نوع مقاله : مقاله پژوهشی

نویسندگان

گروه مهندسی صنایع، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.

چکیده

در این مقاله، ابتدا با استفاده از روش تحلیل پوششی داده‌ها، کاراترین شرکت‌های پذیرفته‌شده در بورس اوراق بهادار تهران تعیین می‌گردد. این روش در مورد شرکت‌های حاضر در سه صنعت بانکداری، پتروشیمی و دارویی بررسی می‌گردد تا شرکت‌های کارا در هر صنعت شناخته شوند. شرکت‌های کارا و ناکارا را مشخص، شرکت‌های ناکارا را رتبه‌بندی و برای انتخاب سبد سهام بهینه از بین شرکت‌های کارا استفاده می‌شود. در ادامه با استفاده از روش برنامه‌ریزی آرمانی درصد سرمایه‌گذاری سهم هر شرکت در سبد سهام محاسبه می‌گردد. در این روش یک‌بار تنها بازده و ریسک سهم به‌عنوان متغیرهای مدل در نظر گرفته می‌شوند و بار دیگر متغیر نقدشوندگی به آن‌ها اضافه می‌شود تا تاثیر این متغیر نیز بررسی گردد. درنهایت، مدل‌ها با داده‌های واقعی استخراج‌شده از صورت‌های مالی شرکت‌های مربوطه و بانک اطلاعاتی بورس اوراق بهادار تهران مورد ارزیابی قرار گرفته و نتایج پژوهش حاصل مورد تحلیل قرار گرفت.

کلیدواژه‌ها

عنوان مقاله [English]

The Application of Data Envelopment Analysis in Determining Efficient Companies in the Stock Exchange

نویسندگان [English]

  • Morteza Joshghanizadeh
  • Maleeha Sabzevari

Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

چکیده [English]

In this article, the most efficient companies admitted to the Tehran Stock Exchange are determined by using the data coverage analysis method. This method is examined for companies in three industries: banking, petrochemical, and pharmaceutical, so that the efficient companies in each industry are recognized. Efficient and ineffective companies are identified and ineffective companies are ranked and used to select the optimal stock portfolio among efficient companies. Next, using the ideal planning method, the investment percentage of each company's share in the stock portfolio is calculated. In this method, once only the yield and risk of the share are considered as variables of the model, and another liquidity variable is added to them so that the effect of this variable is also investigated. Finally, the models were evaluated with real data extracted from the financial statements of the relevant companies and the database of the Tehran Stock Exchange, and the results of the research were analyzed.

کلیدواژه‌ها [English]

  • Portfolio
  • Ideal planning
  • Data envelopment analysis
  • Return and share risk
[1]   Yang, W., Cai, L., Edalatpanah, S. A., & Smarandache, F. (2020). Triangular single valued neutrosophic data envelopment analysis: Application to hospital performance measurement. Symmetry, 12(4), 588. DOI:10.3390/SYM12040588
[2]   Arasu, B. S., Kannaiah, D., Nancy Christina, J., & Shabbir, M. S. (2021). Selection of variables in data envelopment analysis for evaluation of stock performance. Management and labour studies, 46(3), 337–353. DOI:10.1177/0258042X211002511
[3] Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the royal statistical society series A: statistics in society, 120(3), 253–281.
[4]   Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429–444.
[5]   Powers, J., & McMullen, P. (2000). Using data envelopment analysis to select efficient large market cap securities. Journal of business and management, 7(2), 31–42. http://www.joydivisionman.com/vita/jbam2.pdf
[6]   Haslem, J. A., & Scheraga, C. A. (2006). Data envelopment analysis of morningstar’s small-cap mutual funds. The journal of investing, 15(1), 87–92. DOI:10.3905/joi.2006.616858
[7]   Baihaqi, I., Lazakis, I., & Supomo, H. (2024). A novel shipyard performance measurement approach through an integrated Value Engineering and Risk Assessment (VENRA) framework using a hybrid MCDM tool. Proceedings of the institution of mechanical engineers part m: journal of engineering for the maritime environment, 14750902231219532. DOI:10.1177/14750902231219533
[8]   Bowlin, W. F. (1999). An analysis of the financial performance of defense business segments using data envelopment analysis. Journal of accounting and public policy, 18(4–5), 287–310. DOI:10.1016/S0278-4254(99)00018-6
[9]   Edalatpanah, S. A., Godarzi Karim, R., Khalilian, B., & Partouvi, S. (2020). Data envelopment analysis and efficiency of firms: a goal programing approach. Innovation management and operational strategies, 1(1), 1-16. (In Persian). https://www.journal-imos.ir/article_122018.html?lang=en
[10] Mousavi Arab, S. A., Homayounfar, M., & Ajalli, M. (2022). Balanced performance evaluation of B2C online stores with using a hybrid fuzzy ANP and fuzzy WASPAS approach. Journal of decisions and operations research, 6(Spec. Issue), 1–14. (In Persian). https://www.journal-dmor.ir/article_140799.html?lang=en
[11] Donyavi Rad, M., Sadeh, E., Amini Sabegh, Z., & Ehtesham Rasi, R. (2023). Introducing a fuzzy robust integrated model for optimizing humanitarian supply chain processes. Journal of applied research on industrial engineering, 10(3), 427–453.
[12] Maghbouli, M., & Yekta, A. P. (2023). Undesirable input in production process: a DEA-based approach. Journal of operational and strategic analytics, 1(2), 46–54. DOI:10.56578/josa010201
[13] Jing, D., Imeni, M., Edalatpanah, S. A., Alburaikan, A., & Khalifa, H. A. E. W. (2023). Optimal selection of stock portfolios using multi-criteria decision-making methods. Mathematics, 11(2), 415. DOI:10.3390/math11020415