ARALIK TİP-2 BULANIK RANCOM VE ARALIK TİP-2 BULANIK CoCoSo TABANLI ÇOK KRİTERLİ BİR YAKLAŞIMLA YATIRIM ARACI SEÇİMİ

Müslüm Öztürk

doi:10.17780/ksujes.1834494

TR EN

ARALIK TİP-2 BULANIK RANCOM VE ARALIK TİP-2 BULANIK CoCoSo TABANLI ÇOK KRİTERLİ BİR YAKLAŞIMLA YATIRIM ARACI SEÇİMİ

Öz

Bu çalışmada, yatırım aracı seçiminde karar vericilerin çok kriterli tercihlerini değerlendirmek amacıyla Aralık Tip-2 Bulanık RANCOM-CoCoSo (AT2 B-RANCOM-AT2 B-CoCoSo) hibrit yöntemi kullanılmıştır. Çalışmada AT2 B-RANCOM ile kriter ağırlıkları belirlenmiş, ardından AT2 B-CoCoSo kullanılarak altı yatırım aracının performansı değerlendirilip sıralanmıştır. Çalışmada dört uzman, altı kriter ve altı alternatif üzerinde değerlendirmeler gerçekleştirilmiştir. Elde edilen bulgulara göre, kriter ağırlıklarında Getiri Oranı (%21) ve Enflasyona Karşı Koruma (%19) öncelikli olarak belirlenmiş, diğer kriterler ise orta ve düşük öncelikte kalmıştır. Alternatiflerin performans sıralaması ise A3 > A6 > A2 > A4 > A1 > A5 şeklinde gerçekleşmiş ve bu sonuçlar yatırımcıların risk ve getiri önceliklerini yansıtmıştır. Ayrıca, Tip-1 ve Tip-2 yaklaşımları arasında yapılan istatistiksel karşılaştırma, Tip-2 yönteminin alternatifler arasındaki küçük farkları daha hassas bir şekilde ortaya koyabildiğini göstermiştir. 〖ΔSF〗_i değerleri üzerinden yapılan analizde ortalama 0.019 ve standart sapma 0.032 bulunmuştur. Bu sonuç, Tip-2 yönteminin sıralamada ince farklılıkları daha iyi yansıttığını göstermiştir. Çalışmada, kriter ağırlıkları ile alternatif performansları arasındaki ilişki vurgulanmış ve AT2 B-RANCOM + AT2 B-CoCoSo hibrit yaklaşımının yatırım aracı seçiminde güvenilir ve esnek bir yöntem olduğu gösterilmiştir. Sonuçlar, yatırım stratejilerinin optimize edilmesi ve portföy yönetiminde destek süreçlerine katkı sağlayacaktır.

Anahtar Kelimeler

INVESTMENT INSTRUMENT SELECTION USING A MULTI-CRITERIA APPROACH BASED ON INTERVAL TYPE-2 FUZZY RANCOM AND INTERVAL TYPE-2 FUZZY CoCoSo

Abstract

This study employs an Interval Type-2 Fuzzy RANCOM–CoCoSo (IT2 F-RANCOM–IT2 F-CoCoSo) hybrid method to evaluate decision-makers’ multi-criteria preferences. Criterion weights were determined using IT2 F-RANCOM, and the performance of six investment instruments was ranked using IT2 F-CoCoSo. Four experts assessed six criteria and six alternatives. The findings indicated that Return Rate (21%) and Inflation Protection (19%) were the most prioritized criteria, while the remaining criteria held medium and low importance. The performance ranking of the alternatives was A3 > A6 > A2 > A4 > A1 > A5, reflecting investors’ risk and return preferences. Furthermore, a statistical comparison between Type-1 and Type-2 approaches demonstrated that the Type-2 method captured small differences among alternatives more precisely; the 〖ΔSF〗_i values had a mean of 0.019 and a standard deviation of 0.032, supporting the superior sensitivity of Type-2 in reflecting nuanced rankings. The study highlights the relationship between criterion weights and alternative performance and shows that the AT2 F-RANCOM + AT2 F-CoCoSo hybrid approach is a reliable and flexible method for investment instrument selection. The results contribute to optimizing investment strategies and enhancing decision-support in portfolio management

Keywords

Ethical Statement

We hereby declare that all rules stipulated in the “Higher Education Institutions Scientific Research and Publication Ethics Directive” have been fully observed in this study, and that none of the actions listed under the section titled “Acts Contrary to Scientific Research and Publication Ethics” have been engaged in.

