انتخاب سبد دارایی سهام مبتنی بر ریسک و بازده سبد دارایی: مورد مطالعه بازار بورس تهران
محورهای موضوعی : فصلنامه اقتصاد محاسباتیلیلا آسیابی اقدم 1 , محمد باقری 2
1 - دانشگاه آزاد
2 - دانشجوی/ دکترا/ دانشگاه ازاد اسلامی/ واخد زنجان
کلید واژه: سبد دارایی, سهام , ریسک و بازده ,
چکیده مقاله :
انتخاب سبد سهام در مباحث سرمایهگذاری کار دشوار و سختی است تصمیمگیری درباره اینکه کدام سهم در مقایسه با سایر سهام در وضعیت بهتری قرار دارد و شایستگی انتخاب شدن و قرار گرفتن در سبد سرمایهگذاری فرد را دارد و چگونگی تخصیص سرمایه بین این اوراق، مباحثی پبچیده است. با توجه اهمیت موضوع؛ هدف اصلی این تحقیق بررسی انتخاب سبد دارایی سهام مبتنی بر روش ، ریسک و بازده بورس در بازار بورس تهران بود. این مطالعه از حیث هدف کاربردی و از نظر جمع آوری داده تا و اطلاعات توصیفی از نوع علی بود. روش ﺷﻨﺎﺳﻲ از ﻧﻮع ﭘﺲ روﻳﺪادي اﺳﺖ ، داده¬های جمع¬آوری شده بهصورت سالانه از 1391 الی 1402 که شامل بیست شرکت فعال در بازار بورس ایران می¬باشد. در ادامه با استفاده حداقل کردن ریسک بر اساس مدل مارکوتیز سبد بهینه انتخاب گردید. نتایج و تجزیه و تحلیل نشان میدهد، انتخاب سبد کارا براساس نمودار مرز کارایی بازده آخرین قیمت سهام شرکت¬ها بر اساس بازده و ریسک به چادر ملو، پتروشیمی خارک، فولاد مبارکه ریسک بیشتر و بازده خیلی خیلی کمی دارند؛ و نباید انتخاب گردد.
Extended Abstract
Purpose
Objective: Choosing a stock portfolio in investment discussions is a difficult and difficult task, deciding which stock is in a better condition compared to other stocks and deserves to be selected and placed in one's investment portfolio, and how to allocate capital between these stocks It is packed. The main purpose of this article is to choose a stock portfolio based on risk and portfolio returns: the case study of the Tehran stock market.
Methodology
The research method of the current research is based on the purpose of the research (assessing the performance of risk and portfolio returns in the selection of asset portfolios in the Tehran Stock Exchange market) of an applied type, which is through mean-variance designed by Markowitz, the average expected return and variance It shows the portfolio risk. Collecting information and data in conventional methods (risk and return of asset portfolio) in order to test the hypotheses, in order to fulfill the goals and finally answer the questions raised and faced by this research, according to the developed models and the studied variables from the audited financial statements of the companies. Tehran Stock Exchange and in some cases using "Rehvard Naveen" information software and websites related to Tehran Stock Exchange which contain data of Tehran capital market, it has been compiled in the period of 1391 to 1402. From the mean-variance model and to obtain the optimal capital portfolio selection in the Markowitz method, which has the minimum variance, the linear programming model is used.
