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Bist 30 Endeksinde Entropi Ve Yüksek Momentlerle Topsıs Ve Promethee Tabanlı Çok Amaçlı Portföy Seçimi Modeli Önerisi

Year 2017, Volume: 4 Issue: 4, 171 - 188, 28.12.2017
https://doi.org/10.30803/adusobed.356170

Abstract





Modern dönemde portföy seçimi, finansal karar vericilerin
ilgilendiği ve önceden tanımlı kısıtlamalar ile hedefler doğrultusunda optimum
portföy seçimi olarak tanımlanabilecek, finansın önemli bir konusudur.
Portföyler, getirileri politik kriz, finansal dalgalanmalar ve teknolojik
gelişmeler gibi farklı olaylardan etkilenebilecek birden fazla sayıda hisse
senedinden oluşmaktadır. Markowitz tarafından tanımlanan Modern Portföy Teorisi
ve Ortalama Varyans modeli sayesinde portföy riskinin düşürülebilmesi ilk defa
mantıklı bir yapıya oturmuştur. Teoriye göre karar verici, portföy riskini
kendi aralarında pozitif korelasyona sahip olan hisse senetlerini birlikte
portföye dahil etmeyerek düşürebilmektedir. Çalışmada, portföy seçim problemi
için iki aşamalı çok amaçlı portföy seçim modeli önerilmiştir. İlk olarak,
Ortalama Varyans modeli ile Pareto optimum portföyler elde edilmiştir.
Sonrasında ise TOPSIS ve PROMETHEE yöntemleri kullanılarak yatırımcı tipine
göre Pareto optimum portföyler sıralanmıştır. Entropi ve yüksek dereceden momentler,
Pareto portföyleri sıralarken kriter olarak kullanılmıştır. Test periyodunda
Pareto optimum portföylerin getiri performansları, portföy performans
ölçütlerine göre değerlendirilmiş ve değerlendirme sonuçları TOPSIS ve
PROMETHEE sıralama sonuçları ile kıyaslanmıştır. Uygulanan istatistik testleri
sonucu, önerilen PROMETHEE modelinin daha etkin sonuçlar verdiği gözlenmiştir.





