Ranking banks by applying the multilevel I–distance methodology
Banks in the Republic of Srpska are one of the most important drivers of the economy and household savings. The activity of the financial market of the Republic of Srpska is low and banks are still the main source of funding. The question of the objective ranking of banks based on business results is an important element in the business decisions made by companies and the population. A bank’s position and quality would depend on the criteria to be included in the analysis. The professional literature recommends that banks’ liquidity, profitability, efficiency and solvency should be monitored. In most cases, whether to rank banks based on liquidity or adequacy or on another indicator is doubtful. The best picture of the state of the banks is obtained when all indicators are involved in such ranking. The aim of this study is to define and rank the banks headquartered in the Republic of Srpska by following a total of four indicators. In this paper, the calculation of banks’ liquidity, efficiency, profitability and solvency based upon the publicly presented audit reports for the years 2013 and 2014 is given. Then, the statistical model that absorbs information and generates the final ranking of banks in the RS is defined. The subject of the study is the banks that operate and are headquartered in the RS. The hypothesis is to determine their rankings based on their business performance.
Ćurčić U., (1995.) Bankarski portfolio mendažment – Strategijsko upravljanje bankom, bilansom i portfolio rizicima banke. Novi Sad: Fejton;
Dobrota, M., Bulajic, M., Bornmann, L., & Jeremic, V. (2016). A new approach to the QS university ranking using the composite I‐distance indicator: Uncertainty and sensitivity analyses. Journal of the Association for Information Science and Technology, 67(1), 200-211. DOI: https://doi.org/10.1002/asi.23355
Dragašević Z., (2010). Modeli višekriterijumske analize za rangiranje banaka. Podgorica: doctoral dissertation
García, F., Guijarro, F., & Moya, I. (2010). Ranking Spanish savings banks: A multicriteria approach. Mathematical and computer modelling, 52(7-8), 1058-1065. DOI: https://doi.org/10.1016/j.mcm.2010.02.015
Ivanovic B., (1977) Classification Theory. Belgrade: Institute for Industrial Economics;
Jeremić, V., Jovanović-Milenković, M., Radojičić, Z., & Martić, M. (2013). El profesional de la información, 22(5).. El profesional de la información 22, 474-480. DOI: https://doi.org/10.3145/epi.2013.sep.13
Milenkovic, M. J., Brajovic, B., Milenkovic, D., Vukmirovic, D., & Jeremic, V. (2016). Beyond the equal-weight framework of the Networked Readiness Index: a multilevel I-distance methodology. Information Development, 32(4), 1120-1136. DOI: https://doi.org/10.1177/0266666915593136
Maricic, M., & Kostic-Stankovic, M. (2016). Towards an impartial Responsible Competitiveness Index: a twofold multivariate I-distance approach. Quality & Quantity, 50(1), 103-120. DOI: https://doi.org/10.1007/s11135-014-0139-z
Marković, V., Stajić, L., Stević, Ž., Mitrović, G., Novarlić, B., & Radojičić, Z. (2020). A Novel Integrated Subjective-Objective MCDM Model for Alternative Ranking in Order to Achieve Business Excellence and Sustainability. Symmetry, 12(1), 164.
Radojicic, Z., & Jeremic, V. (2012). Quantity or quality: what matters more in ranking higher education institutions?. Current science, 158-162.
Roman A., Saragu A. C., (2015). The impact of bank-specific factors on the commercial banks liquidity: empirical evidence from CEE. 7th International Conference on Globalization an Higher Education in Economics and Business Administration GEBA 2013, Procedia Economics and Finance, 20, 571 – 579. DOI: https://doi.org/10.1016/S2212-5671(15)00110-0
Sinkey J., (1989.) Commercial Bank Financial Management in the Financial Services Industry. 3th Ed. New York: MacMillan Publishing Company;
Upustvo za kompiliranje idikatora finansijskog zdravlja. CCBH; 2012: Paragraph II, Article 28.