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Cites:

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Information Journal Paper

Title

MIN-MAX GOAL PROGRAMMING IN MULTI-OBJECTIVE PORTFOLIO SELECTION UNDER RANDOM CONDITIONS

Pages

  1-15

Abstract

PORTFOLIO SELECTION problem is one of the important areas in financial decision making. Generally, in the PORTFOLIO SELECTION problem the Decision Maker (DM) pays attention to several objectives, such as annual return, annual dividend and risk. MULTI-OBJECTIVE programming techniques such as e-constraint, utility functions and goal programmings are used to select the best satisfying portfolio by the DM. In this paper, we assume that some of the input problem parameters such as return of stocks is random and normally distributed and probabilistic methods, chance constrained programming, are utilized alongside min-max goal programming and goal chance constrained Programming model is introduced as a deterministic transformation to MULTI-OBJECTIVE Stochastic PORTFOLIO SELECTION model. To demonstrate The Proposed program, samples of 20 stocks from the Dow Jones Industrial Average are presented.

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  • Cite

    APA: Copy

    KARIMIAN, N., & ABEDZADEH, M.. (2012). MIN-MAX GOAL PROGRAMMING IN MULTI-OBJECTIVE PORTFOLIO SELECTION UNDER RANDOM CONDITIONS. FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), 3(12), 1-15. SID. https://sid.ir/paper/197664/en

    Vancouver: Copy

    KARIMIAN N., ABEDZADEH M.. MIN-MAX GOAL PROGRAMMING IN MULTI-OBJECTIVE PORTFOLIO SELECTION UNDER RANDOM CONDITIONS. FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT)[Internet]. 2012;3(12):1-15. Available from: https://sid.ir/paper/197664/en

    IEEE: Copy

    N. KARIMIAN, and M. ABEDZADEH, “MIN-MAX GOAL PROGRAMMING IN MULTI-OBJECTIVE PORTFOLIO SELECTION UNDER RANDOM CONDITIONS,” FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), vol. 3, no. 12, pp. 1–15, 2012, [Online]. Available: https://sid.ir/paper/197664/en

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