References

  • AKSARAYLI, M. ve PALA, O., (2016). A Hybrid Multi-objective Optimization Approach Based on Promethee for Portfolio Selection 2016 Socio-Economic Strategies in Turkey. s:90-108.
  • ARACIOGLU, B., DEMIRCAN, F. ve SOYUER, H. (2011). Mean-Variance-Skewness-Kurtosis Approach to Portfolio Optimization: An Application in Istanbul Stock Exchange/Portföy Optimizasyonunda Ortalama-Varyans-Çarpiklik-BasiklikYaklasimi: IMKB Uygulamasi. Ege Akademik Bakis, 11, 9-17.
  • ARDITTI, F. D. (1971). Another Look At Mutual Fund Performance. Journal Of Financial And Quantitative Analysis, 6(03), 909-912.
  • ARDITTI, F. D., ve LEVY, H. (1975). Portfolio Efficiency Analysis In Three Moments: The Multiperiod Case. The Journal Of Finance, 30(3), 797-809.
  • BALLESTERO, E., GÜNTHER, M., PLA-SANTAMARIA, D., ve STUMMER, C. (2007). Portfolio Selection Under Strict Uncertainty: A Multi-Criteria Methodology And Its Application To The Frankfurt And Vienna Stock Exchanges. European Journal Of Operational Research, 181(3), 1476-1487.
  • BEHZADIAN, M., OTAGHSARA, S. K., YAZDANI, M., ve IGNATIUS, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with Applications, 39(17), 13051-13069.
  • BERA, A. K., ve PARK, S. Y. (2008). Optimal Portfolio Diversification Using The Maximum Entropy Principle. Econometric Reviews, 27(4-6), 484-512.
  • BIST web site. Available online:https://datastore.borsaistanbul.com/ (accessed on 17 September 2017).
  • BRANS, J. P. (1982). L’ingénieurie de la décision-Elaboration d’instruments d’aidea la décision. La méthode Prométhée–Dans Nadeau R. et Landry M. L'aide à la décision: nature, intruments et perspectives d'avenir-Québec, Canada, 182-213.
  • BRANS, J. P., ve VINCKE, P. (1985). Note—A Preference Ranking Organisation Method: (The PROMETHEE Method for Multiple Criteria Decision-Making). Management science, 31(6), 647-656.
  • BRANS, J. P., VINCKE, P., ve MARESCHAL, B. (1986). How to select and how to rank projects: The PROMETHEE method. European journal of operational research, 24(2), 228-238.
  • CAPORIN, M., JANNIN, G. M., LISI, F., ve MAILLET, B. B. (2014). A Survey On The Four Families Of Performance Measures. Journal Of Economic Surveys, 28(5), 917-942.
  • CHEN, W. P., CHUNG, H., HO, K. Y., ve HSU, T. L. (2010). Portfolio Optimization Models And Mean–Variance Spanning Tests. In Handbook Of Quantitative Finance And Risk Management (s: 165-184). Springer US.
  • CHUNHACHINDA, P., DANDAPANI, K., HAMID, S., ve PRAKASH, A. J. (1997). Portfolio Selection And Skewness: Evidence From International Stock Markets. Journal Of Banking & Finance, 21(2), 143-167.
  • DEMIRTAŞ, Ö. ve GÜNGÖR, Z. (2004). Portföy Yönetimi Ve Portföy Seçimine Yönelik Uygulama. Journal Of Aeronautics And Space Technologies, 1(4), 103-109.
  • EHRGOTT, M., WATERS, C., KASIMBEYLI, R., ve ÜSTÜN, O. (2009). Multiobjective Programming and Multiattribute Utility Functions in Portfolio Optimization. INFOR: Information Systems and Operational Research, 47(1), 31–42. https://doi.org/10.3138/infor.47.1.31
