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

Journal Title: Dynamic Econometric Models - Year 2011, Vol 11, Issue 1

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.

Authors and Affiliations

Piotr Fiszeder

Keywords

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  • EP ID EP160899
  • DOI -
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How To Cite

Piotr Fiszeder (2011). Minimum Variance Portfolio Selection for Large Number of Stocks – Application of Time-Varying Covariance Matrices. Dynamic Econometric Models, 11(1), 87-98. https://europub.co.uk./articles/-A-160899