Araştırma Makalesi
BibTex RIS Kaynak Göster

Yıl 2025, Cilt: 75 Sayı: 1, 44 - 66, 14.07.2025
https://doi.org/10.26650/ISTJECON2024-1478258

Öz

Kaynakça

  • Akram, M., & Naz, S. (2018). Energy of Pythagorean fuzzy graphs with applications. Mathematics, 6(8), 136. https://doi.org/10.3390/ math6080136 google scholar
  • Akram, M., Shah, S. M. U., Al-Shamiri, M. M. A., & EdalatpaNah, S. A. (2022). ExteNded DEA method for solving multi-objective traNsporta-tion problem with Fermatean fuzzy sets. AIMS Mathematics, 8(1), 924-961. https://doi.org/l0.3934/math.2022047 google scholar
  • Akram, M., Shareef, A., & Al-Kenani, A.N. (2024). Pythagorean fuzzy incidence graphs with Application in one-waY toll road network. Grar-ular Computing, 9, 39. google scholar
  • Atanassov, K. (1986). Intuitionistic fuzzy sets, Fuzzy Sets ard Systems, 20, 87-96. google scholar
  • Atanassov, K., & Gargov, G. (1989). Interval-valued intuitionistic fuzzy sets. Fuzzy Sets ard Systems, 31 343-349. google scholar
  • Biswas, S., Bandyopadhyay, G., Guha, B., & Bhattacharjee, M. (2019). An ensemble approach for portfolio selection in a multi-criteria decision-making framework. Decisior Makirg: Applicatior ir Maragemert Ergireerirg, 2(2), 138-158. google scholar
  • De Araujo Costa, I.P., Moreira, M.A.L., de Ara_ujo Costa, A.P., de Souza de Barros Teixeira, L.F.H., Gomes, C.F.S., & Dos Santos, M. (2022). Strategic study for managing the portfolio of IT courses offered by a corporate training companY: An approach in the light of the ELECTRE-MOr multicriteria hYbrid method. Irterratioral Jourral of Irformatior Techrology & Decisior Makirg, 21, 351-379. google scholar
  • De Blasis R. (2023). Weighted-indexed semi-Markov model: calibration and application to financial Modeling. Firarcial Irroviatior, 9, 35. google scholar
  • Garg, H. (2019). Intuitionistic fuzzY Hamacher aggregation operators with entropY weight and their applications to multi-criteria decision-making problems. Irariar Jourral of Scierce ard Techrology, Trarsactiors of Electrical Ergireerirg, 43, 597-613. google scholar
  • Garg, H., Majumder, P., & Nath, M. (2022). A hYbrid trapezoidal fuzzY FUCOM-AHP approach and their application to the identification of monkeYpox risk factors, Computatioral ard Applied Mathematics, 41, 379. google scholar
  • Garg, H., Sugapriya, C., Rajeswari, S., Nagarajan, D., & Alburaikan A. (2024). A model for returnable container inventory with restoring strategY using the triangular fuzzY numbers. Soft Computing, 28, 2811-2822. google scholar
  • Goldfarb, D., & IYeNgar, G. (2003). Robust portfolio selectioN problems. Mathematics of Operations Research, 28(1), 1-38. google scholar
  • Gupta, P., Mehlawat, M.K., Inuiguchi, M., & Chandra, S. (2014). Ethicality considerations in multicriteria fuzzy portfolio optimization. Fuzzy Portfolio Optimization, 316, 255-281. google scholar
  • Hassan, M.N., & Banerjee, S. (2021). Mindmaps-based tool for planning and structuring design research papers, Design for Tomorrow-Volume 2, 222, 587-593. google scholar
  • Joshi, D., & Kumar, S. (2014). Intuitionistic fuzzY entropY and distance measure based TOPSIS method for multi-criteria decision making. Egyptian Informatics Journal ,15(2), 97-104. google scholar
  • Karmakar, P., Dutta, P., & Biswas, S. (2018). Assessment of mutual fund performance using distance- based multi-criteria decision-making techniques: an Indian perspective. Research Bulletin 44(1), 17-38. google scholar
  • Kirisci, M. (2019). Comparison of the medical decision-making with Intuitionistic fuzzy parameterized fuzzy soft set and Riesz Summa-bility. New Mathematics and Natural Computation, 15, 351-359. google scholar
  • Kirisci, M. (2020). Parameter Reduction Method for Pythagorean Fuzzy Soft Sets. Universal Journal of Mathematics and Applications, 3(1), 33-37. google scholar
  • Kirisci, M. (2022a). Data Analysis for Lung Cancer: Fermatean Hesitant Fuzzy Sets Approach. Applied Mathematics, Modeling and Computer Simulation, 30, 701-710. google scholar
  • Kirisci, M. (2022b). Correlation Coefficients of Fermatean Fuzzy Sets with a Medical Application. Journal of Mathematical Sciences and Modelling, 5(1), 16-23. google scholar
