Advertisement

Forming appropriate peer groups for bank research: a cluster analysis of bank financial statements

  • Ken B. Cyree
  • Travis R. DavidsonEmail author
  • John D. Stowe
Article
  • 7 Downloads

Abstract

Choosing appropriate peer groups for commercial banks is important to investors comparing bank performance, for regulators evaluating safety and soundness, for bank management looking at merger alternatives or relative performance, and for bank researchers testing hypotheses and making policy judgments about the banking system. We use commercial bank financial statements with common size variables as the inputs to a cluster analysis model to identify clusters or groups of banks with financial structures that are relatively homogeneous within groups and distinct across groups. Managerial strategies and idiosyncrasies, local and global economic conditions, and the regulatory environment shape bank financial statements, and financial statements should reflect the financial and operational differences across banks. Using year-end data from 2014, we cluster 6444 banks into several such groups. Our results show that bank clusters are formed largely around loan types, funding differences, and management’s strategic choices. We compare the ability of bank clusters and bank size to explain several widely used measures of bank performance and risk in additional years. These bank clusters are shown to have substantially greater explanatory power in regression models when compared to groupings based on bank size in several different years.

Keywords

Commercial bank taxonomy Financial institutions Cluster analysis Bank financial statements Bank peer groups 

JEL classification

G21 

Notes

References

  1. Ayadi R, De Groen WP, Sassi I, Mathlouthi W, Rey H, Aubry O (2016) Banking business models monitor 2015 EUROPE. International Research Centre on Cooperative Finance, Montreal  https://doi.org/10.2139/ssrn.2784334
  2. Barth JR, Brumbaugh RD Jr, Litan RE (1992) The future of American banking. Routledge, New York.  https://doi.org/10.4324/9781315487014 Google Scholar
  3. Berger AN (1995) The relationship between capital and earnings in banking. J Money Credit Bank 27(2):432–456.  https://doi.org/10.2307/2077877 CrossRefGoogle Scholar
  4. Berger AN, Bouwman CHS (2013) How does capital affect bank performance during financial crises? J Financ Econ 109(1):146–176.  https://doi.org/10.1016/j.jfineco.2013.02.008 CrossRefGoogle Scholar
  5. Berger AN, Mester LJ (1997) Inside the black box: what explains differences in the efficiencies of financial institutions? J Bank Financ 21(7):895–947.  https://doi.org/10.1016/S0378-4266(97)00010-1 CrossRefGoogle Scholar
  6. Black LK, Hazelwood LN (2013) The effect of TARP on bank risk-taking. J Financ Stab 9(4):790–803.  https://doi.org/10.1016/j.jfs.2012.04.001 CrossRefGoogle Scholar
  7. Carlson M, Shan H, Warusawitharana M (2013) Capital ratios and bank lending: a matched bank approach. J Financ Intermed 22(4):663–687.  https://doi.org/10.1016/j.jfi.2013.06.003 CrossRefGoogle Scholar
  8. Cleary S, Hebb G (2016) An efficient and functional model for predicting bank distress: in and out of sample evidence. J Bank Financ 64(C):101–111.  https://doi.org/10.1016/j.jbankfin.2015.12.001 CrossRefGoogle Scholar
  9. Cole RA, Gunther JW (1998) Predicting bank failures: a comparison of on- and off-site monitoring systems. J Financ Serv Res 13(2):103–117.  https://doi.org/10.1023/A:1007954718966 CrossRefGoogle Scholar
  10. Cole RA, White LJ (2012) Déjà vu all over again: the cause of US commercial bank failures this time around. J Finan Serv Res 42(1):5–29.  https://doi.org/10.1007/s10693-011-0116-9 CrossRefGoogle Scholar
  11. Dardac N, Boitan IA (2009) Cluster analysis approach for banks’ risk profile: the Romanian evidence. Eur Res Studies J 12(1):109–118 https://www.um.edu.mt/library/oar//handle/123456789/31853 Google Scholar
  12. Deakin EB (1976) Distributions of financial accounting ratios: some empirical evidence. Account Rev 51(1):90–96 http://www.jstor.org/stable/i302473. Accessed 28 May 2019
  13. DeLong G (2001) Stockholder gains from focusing versus diversifying bank mergers. J Financ Econ 59(2):221–252.  https://doi.org/10.1016/s0304-405x(00)00086-6 CrossRefGoogle Scholar
