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Yeni Bir Çok Kriterli Karar Verme Yaklaşımı “Olabilirlik Değerlendirme Sistemi”: Katılım Fonları Üzerine Bir Uygulama

Year 2024, Volume: 7 Issue: 1, 1 - 8, 15.01.2024
https://doi.org/10.34248/bsengineering.1341340

Abstract

Katılım hisse senedi şemsiye fonları, İslami finans ilkeleri çerçevesinde filtrelenmiş hisse senetlerine yatırım imkânı sağlayan bir yatırım alternatifidir. Olabilirlik teorisi karar vermede önemli bir araçtır. Bu çalışmada katılım hisse senedi şemsiye fonlarının karşılaştırılması gibi problemler için olabilirlik teorisine dayanan yeni bir çok kriterli karar verme (ÇKKV) yaklaşımı önerilmiştir. Bu yaklaşım Olabilirlik Değerlendirme Sistemi (PES) olarak adlandırılmıştır. PES, temel ÇKKV yöntemlerinden olan maksimin kuralı, ağırlıklı toplam yöntemi ve maksimaks kuralı ile ilişkilidir. Alternatiflerin öncelik vektörü PES ile tek olarak elde edilmektedir. Başka bir deyişle portföy seçimi problemi gibi çok amaçlı karar verme problemleri için tek bir çözüm vermektedir. PES, çok nitelikli karar verme problemleri için en yüksek önceliğe sahip alternatifin seçilmesine dayanmaktadır. PES, 31.07.2020 ve 30.12.2022 arasında Türkiye’de işlem gören beş farklı katılım hisse senedi şemsiye fonunun gerçek veri seti kullanılarak tanıtılmıştır. Yapılan uygulamada, PES’in bu temel yöntemlerden daha fazla bilgi ortaya koyduğu gözlemlenmiştir.

