)

Related works:
Journal Article: Multivariate rotated ARCH models (2014)
Working Paper: Multivariate rotated ARCH models (2014)
Working Paper: Multivariate Rotated ARCH models (2012)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nuf:econwp:1201

Access Statistics for this paper

More papers in Economics Papers from Economics Group, Nuffield College, University of Oxford Contact information at EDIRC.
Bibliographic data for series maintained by Maxine Collett ().