  • Kirişci, M. (2023). New cosine similarity and distance measures for Fermatean fuzzy sets and TOPSIS approach. Knowledge and Information Systems, 65(2), 855-868. google scholar
  • Kirisci, M. (2024a). Interval-valued Fermatean fuzzy-based risk assessment for self-driving vehicles. Applied Soft Computing, 152, 111265. google scholar
  • Kirisci, M. (2024b). Measures of Distance and Entropy Based on the Fermatean Fuzzy-Type Soft Sets Approach. Universal Journal of Mathematics and Applications, 7(1),12-29. google scholar Liang, W., Zhang, X., & Liu M. (2015). The maximizing deviation method based on Interval-valued PYthagorean fuzzY weighted aggregating operatör for multiple criteria group decision analYsis, Discrete Dynamics in Nature and Society, 2015, 746572, google scholar
  • Markowitz H. (1952). Portfolio selection. Journal Finance, 7(1), 77-91. google scholar
  • Markowitz, H. (1959). Portfolio Selection. New Haven: Yale University Press. google scholar
  • Mellem, P.M. N., de Araujo Costa, I.P., de Araujo Costa, A.P., Lellis Moreira, M.A., Simoes Gomes, C.F., dos Santos, M., & de Pina Corrica, J.V. (2022). Prospective scenarios applied in the course portfolio management: An approach in light of the momentum and ELECTRE-MOr methods, Procedia Computer Science , 199, 48-55. google scholar
  • MYers, James H. & Mark I. Alpert. (1968). Determinant BuYing Attitudes: Meaning and Measurement. Journal of Marketing, 32, 13-20 google scholar
  • Moccellin, A.P., Valdivieso-Bonilla, A.P., Freitas, C.V., Pinheiro, E., Ruiz-Padillo, A., & Siluk, J.C.M. (2021). Electre i aplicado a problemas de sele_c~ao de carteira de investimentos. Revista De investigacion Sığma, 9, 110-127. google scholar
  • Ogryczak, W. (2000). Multiple criteria linear programming model for portfolio selection. Annals of Operations Research, 97(1), 14-62. google scholar
  • Ronyastra, I.M., Gunarta, I.K., & CiptomulYono, U. (2015). A multi-criteria decision analysis for Reinvestment action portfolio selection problem in an Indonesian real estate company. Procedia Manufacturing, 4, 558-567. google scholar
  • Senapati, T., & Yager, R.R. (2019a). Some new operations over Fermatean fuzzy numbers and application of Fermatean fuzzy WPM in multiple criteria decision making. Informatica, 30, 391-412. google scholar
  • Senapati, T., & Yager R.R. (2019b). Fermatean fuzzy weighted averaging/geometric operators and its application in multi-criteria decision-making methods, Engineering Applications of Artificial Intelligence, 85, 112-121 google scholar
  • Senapati, T., & Yager, R.R. (2020). Fermatean fuzzy sets. Journal of Ambient Intelligence anD HumanizeD Computing 11, 663-674. google scholar
  • Simsek, N., & Kirisci, M. (2023). Incomplete Fermatean Fuzzy Preference Relations and GroupDecision Making. Topological Algebra anD its Applications, 11(1), 20220125 google scholar
  • Trzebinski, A.A., & Majerowska E. (2019). The impact of fundamental investment fund features on the level of risk. Contemporary Trends and Challenges in Finance, 157-164. google scholar
  • Vetschera, R., & De Almeida, A.T. (2012). A PROMETHEE-based approach to portfolio selection problems. Computers & Operations Research,39(5), 1010-1020. google scholar
  • Wang, J.-Z., Wang, J.-J., Zhang, Z.-G., & Guo, S.-P. (2011). Forecasting stock indices with backpropagation neural network. Expert Systems with Applications, 38, 14346-14355. google scholar
  • Wu, Q., Liu, X., QiN, J., Zhou, L., MardaNi, A., & Deveci, M. (2022). AN iNtegrated geNeralized TODIM model for portfolio selectioN based oN the financial performance of firms. Knowledge-BasedSystems, 249, 108794. google scholar
  • Yager, R.R. (2013). PYthagoreay fuzzy subsets. Proc Joint IFSA World Congress and NAFIPS, Annual Meeting, Edmonton, Canada. google scholar
  • Yager, R.R., & Abbasov, A.M. (2013). Pythagorean membership grades, complex numbers, and decision Making. International Journal of Intelligent Systems, 28, 436-452. google scholar
  • Zadeh, L.A. (1965). Fuzzy sets. Information and Computation, 8, 338-353. google scholar