References

  • Ali MY, Sultana A, Khan AFMK. 2016. Comparison of fuzzy multiplication operation on triangular fuzzy number. IOSR J Math, 12(4): 35-41.
  • Alonso JA, Lamata MT. 2006. Consistency in the analytic hierarchy process: a new approach. Int J Uncert Fuzzi Knowledge-bas Syst, 14(04): 445-459.
  • Bayraktar M, Aksoy M. 2020. Katılım esasına dayalı bireysel emeklilik fonlarının performans analizi. Muhas Finan Derg, 86: 153-184.
  • Chakraborty S. 2022. TOPSIS and Modified TOPSIS: A comparative analysis. Decis Analyt J, 2: 100021.
  • Climent F, Mollá P, Soriano P. 2020. The investment performance of U.S. Islamic mutual funds. Sustainability, 12(3530): 1-18.
  • Deng X, Yuan Y. 2021. A novel fuzzy dominant goal programming for portfolio selection with systematic risk and non-systematic risk. Soft Comput, 25(23): 14809-14828.
  • Dubois D. 2006. Possibility theory and statistical reasoning. Computl Stat Data Analysis, 51(1): 47-69.
  • Dubois D, Prade H. 1988. Possibility Theory. Plenum Press, New York, US.
  • El Gibari S, Gómez T, Ruiz F. 2019. Building composite indicators using multicriteria methods: A review. J Busin Econ, 89(1): 1-24.
  • Foroozesh N, Mousavi SM, Mojtahedi M, Gitinavard H. 2022. Maintenance policy selection considering resilience engineering by a new interval-valued fuzzy decision model under uncertain conditions. Sci Iranica, 29(2): 783-799.
  • Fullér R, Harmati IA. 2018. On possibilistic dependencies: A short survey of recent developments. Soft Comput Based Optimiz Decision Models, 2018: 261-273.
  • Fullér R, Mezei J, Varlaki P. 2011. An improved index of interactivity for fuzzy numbers. Fuzzy Sets Syst, 165(1): 50-60.
  • Goldfarb D, Iyengar G. 2003. Robust portfolio selection problems. Math Operat Res, 28(1): 1-38.
  • Göktaş F, Duran A. 2019. A new possibilistic mean-variance model based on the principal components analysis: an application on the Turkish holding stocks. J Multiple-Valued Logic Soft Comput, 32(5-6): 455-476.
  • Garai T, Dalapati S, Garg H, Roy TK. 2020. Possibility mean, variance and standard deviation of single-valued neutrosophic numbers and its applications to multi-attribute decision-making problems. Soft Comput, 24: 18795-18809.
  • Garai T, Garg H. 2022. Multi-criteria decision making of water resource management problem (in Agriculture field, Purulia district) based on possibility measures under generalized single valued non-linear bipolar neutrosophic environment. Expert Syst Appl, 205: 117715.
  • Güçlü F. 2022. Katılım hisse senedi şemsiye fonlarının performansının gri ilişkisel analiz yöntemi ile incelenmesi. Finans Ekon Sos Araş Derg, 7(1): 121-130.
  • Güçlü F, Şekkeli FE. 2020. Türkiye’deki İslami ve konvansiyonel hisse senedi yatırım fonlarının performans analizi ve karşılaştırılması. Busin Manag Stud, 8(5): 4463-4486.
  • MKK. 2023. Uyruk bazında yatırımcı sayıları. Veri Analiz Platformu. URL: https://www.vap.org.tr/uyruk-bazinda-yatirimci-sayilari (erişim tarihi: 29 Eylül 2023).
  • Moghaddam NB, Nasiri M, Mousavi SM. 2011. An appropriate multiple criteria decision making method for solving electricity planning problems, addressing sustainability issue. Int J Environ Sci Technol, 8(3): 605-620.
  • Nainggolan Y, How J, Verhoeven P. 2016. Ethical screening and financial performance: The case of Islamic equity funds. J Busin Ethics, 137(1): 83-99.
  • Odu GO. 2019. Weighting methods for multi-criteria decision making technique. J Appl Sci Environ Manag, 23(8): 1449-1457.
  • Reig-Mullor J, Salas-Molina F. 2022. Non-linear neutrosophic numbers and its application to multiple criteria performance assessment. Int J Fuzzy Syst, 24(6): 2889-2904.
  • Saaty TL. 2003. Decision making with the AHP: why is the principal eigenvector necessary. European Journal of J Operat Res, 145(1): 85-91.
  • Saaty TL, Tran LT. 2007. On the invalidity of fuzzifying numerical judgments in the analytic hierarchy process. Math Comput Model, 46(7-8): 962-975.
  • Saaty TL, Vargas LG. 2012. models, methods, concepts & applications of the analytic hierarchy process. Springer, New York, US, pp: 78.
  • Sikalo M, Arnaut-Berilo A, Zaimovic A. 2022. Efficient asset allocation: Application of game theory-based model for superior performance. Int J Finan Stud, 10(1): 20.
  • Sorooshian S, Parsia Y. 2019. Modified weighted sum method for decisions with altered sources of information. Math Stat, 7(3): 57-60.
  • Taherdoost H, Madanchian M. 2023. Multi-criteria decision making (MCDM) methods and concepts. Encyclopedia, 3(1): 77-87.
  • Tütüncü RH, Koenig M. 2004. Robust asset allocation. Annals Operat Res, 132: 157-187.
  • Vafaei N, Ribeiro RA, Camarinha-Matos LM. 2016. Normalization techniques for multi-criteria decision making: Analytical hierarchy process case study. Doctoral conference on computing, electrical and industrial systems. Springer, Cham, New York, US, pp: 261-269.
  • Wan SP, Li DF. 2013. Possibility mean and variance based method for multi-attribute decision making with triangular intuitionistic fuzzy numbers. J Intell Fuzzy Syst, 24(4): 743-754.
  • Wang X, Yang F, Wei H, Zhang L. 2015. A new ranking method based on TOPSIS and possibility theory for multi-attribute decision making problem. Optik, 126(24): 4852-4860.
  • Ye F, Li Y. 2014. An extended TOPSIS model based on the possibility theory under fuzzy environment. Knowledge-Based Syst, 67: 263-269.
  • Yi ZH, Li HQ. 2018. Triangular norm‐based cuts and possibility characteristics of triangular intuitionistic fuzzy numbers for decision making. Int J Intell Syst, 33(6): 1165-1179.
  • Zadeh LA. 1965. Fuzzy sets. Info Control, 8(3): 338-353.
  • Zadeh LA. 1978. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst, 1(1): 3-28.
  • Zavadskas EK, Turskis Z, Kildienė S. 2014. State of art surveys of overviews on MCDM/MADM methods. Technol Econ Devel Econ, 20(1): 165-179.