References

Akbulut, O. Y., & Hepşen, A. (2021). Finansal performans ve pay senedi getirileri arasındaki ilişkinin Entropi ve CoCoSo ÇKKV teknikleriyle analiz edilmesi. Ekonomi Politika ve Finans Araştırmaları Dergisi, 6(3), 681-709. https://doi.org/10.30784/epfad.945770
Alballa, T., Rahim, M., Alburaikan, A., Almutairi, A., & Khalifa, H. A. E. W. (2024). MCGDM approach based on (p, q, r)-spherical fuzzy Frank aggregation operators: applications in the categorization of renewable energy sources. Scientific Reports, 14(1), 23576. https://doi.org/10.1038/s41598-024-74591-2
Bahmani, N., Yamoah, D., Basseer, P., & Rezvani, F. (1987). Using the analytic hierarchy process to select investment in a heterogenous environment. Mathematical Modelling, 8, 157-162. https://doi.org/10.1016/0270-0255(87)90561-6
Bakar, A. S. A., Khalif, K. M. N. K., & Gegov, A. (2015, November). Ranking of interval type-2 fuzzy numbers based on centroid point and spread. In 2015 7th International Joint Conference on Computational Intelligence (IJCCI) (Vol. 2, pp. 131-140). IEEE.
Baydaş, M., Yılmaz, M., Jović, Ž., Stević, Ž., Özuyar, S. E. G., & Özçil, A. (2024). A comprehensive MCDM assessment for economic data: success analysis of maximum normalization, CODAS, and fuzzy approaches. Financial Innovation, 10(1), 105. https://doi.org/10.1186/s40854-023-00588-x
Boonjing, V., & Boongasame, L. (2017). Combinatorial portfolio selection with the ELECTRE III method: case study of the stock exchange of Thailand. Afro-Asian Journal of Finance and Accounting, 7(4), 351-362. https://doi.org/10.1504/AAJFA.2017.087506
Candan, G., & Toklu, M. C. (2017). Aralık Tip 2 bulanık TOPSIS yöntemi ile yatırım yeri karar analizi. Ekonometri ve Istatistik Dergisi, (27), 16-28.
Castillo, O., & Melin, P. (2014). A review on interval type-2 fuzzy logic applications in intelligent control. Information Sciences, 279, 615-631. https://doi.org/10.1016/j.ins.2014.04.015