  14. Demsetz RS, Strahan PE (1997) Diversification, size, and risk at bank holding companies. J Money Credit Bank 29(3):300–313.  https://doi.org/10.2307/2953695 CrossRefGoogle Scholar
  15. Demyanyk Y, Hasan I (2010) Financial crises and bank failures: a review of prediction methods. Omega 38(5):315–324.  https://doi.org/10.1016/j.omega.2009.09.007 CrossRefGoogle Scholar
  16. Dias JG, Ramos SB (2014) The aftermath of the subprime crisis: a clustering analysis of world banking sector. Rev Quant Finan Acc 42(2):293–308.  https://doi.org/10.1007/s11156-013-0342-3 CrossRefGoogle Scholar
  17. Diaz BD, Azofra SS (2009) Determinants of premiums paid in European banking mergers and acquisitions. Int J Bank Account Financ 1(4):358–380.  https://doi.org/10.1504/ijbaaf.2009.023150 CrossRefGoogle Scholar
  18. Elsas R, Hackethal A, Holhauser M (2010) The anatomy of bank diversification. J Bank Financ 34(6):1274–1287.  https://doi.org/10.1016/j.jbankfin.2009.11.024 CrossRefGoogle Scholar
  19. Ercan H, Sayaseng S (2016) The cluster analysis of the banking sector in Europe. Economics and Management of Global Value Chains, Lengyel I, Vas Z (eds):111–127. http://www.eco.u-szeged.hu/download.php?docID=59412. Accessed 28 May 2019
  20. Hubbard GR, Kuttner KN, Palia DN (2002) Are there bank effects in borrower cost of funds? Evidence from a matched sample of borrowers and banks. J Bus 75(4):559–581.  https://doi.org/10.1086/341635 CrossRefGoogle Scholar
  21. Hughes JP, Mester LJ (1998) Bank capitalization and cost: evidence of scale economies in risk management and signaling. Rev Econ Stat 80(2):314–325.  https://doi.org/10.1162/003465398557401 CrossRefGoogle Scholar
  22. Hughes JP, Mester LJ (2013) Who said large banks don’t experience scale economies? Evidence from a risk-return-driven cost function. J Financ Intermed 22(4):559–585.  https://doi.org/10.1016/j.jfi.2013.06.004 CrossRefGoogle Scholar
  23. Hughes JP, Lang W, Mester LJ, Moon C-G (1996) Efficient banking under interstate branching. J Money Credit Bank 28(4):1045–1071.  https://doi.org/10.2307/2077940 CrossRefGoogle Scholar
  24. Jin JY, Kanagaretnam K, Lobo GJ (2011) Ability of accounting and audit quality variables to predict bank failure during the financial crisis. J Bank Financ 35(11):2811–2819.  https://doi.org/10.1016/j.jbankfin.2011.03.005 CrossRefGoogle Scholar
  25. Laeven L, Levine R (2007) Is there a diversification discount in financial conglomerates? J Financ Econ 85(2):331–367.  https://doi.org/10.3386/w11499 CrossRefGoogle Scholar
  26. Lane WR, Looney SW, Wansley JW (1986) An application of the cox proportional hazards model to bank failure. J Bank Financ 10(4):511–531.  https://doi.org/10.1016/s0378-4266(86)80003-6 CrossRefGoogle Scholar
  27. Lev B, Sunder S (1979) Methodological issues in the use of financial ratios. J Account Econ 1(3):187–210.  https://doi.org/10.1016/0165-4101(79)90007-7 CrossRefGoogle Scholar
  28. Meyer PA, Pifer HW (1970) Prediction of bank failures. J Financ 25(4):853–868.  https://doi.org/10.1111/j.1540-6261.1970.tb00558.x CrossRefGoogle Scholar
  29. Ravi Kumar P, Ravi V (2007) Bankruptcy prediction in banks and firms via statistical and intelligent techniques—a review. Eur J Opers Res 180(1):1–28.  https://doi.org/10.1016/j.ejor.2006.08.043 CrossRefGoogle Scholar
  30. Simonson DG, Stowe JD, Watson CJ (1983) A canonical correlation analysis of commercial bank asset/liability structures. J Financ Quant Anal 18(1):125–140.  https://doi.org/10.2307/2330808 CrossRefGoogle Scholar
  31. Sinkey JF Jr (1975) A multivariate statistical analysis of the characteristics of problem banks. J Financ 30(1):21–36.  https://doi.org/10.1111/j.1540-6261.1975.tb03158.x CrossRefGoogle Scholar
  32. Sorensen CK, Gutierrez JMP (2006) Euro area banking sector integration using hierarchical cluster analysis techniques. European Central Bank Working Paper Series https://papers.ssrn.com/sol3/papers.cfm?abstract_id=900399. Accessed 28 May 2019
  33. White HL (1980) A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48(4):817–838.  https://doi.org/10.2307/1912934 CrossRefGoogle Scholar

Copyright information

© Academy of Economics and Finance 2019

Authors and Affiliations

  • Ken B. Cyree
    • 1
  • Travis R. Davidson
    • 2
    Email author
  • John D. Stowe
    • 3
  1. 1.University of Mississippi UniversityUSA
  2. 2.Ohio UniversityAthensUSA
  3. 3.Ohio UniversityAthensUSA

Personalised recommendations