Skip to main content
SpringerLink
Log in

Determining the Priorities of CAMELS Dimensions Based on Bank Performance

  • Chapter
  • First Online:
Global Approaches in Financial Economics, Banking, and Finance

Part of the book series: Contributions to Economics ((CE))

Abstract

Banks’ performances are important not only for the stability/growth of the firms and economic situation of a country; it is also important for the stability/growth of the world economy. The aim of this study is to determine the priorities of CAMELS dimensions with respect to bank performance via AHP method and to present the results as an information to researchers, investors and decision-makers. Furthermore, this study shows the feasibility of many statistical hypothesis tests by separately generated priority series from expert’s views based on performance and bankruptcy risk of banks.

CAMELS, used for bank performance appraisal, is a financial ratio analysis comparing the ratios of banks with the industries. Along with evaluating the determined priorities of CAMELS dimensions based on performance of banks, the differences of the views between the priorities based on risk of bankruptcy and performance of banks, the view differences according to the demographic characteristics of the experts, etc., are also examined. According to analysis, “Asset” (24.75%) is the most important dimension of CAMELS, and then “Earnings” (19.16%), “Liquidity” (18.54%) and “Management” (17.68%) are thought as following important dimensions with respect to bank performance. Dimensions of “Sensitivity to market risk” (11.11%) and “Capital” (10.03%) are observed as weak dimensions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Ahsan, M. K. (2016). Measuring financial performance based on CAMEL: A study on selected Islamic Banks in Bangladesh. Asian Business Review, 6(13), 47–56.

    Article  Google Scholar 

  • Akçakanat, Ö., Eren, H., Aksoy, E., & Ömürbek, V. (2017). Performance evaluation by entropy and WASPAS methods at banking sector. SDU the Journal of Faculty of Economics and Administrative Sciences, 22(2), 285–300.

    Google Scholar 

  • Akkoç, S., & Vatansever, K. (2013). Fuzzy performance evaluation with AHP and TOPSIS methods: Evidence from Turkish banking sector after the global financial crisis. Eurasian Journal of Business and Economics, 6(11), 53–74.

    Google Scholar 

  • Aspal, P. K., & Dhawan, S. (2014). Financial performance assessment of banking sector in India: A case study of old private sector banks. The Business & Management Review, 5(3), 196–211.

    Google Scholar 

  • Atyeh, M. H., Yasin, J., & Khatib, A. M. (2015). Measuring the performance of the Kuwaiti banking sector before and after the recent financial crisis. Business & Financial Affairs, 4(3), 1–3.

    Google Scholar 

  • Barr, R. S., Killgo, K. A., Siems, T. F., & Zimmel, S. (2002). Evaluating the productive efficiency and performance of US commercial banks. Managerial Finance, 28(8), 3–25.

    Article  Google Scholar 

  • Bhatia, A., & Mahendru, M. (2015). Assessment of technical efficiency of public sector banks in India using data envelopment analysis. Eurasian Journal of Business and Economics, 8(15), 115–140.

    Article  Google Scholar 

  • Chatzi, I. G., Diakomihalis, M. N., & Chytis, E. Τ. (2015). Performance of the Greek banking sector pre and throughout the financial crisis. Journal of Risk and Control, 2(1), 45–69.

    Google Scholar 

  • Chauhan, K. A., Shah, N. C., & Rao, R. V. (2008). The analytic hierarchy process as a decision-support system in the housing sector: A case study. World Applied Sciences Journal, 3(4), 609–613.

    Google Scholar 

  • Dash, M. (2017). A model for bank performance measurement integrating multivariate factor structure with multi-criteria PROMETHEE methodology. Asian Journal of Finance & Accounting, 9(1), 310–332.

    Article  Google Scholar 

  • Dodd, F. J., Donegan, H. A., & McMaster, T. B. M. (1993). A statistical approach to consistency in AHP. Mathematical and Computer Modelling, 18(6), 19–22.