Çilek, A. (2022). Bütünleşik SV-CoCoSo teknikleriyle etkinlik analizi: mevduat bankaları gruplarında bir uygulama. Karadeniz Sosyal Bilimler Dergisi, 14(26), 52-69. https://doi.org/10.38155/ksbd.1079357
De, A. K., Chakraborty, D., & Biswas, A. (2022). Literature review on type-2 fuzzy set theory. Soft Computing, 26(18), 9049-9068. https://doi.org/10.1007/s00500-022-07304-4
Durmaz, M., & Çermik, Ö. (2022). Çok kriterli karar verme teknikleri kullanılarak yapısal bir uygulama için kompozit malzeme önceliklendirilmesi. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 25(Özel Sayı), 80-97. https://doi.org/10.17780/ksujes.1164490
Emamat, M. S. M. M., Mota, C. M. D. M., Mehregan, M. R., Sadeghi Moghadam, M. R., & Nemery, P. (2022). Using ELECTRE-TRI and FlowSort methods in a stock portfolio selection context. Financial Innovation, 8(1), 11. https://doi.org/10.1186/s40854-021-00318-1
Ersoy, N. (2023). Applying an integrated data-driven weighting system-CoCoSo approach for financial performance evaluation of Fortune 500 companies. E+ M Ekonomie a Management, 26(3), 92-108. https://doi.org/10.15240/tul/001/2023-3-006
Gupta, N., Garg, P., & Ahuja, N. (2025). An integrated pythagorean fuzzy delphi-AHP-CoCoSo approach for exploring barriers and mitigation strategies for sustainable supply chain in the food industry. Supply Chain Analytics, 10, 100105. https://doi.org/10.1016/j.sca.2025.100105
Jankova, Z., & Dostal, P. (2022). Uncertaınty in the type-2 fuzzy logic system for forecasting stock index. Romanian Journal of Economic Forecasting, 25(4), 41
Kahraman, C., & Haktanır, E. (2024). Fuzzy Investment Decision Making with Examples (pp. 103-115). Springer. https://doi.org/10.1007/978-3-031-54660-0
Kao, C. (2010). Weight determination for consistently ranking alternatives in multiple criteria decision analysis. Applied Mathematical Modelling, 34(7), 1779-1787. https://doi.org/10.1016/j.apm.2009.09.022
Kaya, I., Çolak, M., & Terzi, F. (2019). A comprehensive review of fuzzy multi criteria decision making methodologies for energy policy making. Energy strategy reviews, 24, 207-228. https://doi.org/10.1016/j.esr.2019.03.003
Khan, K. I., Kabir, M. A., Mata, M. N., Correia, A. B., Rita, J. X., & Martins, J. N. (2021). Portfolio optimization: An application of MOORA model through stochastic process. Academy of Accounting and Financial Studies Journal, 25(S2), 1–14.
Kumar, S. (2025). Stock selection with intuitionistic fuzzy combined compromise solutions. Applied Soft Computing, 169, 112526. https://doi.org/10.1016/j.asoc.2024.112526
Kumaran, S. (2022). Financial performance index of IPO firms using VIKOR-CRITIC techniques. Finance research letters, 47, 102542. https://doi.org/10.1016/j.frl.2021.102542
Kutlu Gündoğdu, F., & Kahraman, C. (2019). Spherical fuzzy sets and spherical fuzzy TOPSIS method. Journal of intelligent & fuzzy systems, 36(1), 337-352. https://doi.org/10.1007/s00500-022-07749-7
Lucas, F. F., dos Santos, M., Gomes, C. F. S., de Araújo Costa, A. P., de Oliveira Braga, G., da Costa, L. M. A., ... & de Araújo Costa, V. P. (2024). Valuation of real estate investment trusts using the PSI-CoCoSo multicriteria method. Procedia Computer Science, 242, 881-887. https://doi.org/10.1016/j.procs.2024.08.264
Madi, E. N., Zakaria, Z. A., Sambas, A., & Sukono. (2023). Toward effective uncertainty management in decision-making models based on type-2 fuzzy TOPSIS. Mathematics, 11(16), 3512. https://doi.org/10.3390/math11163512
Meniz, B., Bas, S. A., Ozkok, B. A., & Tiryaki, F. (2021). Multilevel AHP approach with interval type-2 fuzzy sets to portfolio selection problem. Journal of Intelligent & Fuzzy Systems, 40(5), 8819-8829. https://doi.org/10.3233/JIFS-200512
