Minimum Variance Portfolio Selection for Large Number of Stocks – Application of Time-Varying Covariance Matrices
AbstractAn 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.
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Bibliographic InfoArticle provided by Wydawnictwo Naukowe Uniwersytetu Mikolaja Kopernika in its journal Dynamic Econometric Models.
Volume (Year): 11 (2011)
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multivariate GARCH models; time-varying covariance matrix; portfolio selection.;
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