    Article  Google Scholar 

  • Doumpos, M., & Zopounidis, C. (2010). A multicriteria decision support system for bank rating. Decision Support Systems, 50, 55–63.

    Article  Google Scholar 

  • Ecer, F. (2013). Türkiye’deki Özel Bankaların Finansal Performanslarının Karşılaştırılması: 2008–2011 Dönemi. AIBU Sosyal Bilimler Enstitüsü Dergisi, 13(2), 171–189.

    Google Scholar 

  • Ghasempour, S., & Salami, M. (2016). Ranking Iranian private banks based on the CAMELS model using the AHP hybrid approach and TOPSIS. International Journal of Academic Research in Accounting, Finance and Management Sciences, 6(4), 52–62.

    Google Scholar 

  • Ginevičius, R., & Podviezko, A. (2013). The evaluation of financial stability and soundness of Lithuanian banks. Ekonomska Istraživanja-Economic Research, 26(2), 191–208.

    Article  Google Scholar 

  • Gökalp, F. (2015). Comparing the financial performance of banks in Turkey by using Promethee method. Ege Strategic Research Journal, 6(1), 63–82.

    Google Scholar 

  • Güneysu, Y., Er, B., & Ar, İ. M. (2015). Türkiye’deki Ticari Bankalarin Performanslarinin AHS ve GIA Yöntemleri ile Incelenmesi. KTU SBE Sosyal Bilimler Dergisi, 9, 71–93.

    Google Scholar 

  • Hamzaçebi, C., & Pekkaya, M. (2011). Determining of stock investments with grey relational analysis. Expert Systems with Applications, 38(8), 9186–9195.

    Article  Google Scholar 

  • Ishaq, A. B., Karim, A., Ahmed, S., & Zaheer, A. (2016). Evaluating performance of commercial banks in Pakistan: “An application of Camel model”. Journal of Business & Financial Affairs, 5(1), 1–30.

    Google Scholar 

  • Jha, S., Hui, X., & Sun, B. (2013). Commercial banking efficiency in Nepal: Application of DEA and Tobit model. Information Technology Journal, 12(2), 306–314.

    Article  Google Scholar 

  • Mohiuddin, G. (2014). Use of CAMEL model: A study on financial performance of selected commercial banks in Bangladesh. Universal Journal of Accounting and Finance, 2(5), 151–160.

    Google Scholar 

  • Nouaili, M., Abaoub, E., & Ochi, A. (2015). The determinants of banking performance in front of financial changes: Case of trade banks in Tunisia. International Journal of Economics and Financial Issues, 5(2), 410–417.

    Google Scholar 

  • Ogunyemi, O., Ibiwoye, A., & Oyatoye, E. O. (2011). Analytic hierarchy process for prioritizing production functions: Illustration with pharmaceutical data. Journal of Economics and International Finance, 3(14), 749–760.

    Google Scholar 

  • Panja, S. (2017). Multivariate bank performance analysis using standardized CAMEL methodology and fuzzy analytical hierarchical process. Indian Journal of Science and Technology, 10(23), 1–17.

    Article  Google Scholar 

  • Pekkaya, M., & Akıllı, F. (2013). Statistical analysis and evaluation of airline service quality by SERVPERF-SERVQUAL scale. The International Journal of Economic and Social Research, 9(1), 75–96.

    Google Scholar 

  • Pekkaya, M., & Aktogan, M. (2014). Dizüstü bilgisayar seçimi: DEA, VIKOR ve TOPSIS ile Karşılaştırmalı bir Analiz. Ekonomik ve Sosyal Araştırmalar Dergisi, 10(1), 107–125.

    Google Scholar 

  • Pekkaya, M., & Başaran, S. (2011). Konaklama İşletmeleri Hizmet Kalitesi Boyutları Önem Derecelerinin AHP ile Belirlenmesi ve İşletmelerin Hizmet Kalitesine göre TOPSIS ile Sıralanması. Mali Ufuklar Dergisi, 5, 111–136.

