ارائه‌ی مدل برنامه ریزی استوار امکانی برای انتخاب سبد سهام بر مبنای نسبت شارپ

محورهای موضوعی : دانش مالی تحلیل اوراق بهادار

مقصود امیری ¹ ( استاد گروه مدیریت صنعتی دانشکده حسابداری و مدیریت دانشگاه علامه طباطبایی، تهران، ایران )
محمدسعید حیدری ² ( دانشجوی دکترای مدیریت مالی دانشگاه علامه طباطبایی، تهران، ایران. )

تاریخ دریافت : 1398/01/31 تاریخ پذیرش : 1398/03/13 تاریخ انتشار : 1399/07/01

کلید واژه: برنامه‌ریزی استوار امکانی, نسبت شارپ, بهینه سازی سبد, بهینه سازی فازی,

چکیده مقاله :

مسئله انتخاب سبد[i] سرمایه‌گذاری یکی از مهم‌ترین مسائل در حوزه مالی است که در آن تلاش می شود تا در طول چند دورۀ زمانی بودجه مشخص‌شده را طوری بین دارایی ها توزیع نمود که بازده[ii] سبد[iii] سرمایه‌گذاری بیشینه و درعین‌حال ریسک آن از یک حد معین بیشتر نشود. در این مقاله ابتدا یک مدل برنامه ریزی[iv] ریاضی غیرخطی[v] مختلط برای مسئله‌ی انتخاب سبد سهام جهت بیشینه‌سازی نسبت های شارپ سهام پیشنهاد و آزمون شده است. سپس به واسطه ی طبیعت غیرقطعی پارامترهای ورودی چنین مسئله ای، یک مدل جدید برنامه ریزی امکانی استوار که قدرت تنظیم درجه استواری تصمیمات خروجی در برابر عدم قطعیت پارامترها را دارد، توسعه داده شده است. جهت بررسی عملکرد مدل، در ابتدا مدل پیشنهادی بر روی 42 شرکت فعال(دارای بیشترین تعداد روز معاملاتی) در بازار بورس اوراق بهادار تهران، در دوره زمانی بهار 1397تست و ارزیابی شده است. در پایان نتایج محاسباتی کارایی مدل پیشنهادی، کیفیت بالای عملکرد و کاربردی بودن مدل برنامه ریزی امکانی استوار پیشنهادی را نشان میدهد. [i] Portfolio selection [ii] return [iii] portfolio [iv] programming [v] Non linear

چکیده انگلیسی:

Portfolio selection and asset management is one of the most important financial issues that seeks to distribute a specified budget over multiple time periods between available assets in such a way that the return of the portfolio is maximized and, at the same time, its risk does not exceed a certain amount. In this paper, we first propose a nonlinear mathematical programming model for Portfolio selection to maximize Sharpe ratios of stocks. Then, due to the uncertain nature of the input parameters of such a problem, a new robust possibilistic programming model has been developed, which is capable of adjusting the robust degree of output decisions to the uncertainty of the parameters. The proposed model was first tested and evaluated on 42 companies active in the Tehran stock market. In the end, the computational results of the proposed model show the high performance and the utility of the robust possibilistic programming model.

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