  • HARVEY, C. R., LIECHTY, J. C., LIECHTY, M. W., ve MÜLLER, P. (2010). Portfolio selection with higher moments. Quantitative Finance, 10(5), 469-485.
  • HUANG, X. (2012). An entropy method for diversified fuzzy portfolio selection. International Journal of Fuzzy Systems, 14(1), 160-165.
  • HÜBNER, G. (2005). The generalized Treynor ratio. Review of Finance, 9(3), 415-435.
  • HWANG, C. L., ve YOON, K. (1981). Multiple Attribute Decision Making, vol. 186 of. Lecture Notes in Economics and Mathematical Systems.
  • JANA, P., ROY, T. K., ve MAZUMDER, S. K. (2007). Multi-objective mean-variance-skewness model for portfolio optimization. Advanced Modeling and Optimization, 9(1), 181-193.
  • JOSHI, D., ve KUMAR, S. (2014). Intuitionistic Fuzzy Entropy And Distance Measure Based TOPSIS Method For Multi-Criteria Decision Making. Egyptian Informatics Journal, 15(2), 97-104.
  • JURCZENKO, E., MAILLET, B. B., ve MERLIN, P. (2005). Hedge funds portfolio selection with higher-order moments: a non-parametric mean-variance-skewness-kurtosis efficient frontier. Available at SSRN 676904.
  • KAPLAN, P. D., ve KNOWLES, J. A. (2004). Kappa: A Generalized Downside Risk-Adjusted Performance Measure. Journal Of Performance Measurement., 8, 42-54.
  • KEMALBAY, G., ÖZKUT, C. M., ve FRANKO, C. (2011). Portfolio Selection With Higher Moments: A Polynomial Goal Programming Approach To ISE-30 Index. Ekonometri Ve Istatistik Dergisi, (13), 41-61.
  • KONNO, H., SHIRAKAWA, H., ve YAMAZAKI, H. (1993). A Mean-Absolute Deviation-Skewness Portfolio Optimization Model. Annals Of Operations Research, 45(1), 205-220.
  • KONNO, H., ve SUZUKI, K. I. (1995). A mean-variance-skewness portfolio optimization model. Journal of the Operations Research Society of Japan, 38(2), 173-187.
  • LAI, K. K., YU, L., ve WANG, S. (2006, June). Mean-variance-skewness-kurtosis-based portfolio optimization. In Computer and Computational Sciences, 2006. IMSCCS'06. First International Multi-Symposiums on (Vol. 2, pp. 292-297). IEEE.
  • LEVY, H. (1974). The rationale of the mean-standard deviation analysis: Comment. The American Economic Review, 64(3), 434-441.
  • LIU, S. Y. W. S., WANG, S. Y., ve QIU, W. (2003). Mean-Variance-Skewness Model For Portfolio Selection With Transaction Costs. International Journal Of Systems Science, 34(4), 255-262.
  • MACHARIS, C., SPRINGAEL, J., DE BRUCKER, K., ve VERBEKE, A. (2004). PROMETHEE and AHP: The Design Of Operational Synergies In Multicriteria Analysis.: Strengthening PROMETHEE with ideas of AHP. European Journal of Operational Research, 153(2), 307-317.
  • MARINGER, D., ve PARPAS, P. (2009). Global Optimization Of Higher Order Moments In Portfolio Selection. Journal Of Global Optimization, 43(2-3), 219-230.
  • MARKOWITZ, H. (1952). Portfolio selection. The journal of finance, 7(1), 77-91.
