TY - JOUR T1 - TOPLAM RİSKE VE SİSTEMATİK RİSKE GÖRE BANKA TÜRLERİNİN PERFORMANSLARININ DEĞERLENDİRİLMESİ TT - Assessing the Performance of Different Bank Types Based on Total and Systematic Risk AU - Çömlekçi, İstemi PY - 2025 DA - September Y2 - 2025 DO - 10.17753/sosekev.1672175 JF - EKEV Akademi Dergisi PB - Erzurum Kültür Eğitim Vakfı WT - DergiPark SN - 1301-6229 SP - 246 EP - 262 IS - 103 LA - tr AB - Çalışmada toplam risk ve sistematik risk faktörlerini dikkate alarak farklı banka türlerinin performanslarını entropi temelli Topsis yöntemi ile belirlenmesi amaçlanmıştır. Bu amaç doğrultusunda toplam riske göre performans ölçüm modellerinden Sharpe oranı, M2 performans ölçütü, Sortino Oranı ve sistematik riske göre performans ölçüm modellerinden Treynor Oranı, T2 performans ölçütü, Jensen Alfa Değeri olmak üzere toplam 6 farklı model kullanılarak karar verme kriterleri hesaplanmıştır. Toplam riske ve sistematik riske göre belirlenen kriterlerin ağırlıkları Entropi yöntemi ile hesaplanmış, daha sonra performanslarının sıralanması ise Topsis yöntemi ile gerçekleştirilmiştir. Entropi yöntemi ile kriter ağırlık değerleri hesaplanması sonucunda, banka türlerinin performansına etki eden en önemli kriterin Jensen Alfa Değeri olduğu, en az etkili kriterin ise T2 değeri olduğu sonucuna ulaşılmıştır. Topsis yöntemi sonucunda banka türlerine göre en yüksek performans sırasıyla Katılım Bankaları, Yabancı sermayeli bankalar, Özel sermayeli bankalar ve kamu bankaları şeklinde gerçekleşmiştir. KW - Banka performansı KW - Toplam risk KW - Sistematik risk KW - Entropi yöntemi KW - Topsis yöntemi N2 - The study aims to determine the performance of different types of banks by considering total risk and systematic risk factors using the entropy-based Topsis method. In line with this objective, decision-making criteria were calculated using six different performance evaluation models: Sharpe Ratio, M2 Performance Measure, and Sortino Ratio for total risk-based models, as well as Treynor Ratio, T2 Performance Measure, and Jensen's Alpha for systematic risk-based models. The weights of the criteria determined based on total and systematic risk were calculated using the Entropy method, and the ranking of performances was conducted using the Topsis method. The results of the Entropy method indicated that Jensen's Alpha was the most influential criterion affecting bank performance, while T2 value was the least influential. According to the Topsis results, the highest performance among the bank types was observed in the following order: Participation Banks, Foreign Banks, Private Banks, and Public Banks. CR - Abdel-Basset, M., Ding, W., Mohamed, R., & Metawa, N. (2020). An integrated plithogenic MCDM approach for financial performance evaluation of manufacturing industries. Risk Management, 22(3), 192–218. https://doi.org/10.1057/s41283-020-00061-4 CR - Ashraf, M. M., & Rehman, Z. U. (2011). The performance analysis of Islamic and conventional banks: The Pakistan’s perspective. Journal of Money, Investment and Banking, 22, 99–113. CR - Bakır, M., & Atalık, Ö. (2018). Entropi ve Aras yöntemleriyle havayolu işletmelerinde hizmet kalitesinin değerlendirilmesi. İşletme Araştırmaları Dergisi, 10(1), 617–638. https://doi.org/10.20491/isarder.2018.410 CR - Banu, A. R., & Santhiyavalli, G. A. (2019). TOPSIS approach to evaluate the financial performance of scheduled commercial banks in India. IOSR International Journal of Business and Management, 21(1), 24–33. CR - Berger, A. N., & Humphrey, D. B. (1997). Efficiency of financial institutions: International survey and directions for future research. European Journal of Operational Research, 98(2), 175–212. https://doi.org/10.1016/S0377-2217(96)00342-6 CR - Bessis, J. (2011). Risk management in banking (3rd ed.). John Wiley & Sons. CR - Bulgurcu, B. K. (2012). Application of TOPSIS technique for financial performance evaluation of technology firms in Istanbul stock exchange market. Procedia - Social and Behavioral Sciences, 62, 1033–1040. https://doi.org/10.1016/j.sbspro.2012.09.176 CR - Bulut, E., & Şimşek, A. İ. (2024). Evaluation of financial performance of BIST