Finansal tabloların finansal inceleme sonuçları üzerindeki etkisi. Finansal durum tablosu mu gelir tablosu mu?

Year 2023, Volume: 9 Issue: 1, 80 - 96, 27.02.2023

M. Esra Atukalp

https://doi.org/10.30855/gjeb.2023.9.1.006

Abstract

Bu çalışma kalkınma ve yatırım bankalarında finansal durum tablosu ve gelir tablosu verilerinin çok kriterli karar verme tekniklerinde kriter olarak belirlenmesi durumunda, değerlendirme sonuçlarının, kriterlerin belirlendiği finansal tablolardaki değişikliklerden etkilenip etkilenmediğini test etmektedir. Bu kapsamda Türk bankacılık sektöründe faaliyet gösteren kalkınma ve yatırım bankaları 2015-2020 dönemi için ele alınmıştır. Finansal durum tablosu ve gelir tablosu verileri ayrıştırılarak incelendiğinde sonuca etki etme olasılığı göz önünde bulundurulmalıdır. Bu amaca uygun olarak kriter ağırlıklandırma için Entropi yöntemi, performans değerlendirmesi için Topsis yöntemi, kriterlerin seçiminde finansal tabloların performans üzerindeki etkisini ve her bir finansal tablo ayrı ayrı ele alındığında bankanın performans sıralaması arasındaki ilişkiyi belirlemek için Spearman sıra korelasyon katsayısı kullanılmıştır. Analiz sonuçlarına göre kalkınma ve yatırım bankalarının finansal değerlendirmelerinde finansal durum tablosu veya gelir tablosu dikkate alındığında yüksek düzeyde ilişkili, benzer sonuçlar ortaya çıkmaktadır. Bu finansal tablolardan biri diğerine göre (olumlu veya olumsuz) farklı sonuçlar vermemektedir.

Keywords

Finansal durum tablosu, gelir tablosu, mukayese, kalkınma ve yatırım bankası, çok kriterli karar verme.

The effect of financial statements on financial review results. Statement of financial position or income statement?

Abstract

This study tests whether the evaluation results are affected by the changes in the financial statements in which the criteria are determined, in the case that the statement of financial position and income statement data in development and investment banks are determined as criteria in multi-criteria decision-making techniques. In this context, development and investment banks operating in the Turkish banking sector have been discussed for the period of 2015-2020. The possibility of affecting the result should be considered, when the statement of financial position and the income statement data are analysed separately. In accordance with this purpose, for criterion weighting Entropy method, for performance evaluation Topsis method and to determine the effect of financial statements on performance in the selection of criteria and the relationship between the bank's performance ranking considering each financial statement separately Spearman rank correlation coefficient have been used. According to the analysis results, when the statement of financial position or the income statement is taken into account, similar highly correlated results emerge in the financial evaluations of development and investment banks. None of these financial statements gives different results (positive or negative) than the other.

Keywords

Statement of financial position, income statement, comparison, development and investment bank, multi-criteria decision making

References

• Amiri, M., Zandieh, M., Vahdani, B., Soltani, R. & Roshanaei, V. (2010). An integrated eigenvector–DEA-TOPSIS methodology for portfolio risk evaluation in the forex spot market. Expert Systems with Applications, 37, 509-516.
• Aras, G., Tezcan, N. & Kutlu Furtuna, Özlem (2018). The value relevance of banking sector multidimensional corporate sustainability performance, Corporate Social Responsibility and Environmental Management, 25(6), 1062-1073.
• Chamodrakas, I., Leftheriotis, I. & Martakos, D. (2011). In-depth analysis and simulation study of an innovative fuzzy approach for ranking alternatives in multiple attribute decision making problems based on TOPSIS. Applied Soft Computing, 11, 900-907.
• Cheng-Min, F. & Rong-Tsu, W. (2001). Considering the financial ratios on the performance evaluation of highway bus industry. Transport Review, 21(4), 449-467.
• Çelen, A. (2014). Comparative analysis of normalization procedures in TOPSIS method: with an application to Turkish deposit banking market. Informatica, 25(2), 185-208.
• Ding, Y., Jeanjean, T. & Stolowy, H. (2005). Why do firms opt for alternative-format financial statements? some evidence from France. https://papers.ssrn.com/sol3/papers.cfm?abstract_id= 657082 (09.09.2021)
• Göktaş, A. & İşçi, Ö. (2011). Comparison of the most commonly used measures of association for doubly ordered square contingency tables via simulation. Metodološki zvezki, 8, 17-37.
• Guru, S. & Mahalik, D. K. (2019). A comparative study on performance measurement of Indian public sector banks using AHP-TOPSIS and AHP-grey relational analysis. Opsearch, 56, 1213-1239.
• Hwang, C. L. & Yoon, K. (1981). Multiple attribute decision making Methods and applications A state-of the art survey. Lecture Notes in Economics and Mathematical Systems, (186), Berlin Heidelberg; New-York: Springer-Verlag.
• Jahanshahloo, G. R., Hosseinzadeh Lotfi, F. & Izadikhah, M. (2006). An algorithmic method to extend TOPSIS for decision-making problems with interval data. Applied Mathematics Computation., 175(2), 1375-1384.
• Malíková, O. & Brabec, Z. (2012). The influence of a different accounting system on informative value of selected financial ratios. Technological and Economic Development of Economy, 18(1), 149-163.
• Marjanović, I. & Marković, M. (2020). Assessing the financial sector development of EU countries: an entropy-based TOPSIS approach. Innovation as an Initiator of the Development “Innovations in the Function of Development, International Thematic Monograph - Thematic Proceedings, Belgrade, Serbia, 148-165.
• Sarı, T. & Kayral, İ. E. (2019). Performance evaluation of Turkish banks with TOPSIS and stepwise regression. International Conference on Research in Business, Management & Finance, Amsterdam, Netherlands, https://www.dpublication.com/wp-content/uploads/2019/07/3-6013-ICRBMF.pdf (09.09.2021)
• Shannon, C. E. (1948). A mathematical theory of communication. Bell Systems and Technology Journal, 27, 379-423.
• Wu, M., Li, C., Fan, J., Wang, X. & Wu, Z. (2018). Assessing the global productive efficiency of Chinese banks using the cross-efficiency interval and VIKOR. Emerging Markets Review, 34, 77-86.
• Zhang, H., Gu, C., Gu. L. & Zhang, Y. (2011). The evaluation of tourism destination competitiveness by TOPSIS & information Entropy - a case in the Yangtze River Delta of China. Tourism Management, 32(2), 443-451.
• Zhang, X., Wang, C., Li, E. & Xu, C. (2014). Assessment model of ecoenvironmental vulnerability based on improved entropy weight method. The Scientific World Journal, 1-7