Portfolio Selection and Post Optimality Test Using Goal Programming

  • Authors

    • Darsha Panwar
    • Manoj Jha
    • Namita Srivastava
    2018-08-15
    https://doi.org/10.14419/ijet.v7i3.27.18001
  • Analytical hierarchy process, Cluster analysis, Biogeographical-based optimization, Post optimality analysis, Goal programing. MSC. 65K10, 62P05, 94D05.

  • In a practical portfolio planning process the investment decision to be taken by an investor is not simple and is influenced by several other constraints like stock price, co-moment with market, return with respect to risk, past performance and so many. In this purview, a hybrid approach is employed for portfolio selection which combines multiple methodologies like investor topology, cluster analysis, analytical hierarchy process (AHP) for ranking the assets and biogeographic-based optimization (BBO). Furthermore, with the help of goal programming (GP), performing post optimality test for betterment the result which is obtained by BBO. In the goal programming, objective is to be minimizing the weighted deviations of desire goals. Weighted deviation is known as achievement, which has two branches namely over achievement and under achievement.

     

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    Panwar, D., Jha, M., & Srivastava, N. (2018). Portfolio Selection and Post Optimality Test Using Goal Programming. International Journal of Engineering & Technology, 7(3.27), 481-487. https://doi.org/10.14419/ijet.v7i3.27.18001