Portfolio Selection Analysis with a Fermatean Fuzzy-type AHP

Yıl 2025, Cilt: 75 Sayı: 1, 44 - 66, 14.07.2025
https://doi.org/10.26650/ISTJECON2024-1478258

Öz

This study aims to tackle decision-making problems on interval-valued Fermatean fuzzy sets; the current research proposed an approach based on the AHP method. The interval-valued Fermatean fuzzy set is a mathematical framework used in decision-making and modelling scenarios that involve uncertainty and imprecision. The interval-valued Fermatean fuzzy set extends traditional fuzzy sets by incorporating an additional layer of flexibility and expressiveness, particularly in cases where precise membership degrees are difficult to assign. The AHP method makes the problem more understandable by dividing it into a hierarchy of targets, criteria, sub-criteria, and alternatives, comparing and prioritizing options, and checking consistency. Multi-attribute decision-making algorithms are well-suited for portfolio selection problems. Complex subjective preferences and diversified financial indices affect investment decisions within the multi-attribute decision-making paradigm. For the investment portfolio selection problem, an algorithm implementation based on an interval-valued Fermatean fuzzy set is chosen. The S&P 500 companies are examined. Ten criteria are established for choosing investment portfolios. The investment portfolios were selected using a multi-attribute decision-making method based on interval-valued Fermatean fuzzy sets. The algorithm based on interval-valued Fermatean fuzzy sets and the portfolio decision-making process using these criteria is suitable for choosing the right options. A model that illustrates how choices about investment portfolios should be made using this procedure was created using a grounded theory methodology. The results show that efficient decision-making methods for investment portfolios create a portfolio mindset and assist in concentrating selection efforts on the appropriate projects. Additionally, it enables extremely flexible decision-making within the investment portfolio. These findings offer managers an evidence-based method for making decisions about their portfolios.

