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Portfolio Selection by Goal Programming Techniques

In: Socially Responsible Investment

Author

Listed:
  • Enrique Ballestero

    (Universitat Politècnica de València)

  • Ana Garcia-Bernabeu

    (Universitat Politècnica de València)

  • Adolfo Hilario

    (Universitat Politècnica de València)

Abstract

Goal programming stems from the Simonian paradigm describing decision makers as seekers of satisfying solutions rather than optimal solutions. Weighted Goal Programming (WGP) is usually viewed as a deterministic model, which provides satisfying solutions to multi-objective technological and economic problems in multiple criteria decision making analysis. Deterministic WGP is less appropriated to select securities portfolios because returns on securities are random variables. To accommodate WGP to portfolio selection, some stochastic versions of different strictness had been proposed. In this chapter, we deal with Mean-Variance Stochastic Goal Programming (MV-SGP) model, which relies on classic expected utility maximization theory, also known as Eu(R), Arrow’s risk aversion and Pratt’s approximation to expected utility.

Suggested Citation

  • Enrique Ballestero & Ana Garcia-Bernabeu & Adolfo Hilario, 2015. "Portfolio Selection by Goal Programming Techniques," International Series in Operations Research & Management Science, in: Enrique Ballestero & Blanca Pérez-Gladish & Ana Garcia-Bernabeu (ed.), Socially Responsible Investment, edition 127, chapter 0, pages 111-129, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-11836-9_5
    DOI: 10.1007/978-3-319-11836-9_5
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    Cited by:

    1. Deng Xiong & Liu Yanli, 2018. "A High-Moment Trapezoidal Fuzzy Random Portfolio Model with Background Risk," Journal of Systems Science and Information, De Gruyter, vol. 6(1), pages 1-28, February.

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