مدیریت استراتژیک هوشمند

مدیریت استراتژیک هوشمند

بهینه‌سازی پرتفوی سهام با رویکرد ترکیبی برنامه‌ریزی محدودیت اعتبار-استوار و مدل‌های تحلیل پوششی داده‌ها

نوع مقاله : مقاله پژوهشی

نویسندگان
1 استادیار گروه ریاضی، دانشگاه پیام نور، تهران، ایران
2 استادیار گروه حسابداری، دانشگاه پیام نور، تهران، ایران
چکیده
این پژوهش با هدف ارائه یک رویکرد نوین و جامع برای بهینه‌سازی پرتفوی سرمایه‌گذاری در بازارهای پرنوسان و با عدم قطعیت بالا انجام شده است. با توجه به اهمیت مدیریت ریسک و کسب بازده مطلوب در سرمایه‌گذاری، مدل پیشنهادی از ترکیب قدرتمند برنامه‌ریزی محدودیت اعتبار-استوار و مدل‌های تحلیل پوششی داده‌ها بهره می‌برد. این مدل به طور همزمان به دنبال بهینه‌سازی ترکیب دارایی‌ها، کاهش ریسک و افزایش بازدهی است. در این تحقیق، با استفاده از داده‌های بورس تهران، عملکرد مدل پیشنهادی در مقایسه با روش‌های سنتی ارزیابی شده است. نتایج نشان می‌دهد که مدل پیشنهادی قادر است پرتفوی‌هایی با بازدهی بالاتر و ریسک کمتر نسبت به روش‌های سنتی ایجاد کند. همچنین، این مدل انعطاف‌پذیری بالایی در برابر تغییرات ناگهانی بازار از خود نشان داده و در برابر شوک‌های اقتصادی مقاوم‌تر است.
کلیدواژه‌ها

عنوان مقاله English

Stock Portfolio Optimization with a Hybrid Approach of Credit-Rigid Constraint Programming and Data Envelopment Analysis Models

نویسندگان English

Ahmad Rezaei 1
Mehdi Khorramabadi 2
1 1. Assistant Professor, Department of Mathematics, Payame Noor University, Tehran, Iran
2 Assistant Professor, Department of Accounting, Payame Noor University, Tehran, Iran
چکیده English

This research aims to provide a new and comprehensive approach to optimizing investment portfolios in volatile and highly uncertain markets. Given the importance of risk management and achieving optimal returns in investment, the proposed model utilizes a powerful combination of credit-constrained programming and data envelopment analysis models. This model simultaneously seeks to optimize asset mix, reduce risk, and increase returns. In this research, using Tehran Stock Exchange data, the performance of the proposed model has been evaluated in comparison to traditional methods. The results show that the proposed model is able to create portfolios with higher returns and lower risks than traditional methods. Also, this model has shown high flexibility against sudden market changes and is more resistant to economic shocks.

کلیدواژه‌ها English

Portfolio optimization
uncertainty
credit-robust constraint programming
data envelopment analysis models
and stock selection
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