Dynamic factor multivariate GARCH model

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...

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Bibliographic Details
Published in:Computational statistics & data analysis 2014-08, Vol.76, p.606-617
Main Authors: Santos, André A.P., Moura, Guilherme V.
Format: Article
Language:English
Subjects:
Benchmarking
Covariance
Data processing
Dynamic conditional correlation (DCC)
Flexibility
Forecasting
Kalman filter
Learning CAPM
Mathematical models
Performance evaluation
Sharpe ratio
Specifications
Statistics
Variance
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Summary: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.
ISSN:0167-9473
1872-7352
DOI:10.1016/j.csda.2012.09.010