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Seleção De Carteiras Utilizando O Modelofama-French-Carhart
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Seleção De Carteiras Utilizando O Modelofama-French-Carhart

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  • GUILHERME VALLE MOURA
  • JOÃO FROIS CALDEIRA
  • ANDRÉ SANTOS

Abstract

In this article the Fama-French-Carhart factor model is used to obtain short selling-constrained and unconstrained minimum variance portfolios. For that purpose, conditional covariance matrices are obtained based on a recent multivariate factor GARCH specification with a flexible modeling strategy for the common factors, for the individual assets, and for the factor loads proposed by Santos & Moura (2012). An application involving 61 stocks traded on the São Paulo stock exchange (BM\&FBovespa) shows that the proposed specification delivers less risky portfolios on an out-of-sample basis in comparison to several benchmark models, including existing factor approaches.
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  • Guilherme Valle Moura & João Frois Caldeira & André Santos, 2014. "Seleção De Carteiras Utilizando O Modelofama-French-Carhart," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 117, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    • Handle: RePEc:anp:en2012:117
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    Cited by:

    1. Paulo Ferreira Naibert & João F. Caldeira, 2016. "Seleção De Carteiras Com Restrição Das Normas Das Posições: Uma Comparação Empírica Entre Diferentes Níveis De Restrição De Exposição Para Dados Da Bm&Fbovespa," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 132, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    2. Ziegelmann, Flávio Augusto & Borges, Bruna & Caldeira, João F., 2015. "Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 35(1), October.

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