A New Multi-Criteria Decision Making Approach “Possibilistic Evaluation System”: An Application on Participation Funds

Year 2024, Volume: 7 Issue: 1, 1 - 8, 15.01.2024
https://doi.org/10.34248/bsengineering.1341340

Abstract

Participation stock umbrella funds are an investment alternative that provides the opportunity to invest in stocks filtered within the framework of Islamic finance principles. Possibility theory is an important tool in decision making. In this study, we propose a new multi-criteria decision making (MCDM) approach based on possibility theory for problems such as comparing participation stock umbrella funds. We call this approach as the Possibilistic Evaluation System (PES). PES is related to the maximin rule, weighted sum method and maximax rule, which are the elementary MCDM methods. We uniquely derive alternatives’ priority vector with PES. In other words, it gives a unique solution for multi-objective decision making problems such as portfolio selection. It depends on selecting the alternative having the highest priority for multi-attribute decision making problems. We illustrate PES by using the real data set of five different participation stock umbrella funds traded in Türkiye between 31.07.2020 and 30.12.2022. In our application, we observe that PES reveals more information than these elementary methods.

References

  • Ali MY, Sultana A, Khan AFMK. 2016. Comparison of fuzzy multiplication operation on triangular fuzzy number. IOSR J Math, 12(4): 35-41.
  • Alonso JA, Lamata MT. 2006. Consistency in the analytic hierarchy process: a new approach. Int J Uncert Fuzzi Knowledge-bas Syst, 14(04): 445-459.
  • Bayraktar M, Aksoy M. 2020. Katılım esasına dayalı bireysel emeklilik fonlarının performans analizi. Muhas Finan Derg, 86: 153-184.
  • Chakraborty S. 2022. TOPSIS and Modified TOPSIS: A comparative analysis. Decis Analyt J, 2: 100021.
  • Climent F, Mollá P, Soriano P. 2020. The investment performance of U.S. Islamic mutual funds. Sustainability, 12(3530): 1-18.
  • Deng X, Yuan Y. 2021. A novel fuzzy dominant goal programming for portfolio selection with systematic risk and non-systematic risk. Soft Comput, 25(23): 14809-14828.
  • Dubois D. 2006. Possibility theory and statistical reasoning. Computl Stat Data Analysis, 51(1): 47-69.
  • Dubois D, Prade H. 1988. Possibility Theory. Plenum Press, New York, US.
  • El Gibari S, Gómez T, Ruiz F. 2019. Building composite indicators using multicriteria methods: A review. J Busin Econ, 89(1): 1-24.
  • Foroozesh N, Mousavi SM, Mojtahedi M, Gitinavard H. 2022. Maintenance policy selection considering resilience engineering by a new interval-valued fuzzy decision model under uncertain conditions. Sci Iranica, 29(2): 783-799.
  • Fullér R, Harmati IA. 2018. On possibilistic dependencies: A short survey of recent developments. Soft Comput Based Optimiz Decision Models, 2018: 261-273.
  • Fullér R, Mezei J, Varlaki P. 2011. An improved index of interactivity for fuzzy numbers. Fuzzy Sets Syst, 165(1): 50-60.
  • Goldfarb D, Iyengar G. 2003. Robust portfolio selection problems. Math Operat Res, 28(1): 1-38.
  • Göktaş F, Duran A. 2019. A new possibilistic mean-variance model based on the principal components analysis: an application on the Turkish holding stocks. J Multiple-Valued Logic Soft Comput, 32(5-6): 455-476.
  • Garai T, Dalapati S, Garg H, Roy TK. 2020. Possibility mean, variance and standard deviation of single-valued neutrosophic numbers and its applications to multi-attribute decision-making problems. Soft Comput, 24: 18795-18809.