JEL Classification : C63 , G11 , F21

Kaynakça

  • Akram, M., & Naz, S. (2018). Energy of Pythagorean fuzzy graphs with applications. Mathematics, 6(8), 136. https://doi.org/10.3390/ math6080136 google scholar
  • Akram, M., Shah, S. M. U., Al-Shamiri, M. M. A., & EdalatpaNah, S. A. (2022). ExteNded DEA method for solving multi-objective traNsporta-tion problem with Fermatean fuzzy sets. AIMS Mathematics, 8(1), 924-961. https://doi.org/l0.3934/math.2022047 google scholar
  • Akram, M., Shareef, A., & Al-Kenani, A.N. (2024). Pythagorean fuzzy incidence graphs with Application in one-waY toll road network. Grar-ular Computing, 9, 39. google scholar
  • Atanassov, K. (1986). Intuitionistic fuzzy sets, Fuzzy Sets ard Systems, 20, 87-96. google scholar
  • Atanassov, K., & Gargov, G. (1989). Interval-valued intuitionistic fuzzy sets. Fuzzy Sets ard Systems, 31 343-349. google scholar
  • Biswas, S., Bandyopadhyay, G., Guha, B., & Bhattacharjee, M. (2019). An ensemble approach for portfolio selection in a multi-criteria decision-making framework. Decisior Makirg: Applicatior ir Maragemert Ergireerirg, 2(2), 138-158. google scholar
  • De Araujo Costa, I.P., Moreira, M.A.L., de Ara_ujo Costa, A.P., de Souza de Barros Teixeira, L.F.H., Gomes, C.F.S., & Dos Santos, M. (2022). Strategic study for managing the portfolio of IT courses offered by a corporate training companY: An approach in the light of the ELECTRE-MOr multicriteria hYbrid method. Irterratioral Jourral of Irformatior Techrology & Decisior Makirg, 21, 351-379. google scholar
  • De Blasis R. (2023). Weighted-indexed semi-Markov model: calibration and application to financial Modeling. Firarcial Irroviatior, 9, 35. google scholar
  • Garg, H. (2019). Intuitionistic fuzzY Hamacher aggregation operators with entropY weight and their applications to multi-criteria decision-making problems. Irariar Jourral of Scierce ard Techrology, Trarsactiors of Electrical Ergireerirg, 43, 597-613. google scholar
  • Garg, H., Majumder, P., & Nath, M. (2022). A hYbrid trapezoidal fuzzY FUCOM-AHP approach and their application to the identification of monkeYpox risk factors, Computatioral ard Applied Mathematics, 41, 379. google scholar
  • Garg, H., Sugapriya, C., Rajeswari, S., Nagarajan, D., & Alburaikan A. (2024). A model for returnable container inventory with restoring strategY using the triangular fuzzY numbers. Soft Computing, 28, 2811-2822. google scholar
  • Goldfarb, D., & IYeNgar, G. (2003). Robust portfolio selectioN problems. Mathematics of Operations Research, 28(1), 1-38. google scholar
  • Gupta, P., Mehlawat, M.K., Inuiguchi, M., & Chandra, S. (2014). Ethicality considerations in multicriteria fuzzy portfolio optimization. Fuzzy Portfolio Optimization, 316, 255-281. google scholar
  • Hassan, M.N., & Banerjee, S. (2021). Mindmaps-based tool for planning and structuring design research papers, Design for Tomorrow-Volume 2, 222, 587-593. google scholar
  • Joshi, D., & Kumar, S. (2014). Intuitionistic fuzzY entropY and distance measure based TOPSIS method for multi-criteria decision making. Egyptian Informatics Journal ,15(2), 97-104. google scholar
  • Karmakar, P., Dutta, P., & Biswas, S. (2018). Assessment of mutual fund performance using distance- based multi-criteria decision-making techniques: an Indian perspective. Research Bulletin 44(1), 17-38. google scholar
  • Kirisci, M. (2019). Comparison of the medical decision-making with Intuitionistic fuzzy parameterized fuzzy soft set and Riesz Summa-bility. New Mathematics and Natural Computation, 15, 351-359. google scholar
  • Kirisci, M. (2020). Parameter Reduction Method for Pythagorean Fuzzy Soft Sets. Universal Journal of Mathematics and Applications, 3(1), 33-37. google scholar
  • Kirisci, M. (2022a). Data Analysis for Lung Cancer: Fermatean Hesitant Fuzzy Sets Approach. Applied Mathematics, Modeling and Computer Simulation, 30, 701-710. google scholar
  • Kirisci, M. (2022b). Correlation Coefficients of Fermatean Fuzzy Sets with a Medical Application. Journal of Mathematical Sciences and Modelling, 5(1), 16-23. google scholar
