Stock Market Performance Evaluation of Listed Food and Beverage Companies in Istanbul Stock Exchange with MCDM Methods
DOI:
https://doi.org/10.31181/dmame722024692Keywords:
Stock market performance, Financial ratios, DEMATEL, CRITIC, EDAS, TOPSIS, WASPASAbstract
The analysis of the stock market performance ratios is crucial for investors and fund managers. The food and beverage industry in Turkey is the largest sector in the Istanbul Stock Exchange (ISE). It contributes over half of the country’s GDP and is a highly attractive sector. This study aims to rank the top food and beverage companies based on their stock market performance ratios. The criteria weights were determined by using DEMATEL and CRITIC methods, with the help of three experts for DEMATEL. The stock market performances of the companies were evaluated by using three MCDM methods; EDAS, WASPAS, and TOPSIS, with the weights obtained from both DEMATEL and CRITIC. The robustness of the results was tested by applying various combinations of weighting and evaluation methods. According to the DEMATEL, earnings per share had the highest weight while CRITIC found the market value to book value ratio as the most important criterion. The study concluded that the best-ranked companies are CCOLA and TBORG. Also, there is no significant stability in other companies’ rankings. To reveal which methods produced similar rankings, Spearman’s Rank Correlation analysis was conducted: while WASPAS combinations produced similar rankings, all EDAS and TOPSIS combinations gave similar findings.
Downloads
References
Öztürk, Y. (2021). Food Production in Türkiye and Opportunities for Swiss SMEs. https://www.s-ge.com/en/article/global-opportunities/20211-c5-food-turkey-market-overview?ct
Aldalou, E., & Perçin, S. (2020). Financial Performance Evaluation of Food and Drink Index Using Fuzzy MCDM Approach. International Journal of Economics and Innovation, 6(1), 1-19.
Baydaş, M., & Pamučar, D. (2022). Determining Objective Characteristics of MCDM Methods under Uncertainty: An Exploration Study with Financial Data. Mathematics, 10(7), 1115. https://doi.org/10.3390/math10071115
Ayan, B., & Abacıoğlu, S. (2022). Bibliometric Analysis of the MCDM Methods in the Last Decade: WASPAS, MABAC, EDAS, CODAS, COCOSO, and MARCOS. International Journal of Business and Economic Studies, 4(2), 65-85. https://doi.org/10.54821/uiecd.1183443
Iç, Y.T. (2014). A TOPSIS based design of experiment approach to assess company ranking. Applied Mathematics and Computation, 227, 630–647. https://doi.org/10.1016/J.AMC.2013.11.043
Liew, K. F., Lam, W. S., & Lam, W. H. (2022). Financial Network Analysis on the Performance of Companies Using Integrated Entropy–DEMATEL–TOPSIS Model. Entropy, 24(8), 1056. https://doi.org/10.3390/e24081056
Sarigül, S. S. (2023). Financial Performance Analysis of Airlines Operating in Europe: CRITIC Based MAUT and MARCOS Methods Avrupa’da Faaliyet Gösteren Havayolu İşletmelerinin Finansal Performans Analizi: CRITIC Temelli MAUT ve MARCOS Yöntemleri. International Journal of Business & Economic Studies, 5(2), 76–97. https://doi.org/10.54821/uiecd.1257488
Mitra, A. (2022). Selection of Cotton Fabrics Using EDAS Method. Journal of Natural Fibers, 19(7), 2706–2718. https://doi.org/10.1080/15440478.2020.1821289
Chaitanya, K. L., & Kolla, S. (2019). Sensitive Analysis on Selection of Piston Material Using MADM Techniques. Strojnicky Casopis, 69(4), 45–56. https://doi.org/10.2478/scjme-2019-0042
Tzeng, G. H., & H. J. J. (2011). Multiple Attribute Decision Making: Methods and Application. CRC Press.
