Identifying distress among banks prior to a major crisis using non-oriented super-SBM.

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  • Additional Information
    • Author-Supplied Keywords:
      C21
      Distress prediction
      Financial crisis
    • NAICS/Industry Codes:
      551111 Offices of Bank Holding Companies
      551113 Holding companies
    • Abstract:
      We illustrate how data envelopment analysis (DEA) can be used as a forward-looking method to flag bank holding companies (BHCs) likely to become distressed. Various financial performance models are tested in the period leading up to the recent global financial crisis. Results generally support DEA's discriminatory and predictive power, suggesting that it can identify distressed banks up to 2 years in advance. Robustness tests reveal that DEA has a stable efficient frontier and its discriminatory and predictive powers prevail even after data perturbations. DEA can be used as a preliminary off-site screening tool by regulators, by business managers to ascertain their standing among competitors, and by investors. Attention by regulators can be further directed at potentially distressed banks as some of them would be candidates for closer monitoring. In conclusion, DEA may be useful in making economic decisions because there is an identifiable link between inefficiency and financial distress. To the best of our knowledge, application of DEA to predict financial distress among BHCs prior to a major crisis has not been published. [ABSTRACT FROM AUTHOR]
    • Abstract:
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    • Author Affiliations:
      1UQ Business School, The University of Queensland, Brisbane 4072 Australia
    • ISSN:
      0254-5330
    • Accession Number:
      10.1007/s10479-014-1568-8
    • Accession Number:
      96324345
  • Citations
    • ABNT:
      AVKIRAN, N.; CAI, L. Identifying distress among banks prior to a major crisis using non-oriented super-SBM. Annals of Operations Research, [s. l.], v. 217, n. 1, p. 31–53, 2014. DOI 10.1007/s10479-014-1568-8. Disponível em: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bth&AN=96324345&custid=s6224580. Acesso em: 19 jan. 2020.
    • AMA:
      Avkiran N, Cai L. Identifying distress among banks prior to a major crisis using non-oriented super-SBM. Annals of Operations Research. 2014;217(1):31-53. doi:10.1007/s10479-014-1568-8.
    • APA:
      Avkiran, N., & Cai, L. (2014). Identifying distress among banks prior to a major crisis using non-oriented super-SBM. Annals of Operations Research, 217(1), 31–53. https://doi.org/10.1007/s10479-014-1568-8
    • Chicago/Turabian: Author-Date:
      Avkiran, Necmi, and Lin Cai. 2014. “Identifying Distress among Banks Prior to a Major Crisis Using Non-Oriented Super-SBM.” Annals of Operations Research 217 (1): 31–53. doi:10.1007/s10479-014-1568-8.
    • Harvard:
      Avkiran, N. and Cai, L. (2014) ‘Identifying distress among banks prior to a major crisis using non-oriented super-SBM’, Annals of Operations Research, 217(1), pp. 31–53. doi: 10.1007/s10479-014-1568-8.
    • Harvard: Australian:
      Avkiran, N & Cai, L 2014, ‘Identifying distress among banks prior to a major crisis using non-oriented super-SBM’, Annals of Operations Research, vol. 217, no. 1, pp. 31–53, viewed 19 January 2020, .
    • MLA:
      Avkiran, Necmi, and Lin Cai. “Identifying Distress among Banks Prior to a Major Crisis Using Non-Oriented Super-SBM.” Annals of Operations Research, vol. 217, no. 1, June 2014, pp. 31–53. EBSCOhost, doi:10.1007/s10479-014-1568-8.
    • Chicago/Turabian: Humanities:
      Avkiran, Necmi, and Lin Cai. “Identifying Distress among Banks Prior to a Major Crisis Using Non-Oriented Super-SBM.” Annals of Operations Research 217, no. 1 (June 2014): 31–53. doi:10.1007/s10479-014-1568-8.
    • Vancouver/ICMJE:
      Avkiran N, Cai L. Identifying distress among banks prior to a major crisis using non-oriented super-SBM. Annals of Operations Research [Internet]. 2014 Jun [cited 2020 Jan 19];217(1):31–53. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bth&AN=96324345&custid=s6224580