برنامه ریزی تصادفی چندهدفه برای انتخاب سبد سهام

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 دانشجوی دکتری، مدیریت صنعتی، دانشکدۀ مدیریت، دانشگاه تهران، تهران، ایران

2 استاد، مدیریت صنعتی، دانشکدۀ مدیریت، دانشگاه تهران، تهران، ایران

3 استاد، مهندسی صنایع، دانشکدۀ مهندسی صنایع، دانشگاه صنعتی شریف، تهران، ایران

4 استاد، مدیریت مالی، دانشکدۀ مدیریت، دانشگاه تهران، تهران، ایران

چکیده

در رویکردهای سنتی مقادیر مرتبط با اهداف یک مدل تصمیم­گیری اغلب معین و قطعی فرض می‌شود، درحالی‌که در دنیای واقعی این مقادیر احتمالی است و تصمیم­گیرنده نمی­تواند آنها را به­طور قطعی تعیین کند. بهینه­سازی مالی یکی از حوزه­های جذاب در تصمیم­گیری در شرایط عدم اطمینان است. در مسئلۀ انتخاب سبد سرمایه­گذاری، تصمیم­گیرنده همزمان با اهداف مختلف و گاه متعارض مانند نرخ بازده، نقدینگی، سود تقسیمی و ریسک مواجه است. تاکنون روش‌های مختلف برنامه­ریزی چندهدفه از جمله برنامه­ریزی آرمانی و برنامه­ریزی توافقی که بیشترین میزان ترجیحات و آرمان‌های تصمیم‌گیرنده را ارضا کند و روش‌های مختلف برنامه­ریزی چندمعیاره برای مواجهه با مسئلۀ انتخاب سبد سهام استفاده‌ شده‌اند. در این پژوهش با تشکیل برنامه­ریزی تصادفی چندهدفه که شاخص‌های مرتبط با اهداف، تصادفی و مبتنی بر توزیع نرمال هستند، از مدل برنامه­ریزی توافقی با محدودیت تصادفی به‌منظور انتخاب سبد استفاده شد. پس از توسعه و حل مدل، در نهایت نتایج مدل برنامه‌ریزی برای انتخاب سبد سهام در بازار بورس تهران ارائه ‌شده است.

کلیدواژه‌ها

عنوان مقاله [English]

Designing a Multi-objective Stochastic programming model for portfolio selection

نویسندگان [English]

  • Alireza Sharifisalim 1
  • Mansour Momeni 2
  • Mohammad Modarres Yazdi 3
  • Reza Rayi 4
1 Ph.D. Student in Operational Research Management, Faculty of Management, Tehran University, , Tehran, Iran.
2 Prof., Industrial Management, Faculty of Management, Tehran University, Tehran, Iran.
3 Prof., Industrial Engineering, Sharif University of Technology, Tehran, Iran.
4 Prof., Financial Management, Faculty of Management, Tehran University, Tehran, Iran.
چکیده [English]

In traditional portfolio selection model coefficients often are certain and deterministic, but in real world these coefficients are probabilistic. So decision maker cannot estimate them exactly. Financial optimization is one of the most attractive areas in decision under uncertainty. In the portfolio selection problem the Decision Maker considers simultaneously conflicting objectives such as rate of return, liquidity, Dividend and risk. Multi-objective programming techniques such as goal programming and compromise programming are used to choose the portfolio best satisfying the Decision Maker’s aspirations and preferences; additionally Multi Criteria Decision Making (MCDM)Techniques for dealing with portfolio selection have been used. In this article, we assume that the parameters associated with the objectives are random and normally distributed. We propose a chance constrained compromise programming model is based on compromise programming and chance constrained programming models as a deterministic transformation to multi-objective stochastic programming portfolio model. To determine the share of industry investment planning MCDM were used. The result of the planning model for portfolio selection in Tehran Stock Exchange is shown.

کلیدواژه‌ها [English]

  • Chance Constrained Programming
  • Chance constrained compromise programming
  • Compromise programming
  • Portfolio Selection

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مدیریت صنعتی
دوره 7، شماره 3
پاییز 1394
صفحه 489-510

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