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Portfolio selection in a data-rich environment.

Bouaddi, M. and Taamouti, A. (2013) 'Portfolio selection in a data-rich environment.', Journal of economic dynamics and control., 37 (12). pp. 2943-2962.


We model portfolio weights as a function of latent factors that summarize the information in a large number of economic variables. This approach (hereafter diffusion index approach) offers the opportunity to exploit a much richer information base to improve portfolio selection. We use factor analysis to estimate the space spanned by the factors. This provides consistent estimates for the optimal weights as the number of economic variables and sample size go to infinity. We consider an empirical application to illustrate the practical usefulness of our approach. The results indicate that the diffusion index approach helps to improve the portfolio performance.

Item Type:Article
Keywords:Portfolio's weights modeling, Factor analysis, Principal components, Portfolio performance, Stock returns, Fama–French factors, Economic factors, VIX.
Full text:Full text not available from this repository.
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Record Created:07 Nov 2014 10:50
Last Modified:31 Jul 2017 16:38

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