On the Benefits of Equicorrelation for Portfolio Allocation

Adam Clements, Ayesha Scott () and Annastiina Silvennoinen
Additional contact information
Ayesha Scott: QUT

No 99, NCER Working Paper Series from National Centre for Econometric Research

Abstract: The importance of modelling correlation has long been recognised in the field of portfolio management with large dimensional multivariate problems are increasingly becoming the focus of research. This paper provides a straightforward and commonsense approach toward investigating a number of models used to generate forecasts of the correlation matrix for large dimensional problems. We find evidence in favour of assuming equicorrelation across various portfolio sizes, particularly during times of crisis. During periods of market calm however, the suitability of the constant conditional correlation model cannot be discounted especially for large portfolios. A portfolio allocation problem is used to compare forecasting methods. The global minimum variance portfolio and Model Confidence Set are used to compare methods, whilst portfolio weight stability and relative economic value are also considered.

Keywords: Volatility; multivariate GARCH; portfolio allocation (search for similar items in EconPapers)
JEL-codes: C22 G11 G17 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2013-12-11
New Economics Papers: this item is included in nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.ncer.edu.au/papers/documents/WP99.pdf (application/pdf)

Related works:
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:qut:auncer:2013_92

Access Statistics for this paper

More papers in NCER Working Paper Series from National Centre for Econometric Research Contact information at EDIRC.
Bibliographic data for series maintained by School of Economics and Finance ( this e-mail address is bad, please contact ).