  • MARKOWITZ, H. (1959). Portfolio Selection, Efficient Diversification of Investments. J. Wiley.
  • MARKOWITZ, H. M. (1991). Foundations Of Portfolio Theory. The Journal Of Finance, 46(2), 469-477.
  • MHIRI, M., ve PRIGENT, J. L. (2010). International portfolio optimization with higher moments. International Journal of Economics and Finance, 2(5), 157-169.
  • OPRICOVIC, S., ve TZENG, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European journal of operational research, 156(2), 445-455.
  • PALA, O., ve AKSARAYLI, M. (2016). Bulanik Hedef Programlama Tabanli Yüksek Dereceden Momentlerle Bist 30 Endeksinde Portföy Seçimi. Sosyal Bilimler Metinleri Dergisi. (ICOMEP16, Özel Sayı) 98-113.
  • PEZIER, J.,ve WHITE, A. (2006). The Relative Merits Of Investable Hedge Fund Indices And Of Funds Of Hedge Funds In Optimal Passive Portfolios (No. icma-dp2006-10). Henley Business School, Reading University. 1-32.
  • PRAKASH, A. J., CHANG, C. H., ve PACTWA, T. E. (2003). Selecting a portfolio with skewness: Recent evidence from US, European, and Latin American equity markets. Journal of Banking & Finance, 27(7), 1375-1390.
  • QIN, Z., LI, X., ve JI, X. (2009). Portfolio Selection Based On Fuzzy Cross-Entropy. Journal Of Computational And Applied Mathematics, 228(1), 139-149.
  • SAMUELSON, P. A. (1970). The Fundamental Approximation Theorem Of Portfolio Analysis In Terms Of Means, Variances And Higher Moments. The Review of Economic Studies, 37(4), 537-542.
  • SINGLETON, J. C., ve WINGENDER, J. (1986). Skewness Persistence In Common Stock Returns. Journal Of Financial And Quantitative Analysis, 21(03), 335-341.
  • STEINBACH, M. C. (2001). Markowitz Revisited: Mean-Variance Models In Financial Portfolio Analysis. SIAM Review, 43(1), 31-85.
  • USTA, I., ve KANTAR, Y. M. (2011). Mean-Variance-Skewness-Entropy Measures: A Multi-Objective Approach For Portfolio Selection. Entropy, 13(1), 117-133.
  • WANG, S., ve XIA, Y. (2002). Portfolio Selection And Asset Pricing (Vol. 514). Springer Science & Business Media.
  • XIDONAS, P., ASKOUNIS, D., ve PSARRAS, J. (2009). Common Stock Portfolio Selection: A Multiple Criteria Decision Making Methodology And An Application To The Athens Stock Exchange. Operational Research, 9(1), 55-79.
  • YARALIOĞLU, K. (2004). Uygulamada Karar Destek Sistemleri. İlkem Ofset, İzmir, ISBN, 975-270.
  • YUE, W., ve WANG, Y. (2017). A New Fuzzy Multi-Objective Higher Order Moment Portfolio Selection Model For Diversified Portfolios. Physica A: Statistical Mechanics and its Applications, 465, 124-140.
  • ZAKAMOULINE, V., ve KOEKEBAKKER, S. (2009). Portfolio Performance Evaluation With Generalized Sharpe Ratios: Beyond The Mean And Variance. Journal Of Banking & Finance, 33(7), 1242-1254.
  • ZHOU, R., CAI, R., ve TONG, G. (2013). Applications Of Entropy In Finance: A Review. Entropy, 15(11), 4909-4931.
Year 2017, Volume: 4 Issue: 4, 171 - 188, 28.12.2017
https://doi.org/10.30803/adusobed.356170