Battal, Ü. (2018). Türkiye’de Havayolu Taşımacılığının Finansman Sorunları: Dematel Yöntemi Uygulaması. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 11(2), 96–111. https://doi.org/10.25287/ohuiibf.394862
Yalnız, T., &Candan, G. (2019). Belirsizlik Şartlarında Yatırım Karar Analizine Etki Eden Faktörlerin Bulanık DEMATEL Yaklaşımıyla Değerlendirilmesi. EKOIST Journal of Econometrics and Statistics, 30, 49-64. https://doi.org/10.26650/ekoist.2018.30.0009
Ersin, İ., Dinçer, H., & Yüksel, S. (2019). Yerel Yönetimlerde Yatırım Kriterlerinin Belirlenmesi: Bulanık DEMATEL Yöntemiyle Bir Analiz. Yönetim ve Ekonomi Dergisi, 26(2), 477–493. https://doi.org/10.18657/yonveek.496291
Altın, H. (2021). Analysis of financial markets with the DEMATEL method. Pressacademia, 8(1), 53–66. https://doi.org/10.17261/pressacademia.2021.1378
Si, S. L., You, X. Y., Liu, H. C., & Zhang, P. (2018). DEMATEL Technique: A Systematic Review of the State-of-the-Art Literature on Methodologies and Applications. Mathematical Problems in Engineering, 2018, 3696457. https://doi.org/10.1155/2018/3696457
Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The critic method. Computers and Operations Research, 22(7), 763–770. https://doi.org/10.1016/0305-0548(94)00059-H
Bayram, E. (2019). Katılım Bankalarının Finansal Performans Analizi: CRITIC ve PROMETHEE Yaklaşımları. Balkan Journal of Social Sciences, 9(18), 32-38.
Büyükgebiz Koca, E., & Tunca, M. Z. (2019). G20 Ülkelerinin Ekonomik Performanslarının Gri İlişkisel Analiz Yöntemi ile Değerlendirilmesi. Mehmet Akif Ersoy Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 11(28), 348–357. https://doi.org/10.20875/makusobed.541005
Doğan, H. (2022). Türkiye’nin Makroekonomik Performansının 2010-2020 Yılları İçin CRITIC Temelli ARAS Yöntemi ile Değerlendirilmesi. Asya Studies, 6(19), 189–202.
Pala, O. (2022). BIST Sigorta Endeksinde CRITIC ve MULTIMOOSRAL Tekniklerine Dayalı Finansal Analiz. İzmir İktisat Dergisi, 37(1), 218–235. https://doi.org/10.24988/ije.939532
Ghorabaee, M. K., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-Criteria Inventory Classification Using a New Method of Evaluation Based on Distance from Average Solution (EDAS). Informatica, 26(3), 435–451. https://doi.org/10.15388/Informatica.2015.57
Koşaroğlu, Ş. M. (2020). BİST’te İşlem Gören Bankaların Performanslarının SD ve EDAS Yöntemleriyle Değerlendirilmesi. Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 5(3), 406–417. https://doi.org/10.29106/fesa.758281
Öndeş, T., & Özkan, T. (2021). Bütünleşik CRITIC-EDAS Yaklaşımıyla Covid-19 Pandemisinin Bilişim Sektörü Üzerindeki Finansal Performans Etkisi. Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 12(2), 506-522.
Özdemir, O., & Parmaksız, S. (2022). BIST Enerji İşletmelerinin Finansal Performanslarının Çok Kriterli Karar Verme Teknikleri ile Karşılaştırılması: TOPSIS ve EDAS Yöntemleri ile Analiz. Başkent Üniversitesi Ticari Bilimler Fakültesi Dergisi, 6(1), 34-56.
Çakalı, K. R. (2022). Performance Evaluation of Deposit Banks with Financial Ratios: Combined Use of Objective and Subjective Criteria Weighting Methods (Combined Entropy-SWARA Based EDAS Method). Alanya Akademik Bakış, 6(2), 2351–2377. https://doi.org/10.29023/alanyaakademik.1056754
Bhutia, P. W., & Phipon, R. (2012). Application of ahp and topsis method for supplier selection problem. IOSR Journal of Engineering, 2(10), 43-50.
