Dynamic factor multivariate GARCH model

André A.P. Santos*, Guilherme V. Moura

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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.

Original languageEnglish
Pages (from-to)606-617
Number of pages12
JournalComputational Statistics and Data Analysis
Volume76
DOIs
Publication statusPublished - 1 Aug 2014

Keywords / Materials (for Non-textual outputs)

  • dynamic conditional correlation (DCC)
  • forecasting
  • Kalman filter
  • learning CAPM
  • performance evaluation
  • sharpe ratio

Fingerprint

Dive into the research topics of 'Dynamic factor multivariate GARCH model'. Together they form a unique fingerprint.

Cite this