Narang, M., Joshi, M. C., Bisht, K., & Pal, A. (2022). Stock portfolio selection using a new decision-making approach based on the integration of fuzzy CoCoSo with Heronian mean operator. Decision making: applications in management and engineering, 5(1), 90-112. https://doi.org/10.31181/dmame0310022022n
Narang, M., Joshi, M. C., Bisht, K., & Pal, A. (2022). Stock portfolio selection using a new decision-making approach based on the integration of fuzzy CoCoSo with Heronian mean operator. Decision making: applications in management and engineering, 5(1), 90-112. https://doi.org/10.31181/dmame0310022022n
Özdağoğlu, A., Keleş, M. K., & Eren, F. Y. (2019). Bir üniversite hastanesinde makroelisa ekipmani alternatiflerinin WASPAS ve SWARA yöntemleri ile değerlendirilmesi. Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 24(2), 319-331.
Öztürk, M. (2025). A Hybrid Approach for Battery Selection Based on Green Criteria in Electric Vehicles: DEMATEL-QFD-Interval Type-2 Fuzzy VIKOR. Sustainability, 17(14), 6277. https://doi.org/10.3390/su17146277
Öztürk, M., & Paksoy, T. (2016). Otoyollardaki Trafik Işıkları Kontrol Sistemi Modellemesi Bulanık Karar Tabanlı Görsel Uygulaması. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 19(3), 170-183.
Öztürk, M., Paksoy, T., & Öztürk, M. (2017). Aralık tip-2 bulanık mantık yönteminin tedarikçi seçiminde kullanımının önemi üzerine bir araştırma. Türkiye Bilişim Vakfı Bilgisayar Bilimleri ve Mühendisliği Dergisi, 10(2), 1-18.
Öztürk, M., Torğul, B., & Paksoy, T. (2022). Interval Type-2 Fuzzy Rule-Based Bwm Approach for Sustainable Supplier Selection. Konya Journal of Engineering Sciences, 10(2), 312-336.
Peng, X., & Huang, H. (2020). Fuzzy decision making method based on CoCoSo with critic for financial risk evaluation. Technological and Economic Development of Economy, 26(4), 695-724. https://doi.org/10.3846/tede.2020.11920
Peng, X., Huang, H. H., & Luo, Z. (2023). Fuzzy dynamic MCDM method based on PRSRV for financial risk evaluation of new energy vehicle industry. Applied Soft Computing, 136, 110115. https://doi.org/10.1016/j.asoc.2023.110115
Rasoanaivo, R. G., Yazdani, M., Zaraté, P., & Fateh, A. (2024). Combined Compromise for Ideal Solution (CoCoFISo): a multi-criteria decision-making based on the CoCoSo method algorithm. Expert Systems with Applications, 251, 124079. https://doi.org/10.1016/j.eswa.2024.124079
Shabani, M., Khodarahmi, A., Ghousi, R., Mohammadi, E., & Ghanbari, H. (2025). An appraisal of fund of funds efficiency based on risk-adjusted performance measures: Application of an augmented WASPAS methodology. PLoS One, 20(7), e0314918. https://doi.org/10.1371/journal.pone.0314918
Sharma, S. K. (2025). Enhancing stock portfolio selection with trapezoidal bipolar fuzzy VIKOR technique with Boruta-GA hybrid optimization model: a multicriteria decision-making approach. International Journal of Computational Intelligence Systems, 18(1), 17. https://doi.org/10.1007/s44196-025-00733-7
Silva, N. F., dos Santos, M., Gomes, C. F. S., & de Andrade, L. P. (2023). An integrated CRITIC and Grey Relational Analysis approach for investment portfolio selection. Decision analytics journal, 8, 100285. https://doi.org/10.1016/j.dajour.2023.100285
State Street Global Advisors. (2025, 5 Mart). How economic factors impact asset performance. State Street. https://www.ssga.com/us/en/intermediary/insights/how-economic-factors-impact-asset-performance