Abstract

References

  • AKSARAYLI, M. ve PALA, O., (2016). A Hybrid Multi-objective Optimization Approach Based on Promethee for Portfolio Selection 2016 Socio-Economic Strategies in Turkey. s:90-108.
  • ARACIOGLU, B., DEMIRCAN, F. ve SOYUER, H. (2011). Mean-Variance-Skewness-Kurtosis Approach to Portfolio Optimization: An Application in Istanbul Stock Exchange/Portföy Optimizasyonunda Ortalama-Varyans-Çarpiklik-BasiklikYaklasimi: IMKB Uygulamasi. Ege Akademik Bakis, 11, 9-17.
  • ARDITTI, F. D. (1971). Another Look At Mutual Fund Performance. Journal Of Financial And Quantitative Analysis, 6(03), 909-912.
  • ARDITTI, F. D., ve LEVY, H. (1975). Portfolio Efficiency Analysis In Three Moments: The Multiperiod Case. The Journal Of Finance, 30(3), 797-809.
  • BALLESTERO, E., GÜNTHER, M., PLA-SANTAMARIA, D., ve STUMMER, C. (2007). Portfolio Selection Under Strict Uncertainty: A Multi-Criteria Methodology And Its Application To The Frankfurt And Vienna Stock Exchanges. European Journal Of Operational Research, 181(3), 1476-1487.
  • BEHZADIAN, M., OTAGHSARA, S. K., YAZDANI, M., ve IGNATIUS, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with Applications, 39(17), 13051-13069.
  • BERA, A. K., ve PARK, S. Y. (2008). Optimal Portfolio Diversification Using The Maximum Entropy Principle. Econometric Reviews, 27(4-6), 484-512.
  • BIST web site. Available online:https://datastore.borsaistanbul.com/ (accessed on 17 September 2017).
  • BRANS, J. P. (1982). L’ingénieurie de la décision-Elaboration d’instruments d’aidea la décision. La méthode Prométhée–Dans Nadeau R. et Landry M. L'aide à la décision: nature, intruments et perspectives d'avenir-Québec, Canada, 182-213.
  • BRANS, J. P., ve VINCKE, P. (1985). Note—A Preference Ranking Organisation Method: (The PROMETHEE Method for Multiple Criteria Decision-Making). Management science, 31(6), 647-656.
  • BRANS, J. P., VINCKE, P., ve MARESCHAL, B. (1986). How to select and how to rank projects: The PROMETHEE method. European journal of operational research, 24(2), 228-238.
  • CAPORIN, M., JANNIN, G. M., LISI, F., ve MAILLET, B. B. (2014). A Survey On The Four Families Of Performance Measures. Journal Of Economic Surveys, 28(5), 917-942.
  • CHEN, W. P., CHUNG, H., HO, K. Y., ve HSU, T. L. (2010). Portfolio Optimization Models And Mean–Variance Spanning Tests. In Handbook Of Quantitative Finance And Risk Management (s: 165-184). Springer US.
  • CHUNHACHINDA, P., DANDAPANI, K., HAMID, S., ve PRAKASH, A. J. (1997). Portfolio Selection And Skewness: Evidence From International Stock Markets. Journal Of Banking & Finance, 21(2), 143-167.
  • DEMIRTAŞ, Ö. ve GÜNGÖR, Z. (2004). Portföy Yönetimi Ve Portföy Seçimine Yönelik Uygulama. Journal Of Aeronautics And Space Technologies, 1(4), 103-109.
  • EHRGOTT, M., WATERS, C., KASIMBEYLI, R., ve ÜSTÜN, O. (2009). Multiobjective Programming and Multiattribute Utility Functions in Portfolio Optimization. INFOR: Information Systems and Operational Research, 47(1), 31–42. https://doi.org/10.3138/infor.47.1.31
  • HARVEY, C. R., LIECHTY, J. C., LIECHTY, M. W., ve MÜLLER, P. (2010). Portfolio selection with higher moments. Quantitative Finance, 10(5), 469-485.
  • HUANG, X. (2012). An entropy method for diversified fuzzy portfolio selection. International Journal of Fuzzy Systems, 14(1), 160-165.
  • HÜBNER, G. (2005). The generalized Treynor ratio. Review of Finance, 9(3), 415-435.
  • HWANG, C. L., ve YOON, K. (1981). Multiple Attribute Decision Making, vol. 186 of. Lecture Notes in Economics and Mathematical Systems.
  • JANA, P., ROY, T. K., ve MAZUMDER, S. K. (2007). Multi-objective mean-variance-skewness model for portfolio optimization. Advanced Modeling and Optimization, 9(1), 181-193.
  • JOSHI, D., ve KUMAR, S. (2014). Intuitionistic Fuzzy Entropy And Distance Measure Based TOPSIS Method For Multi-Criteria Decision Making. Egyptian Informatics Journal, 15(2), 97-104.
  • JURCZENKO, E., MAILLET, B. B., ve MERLIN, P. (2005). Hedge funds portfolio selection with higher-order moments: a non-parametric mean-variance-skewness-kurtosis efficient frontier. Available at SSRN 676904.
  • KAPLAN, P. D., ve KNOWLES, J. A. (2004). Kappa: A Generalized Downside Risk-Adjusted Performance Measure. Journal Of Performance Measurement., 8, 42-54.
  • KEMALBAY, G., ÖZKUT, C. M., ve FRANKO, C. (2011). Portfolio Selection With Higher Moments: A Polynomial Goal Programming Approach To ISE-30 Index. Ekonometri Ve Istatistik Dergisi, (13), 41-61.