  • Garai T, Garg H. 2022. Multi-criteria decision making of water resource management problem (in Agriculture field, Purulia district) based on possibility measures under generalized single valued non-linear bipolar neutrosophic environment. Expert Syst Appl, 205: 117715.
  • Güçlü F. 2022. Katılım hisse senedi şemsiye fonlarının performansının gri ilişkisel analiz yöntemi ile incelenmesi. Finans Ekon Sos Araş Derg, 7(1): 121-130.
  • Güçlü F, Şekkeli FE. 2020. Türkiye’deki İslami ve konvansiyonel hisse senedi yatırım fonlarının performans analizi ve karşılaştırılması. Busin Manag Stud, 8(5): 4463-4486.
  • MKK. 2023. Uyruk bazında yatırımcı sayıları. Veri Analiz Platformu. URL: https://www.vap.org.tr/uyruk-bazinda-yatirimci-sayilari (erişim tarihi: 29 Eylül 2023).
  • Moghaddam NB, Nasiri M, Mousavi SM. 2011. An appropriate multiple criteria decision making method for solving electricity planning problems, addressing sustainability issue. Int J Environ Sci Technol, 8(3): 605-620.
  • Nainggolan Y, How J, Verhoeven P. 2016. Ethical screening and financial performance: The case of Islamic equity funds. J Busin Ethics, 137(1): 83-99.
  • Odu GO. 2019. Weighting methods for multi-criteria decision making technique. J Appl Sci Environ Manag, 23(8): 1449-1457.
  • Reig-Mullor J, Salas-Molina F. 2022. Non-linear neutrosophic numbers and its application to multiple criteria performance assessment. Int J Fuzzy Syst, 24(6): 2889-2904.
  • Saaty TL. 2003. Decision making with the AHP: why is the principal eigenvector necessary. European Journal of J Operat Res, 145(1): 85-91.
  • Saaty TL, Tran LT. 2007. On the invalidity of fuzzifying numerical judgments in the analytic hierarchy process. Math Comput Model, 46(7-8): 962-975.
  • Saaty TL, Vargas LG. 2012. models, methods, concepts & applications of the analytic hierarchy process. Springer, New York, US, pp: 78.
  • Sikalo M, Arnaut-Berilo A, Zaimovic A. 2022. Efficient asset allocation: Application of game theory-based model for superior performance. Int J Finan Stud, 10(1): 20.
  • Sorooshian S, Parsia Y. 2019. Modified weighted sum method for decisions with altered sources of information. Math Stat, 7(3): 57-60.
  • Taherdoost H, Madanchian M. 2023. Multi-criteria decision making (MCDM) methods and concepts. Encyclopedia, 3(1): 77-87.
  • Tütüncü RH, Koenig M. 2004. Robust asset allocation. Annals Operat Res, 132: 157-187.
  • Vafaei N, Ribeiro RA, Camarinha-Matos LM. 2016. Normalization techniques for multi-criteria decision making: Analytical hierarchy process case study. Doctoral conference on computing, electrical and industrial systems. Springer, Cham, New York, US, pp: 261-269.
  • Wan SP, Li DF. 2013. Possibility mean and variance based method for multi-attribute decision making with triangular intuitionistic fuzzy numbers. J Intell Fuzzy Syst, 24(4): 743-754.
  • Wang X, Yang F, Wei H, Zhang L. 2015. A new ranking method based on TOPSIS and possibility theory for multi-attribute decision making problem. Optik, 126(24): 4852-4860.
  • Ye F, Li Y. 2014. An extended TOPSIS model based on the possibility theory under fuzzy environment. Knowledge-Based Syst, 67: 263-269.
  • Yi ZH, Li HQ. 2018. Triangular norm‐based cuts and possibility characteristics of triangular intuitionistic fuzzy numbers for decision making. Int J Intell Syst, 33(6): 1165-1179.
  • Zadeh LA. 1965. Fuzzy sets. Info Control, 8(3): 338-353.
  • Zadeh LA. 1978. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst, 1(1): 3-28.
  • Zavadskas EK, Turskis Z, Kildienė S. 2014. State of art surveys of overviews on MCDM/MADM methods. Technol Econ Devel Econ, 20(1): 165-179.
There are 38 citations in total.