    Google Scholar 

  • Pekkaya, M., & Çolak, N. (2013). Determining the priorities of ratings via AHP for the factors that effects in choosing professions for the University students. The Journal of Academic Social Science Studies, 6(2), 797–818.

    Google Scholar 

  • Pekkaya, M., & Demir, F. E. (2016). Determining the priorities of criteria in assessing the bankruptcy risk of the banks via AHP. International Journal of Management Economics and Business, ICAFR 16 Special Issue, 40–45.

    Google Scholar 

  • Pekkaya, M., & Zilifli, V. (2016). Determining the priorities of the criteria which the banks take in consideration in the assessment process of commercial credit. International Journal of Management Economics and Business, ICAFR 16 Special Issue, 201–210.

    Google Scholar 

  • Rezaei, M., & Ketabi, S. (2016). Ranking the banks through performance evaluation by integrating fuzzy AHP and TOPSIS methods: A study of Iranian private banks. International Journal of Academic Research in Accounting, Finance and Management Sciences, 6(3), 19–30.

    Article  Google Scholar 

  • Rostami, M. (2015). Determination of Camels model on bank’s performance. International Journal of Multidisciplinary Research and Development, 2(10), 652–664.

    Google Scholar 

  • Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.

    Google Scholar 

  • Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83–98.

    Article  Google Scholar 

  • Socol, A., & Dănuleţiu, A. E. (2013). Analysis of the Romanian banks’ performance through ROA, ROE and non-performing loans models. Annales Universitatis Apulensis Series Oeconomica, 15(2), 594–604.

    Google Scholar 

  • Tata, H. K., & Nimmagadda, V. S. (2016). Performance evaluation of banks through four phased DEA – A case study. International Journal of Industrial Engineering Research and Development, 7(1), 24–34.

    Google Scholar 

  • Toplu, H. Y. (2017). Effective ratios on financial performance with CAMELS approach: An application of panel regression on commercial banks in Turkey. Unpublished PhD Thesis, BEU Institute of Social Sciences, Zonguldak.

    Google Scholar 

  • Wanke, P., Kabir Hassan, M., & Gavião, L. O. (2017). Islamic banking and performance in the Asean banking industry: A TOPSIS approach with probabilistic weights. International Journal of Business and Society, 18(S1), 129–150.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Business Administration, Bülent Ecevit University, Zonguldak, Turkey

    Mehmet Pekkaya

  2. Bülent Ecevit University, Zonguldak, Turkey

    Figen Erol Demir

Authors
  1. Mehmet Pekkaya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Figen Erol Demir
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Istanbul Medipol University, Istanbul, Turkey

    Hasan Dincer

  2. Istanbul Medipol University, Istanbul, Turkey

    Ümit Hacioglu

  3. Istanbul Medipol University , Istanbul, Turkey

    Serhat Yüksel

Appendix: Characteristics of Experts

Appendix: Characteristics of Experts

 

Count

%

 

Count

%

Gender

Experience

Male

63

66.3

1–5 years

18

18.9

Female

27

28.4

6–10 year

23

24.2

Total

90

94.7

11–15 year

29

30.5

Education

16–30 year

16

16.8

Bachelor

42

44.2

Total

86

90.5

Master

39

41.1

Experts’ job

PhD

4

4.2

Academician

2

2.1

Total

85

89.5

(Assistant) Expert

47

49.5

Age (year)

(Assistant) Manager/inspector

3

3.2

26–34

25

26.3

(Assistant) Consultant

1

1.1

35–61

41

43.2

Special auditor

1

1.1

Total

66

69.5

Other

37

38.9

   

Total

91

95.8

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Pekkaya, M., Demir, F.E. (2018). Determining the Priorities of CAMELS Dimensions Based on Bank Performance. In: Dincer, H., Hacioglu, Ü., Yüksel, S. (eds) Global Approaches in Financial Economics, Banking, and Finance. Contributions to Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-78494-6_21

Download citation

Publish with us

Policies and ethics

Search

Navigation