participation banks: CAMELS and multi-criteria decision making (MCDM) approach. Alanya Akademik Bakış, 8(3), 923–940. CR - Chen, P. (2019). Effects of normalization on the entropy-based TOPSIS method. Expert Systems with Applications, 136, 33–41. https://doi.org/10.1016/j.eswa.2019.06.035 CR - Chitnis, A., & Vaidya, O. S. (2016). Efficiency ranking method using DEA and TOPSIS (ERM-DT): Case of an Indian bank. Benchmarking: An International Journal, 23(1), 165–182. https://doi.org/10.1108/BIJ-09-2013-0093 CR - Christopherson, J. A., Cariño, D. R., & Ferson, W. E. (2009). Portfolio performance measurement and benchmarking. McGraw-Hill. CR - Coşkun, B., Öncü, M. A., Çömlekçi, İ., & Hiçyılmaz, E. (2021). COVID-19’un banka finansal performanslarına etkisinin Entropi ve Waspas yöntemiyle analizi. Uluslararası İşletme, Ekonomi ve Yönetim Perspektifleri Dergisi (IJBEMP), 5(2), 810–828. https://doi.org/10.29228/ijbemp.54686 CR - Erdoğan, B. (2023). Financial performance analysis of development and investment banks: TOPSIS method. Dicle Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 34, 1–15. https://doi.org/10.15182/diclesosbed.1264349 CR - Gülençer, S. (2020). Türkiye’deki mevduat bankalarının TOPSIS ve VIKOR yöntemleriyle analizi. Kırklareli Üniversitesi Sosyal Bilimler Meslek Yüksekokulu Dergisi, 1(1), 1–22. CR - Hazzi, O. A., & Kilani, M. I. A. (2013). The financial performance analysis of Islamic and traditional banks: Evidence from Malaysia. European Journal of Economics, Finance and Administrative Sciences, 57, 133–144. CR - Hemmati, M., Dalghandi, S. A., & Nazari, H. (2013). Measuring relative performance of banking industry using a DEA and TOPSIS. Management Science Letters, 3(2), 499–504. https://doi.org/10.5267/j.msl.2012.12.025 CR - Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Multiple attribute decision making (Lecture Notes in Economics and Mathematical Systems, Vol. 186). Springer. https://doi.org/10.1007/978-3-642-48318-9_3 CR - Jayachitra, T. A., & Geetha, K. T. (2019). Profitability evaluation of selected public sector banks using TOPSIS. Journal of Xi’an University of Architecture & Technology, 9, 1177–1187. CR - Jensen, M. C. (1968). The performance of mutual funds in the period 1945–1964. The Journal of Finance, 23(2), 389–416. https://doi.org/10.2307/2325404 CR - Kakakhel, S. J., Raheem, F., & Tariq, M. (2013). A study of performance comparison between conventional and Islamic banking in Pakistan. Abasyn Journal of Social Sciences, 6(2), 91–105. CR - Karakaş, A., & Öztel, A. (2020). BIST’de yer alan turizm işletmelerinin finansal performanslarının Entropi tabanlı TOPSIS yöntemi ile belirlenmesi: Bir Python uygulaması. Dicle Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 10(20), 543–562. CR - Mandic, K., Delibasic, B., Knezevic, S., & Benkovic, S. (2014). Analysis of the financial parameters of Serbian banks through the application of the fuzzy AHP and TOPSIS methods. Economic Modelling, 43, 30–37. https://doi.org/10.1016/j.econmod.2014.07.036 CR - Marhfor, A. (2016). Portfolio performance measurement: Review of literature and avenues of future research. American Journal of Industrial and Business Management, 6(4), 432–438. https://doi.org/10.4236/ajibm.2016.64039 CR - Moghimi, R., & Anvari, A. (2014). An integrated fuzzy MCDM approach and analysis to evaluate the financial performance of Iranian cement companies. The International Journal of Advanced Manufacturing Technology, 71(1), 685–698. https://doi.org/10.1007/s00170-013-5370-6 CR - Oral, N., & Engin, O. (2024). Ticari kredilerde Bulanık-AHP ve TOPSIS yardımıyla risk analizi. Harran Üniversitesi Mühendislik Dergisi, 9(1), 22–38. https://doi.org/10.46578/humder.1419372 CR - Ova, A. (2021). Analyzing financial performance of Turkish deposit banks using TOPSIS method. