Yıl 2019, Cilt 7 , Sayı 1, Sayfalar 55 - 70 2019-06-30

Fuzzy Decision Making Methodology for Portfolio Selection Problem Under Uncertainty: An Application at Borsa İstanbul (BIST)
Belirsizlik Altında Portföy Seçimi Problemi için Bulanık Karar Verme Metodolojisi: Borsa İstanbul (BIST)’da Bir Uygulama

Beyza Özkök [1]


Evaluation of investment alternatives, taking effective and efficient investment decisions are became one of the most important decision-making problems in human history. Portfolio management and selection are the subject of interest of scientists and the practitioners at the business world for many years. More specifically, the decision-making problem is to decide which stocks are to be chosen for investment and in what proportions they will be bought. In this study, we handled the portfolio selection problem under uncertainty. In this context; we used minimum criterion, co-probability criterion, regret criterion, optimistic criterion, geometric mean and harmonic mean. The membership functions created with the help of the characteristics of used criteria, and we tried to provide consistent investment decisions by using these memberships for evaluating alternative stocks. While portfolio selection under uncertainty, the membership functions created by examining only the data obtained from previous periods of financial ratios of companies. During the analysis, no need to use expert opinion is a strong aspect of the methodology used in the decision-making.
Yatırım alternatiflerinin etkin bir şekilde değerlendirilmesi ve verimli yatırım kararlarının alınabilmesi insanlık tarihinin en önemli karar problemlerden birini oluşturmuştur. Portföy yönetimi ve seçimi uzun yıllardır hem bilim adamlarının hem de iş dünyasındaki uygulamacıların ilgisini çeken bir konu olmuştur. Yatırımcıların hangi yatırım araçlarından ne oranda portföylerine almaları gerektiği sorusu portföy seçimi problemini doğurmuştur. Bu çalışmada belirsizlik altında portföy seçimi ele alınmış ve bu kapsamda sırasıyla Minimum, Eş Olasılık, Pişmanlık, İyimserlik, Geometrik ve Harmonik Ortalama kriterleri kullanılarak portföy seçimi yapılmıştır. Bu kriterler ışığında farklı tip yatırımcılar için planlar önerilmiştir. Belirsizlik altında portföy seçimi yapılırken sadece şirketlerin geçmiş dönem verileri incelenerek elde edilen finansal oranlarına bakılarak ve kullanılan kriterlerin karakteristikleri yardımıyla üyelik fonksiyonları oluşturulmuştur. Analiz yapılırken uzman görüşlerine başvuru ihtiyacı duyulmaması, kullanılan karar verme metodolojisinin kuvvetli ve pratik yönüdür.
  • Alexander, G. J., Sharpe, W. F., & Bailey, J. V. (1999). Fundamentals of investments. Pearson College Division, six ed.
  • Bhattacharyya, R., Kar, S., & Majumder, D. D. (2011). Fuzzy mean–variance–skewness portfolio selection models by interval analysis. Computers & Mathematics with Applications, 61(1), 126-137.
  • Bilbao-Terol, A., Pérez-Gladish, B., Arenas-Parra, M., & Rodríguez-Uría, M. V. (2006). Fuzzy compromise programming for portfolio selection. Applied Mathematics and computation, 173(1), 251-264.
  • Durer, S., Ahlatcioglu, M., & Tiryaki, F. (1994). Ideal menkul kiymet portföyü olusturmada analitik hiyerarsi yaklasimi. Arastırma Sempozyumu, 94, 21-23.
  • Giove, S., Funari, S., & Nardelli, C. (2006). An interval portfolio selection problem based on regret function. European Journal of Operational Research, 170(1), 253-264.