Zulqarnain, R. M., Saeed, M., Dayan, F., Ahmad, B. (2020). Application of TOPSIS Method for Decision Making. International Journal of Scientific Research in Mathematical and Statistical Sciences, 7, 76–81.
Yamaltdinova, A. (2017). Kırgızistan’daki Bankaların Finansal Performanslarının TOPSIS Yöntemiyle Değerlendirilmesi. International Review of Economics and Management, 5(2), 68–87. https://doi.org/10.18825/iremjournal.316694
Alsu, E., Taşdemir, A., & Kallo, Z. (2018). Evaluation of Performances of Participation Banks: International Comparison with TOPSIS Method. Gaziantep University Journal of Social Sciences, 17(1), 303-316. https://doi.org/10.21547/jss.342372
Bilice, N. (2019). Turizm Sektörünün Finansal Performansının Oran Analizi ve TOPSIS Yöntemiyle Değerlendirilmesi. Atatürk University Journal of Graduate School of Social Sciences, 23(1), 173–194.
Gül, Y. (2021). Entropiye Dayalı TOPSIS Yöntemi ile Bankaların Performans Değerlendirmesi. Uşak Üniversitesi Sosyal Bilimler Dergisi, 14(1), 1-26.
Paksoy, S., & Dawai, A. (2021). FTOPSIS ve TOPSIS Yöntemleri ile Sudan’ın Makroekonomik Performansının Değerlendirilmesi. Süleyman Demirel Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 40, 255-271.
Chakraborty, S., Zavadskas, E., K., & Antucheviciene, J. (2015). Applications of waspas method as a multi-criteria decision-making tool. Economic Computation and Economic Cybernetics Studies and Research.
Stanujkić, D., & Karabašević, D. (2018). An extension of the waspas method for decision-making problems with intuitionistic fuzzy numbers: A case of website evaluation. Operational Research in Engineering Sciences: Theory and Applications, 1(1), 29–39. https://doi.org/10.31181/oresta19012010129s
Eş, A., & Kök, E. (2020). Banka Performanslarının Entropi Tabanlı WASPAS Yöntemiyle Analizi. Düzce Üniversitesi Sosyal Bilimler Dergisi, 10(2), 233-250.
Terzioğlu, M. K., Kurt, E. S., Yaşar, A., & Köken, M. (2022). BİST100-Enerji Sektörü Finansal Performansı: SWARA-VIKOR ve SWARA-WASPAS. Alanya Akademik Bakış, 6(2), 2439–2455. https://doi.org/10.29023/alanyaakademik.1079820
Demireli, E., Ural, M., & Güler Çalık, S. (2018). KAMU BANKALARINDA PERFORMANS ANALİZİ: ENTROPİ VE WASPAS YÖNTEMLERİ İLE BİR UYGULAMA. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 31, 129–141. https://doi.org/10.30794/pausbed.414721
Rençber, Ö. F., & Avcı, T. (2018). BIST’te İşlem Gören Bankaların Sermaye Yeterliliklerine Göre Karşılaştırılması: WASPAS Yöntemi ile Uygulama. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, 6(ICEESS’18), 169–175. https://doi.org/10.18506/anemon.452713
Marqués, A. I., García, V., & Sánchez, J. S. (2020). Ranking-based MCDM models in financial management applications: analysis and emerging challenges. Progress in Artificial Intelligence, 9(3), 171–193. https://doi.org/10.1007/s13748-020-00207-1
Bağcı, H., & Yerdelen Kaygın, C. (2020). BİST Holding ve Yatırım Endeksinde Yer Alan Şirketlerin Finansal Performanslarının MCDM Yöntemleri İle Ölçümü. Muhasebe ve Finansman Dergisi, 87, 301–324. https://doi.org/10.25095/mufad.756394
Kumaran, S. (2022). Financial performance index of IPO firms using VIKOR-CRITIC techniques. Finance Research Letters, 47(A), 102542. https://doi.org/10.1016/j.frl.2021.102542
