پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 25 |
| تعداد شماره‌ها | 931 |
| تعداد مقالات | 7,652 |
| تعداد مشاهده مقاله | 12,492,032 |
| تعداد دریافت فایل اصل مقاله | 8,884,364 |
بکارگیری رویکرد تصمیم گیری کلامی و بهینه سازی چندهدفه فازی در انتخاب سبد سهام | ||
| راهبرد مدیریت مالی | ||
| مقاله 10، دوره 11، شماره 1 - شماره پیاپی 40، فروردین 1402، صفحه 211-230 اصل مقاله (510.72 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22051/jfm.2019.25913.2074 | ||
| نویسندگان | ||
| سارا بیک جانی1؛ حسین دیده خانی* 2 | ||
| 1دانشجو، گروه مهندسی صنایع، واحد علی آباد کتول، دانشگاه آزاد اسلامی، علی آباد کتول، ایران | ||
| 2استادیار، گروه مهندسی صنایع، واحد علی آباد کتول، دانشگاه آزاد اسلامی، علی آباد کتول، ایران | ||
| چکیده | ||
| در این مقاله به برخی از چالش‌های بهینه‌سازی پرتفوی به‌طور همزمان پرداخته می‌شود. به‌طوری‌که جهت در نظرگرفتن ماهیت چندمعیاره بودن انتخاب سهام و عدم‌قطعیت مرتبط با نرخ بازده دارایی‌ها از مدل برنامه‌ریزی چندهدفه فازی استفاده شد. همچنین با توجه به نقاط ضعف معیارهای ریسک سنتی نظیر واریانس برای اندازه‌گیری ریسک سرمایه‌گذار، معیار ارزش در معرض خطر میانگین به‌عنوان یک معیار ریسک منسجم با رویکرد تئوری اعتبار فازی جایگزین آن‌ها شدند. از طرفی در این پژوهش به‌منظور دخالت‌دادن نظرات و قضاوت‌های ذهنی سرمایه‌گذاران از روش ZAPROS III استفاده و با محاسبه شاخص رسمی کیفیت (FIQ) دیدگاه‌های سرمایه‌گذاران در بهینه‌سازی پرتفوی لحاظ گردید. در طراحی مدل علاوه‌بر محدودیت‌های اصلی، محدودیت‌هایی مانند حداقل و حداکثر تخصیص ثروت به هر دارایی و نیز حداقل و حداکثر تعداد سهام موجود در پرتفوی در نظر گرفته شده است. جهت نمایش قابلیت کاربرد مدل توسعه داده شده از 10 شرکت فعال‌تر پذیرفته شده در بورس اوراق بهادار تهران استفاده شد. نتایج حاصل از اجرای مدل با استفاده از الگوریتم MOPSO نشان داد پرتفوهای پارتو بهینه ایجاد شده از اجرای مدل در مقایسه با پرتفوهای با وزن‌های تصادفی از لحاظ رسیدن به اهداف از پیش‌تعیین شده، عملکرد بهتر و مطلوب‌تری دارند | ||
| کلیدواژه‌ها | ||
| بهینه‌سازی چند هدفه پرتفوی؛ تئوری اعتبار؛ روش ZAPROS III؛ الگوریتم .MOPSO | ||
| عنوان مقاله [English] | ||
| Applying Verbal Decision Making and Multi-objective Fuzzy Optimization Approach in Portfolio Selection | ||
| نویسندگان [English] | ||
| Sara Beykjani1؛ Hosein Didehkhani2 | ||
| 1Student, Department of Industrial Engineering, Aliabad Katul Branch, Islamic Azad University, Aliabad Katul, Iran | ||
| 2Assistant Professor, Department of Industrial Engineering, Aliabad Katul Branch, Islamic Azad University, Aliabad Katul, Iran | ||
| چکیده [English] | ||
| Abstract In this paper, some of the challenges of portfolio optimization are discussed simultaneously. So that the fuzzy multi-objective programming model was used to consider the multi-criteria nature of stock selection and the lack of correlation with the return on assets. Also, due to the weaknesses of traditional risk measures such as variance for risk assessment of the investor, the criterion of value at risk was replaced as a coherent risk criterion with the fuzzy credit theory approach. On the other hand, in this research, ZAPROS III method was used to interfere with investors' subjective opinions and judgments, and by considering the formal index of quality (FIQ), the views of investors in portfolio optimization were considered. In designing the model, in addition to the main constraints, limitations such as the minimum and maximum allocation of wealth to each asset, as well as the minimum and maximum number of stocks in the portfolio are considered. To demonstrate the applicability of the developed model, 10 of the more active companies accepted in Tehran Stock Exchange were used. The results of model implementation using the MOPSO algorithm showed that optimal pareto-optimized models of model execution compared to randomly assigned portfolios have better and more favorable performance in terms of achievement of predetermined goals. | ||
| کلیدواژه‌ها [English] | ||
| Multi-objective Optimization of Portfolio, Credit theory, ZAPROS III Method, MOPSO Algorithm | ||
|
سایر فایل های مرتبط با مقاله
|
||
| مراجع | ||
|
Alexander, G. J., & Baptista, A. M. (2004)." A comparison of VaR and CVaR constraints on portfolio selection with the mean-variance model". Management science, 50(9), 1261-1273.