  • KONNO, H., SHIRAKAWA, H., ve YAMAZAKI, H. (1993). A Mean-Absolute Deviation-Skewness Portfolio Optimization Model. Annals Of Operations Research, 45(1), 205-220.
  • KONNO, H., ve SUZUKI, K. I. (1995). A mean-variance-skewness portfolio optimization model. Journal of the Operations Research Society of Japan, 38(2), 173-187.
  • LAI, K. K., YU, L., ve WANG, S. (2006, June). Mean-variance-skewness-kurtosis-based portfolio optimization. In Computer and Computational Sciences, 2006. IMSCCS'06. First International Multi-Symposiums on (Vol. 2, pp. 292-297). IEEE.
  • LEVY, H. (1974). The rationale of the mean-standard deviation analysis: Comment. The American Economic Review, 64(3), 434-441.
  • LIU, S. Y. W. S., WANG, S. Y., ve QIU, W. (2003). Mean-Variance-Skewness Model For Portfolio Selection With Transaction Costs. International Journal Of Systems Science, 34(4), 255-262.
  • MACHARIS, C., SPRINGAEL, J., DE BRUCKER, K., ve VERBEKE, A. (2004). PROMETHEE and AHP: The Design Of Operational Synergies In Multicriteria Analysis.: Strengthening PROMETHEE with ideas of AHP. European Journal of Operational Research, 153(2), 307-317.
  • MARINGER, D., ve PARPAS, P. (2009). Global Optimization Of Higher Order Moments In Portfolio Selection. Journal Of Global Optimization, 43(2-3), 219-230.
  • MARKOWITZ, H. (1952). Portfolio selection. The journal of finance, 7(1), 77-91.
  • MARKOWITZ, H. (1959). Portfolio Selection, Efficient Diversification of Investments. J. Wiley.
  • MARKOWITZ, H. M. (1991). Foundations Of Portfolio Theory. The Journal Of Finance, 46(2), 469-477.
  • MHIRI, M., ve PRIGENT, J. L. (2010). International portfolio optimization with higher moments. International Journal of Economics and Finance, 2(5), 157-169.
  • OPRICOVIC, S., ve TZENG, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European journal of operational research, 156(2), 445-455.
  • PALA, O., ve AKSARAYLI, M. (2016). Bulanik Hedef Programlama Tabanli Yüksek Dereceden Momentlerle Bist 30 Endeksinde Portföy Seçimi. Sosyal Bilimler Metinleri Dergisi. (ICOMEP16, Özel Sayı) 98-113.
  • PEZIER, J.,ve WHITE, A. (2006). The Relative Merits Of Investable Hedge Fund Indices And Of Funds Of Hedge Funds In Optimal Passive Portfolios (No. icma-dp2006-10). Henley Business School, Reading University. 1-32.
  • PRAKASH, A. J., CHANG, C. H., ve PACTWA, T. E. (2003). Selecting a portfolio with skewness: Recent evidence from US, European, and Latin American equity markets. Journal of Banking & Finance, 27(7), 1375-1390.
  • QIN, Z., LI, X., ve JI, X. (2009). Portfolio Selection Based On Fuzzy Cross-Entropy. Journal Of Computational And Applied Mathematics, 228(1), 139-149.
  • SAMUELSON, P. A. (1970). The Fundamental Approximation Theorem Of Portfolio Analysis In Terms Of Means, Variances And Higher Moments. The Review of Economic Studies, 37(4), 537-542.
  • SINGLETON, J. C., ve WINGENDER, J. (1986). Skewness Persistence In Common Stock Returns. Journal Of Financial And Quantitative Analysis, 21(03), 335-341.
  • STEINBACH, M. C. (2001). Markowitz Revisited: Mean-Variance Models In Financial Portfolio Analysis. SIAM Review, 43(1), 31-85.
  • USTA, I., ve KANTAR, Y. M. (2011). Mean-Variance-Skewness-Entropy Measures: A Multi-Objective Approach For Portfolio Selection. Entropy, 13(1), 117-133.
  • WANG, S., ve XIA, Y. (2002). Portfolio Selection And Asset Pricing (Vol. 514). Springer Science & Business Media.
  • XIDONAS, P., ASKOUNIS, D., ve PSARRAS, J. (2009). Common Stock Portfolio Selection: A Multiple Criteria Decision Making Methodology And An Application To The Athens Stock Exchange. Operational Research, 9(1), 55-79.
  • YARALIOĞLU, K. (2004). Uygulamada Karar Destek Sistemleri. İlkem Ofset, İzmir, ISBN, 975-270.
  • YUE, W., ve WANG, Y. (2017). A New Fuzzy Multi-Objective Higher Order Moment Portfolio Selection Model For Diversified Portfolios. Physica A: Statistical Mechanics and its Applications, 465, 124-140.
  • ZAKAMOULINE, V., ve KOEKEBAKKER, S. (2009). Portfolio Performance Evaluation With Generalized Sharpe Ratios: Beyond The Mean And Variance. Journal Of Banking & Finance, 33(7), 1242-1254.
  • ZHOU, R., CAI, R., ve TONG, G. (2013). Applications Of Entropy In Finance: A Review. Entropy, 15(11), 4909-4931.
There are 51 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Osman Pala

