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Predicting corporate failure-- Some results for the UK corporate sector

Author

Listed:
  • Peel, MJ
  • Peel, DA
  • Pope, PF

Abstract

A large number of authors have developed statistical models, which are based solely on conventional financial ratios constructed from published accounting data, with the aim of predicting corporate failure as evidenced by the event of 'bankruptcy'. The purpose of this paper is to report some empirical results for a study of the UK corporate sector in which corporate failure is predicted employing a statistical model which incorporates both conventional accounting ratios and a number of new variables which are not derived from profit and loss accounts and balance sheet items, but which are computed from annual company reports and accounts. The empirical results suggesting that our new variables enhance the predictive power of models which employ conventional financial ratios only.

Suggested Citation

  • Peel, MJ & Peel, DA & Pope, PF, 1986. "Predicting corporate failure-- Some results for the UK corporate sector," Omega, Elsevier, vol. 14(1), pages 5-12.
  • Handle: RePEc:eee:jomega:v:14:y:1986:i:1:p:5-12
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    Cited by:

    1. Llano Monelos Pablo De & Piñeiro Sánchez Carlos & Rodríguez López Manuel, 2014. "DEA as a business failure prediction tool. Application to the case of galician SMEs," Contaduría y Administración, Accounting and Management, vol. 59(2), pages 65-96, abril-jun.
    2. Hunter, John & Isachenkova, Natalia, 2006. "Aggregate economy risk and company failure: An examination of UK quoted firms in the early 1990s," Journal of Policy Modeling, Elsevier, vol. 28(8), pages 911-919, November.
    3. Natalia Isachenkova & John Hunter, 2002. "A Panel Analysis Of UK Industrial Company Failure," Working Papers wp228, Centre for Business Research, University of Cambridge.
    4. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
    5. Antonio Blanco-Oliver & Ana Irimia-Dieguez & María Oliver-Alfonso & Nicholas Wilson, 2015. "Systemic Sovereign Risk and Asset Prices: Evidence from the CDS Market, Stressed European Economies and Nonlinear Causality Tests," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(2), pages 144-166, April.
    6. Serrano Cinca, C. & Mar Molinero, C. & Gallizo Larraz, J.L., 2005. "Country and size effects in financial ratios: A European perspective," Global Finance Journal, Elsevier, vol. 16(1), pages 26-47, August.
    7. Jason J. Constable & David R. Woodliff, 1994. "Predicting Corporate Failure Using Publicly Available Information," Australian Accounting Review, CPA Australia, vol. 4(7), pages 13-27, May.
    8. García-Gallego, Ana & Mures-Quintana, María-Jesús, 2013. "La muestra de empresas en los modelos de predicción del fracaso: influencia en los resultados de clasificación || The Sample of Firms in Business Failure Prediction Models: Influence on Classification," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 15(1), pages 133-150, June.
    9. repec:eee:spacre:v:15:y:2012:i:1:p:7-58 is not listed on IDEAS
    10. Andreas Charitou & Evi Neophytou & Chris Charalambous, 2004. "Predicting corporate failure: empirical evidence for the UK," European Accounting Review, Taylor & Francis Journals, vol. 13(3), pages 465-497.
    11. Robert C. Cressy, 1992. "U.K. Small Firm Bankruptcy Prediction: A Logit Analysis of Financial Trend-, Industry-, and Macro-Effects," Journal of Entrepreneurial Finance, Pepperdine University, Graziadio School of Business and Management, vol. 1(3), pages 233-253, Spring.
    12. Emel, Ahmet Burak & Oral, Muhittin & Reisman, Arnold & Yolalan, Reha, 2003. "A credit scoring approach for the commercial banking sector," Socio-Economic Planning Sciences, Elsevier, vol. 37(2), pages 103-123, June.
    13. Layla Khoja & Maxwell Chipulu & Ranadeva Jayasekera, 2016. "Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling," Review of Quantitative Finance and Accounting, Springer, vol. 46(3), pages 483-518, April.
    14. Pablo de Llano Monelos & Manuel Rodríguez López & Carlos Piñeiro Sánchez, 2013. "Bankruptcy Prediction Models in Galician companies. Application of Parametric Methodologies and Artificial Intelligence," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 117-136.
    15. D'Antoni, Jeremy M. & Mishra, Ashok K. & Chintawar, Sachin, 2009. "Predicting Financial Stress in Young and Beginning Farmers in the United States," 2009 Annual Meeting, January 31-February 3, 2009, Atlanta, Georgia 46861, Southern Agricultural Economics Association.
    16. Ciampi, Francesco, 2015. "Corporate governance characteristics and default prediction modeling for small enterprises. An empirical analysis of Italian firms," Journal of Business Research, Elsevier, vol. 68(5), pages 1012-1025.
    17. repec:rss:jnljfe:v2i2p1 is not listed on IDEAS
    18. Piñeiro Sánchez Carlos & Llano Monelos Pablo De & Rodríguez López Manuel, 2013. "A parsimonious model to forecast financial distress, based on audit evidence," Contaduría y Administración, Accounting and Management, vol. 58(4), pages 151-173, octubre-d.
    19. Teija Laitinen & Maria Kankaanpaa, 1999. "Comparative analysis of failure prediction methods: the Finnish case," European Accounting Review, Taylor & Francis Journals, vol. 8(1), pages 67-92.
    20. repec:pab:rmcpee:v:24:y:2018:i:1:p:54-88 is not listed on IDEAS

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