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 45, 1–13. https://doi.org/10.30794/pausbed.796587 CR - Pineda, P. J. G., Liou, J. J., Hsu, C. C., & Chuang, Y. C. (2018). An integrated MCDM model for improving airline operational and financial performance. Journal of Air Transport Management, 68, 103–117. https://doi.org/10.1016/j.jairtraman.2017.06.003 CR - Rabbani, A., Zamani, M., Yazdani-Chamzini, A., & Zavadskas, E. K. (2014). Proposing a new integrated model based on sustainability balanced scorecard (SBSC) and MCDM approaches by using linguistic variables for the performance evaluation of oil producing companies. Expert Systems with Applications, 41(16), 7316–7327. https://doi.org/10.1016/j.eswa.2014.05.023 CR - Safiullah, M. (2010). Superiority of conventional banks & Islamic banks of Bangladesh: A comparative study. International Journal of Economics and Finance, 2(3), 199–207. CR - Samad, A. (2004). Performance of interest-free Islamic banks vis-à-vis interest-based conventional banks of Bahrain. IIUM Journal of Economics and Management, 12(2), 1–15. https://doi.org/10.31436/ijema.v12i2.99 CR - Seçme, N. Y., Bayrakdaroğlu, A., & Kahraman, C. (2009). Fuzzy performance evaluation in Turkish banking sector using analytic hierarchy process and TOPSIS. Expert Systems with Applications, 36(9), 11699–11709. https://doi.org/10.1016/j.eswa.2009.03.013 CR - Sharpe, W. F. (1966). Mutual fund performance. The Journal of Business, 39(1), 119–138. CR - Şendurur, U., & Temelli, F. (2018). Türkiye’de faaliyet gösteren geleneksel bankalar ve katılım bankalarının sürdürülebilirlik açısından karşılaştırılması. Muhasebe Bilim Dünyası Dergisi, 20(2), 330–346. https://doi.org/10.31460/mbdd.344785 CR - Tavana, M., Khalili-Damghani, K., & Rahmatian, R. (2015). A hybrid fuzzy MCDM method for measuring the performance of publicly held pharmaceutical companies. Annals of Operations Research, 226, 589–621. https://doi.org/10.1007/s10479-014-1738-8 CR - Türkiye Bankalar Birliği. “Bankalarımız Kitabı 2020”. 339, 1-328. Mayıs 2021, Web: https://www.tbb.org.tr/istatistiki-raporlar/2020-yillik-bankalarimiz-kitabi adresinden 02 Mart 2025’de alınmıştır. CR - Teker, S., Teker, D., & Kent, O. (2008). Yatırım fonlarının risk odaklı performans değerlemesi. Doğuş Üniversitesi Dergisi, 9(1), 89–105. CR - Treynor, J. (1965). How to rate management of investment funds. Harvard Business Review, 43(1), 63–75. CR - Ünvan, 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 CR - Vásquez, J. A., Escobar, J. W., & Manotas, D. F. (2021). AHP–TOPSIS methodology for stock portfolio investments. Risks, 10(1-4), 1-20. https://doi.org/10.3390/risks10010004 CR - Wang, Y. J., & Lee, H. S. (2007). Generalizing TOPSIS for fuzzy multiple-criteria group decision-making. Computers & Mathematics with Applications, 53(11), 1762–1772. https://doi.org/10.1016/j.camwa.2006.08.037 CR - Wanke, P., Hassan, M. K., & Gavião, L. O. (2017). Islamic banking and performance in the ASEAN banking industry: A TOPSIS approach with probabilistic weights. International Journal of Business & Society, 18, 139–162. https://doi.org/10.33736/ijbs.1322.2017 CR - Weerathunga, P. R., Xiaofang, C., Samarathunga, W. H. M. S., & Kulathunga, K. M. M. C. B. (2020). Application of entropy based TOPSIS in analysis of sustainability performance of Sri Lanka hotels. RISUS Journal on Innovation and Sustainability, 11(3), 100–108. https://doi.org/10.23925/2179-3565.2020v11i3p100-108 CR - Wu, H. Y., Tzeng, G. H., & Chen, Y. H. (2009). A fuzzy MCDM approach for evaluating banking performance based on balanced scorecard. Expert Systems with Applications, 36(6), 10135–10147. https://doi.org/10.1016/j.eswa.2009.02.042 CR - Wu, J., Sun, J., Liang, L., & Zha, Y. (2011). Determination of weights for ultimate cross efficiency using Shannon entropy. Expert Systems with Applications, 38(5), 5162–5165. https://doi.org/10.1016/j.eswa.2010.11.090 CR - Yetiz, F. (2021). TOPSIS yöntemi ile Türk katılım bankalarının performans analizi ve bankacılıkta risk yönetim politikalarının önemi. Journal of Empirical Economics and Social Sciences, 3(1), 121–138. https://doi.org/10.46959/jeess.899919 CR - Zavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). State of art surveys of overviews on MCDM/MADM methods. Technological and Economic Development of Economy, 20(1), 165–179. https://doi.org/10.3846/20294913.2014.892037 UR - https://doi.org/10.17753/sosekev.1672175 L1 - https://dergipark.org.tr/tr/download/article-file/4755420 ER -