بهینه سازی سبد سهام با استفاده از روش تبرید شبیه‌ سازی شده

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 کارشناس‎ارشد مدیریت مالی، دانشگاه تهران، تهران، ایران

2 دانشیار مدیریت مالی، دانشکدۀ مدیریت دانشگاه تهران، تهران، ایران

3 دانشیار مهندسی صنایع، دانشکدۀ فنی دانشگاه شاهد، تهران، ایران

چکیده

 مسئلۀ بهینه­سازی مارکویتز و تعیین مرز کارای سرمایه­گذاری، هنگامی­که وضعیت و محدودیت­های دنیای واقعی در نظر گرفته شود، به سادگی با استفاده از شیوه­های دقیق ریاضی، مانند برنامه­ریزی درجۀ دوم، حل نمی­شود. از سوی دیگر، اغلب مدیران ترجیح می­دهند به جای مدیریت سبد بسیار بزرگ، سبد کوچکی از دارایی­ها را اداره کنند. این مسئله را می‎توان به محدودیت­های کاردینال، یعنی محدودیت­های حداقل و حداکثر تعداد دارایی­های سبد تشبیه کرد. پژوهش پیش رو با بهره‎مندی از الگوریتم فرا­ابتکاری تبرید شبیه‎سازی‎شده، به حل مسئلۀ بهینه­سازی سبد با محدودیت­های کاردینال پرداخته است. بدین منظور با استفاده از اطلاعات سهام پنجاه شرکت فعال­تر در بورس اوراق بهادار تهران در فاصلۀ زمانی اول فروردین 1389 تا پایان فروردین 1391، مرز کارای سبدهای مختلف 10 تا 50 سهمی ترسیم شده است. نتایج پژوهش موفقیت الگوریتم تبرید شبیه­سازی‎شده را در حل مسئلۀ فوق نشان می‎دهد. همچنین با انتخاب درست سهام و تعیین وزن­های مناسب از آن، می­توان سبد­های کوچک‎تری که عملکرد مناسب­تری دارند، انتخاب کرد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Portfolio optimization with simulated annealing algorithm

نویسندگان [English]

  • Saeid Qodsi 1
  • Reza Tehrani 2
  • Mahdi Bashiri 3
1 Master of Financial Management, University of Tehran, Iran
2 Associate Prof., Financial Management, University of Tehran, Iran
3 Associate Prof., Industrial Engineering, University of Shahed, Iran
چکیده [English]

The Markowitz issue of optimization can’t be solved by precise mathematical methods such as second order schematization, when real world condition and limitations are considered. On the other hand, most managers prefer to manage a small Portfolio of available assets in place of a huge Portfolio. It can be analogized to cardinal constrains, that is, constrains related to minimum and maximum current assets on Portfolios. This study aims to solve the problem of optimizing Portfolios with cardinality constrains, using simulated annealing algorithm. Therefore, by using the information of 50 companies which have been more active in Tehran’s exchange stock from April 2010 to April 2012, Portfolios’ efficient frontier has been supposed from 10 to 50. Results shows that first, simulated annealing algorithm has been successful in solving the above problem, and second, by selecting shares appropriately and determining suitable weights from it, smaller Portfolios with more suitable performances can be selected.

کلیدواژه‌ها [English]

  • cardinality constrains
  • efficient frontier
  • Mean-variance model
  • optimization portfolios
  • Simulated Annealing
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