  • Kirişci, M. (2023). New cosine similarity and distance measures for Fermatean fuzzy sets and TOPSIS approach. Knowledge and Information Systems, 65(2), 855-868. google scholar
  • Kirisci, M. (2024a). Interval-valued Fermatean fuzzy-based risk assessment for self-driving vehicles. Applied Soft Computing, 152, 111265. google scholar
  • Kirisci, M. (2024b). Measures of Distance and Entropy Based on the Fermatean Fuzzy-Type Soft Sets Approach. Universal Journal of Mathematics and Applications, 7(1),12-29. google scholar Liang, W., Zhang, X., & Liu M. (2015). The maximizing deviation method based on Interval-valued PYthagorean fuzzY weighted aggregating operatör for multiple criteria group decision analYsis, Discrete Dynamics in Nature and Society, 2015, 746572, google scholar
  • Markowitz H. (1952). Portfolio selection. Journal Finance, 7(1), 77-91. google scholar
  • Markowitz, H. (1959). Portfolio Selection. New Haven: Yale University Press. google scholar
  • Mellem, P.M. N., de Araujo Costa, I.P., de Araujo Costa, A.P., Lellis Moreira, M.A., Simoes Gomes, C.F., dos Santos, M., & de Pina Corrica, J.V. (2022). Prospective scenarios applied in the course portfolio management: An approach in light of the momentum and ELECTRE-MOr methods, Procedia Computer Science , 199, 48-55. google scholar
  • MYers, James H. & Mark I. Alpert. (1968). Determinant BuYing Attitudes: Meaning and Measurement. Journal of Marketing, 32, 13-20 google scholar
  • Moccellin, A.P., Valdivieso-Bonilla, A.P., Freitas, C.V., Pinheiro, E., Ruiz-Padillo, A., & Siluk, J.C.M. (2021). Electre i aplicado a problemas de sele_c~ao de carteira de investimentos. Revista De investigacion Sığma, 9, 110-127. google scholar
  • Ogryczak, W. (2000). Multiple criteria linear programming model for portfolio selection. Annals of Operations Research, 97(1), 14-62. google scholar
  • Ronyastra, I.M., Gunarta, I.K., & CiptomulYono, U. (2015). A multi-criteria decision analysis for Reinvestment action portfolio selection problem in an Indonesian real estate company. Procedia Manufacturing, 4, 558-567. google scholar
  • Senapati, T., & Yager, R.R. (2019a). Some new operations over Fermatean fuzzy numbers and application of Fermatean fuzzy WPM in multiple criteria decision making. Informatica, 30, 391-412. google scholar
  • Senapati, T., & Yager R.R. (2019b). Fermatean fuzzy weighted averaging/geometric operators and its application in multi-criteria decision-making methods, Engineering Applications of Artificial Intelligence, 85, 112-121 google scholar
  • Senapati, T., & Yager, R.R. (2020). Fermatean fuzzy sets. Journal of Ambient Intelligence anD HumanizeD Computing 11, 663-674. google scholar
  • Simsek, N., & Kirisci, M. (2023). Incomplete Fermatean Fuzzy Preference Relations and GroupDecision Making. Topological Algebra anD its Applications, 11(1), 20220125 google scholar
  • Trzebinski, A.A., & Majerowska E. (2019). The impact of fundamental investment fund features on the level of risk. Contemporary Trends and Challenges in Finance, 157-164. google scholar
  • Vetschera, R., & De Almeida, A.T. (2012). A PROMETHEE-based approach to portfolio selection problems. Computers & Operations Research,39(5), 1010-1020. google scholar
  • Wang, J.-Z., Wang, J.-J., Zhang, Z.-G., & Guo, S.-P. (2011). Forecasting stock indices with backpropagation neural network. Expert Systems with Applications, 38, 14346-14355. google scholar
  • Wu, Q., Liu, X., QiN, J., Zhou, L., MardaNi, A., & Deveci, M. (2022). AN iNtegrated geNeralized TODIM model for portfolio selectioN based oN the financial performance of firms. Knowledge-BasedSystems, 249, 108794. google scholar
  • Yager, R.R. (2013). PYthagoreay fuzzy subsets. Proc Joint IFSA World Congress and NAFIPS, Annual Meeting, Edmonton, Canada. google scholar
  • Yager, R.R., & Abbasov, A.M. (2013). Pythagorean membership grades, complex numbers, and decision Making. International Journal of Intelligent Systems, 28, 436-452. google scholar
  • Zadeh, L.A. (1965). Fuzzy sets. Information and Computation, 8, 338-353. google scholar
Toplam 41 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Finans, Finans ve Yatırım (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Serdar Kuzu 0000-0001-8178-8749