Černevičienė, J., & Kabašinskas, A. (2022). Review of Multi-Criteria Decision-Making Methods in Finance Using Explainable Artificial Intelligence. Frontiers in Artificial Intelligence, 5. https://doi.org/10.3389/frai.2022.827584
Baydaş, M., & Elma, O. E. (2021). An objective criteria proposal for the comparison of MCDM and weighting methods in financial performance measurement: An application in Borsa Istanbul. Decision Making: Applications in Management and Engineering, 4(2), 257–279. https://doi.org/10.31181/DMAME210402257B
Shen, K. Y., & Tzeng, G. H. (2015). A new approach and insightful financial diagnoses for the IT industry based on a hybrid MADM model. Knowledge-Based Systems, 85, 112–130. https://doi.org/10.1016/j.knosys.2015.04.024
Saini, N., Khanduja, D. (2019). Financial Performance Evaluation Using MADM Approaches in Indian Banks. Advances in Interdisciplinary Engineering, Lecture Notes in Mechanical Engineering, 439–449.
Özçalıcı, M., Kaya, A., & Gürler, H. E. (2021). Long-Term Performance Evaluation of Deposit Banks with Multi-Criteria Decision Making Tools: The Case of Turkey. Pamukkale University Journal of Social Sciences Institute, 50, 87-114. https://doi.org/10.30794/pausbed.975901
Yıldırım, B. F., & Meydan, C. (2021). Sezgisel Bulanık EDAS (SB-EDAS) Yöntemi ile Finansal Performans Değerlendirme: BİST Perakende Ticaret Sektöründe Bir Uygulama. Süleyman Demirel Üniversitesi Vizyoner Dergisi, 12(29), 235–251. https://doi.org/10.21076/vizyoner.734092
Unvan, Y. A. (2020). Financial performance analysis of banks with TOPSIS and fuzzy TOPSIS approaches. Gazi University Journal of Science, 33(4), 904–923. https://doi.org/10.35378/gujs.730294
No, R. K. G., Niroomand, S., Didehkhani, H., & Mahmoodirad, A. (2021). Modified interval EDAS approach for the multi-criteria ranking problem in banking sector of Iran. Journal of Ambient Intelligence and Humanized Computing, 12(7), 8129–8148. https://doi.org/10.1007/s12652-020-02550-6
Haftacı, V. (2005). İşletme Bütçeleri, Beta Basım Yayım, Istanbul. (5th Edition).
Li, B., Lajbcygier, P., Chen, C. (2015). Book to Market Ration, Default Risk and Return Implications: From A Negative Perspective. From A Negative Perspective. JASSA-The Finsia Journal of Applied Finance 3, 26–32.
Fernando, J. (2022). Earnings Per Share (EPS): What It Means and How to Calculate It, Investopedia.
Gibson, C. H. (2009). Financial Reporting and Analysis: Using Financial Accounting Information. South Western Cengage Learning, USA. (11th Edition).
Sead, O. (2014). Identification and Evaluation of Factors of Dividend Policy, Economic Analysis, 47(1-2), 42-58.
Pandey, M., Litoriya, R., & Pandey, P. (2019). Application of Fuzzy DEMATEL Approach in Analyzing Mobile App Issues. Programming and Computer Software, 45(5), 268–287. https://doi.org/10.1134/S0361768819050050
Kahraman, C., Engin, O., Kabak, Ö., & Kaya, I. (2009). Information systems outsourcing decisions using a group decision-making approach. Engineering Applications of Artificial Intelligence, 22(6), 832–841. https://doi.org/10.1016/j.engappai.2008.10.009
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Decision Making: Applications in Management and Engineering
This work is licensed under a Creative Commons Attribution 4.0 International License.