Andersson, F., Mausser, H., Rosen, D., & Uryasev, S. (2001). "Credit risk optimization with conditional value-at-risk criterion". Mathematical Programming, .89(2), 273-291.
Artzner, P., Delbaen, F., Eber, J. M., & Heath, D. (1999). "Coherent measures of risk". Mathematical finance, 9(3), 203-228.
Behzadi, A., Bakhtiari, M. (2014). "A Model Based on Average-Entropy- Skillet for Optimization of Stock Basket in Fuzzy Environment". Journal of Financial Engineering and Management of Securities, Summer 2014, Issue 19, 39-56. (In Persian)
Ben-Tal, A., & Nemirovski, A. (2002). "Robust optimization–methodology and applications". Mathematical Programming, 92(3), 453-480.
Chen, Y., Liu, Y. K., & Chen, J. (2006). "Fuzzy portfolio selection problems based on credibility theory". Advances in Machine Learning and Cybernetics, 377-386.
Chunhachinda, P., Dandapani, K., Hamid, S., & Prakash, A. J. (1997). "Portfolio selection and skewness: Evidence from international stock markets". Journal of Banking & Finance, 21(2), 143-167.
Didehkhani, H., Hojjati Ostani, S. (2017). "Multi-objective programming model for stock selection with consideration of fuzzy risk value: fuzzy credit theory theory approach". Financial Engineering and Management of Securities, Vol. 8 (32), 239-268. (In Persian)
Feinstein, C. D., & Thapa, M. N. (1993). "A Reformulation of a Mean-absolute Deviation Portfolio Optimization Model". Management Science, 39(12).
Grootveld, H., & Hallerbach, W. (1999). "Variance vs downside risk: Is there really that much difference? ". European Journal of operational research, 114(2), 304-319.
Gupta, P., Mehlawat, M. K., Inuiguchi, M., & Chandra, S. (2014). "Fuzzy Portfolio Optimization ". Springer-Verlag, Berlin.
Huang, X. (2006). "Fuzzy chance-constrained portfolio selection". Applied mathematics and computation, 177(2), 500-507.
Huang, X. (2008). "Mean-variance model for fuzzy capital budgeting". Computers & Industrial Engineering, 55(1), 34-47.
Huang, X. (2008). "Risk curve and fuzzy portfolio selection". Computers & Mathematics with Applications, 55(6), 1102-1112.
Huang, X. (2008). "Mean-entropy models for fuzzy portfolio selection". IEEE Transactions on Fuzzy Systems, 16(4), 1096-1101.
Katagiri, H., & Ishii, H. (1999). "Fuzzy portfolio selection problem". In Systems, Man, and Cybernetics, IEEE SMC'99 Conference Proceedings, IEEE International Conference on, Vol. 3, 973-978.
Konno, H., & Yamazaki, H. (1991). "Mean-absolute deviation portfolio optimization model and its applications to Tokyo stock market". Management science, 37(5), 519.
Larichev, O.I., (2001)." Ranking multicriteria alternatives: The method ZAPROS III." European Journal of Operational Research, 131, 550- 558.
León, T., Liern, V., & Vercher, E. (2002). "Viability of infeasible portfolio selection problems: A fuzzy approach". European Journal of Operational Research, 139(1), 178-189.
Leung, P. l., Ng lui, K., wong, W. (2012). "An improved estimation to make Markowitz’s portfolio optimization theory users friendly and estimation accurate with application on the US stock market investment ". 85-98.
Li, X., Qin, Z., & Kar, S. (2010). "Mean-variance-skewness model for portfolio selection with fuzzy returns". European Journal of Operational Research, 202(1), 239-247.
