Dynamic factor multivariate GARCH model

Andre Santos () and Guilherme Moura ()

Computational Statistics & Data Analysis, 2014, vol. 76, issue C, 606-617

Abstract: A novel multivariate factor GARCH specification is used to obtain conditional covariance matrices of minimum variance portfolios containing a very large number of assets. The approach allows for time varying factor loads, and achieves great flexibility by allowing alternative specifications for the covariance among factors and for the variance of the asset-specific part of return. Minimum variance portfolios based on the proposed conditional covariance matrix specification are shown to deliver less risky portfolios in comparison to benchmark models, including existing factor approaches.

Keywords: Dynamic conditional correlation (DCC); Forecasting; Kalman filter; Learning CAPM; Performance evaluation; Sharpe ratio (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167947312003398
Full text for ScienceDirect subscribers only.

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:eee:csdana:v:76:y:2014:i:c:p:606-617

DOI: 10.1016/j.csda.2012.09.010

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().