  • Huang, J. J., Tzeng, G. H., & Ong, C. S. (2006). A novel algorithm for uncertain portfolio selection. Applied Mathematics and computation, 173(1), 350-359.
  • Huang, X. (2011). Mean-risk model for uncertain portfolio selection. Fuzzy Optimization and Decision Making, 10(1), 71-89.
  • Inuiguchi, M., & Ramık, J. (2000). Possibilistic linear programming: a brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem. Fuzzy sets and systems, 111(1), 3-28.
  • Inuiguchi, M., & Tanino, T. (2000). Portfolio selection under independent possibilistic information. Fuzzy sets and systems, 115(1), 83-92.
  • Lacagnina, V., & Pecorella, A. (2006). A stochastic soft constraints fuzzy model for a portfolio selection problem. Fuzzy sets and systems, 157(10), 1317-1327.
  • 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, X., Guo, S., & Yu, L. (2015). Skewness of fuzzy numbers and its applications in portfolio selection. IEEE Transactions on Fuzzy Systems, 23(6), 2135-2143.
  • Markowitz, H. M. (1952). Portfolio Selection/Harry Markowitz. The Journal of Finance, 7(1), 77-91.
  • Ong, C. S., Huang, J. J., & Tzeng, G. H. (2005). A novel hybrid model for portfolio selection. Applied Mathematics and computation, 169(2), 1195-1210.
  • Parra, M. A., Terol, A. B., & Urıa, M. R. (2001). A fuzzy goal programming approach to portfolio selection. European Journal of Operational Research, 133(2), 287-297.
  • Tanaka, H., & Guo, P. (1999). Portfolio selection based on upper and lower exponential possibility distributions. European Journal of operational research, 114(1), 115-126.
  • Tanaka, H., Guo, P., & Türksen, I. B. (2000). Portfolio selection based on fuzzy probabilities and possibility distributions. Fuzzy sets and systems, 111(3), 387-397.
  • Tiryaki, F. (2001). The use of data envelopment analysis for stocks selection on Istanbul stock exchange. In PICMET'01. Portland International Conference on Management of Engineering and Technology. Proceedings Vol. 1: Book of Summaries (IEEE Cat. No. 01CH37199) (Vol. 1, pp. 373-vol). IEEE.
  • Tiryaki, F., & Ahlatcioglu, M. (2005). Fuzzy stock selection using a new fuzzy ranking and weighting algorithm. Applied Mathematics and Computation, 170(1), 144-157.
  • Tiryaki, F., & Ahlatcioglu, B. (2009). Fuzzy portfolio selection using fuzzy analytic hierarchy process. Information Sciences, 179(1-2), 53-69.
  • T.L. Saaty, (1980). The Analytic Hierarchy Process, McGraw-Hill. New York.
  • 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.
  • Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353.
  • Zimmermann, H. J. (2011). Fuzzy set theory—and its applications. Springer Science & Business Media.
  • Zhang, W. G., Wang, Y. L., Chen, Z. P., & Nie, Z. K. (2007). Possibilistic mean–variance models and efficient frontiers for portfolio selection problem. Information Sciences, 177(13), 2787-2801.
  • Zhou, X., Wang, J., Yang, X., Lev, B., Tu, Y., & Wang, S. (2018). Portfolio selection under different attitudes in fuzzy environment. Information Sciences, 462, 278-289.
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Orcid: 0000-0003-2763-1665
Yazar: Beyza Özkök (Sorumlu Yazar)
Kurum: YILDIZ TECHNICAL UNIVERSITY, FACULTY OF SCIENCE AND LETTERS
Ülke: Turkey


Tarihler

Başvuru Tarihi : 26 Şubat 2019
Kabul Tarihi : 22 Mart 2019
Yayımlanma Tarihi : 30 Haziran 2019

APA Özkök, B . (2019). Belirsizlik Altında Portföy Seçimi Problemi için Bulanık Karar Verme Metodolojisi: Borsa İstanbul (BIST)’da Bir Uygulama. Alphanumeric Journal , 7 (1) , 55-70 . DOI: 10.17093/alphanumeric.532667