Li, J., & Xu, J. (2009). "A novel portfolio selection model in a hybrid uncertain environment". Omega, 37(2), 439-449.
Liu, B. D. (2004). "Uncertain theory: An introduction to its axiomatic foundation". Berlin: Springer-Verlag.
Liu, B., & Liu, Y. K. (2008)." Expected value of fuzzy variable and fuzzy expected value models". Fuzzy Systems, IEEE Transactions on, 10(4), 445-450. Finance 14 ; 107–123.
Markowitz, H. (1952). "Portfolio selection". The journal of finance, 7(1), 77-91.
Markowitz, H., & Selection, P. (1959). "Efficient diversification of investments". John Wiley and Sons, 12, 26-31.
Mohammadi, M., Barati, M., A., & Naderi, B. (2015). "Selection of Fuzzy Multi-Phase Investment Basis Using Faraborative Method". Master's thesis, Faculty of Engineering and Engineering, Kharazmi University. (In Persian)
Moushakhian, S., Najafi, A., A. (2015). "Optimization of Investment Basis Using Multi-Objective Particle Swarm Algorithm for Multi-Term Multiplier-Half-Variance-Skidding Model". Journal of Financial Engineering and Management of Securities, Vol. 23, 133-147. (In Persian)
Pakmaram, A., Bahri Thales, J., & Valizadeh, M. (2017). "Portfolio Selection and Optimization Using Genetic Algorithm Using Markovitz Half-Mean Mean Model". Journal of Financial Engineering and Securities Management, No. 31. (In Persian)
Peng, J. (2011). "Credibilistic value and average value at risk in fuzzy risk analysis". Fuzzy Information and Engineering, 3(1), 69-79.
Rachev, S. T., Stoyanov, S. V., & Fabozzi, F. J. (2008). "Advanced stochastic models, risk assessment, and portfolio optimization: The ideal risk, uncertainty, and performance measures". John Wiley & Sons, Vol. 149.
Rockafellar, R. T., & Uryasev, S. (2000)." Optimization of conditional value-at-risk". Journal of risk, 2, 21-42.
Rockafellar, R. T., Uryasev, S., & Zabarankin, M. (2006)." Generalized deviations in risk analysis". Finance and Stochastics, 10(1), 51-74.
Rostami, M., R., Kalantari Banejar, M., & Behzadi, A. (2015) "Higher momentum in optimizing stock portfolio in fuzzy environment". Journal of Financial Engineering and Management of Securities, No. 24, 41-61. (In Persian)
Shahmohammadi, M., Emami-Mibdi, L., & Zare mehrjjerdi, Y. (2012). "Presentation of Combined Intelligent Algorithm Based on the Fuzzy Mean-Variance-Skillet Model for Portfolio Selection". International Journal of Industrial Engineering and Management, Vol. 4, No. 23, 448-458. (In Persian)
Speranza, M. G. (1993)." Linear programming models for portfolio optimization". J.
Tamanini, I., Machado, T. C. S., Mendes, M. S., Carvalho, A. L., Furtado, S., Pinheiro, P. R. (2008). "A model for mobile television applications based on verbal decision analysis, In: Elleithy, K. (ed.) ". Advances and Innovations in Systems, Computing Sciences and Software Engineering, vol. 19.
Uryasev, S. (2000). "Conditional value-at-risk: Optimization algorithms and applications". In Computational Intelligence for Financial Engineering, (CIFEr) Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on ,49-57
Watada, J. (1997). "Fuzzy portfolio selection and its applications to decision making". Tatra Mountains Mathematical Publication, 13(4), 219-248.
Xia, Y., Liu, B., Wang, S., & Lai, K. K. (2000). "A model for portfolio selection with order of expected returns". Computers & Operations Research, 27(5), 409-422.
Yoshimoto, A. (1996)." The mean-variance approach to portfolio optimization subject to transaction costs". Journal of the Operations Research Society of Japan, 39(1), 99-117.
Zhang, W. G., Liu, Y. J., & Xu, W. J. (2014)." A new fuzzy programming approach for multi-period portfolio optimization with return demand and risk control". Fuzzy Sets and Systems, 246, 107-126.
Zhang, W. G., & Xiao, W. L. (2009). "On weighted lower and upper possibilistic means and variances of fuzzy numbers and its application in decision". Knowledge and information systems, 18(3), 311-330. | ||
|
آمار تعداد مشاهده مقاله: 1,076 تعداد دریافت فایل اصل مقاله: 500 |
||