Murat Kirisci 0000-0003-4938-5207

Ali Kablan 0000-0003-2711-0034

Özden Calay 0000-0003-4539-0527

Yayımlanma Tarihi 14 Temmuz 2025
Gönderilme Tarihi 6 Mayıs 2024
Kabul Tarihi 12 Haziran 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 75 Sayı: 1

Kaynak Göster

APA Kuzu, S., Kirisci, M., Kablan, A., Calay, Ö. (2025). Portfolio Selection Analysis with a Fermatean Fuzzy-type AHP. İstanbul İktisat Dergisi, 75(1), 44-66. https://doi.org/10.26650/ISTJECON2024-1478258
AMA Kuzu S, Kirisci M, Kablan A, Calay Ö. Portfolio Selection Analysis with a Fermatean Fuzzy-type AHP. İstanbul İktisat Dergisi. Temmuz 2025;75(1):44-66. doi:10.26650/ISTJECON2024-1478258
Chicago Kuzu, Serdar, Murat Kirisci, Ali Kablan, ve Özden Calay. “Portfolio Selection Analysis with a Fermatean Fuzzy-type AHP”. İstanbul İktisat Dergisi 75, sy. 1 (Temmuz 2025): 44-66. https://doi.org/10.26650/ISTJECON2024-1478258.
EndNote Kuzu S, Kirisci M, Kablan A, Calay Ö (01 Temmuz 2025) Portfolio Selection Analysis with a Fermatean Fuzzy-type AHP. İstanbul İktisat Dergisi 75 1 44–66.
IEEE S. Kuzu, M. Kirisci, A. Kablan, ve Ö. Calay, “Portfolio Selection Analysis with a Fermatean Fuzzy-type AHP”, İstanbul İktisat Dergisi, c. 75, sy. 1, ss. 44–66, 2025, doi: 10.26650/ISTJECON2024-1478258.
ISNAD Kuzu, Serdar vd. “Portfolio Selection Analysis with a Fermatean Fuzzy-type AHP”. İstanbul İktisat Dergisi 75/1 (Temmuz2025), 44-66. https://doi.org/10.26650/ISTJECON2024-1478258.
JAMA Kuzu S, Kirisci M, Kablan A, Calay Ö. Portfolio Selection Analysis with a Fermatean Fuzzy-type AHP. İstanbul İktisat Dergisi. 2025;75:44–66.
MLA Kuzu, Serdar vd. “Portfolio Selection Analysis with a Fermatean Fuzzy-type AHP”. İstanbul İktisat Dergisi, c. 75, sy. 1, 2025, ss. 44-66, doi:10.26650/ISTJECON2024-1478258.
Vancouver Kuzu S, Kirisci M, Kablan A, Calay Ö. Portfolio Selection Analysis with a Fermatean Fuzzy-type AHP. İstanbul İktisat Dergisi. 2025;75(1):44-66.