Finding
Strategy one shows; The investor should allocate 0.041% of his chosen portfolio to Khark Petrochemical shares; Allocate 0.065 to the share of Finavaran Petrochemical, 0.2030 to the share of Rohtargar, 0.0357 to the share of Pars Industrial Carbon Black, 0.407 to the mineral processing and 0.2477 to the share of Amir Kabir Kashan Steel. The second strategy shows; The investor should allocate 0.072 to the shares of Fanavaran Petrochemical, 0.1422 to the shares of Rohtargar, 0.0448 to the shares of Pars Industrial Carbon Black, 0.4058 to the mineral processing, 0.275 to the shares of Amir Kabir Kashan Steel and allocate 0.0592 to the share of pharmaceutical factories. The third strategy shows; The investor should invest 0.098/098 in the share of Finavaran Petrochemical, 0.0161/0 in the share of Rotagar, 0.0436/0 in the share of Pars Industrial Carbon Black, 0.3770/0 in the processing of minerals, 00/3216 in the share of Amir Kabir Kashan Steel and 1626/0. allocate 0/0 to the share of pharmaceutical factories. The fourth strategy shows; The investor should allocate 0.1159/0 to Fanavaran petrochemical shares, 0.011/0 to Pars industrial carbon black shares, 0.3468/0 to mineral processing shares, 0.4174/0 to Amir Kabir Kashan steel shares and 0.1260/0 to Daropaksh factories. The fifth strategy shows; The investor must allocate its selected portfolio of 0.1159 to the Fernavaran Petrochemical Company, 0.3051 to the share of mineral processing, 087.50 to Amir Kabir Kashan Steel and 0.0704 to the share of pharmaceutical factories. The sixth strategy shows; The investor should allocate 0.1311.01311 to the petrochemical share of Fanavaran, 0.2585.000 to the share of mineral processing, 0.5950.000 to the share of Amir Kabir Kashan Steel and 0.0115 to the share of Daropakhsh factories. The seventh strategy shows; The investor should allocate 0.1377 to the share of Fan-Avaran Petrochemical, 0.6749 to the share of mineral processing and 0.6749 to the share of Amir Kabir Kashan Steel. The eighth strategy shows; The investor should allocate 0.1410/0 to the share of Fan-Avaran Petrochemical, 0.066/0 to the share of mineral processing and 0.7523 to the share of Amir Kabir Kashan Steel. The ninth strategy shows; The investor should allocate 0.1443 to the share of Fan-Avaran petrochemicals, 0.259 to the share of mineral processing and 0.8298 to the share of Amir Kabir Kashan Steel. The tenth strategy shows; The investor should allocate 100% of his chosen portfolio to Amir Kabir Kashan Steel. The eleventh strategy shows; It is better for an investor to leave the stocks of Alborzdaro, Iran Khodro, Iran Daru, Shazand Petrochemical, Tractorsazi, Chadormelo, Shimi Darupakhsh, Fars Chemical, Sepahan Industrial, Khuzestan Steel, Mobarake Isfahan Steel, Khorasan Steel, and automobile parts in their selected portfolio. Based on the performance efficiency frontier diagram, the latest stock price of the companies shows based on return and risk, for example, Amir Kabir Kashan Steel has less risk and more return than all the items. Pars industrial carbon black is less risky than Fan Avaran Petrochemicals, Chem Daro Pars. However, it is less efficient compared to Techno-Avaran petrochemicals, but it is more efficient compared to Dorofos chemical. Khuzestan Steel has more risk and zero return than all items and should not be chosen. Chader Melo, Khark Petrochemical, Mobarakeh Steel have more risk and very very little return. And should not be chosen. Choosing a stock portfolio in investment discussions is a difficult and difficult task. Deciding which stock is in a better position compared to other stocks and deserves to be selected and placed in one's investment portfolio, and how to allocate capital between these stocks, is a complex issue. Theoretically, the issue of stock portfolio selection in the case of risk minimization in the case of fixed returns can be solved by using mathematical formulas and through a quadratic equation, but in practice and in the real world, according to the number of choices Much like in capital markets, the mathematical approach used to solve this model requires extensive calculations and planning.
Conclusion
The results and analysis show that the selection of the efficient portfolio is based on the efficiency frontier diagram of the latest stock price of the companies based on yield and risk, for example; Amir Kabir Kashan steel has less risk and more yield than all the items. Pars Industrial Carbon Black is less risky than Fan Avran Petrochemical, Chemical Daro Pars. However, it is less efficient compared to Techno-Avaran petrochemicals, but it is more efficient compared to Dorofos chemical. Khuzestan steel has the highest risk and zero return of all items and should not be chosen. Chador Melo, Khark Petrochemical, Mobarakeh Steel have more risk and very very little return; And should not be chosen.
ابوالفتحی، حسن.(1395). کشف پرتفوی سهام با استفاده از محدودیت کاردینال، رساله¬ دکتری، دانشگاه آزاد اسلامی تهران واحد جنوب.
اصغرپور، حسین.؛ رضازاده، علی(1394). تعیین سبد بهینه سهام با استفاده از روش ارزش در معرض خطر، فصلنامه نظریه¬های کاربردی اقتصاد، سال دوم، شماره 4 ، صفحات 113-98.
سلامی، اکبر. اصلی¬زاده، احمد. و عسگری، محمدرضا.(1396). اطمینان بیشازحد مدیریتی، دخالت دولت و تصمیم تأمین مالی شرکتها در بورس اوراق بهادار تهران. مطالعات اقتصاد، مدیریت مالی و حسابداری، دوره 3، شماره 2: 88-72.
