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Stock portfolio selection using aspiration level-oriented procedure: real case on the RM-SYSTEM Czech stock exchange

Author

Listed:
  • Petr Fiala

    (Prague University of Economics and Business)

  • Adam Borovička

    (Prague University of Economics and Business)

Abstract

Many approaches have been designed to solve a stock portfolio selection problem. The aim of this paper is to provide a complex supporting tool for a portfolio selection. So, the problem is seen as a multi-objective one. People tend to settle for a reasonably satisfactory rather than an optimal solution which is provided by the existing methods. That means they substitute the goal of reaching specified aspiration levels for the goal of maximization. Developed Aspiration Level-Oriented procedure (ALOP) is based on searching a linear decision space and current solutions are sought by means of an interactive goal programming approach. Such a procedure has significant advantages for investment decision making. The decision space is searched by changes of aspiration levels using problem-solving approaches. Moreover, the approach can be combined with a weight model of preferences. The power of the developed method is demonstrated on a real investment portfolio making on the RM-SYSTEM Czech stock exchange. A stock portfolio process is performed for two most typical investment strategies-dividend-oriented and capital-oriented investor. The essential criteria (objectives) are determined, as well as their importance (according to the investor’s preferences). After a decision making procedure, their resulting portfolios are analysed and compared.

Suggested Citation

  • Petr Fiala & Adam Borovička, 2022. "Stock portfolio selection using aspiration level-oriented procedure: real case on the RM-SYSTEM Czech stock exchange," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 781-805, June.
  • Handle: RePEc:spr:cejnor:v:30:y:2022:i:2:d:10.1007_s10100-020-00731-4
    DOI: 10.1007/s10100-020-00731-4
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    References listed on IDEAS

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    1. Ballestero, Enrique, 2001. "Stochastic goal programming: A mean-variance approach," European Journal of Operational Research, Elsevier, vol. 131(3), pages 476-481, June.
    2. Abdelaziz, Fouad Ben & Aouni, Belaid & Fayedh, Rimeh El, 2007. "Multi-objective stochastic programming for portfolio selection," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1811-1823, March.
    3. Güray Kara & Ayşe Özmen & Gerhard-Wilhelm Weber, 2019. "Stability advances in robust portfolio optimization under parallelepiped uncertainty," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(1), pages 241-261, March.
    4. Miettinen, Kaisa & Makela, Marko M., 2006. "Synchronous approach in interactive multiobjective optimization," European Journal of Operational Research, Elsevier, vol. 170(3), pages 909-922, May.
    5. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    6. Pomerol, J. Ch. & Trabelsi, T., 1987. "An adaptation of to multiobjective linear programming," European Journal of Operational Research, Elsevier, vol. 31(3), pages 335-341, September.
    7. Shing, Chue & Nagasawa, Hiroyuki, 1999. "Interactive decision system in stochastic multiobjective portfolio selection," International Journal of Production Economics, Elsevier, vol. 60(1), pages 187-193, April.
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    More about this item

    Keywords

    AHP; Aspiration levels; Goal programming; Portfolio selection; RM-SYSTEM; Stock;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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