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http://ssrn.com/abstract=2110298
 
 

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Dynamic Factor Multivariate GARCH Model


Andre A. P. Santos


Universidade Federal de Santa Catarina (UFSC) - Department of Economics

Guilherme V. Moura


Universidade Federal de Santa Catarina (UFSC) - Department of Economics

June 24, 2012

Forthcoming, Computational Statistics and Data Analysis

Abstract:     
Factor models are well established as promising alternatives to obtain covariance matrices of portfolios containing a very large number of assets. In this paper, we consider a novel multivariate factor GARCH speci cation with a flexible modeling strategy for the common factors, for the individual assets, and for the factor loads. We apply the proposed model to obtain minimum variance portfolios of all stocks that belonged to the S&P100 during the sample period and show that it delivers less risky portfolios in comparison to benchmark models, including existing factor approaches.

Number of Pages in PDF File: 27

Keywords: dynamic conditional correlation (DCC), forecasting, Kalman filter, learning, CAPM, performance evaluation, Sharpe ratio

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Date posted: July 17, 2012 ; Last revised: October 9, 2012

Suggested Citation

Santos, Andre A. P. and Moura, Guilherme V., Dynamic Factor Multivariate GARCH Model (June 24, 2012). Forthcoming, Computational Statistics and Data Analysis . Available at SSRN: http://ssrn.com/abstract=2110298 or http://dx.doi.org/10.2139/ssrn.2110298

Contact Information

Andre A. P. Santos (Contact Author)
Universidade Federal de Santa Catarina (UFSC) - Department of Economics ( email )
PO Box 476
Florianopolis, SC 88010-970
Brazil
HOME PAGE: http://https://sites.google.com/site/andreportela
Guilherme Valle Moura
Universidade Federal de Santa Catarina (UFSC) - Department of Economics ( email )
PO Box 476
Florianopolis, SC 88010-970
Brazil
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