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Minimum Variance Portfolio Selection for Large Number of Stocks – Application of Time-Varying Covariance Matrices

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  • Piotr Fiszeder

    (Nicolaus Copernicus University in Toruñ)

Abstract

An evaluation of the efficiency of different methods of the minimum variance portfolio selection was performed for seventy stocks from the Warsaw Stock Exchange. Eight specifications of multivariate GARCH models and six other methods were used. The application of all considered GARCH-class models was more efficient in stocks allocation than the implementation of the other analyzed methods. The simple specifications of multivariate GARCH models, whose parameters were estimated in two stages, like the DCC and CCC models were the best performing models.

Suggested Citation

  • Piotr Fiszeder, 2011. "Minimum Variance Portfolio Selection for Large Number of Stocks – Application of Time-Varying Covariance Matrices," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 11, pages 87-98.
    • Handle: RePEc:cpn:umkdem:v:11:y:2011:p:87-98
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    References listed on IDEAS

    as
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