Tan, W. W., & Chua, T. W. (2007). Uncertain rule-based fuzzy logic systems: introduction and new directions (Mendel, JM; 2001)[book review]. IEEE Computational intelligence magazine, 2(1), 72-73. https://doi.org/10.1109/MCI.2007.357196
Tavana, M., Shaabani, A., Di Caprio, D., & Bonyani, A. (2022). A novel Interval Type-2 Fuzzy best-worst method and combined compromise solution for evaluating eco-friendly packaging alternatives. Expert systems with applications, 200, 117188. https://doi.org/10.1016/j.eswa.2022.117188
Vásquez, J. A., Escobar, J. W., & Manotas, D. F. (2021). AHP–TOPSIS methodology for stock portfolio investments. Risks, 10(1), 4. https://doi.org/10.3390/risks10010004
Wang, J. Q., Yu, S. M., Wang, J., Chen, Q. H., Zhang, H. Y., & Chen, X. H. (2015). An interval type-2 fuzzy number based approach for multi-criteria group decision-making problems. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 23(04), 565-588. https://doi.org/10.1142/S0218488515500257
Wang, Y., Hussain, A., Mahmood, T., Ali, M. I., Wu, H., & Jin, Y. (2020). Decision‐Making Based on q‐Rung Orthopair Fuzzy Soft Rough Sets. Mathematical Problems in Engineering, 2020(1), 6671001. https://doi.org/10.1155/2020/6671001
Wang, Z., & Rangaiah, G. P. (2025). Multi-Criteria Decision-Making: Reference-Type Methods. arXiv preprint arXiv:2508.16087. https://doi.org/10.48550/arXiv.2508.16087
Wu, D., & Mendel, J. M. (2007). Uncertainty measures for interval type-2 fuzzy sets. Information sciences, 177(23), 5378-5393. https://doi.org/10.1016/j.ins.2007.07.012
Wu, Q., Liu, X., Qin, J., Zhou, L., Mardani, A., & Deveci, M. (2022). An integrated generalized TODIM model for portfolio selection based on financial performance of firms. Knowledge-Based Systems, 249, 108794. https://doi.org/10.1016/j.knosys.2022.108794
Xue, Q., Ling, Y., & Tian, B. (2022). Portfolio Optimization Model for Gold and Bitcoin Based on Weighted Unidirectional Dual‐Layer LSTM Model and SMA‐Slope Strategy. Computational intelligence and neuroscience, 2022(1), 1869897. https://doi.org/10.1155/2022/1869897
Yazdani, M., Zarate, P., Kazimieras Zavadskas, E., & Turskis, Z. (2019). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management decision, 57(9), 2501-2519. https://doi.org/10.1108/MD-05-2017-0458
Zadeh, L. A. (2001). A new direction in AI: Toward a computational theory of perceptions. AI magazine, 22(1), 73-73. https://doi.org/10.1609/aimag.v22i1.1545
Zhang, L., Feng, J., & Feng, B. (2024). Research on PPP-ABS projects hesitant fuzzy multi-criteria investment decision-making with prospect theory and VIKOR method. Journal of Industrial and Management Optimization, 20(8), 2570-2590. https://doi.org/10.3934/jimo.2024016
Zolfaghari, S., Mousavi, S. M., & Antuchevičienė, J. (2021). A type-2 fuzzy optimization model for project portfolio selection and scheduling incorporating project interdependency and splitting. https://etalpykla.vilniustech.lt/handle/123456789/152034

Details

Primary Language

Turkish

Subjects

Fuzzy Computation , Multiple Criteria Decision Making

Journal Section

Research Article

Authors

Müslüm Öztürk ^*
0000-0003-1941-3115
Türkiye

Publication Date

March 3, 2026

Submission Date

December 2, 2025

Acceptance Date

January 29, 2026

Published in Issue

Year 2026 Volume: 29 Number: 1

DOI

https://doi.org/10.17780/ksujes.1834494

IZ

https://izlik.org/JA96ED58DE

Cite

RIS / Bibtex

APA

Öztürk, M. (2026). ARALIK TİP-2 BULANIK RANCOM VE ARALIK TİP-2 BULANIK CoCoSo TABANLI ÇOK KRİTERLİ BİR YAKLAŞIMLA YATIRIM ARACI SEÇİMİ. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 29(1), 344-369. https://doi.org/10.17780/ksujes.1834494