Details

Primary Language Turkish
Subjects Multiple Criteria Decision Making
Journal Section Research Articles
Authors

Furkan Göktaş 0000-0001-9291-3912

Fatih Güçlü 0000-0002-1007-4594

Early Pub Date November 29, 2023
Publication Date January 15, 2024
Submission Date August 11, 2023
Acceptance Date October 27, 2023
Published in Issue Year 2024 Volume: 7 Issue: 1

Cite

APA Göktaş, F., & Güçlü, F. (2024). Yeni Bir Çok Kriterli Karar Verme Yaklaşımı “Olabilirlik Değerlendirme Sistemi”: Katılım Fonları Üzerine Bir Uygulama. Black Sea Journal of Engineering and Science, 7(1), 1-8. https://doi.org/10.34248/bsengineering.1341340
AMA Göktaş F, Güçlü F. Yeni Bir Çok Kriterli Karar Verme Yaklaşımı “Olabilirlik Değerlendirme Sistemi”: Katılım Fonları Üzerine Bir Uygulama. BSJ Eng. Sci. January 2024;7(1):1-8. doi:10.34248/bsengineering.1341340
Chicago Göktaş, Furkan, and Fatih Güçlü. “Yeni Bir Çok Kriterli Karar Verme Yaklaşımı ‘Olabilirlik Değerlendirme Sistemi’: Katılım Fonları Üzerine Bir Uygulama”. Black Sea Journal of Engineering and Science 7, no. 1 (January 2024): 1-8. https://doi.org/10.34248/bsengineering.1341340.
EndNote Göktaş F, Güçlü F (January 1, 2024) Yeni Bir Çok Kriterli Karar Verme Yaklaşımı “Olabilirlik Değerlendirme Sistemi”: Katılım Fonları Üzerine Bir Uygulama. Black Sea Journal of Engineering and Science 7 1 1–8.
IEEE F. Göktaş and F. Güçlü, “Yeni Bir Çok Kriterli Karar Verme Yaklaşımı ‘Olabilirlik Değerlendirme Sistemi’: Katılım Fonları Üzerine Bir Uygulama”, BSJ Eng. Sci., vol. 7, no. 1, pp. 1–8, 2024, doi: 10.34248/bsengineering.1341340.
ISNAD Göktaş, Furkan - Güçlü, Fatih. “Yeni Bir Çok Kriterli Karar Verme Yaklaşımı ‘Olabilirlik Değerlendirme Sistemi’: Katılım Fonları Üzerine Bir Uygulama”. Black Sea Journal of Engineering and Science 7/1 (January 2024), 1-8. https://doi.org/10.34248/bsengineering.1341340.
JAMA Göktaş F, Güçlü F. Yeni Bir Çok Kriterli Karar Verme Yaklaşımı “Olabilirlik Değerlendirme Sistemi”: Katılım Fonları Üzerine Bir Uygulama. BSJ Eng. Sci. 2024;7:1–8.
MLA Göktaş, Furkan and Fatih Güçlü. “Yeni Bir Çok Kriterli Karar Verme Yaklaşımı ‘Olabilirlik Değerlendirme Sistemi’: Katılım Fonları Üzerine Bir Uygulama”. Black Sea Journal of Engineering and Science, vol. 7, no. 1, 2024, pp. 1-8, doi:10.34248/bsengineering.1341340.
Vancouver Göktaş F, Güçlü F. Yeni Bir Çok Kriterli Karar Verme Yaklaşımı “Olabilirlik Değerlendirme Sistemi”: Katılım Fonları Üzerine Bir Uygulama. BSJ Eng. Sci. 2024;7(1):1-8.

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