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Market Graph and Markowitz Model

In: Optimization in Science and Engineering

Author

Listed:
  • Valery Kalyagin

    (National Research University Higher School of Economics, Laboratory of Algorithms and Technologies for Network Analysis and Department of Applied Mathematics and Informatics)

  • Alexander Koldanov

    (National Research University Higher School of Economics, Laboratory of Algorithms and Technologies for Network Analysis and Department of Applied Mathematics and Informatics)

  • Petr Koldanov

    (National Research University Higher School of Economics, Laboratory of Algorithms and Technologies for Network Analysis and Department of Applied Mathematics and Informatics)

  • Viktor Zamaraev

    (National Research University Higher School of Economics, Laboratory of Algorithms and Technologies for Network Analysis and Department of Applied Mathematics and Informatics)

Abstract

Market graph is known to be a useful tool for market network analysis. Cliques and independent sets of the market graph give an information about concentrated dependent sets of stocks and distributed independent sets of stocks on the market. In the present paper the connections between market graph and classical Markowitz portfolio theory are studied. In particular, efficient frontiers of cliques and independent sets of the market graph are compared with the efficient frontier of the market. The main result is: efficient frontier of the market can be well approximated by the efficient frontier of the maximum independent set of the market graph constructed on the sets of stocks with the highest Sharp ratio. This allows to reduce the number of stocks for portfolio optimization without the loss of quality of obtained portfolios. In addition it is shown that cliques of the market graphs are not suitable for portfolio optimization.

Suggested Citation

  • Valery Kalyagin & Alexander Koldanov & Petr Koldanov & Viktor Zamaraev, 2014. "Market Graph and Markowitz Model," Springer Books, in: Themistocles M. Rassias & Christodoulos A. Floudas & Sergiy Butenko (ed.), Optimization in Science and Engineering, edition 127, pages 293-306, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4939-0808-0_15
    DOI: 10.1007/978-1-4939-0808-0_15
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