Mehmet Aksaraylı

Publication Date December 28, 2017
Acceptance Date December 2, 2017
Published in Issue Year 2017 Volume: 4 Issue: 4

Cite

APA Pala, O., & Aksaraylı, M. (2017). Bist 30 Endeksinde Entropi Ve Yüksek Momentlerle Topsıs Ve Promethee Tabanlı Çok Amaçlı Portföy Seçimi Modeli Önerisi. Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 4(4), 171-188. https://doi.org/10.30803/adusobed.356170
AMA Pala O, Aksaraylı M. Bist 30 Endeksinde Entropi Ve Yüksek Momentlerle Topsıs Ve Promethee Tabanlı Çok Amaçlı Portföy Seçimi Modeli Önerisi. ADUSOBIED. December 2017;4(4):171-188. doi:10.30803/adusobed.356170
Chicago Pala, Osman, and Mehmet Aksaraylı. “Bist 30 Endeksinde Entropi Ve Yüksek Momentlerle Topsıs Ve Promethee Tabanlı Çok Amaçlı Portföy Seçimi Modeli Önerisi”. Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 4, no. 4 (December 2017): 171-88. https://doi.org/10.30803/adusobed.356170.
EndNote Pala O, Aksaraylı M (December 1, 2017) Bist 30 Endeksinde Entropi Ve Yüksek Momentlerle Topsıs Ve Promethee Tabanlı Çok Amaçlı Portföy Seçimi Modeli Önerisi. Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 4 4 171–188.
IEEE O. Pala and M. Aksaraylı, “Bist 30 Endeksinde Entropi Ve Yüksek Momentlerle Topsıs Ve Promethee Tabanlı Çok Amaçlı Portföy Seçimi Modeli Önerisi”, ADUSOBIED, vol. 4, no. 4, pp. 171–188, 2017, doi: 10.30803/adusobed.356170.
ISNAD Pala, Osman - Aksaraylı, Mehmet. “Bist 30 Endeksinde Entropi Ve Yüksek Momentlerle Topsıs Ve Promethee Tabanlı Çok Amaçlı Portföy Seçimi Modeli Önerisi”. Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 4/4 (December 2017), 171-188. https://doi.org/10.30803/adusobed.356170.
JAMA Pala O, Aksaraylı M. Bist 30 Endeksinde Entropi Ve Yüksek Momentlerle Topsıs Ve Promethee Tabanlı Çok Amaçlı Portföy Seçimi Modeli Önerisi. ADUSOBIED. 2017;4:171–188.
MLA Pala, Osman and Mehmet Aksaraylı. “Bist 30 Endeksinde Entropi Ve Yüksek Momentlerle Topsıs Ve Promethee Tabanlı Çok Amaçlı Portföy Seçimi Modeli Önerisi”. Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, vol. 4, no. 4, 2017, pp. 171-88, doi:10.30803/adusobed.356170.
Vancouver Pala O, Aksaraylı M. Bist 30 Endeksinde Entropi Ve Yüksek Momentlerle Topsıs Ve Promethee Tabanlı Çok Amaçlı Portföy Seçimi Modeli Önerisi. ADUSOBIED. 2017;4(4):171-88.

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