شاهمنصوري، اسفندیار.(1396). آزمون سبد اوراق بهادار مبتني بر راهبردهاي بنيادي،تكنيكي و شهودي با اهداف و ويژگي¬هاي رفتاري سرمايه¬گذاران بورس اوراق بهادار تهران، رساله¬ دک شريفي سليم تری، دانشگاه آزاد اسلامی واحد علوم و تحقیقات.
شريفي سليم، علیرضا.؛ مؤمنی، منصور.؛ مدرس یزدی، محمد. و راعی، رضا.(1394). برنامه¬ريزي تصادفي چندهدفه براي انتخاب سبد سهام،فصلنامه مدیریت صنعتی، دوره 7، شماره3، صحفه 510 – 489.
صالحی ، مهدی.؛ لاری دشت بیاض، محمود. و مخملباف ، نرگس.(1396). حداقل کردن واریانس پورتفوی با محدودیتهای L، فصلنامـه علمي پژوهشي دانش سرمايه¬گـذاري، سال ششم، شماره بیست ويکم، صحفه95-80.
راعي، رضا وتلنگي، احمد. (1389). مديريت سرمايهگذاري پيشرفته، چاپ اول، تهران، سمت.
Alexander, G.J., & Baptistab, A.M. (2002). Economic implications of using a Mean-Var model for portfolio selection: A comparision with Mean- Variance analysis. Journal of Economic Dynamics & Control, 26, 1159-1193.
Dowd, K., Blake, D., & Cairns, A. (2003). Long-term value at risk. Discussion paper: UBS Pensions Series 017, 468, Financial Markets Group, London School of Economics and Political Science, London, UK.
Engelbrecht, R. (2003). A comparison of Value-at-Risk methods for portfolios consisting of interest rate swaps and FRAs. Master Thesis, University of the Wiewatersrand.
Diyarbakrlolu, E., & Satman, M. H. (2013). The Maximum Diversification Index. Journal of Asset Management, 14(6), 400-409.
El hachloufi, M., & Guennoun, Z., & Hamza, F. (2012). Stocks Portfolio Optimization Using Classification and Genetic Algorithms. Applied Mathematical Sciences, 6, pp. 4673-4684
Farzi, S., & Shavazi, A. R., & Pandari, A. R. (2013). Using quantum-behaved particle swarm optimization for portfolio selection problem. International Arab Journal of Information Technology, 10(2), 111-119.
Francis, J. C., Kim, D. (2013). Modern Portfolio Theory: Foundations, Analysis, and New Developments. John Wiley & Sons.
Huang, Y.C., & Lin, B. J. (2004). Value at Risk analysis for Taiwan stock index futures: Fat tails and conditional asymmetries in return innovations. Review of Quantitative Finance and Accounting, 22, 79-95.
Li, J., & Xu, M. (2013). Optimal dynamic portfolio with Mean-CVaR criterion. Risks, 1(3), 119-147
Kirchner, U., & Zunckel, C. (2011). Measuring Portfolio Diversification, arXiv.org Quantitative Finance Paper, No. 1102.4722.
Markowitz, H. (1952). Portfolio selection. Journal of Finance, 7(1):77-91.Monahan, G. (2000). Managing Inventories in a Two-Eschelon Dual-Channel Supply Chain. European Journal of Operational Research, 162(2): 325-341.
Mir mohammadi sadrabadi, M., Moinaddin, M., & Nayebzadeh, S. (2013). Determining the optimal portfolio in Iran stock exchange by value at risk approach. Journal of basic and applied scientific research, 3(3), 813-820.
Moutameni, A., & Sharifi, S.A. (2012). Propounding a Model for Portfolio Selection in Stock Exchange by Using of MCDM (Case Study: 50 Better Companies), Journal of Industrial Management Perspective, 5, 73-89, (In Persian).
Mushkhian, S., & Najafi, A. (2016). A Possibilistic Mean-SemivarianceSkweness Model for Portfolio Selection with Multi Objective Particle
Pandari, A.R., & Azar, A., & Shavazi, A.R. (2012). Genetic algorithms for portfolio selection problem with non-linear objectives. African Journal of Business Management, 6, 6209-6216.
Sharpe, William F., Gordon J. Alexander. 1990. Investments. Fourth Edition, Prentice-Hall.
Yoon، K. P.، & Hwang، C.-L. Multiple attribute decision making: an introduction. sage university paper series on quantative applications in the social sciences، Thousand Oapks، CA.1995
Yu, X., Sun. H., & Chen, G. (2011). The optimal portfolio model based on Mean-CVaR. Journal of Mathematical Finance, 1, 132-134.