PREDICTION OF CORPORATE BANKRUPTCY: EVIDENCE FROM WEST AFRICAN’S SMEs

Year 2015, Volume: 2 Issue: 3, 0 - 0, 29.09.2015

Kokou Adalessossi

Abstract

Bankruptcy is a legal proceeding in which a corporation has become insolvent and therefore cannot pay its obligations .The purpose of this paper is to assess the default risk or to predict bankruptcy of some public firms listed on the stock Exchange Securities (BRVM) of West African Economic and Monetary Union (WAEMU) and on the Ghana Stock Exchange (GSE). 34 companies from different sectors and sizes have taken place in this study. The main purpose is to measure the performance of these companies that constitute the backbone of the regional economy whether banks or investors can have confidence on them to finance their activities. To perform this study, the 2013 dataset   financial statements were taken from the website of the two stock exchanges. Then, Discriminant function named Z-scores model of Altman, financial ratio analysis, and the Principal Component Analysis were used. The results of this study show that out of the 34 public companies, only 8 companies have had good financial performance, and on which financial institutions or investors can have confidence for financing or investment. Among all the companies, the most best performing company was listed in Ghana Stock Exchange. The most problem encountered by 85% of the 34 companies was the liquidity problem. This study will permit investors and banks to put regards on these companies on one side, and to awaken those companies which have realized bad financial performances on the other side.

References

• Adalessossi Kokou and Utku. D. Burcu,(2015) Financing difficulty of Small and Medium Entreprises in West
• African Economic and Monetary Union Area, (edit; David publishing ) China-USA Business Review, February 2015, Vol. 14, No. 2, 79-99 doi: 10.17265/1537-1514/2015.02.003
• Altman E.I. (1968). Financial ratios discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance 23. 589-609.
• Altman. Edward I.. “Corporate Credit Scoring Insolvency Risk Models in a Benign Credit and Basel II environment”. NYU working paper. 2004.
• Altman. Edward I.. R.G. Haldeman. and P. Narayanan. “Zeta-analysis. A New Model. Aziz, A., D. Emanuel and G. Lawson. 1988. Bankruptcy prediction - An investigation of cash flow based models.
• Journal of Management Studies 25(5): 419-437. Barefoot. A.S. (1996). Credit scoring at crossroads. ABA Banking Journal. June. p.26.
• Beaver. W. H. (1967). Financial Ratios as Predictors of Failure. Empirical Research in Accounting: Selected
• Studies. University of Chicago. 1967. 71 –111.
• Berger. A.N.. Klapper. L.F.. Udell. G.F. (2001). The ability of banks to lend to informationally opaque small businesses. Journal of Banking & Finance. 25. 2127-2167.
• Berger. A.. Udell. G. (1996). Universal banking and the future of small business lending. In Frame. W.. et al..
• (2001). Effect of Credit Scoring on Small Business Lending. Journal of Money. Credit and Banking.. 33. 813-825.
• Berger. A.N.. Udell. G.F. (2006). A more complete conceptual framework for SME finance. Journal of Banking & Finance. 30. 2945-2966.
• Becchetti, L. and Sierra J., “Bankruptcy risk a nd productive efficiency in manufacturing firms”, Journal of Banking and Finance, Vol. 27, 2002.
• Bilderbeek, J., “An empirical study of the predictive ability of financial ratios in the Netherlands”, Zeitschrift Für Betriebswirtschaft May 1979.
• Blum, M. 1974. Failing company discriminant analysis. Journal of Accounting Research 12(1): 1-25.
• Callahan; K. R; Stetz, G. S; Brooks, L. M (2007). Project Management Accounting: Budgeting, Tracking, and Reporting Costs and Profitability. Published by John Willey and Sons, Inc, Hoboken, New Jersey.
• Courtis. J.K. (1978). Modeling a financial ratios categorical framework. Journal of Business Finance and Accounting. 5. 371-386.
• Deakin, E. 1972. A discriminant analysis of predictors of business failure. Journal of
• Accounting Research 10(1): 167-179. Dietsch, Michel and Joel Petey, “Should SME Exposures be treated as Retail or as Corporate Exposures? A Comparative Analysis of Default Probabilities and Asset Correlation in French and German SMEs”, Journal of Banking and Finance 28, 2004.
• 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,
• Edmister. R.O. (1972). An empirical test of financial ratio analysis for small business failure prediction. The Journal of Financial and Quantitative Analysis. 7. 1477-1493.
• Eisenbeis, R. A., (1977), “Pitfalls in the Application of Discriminant Analysis in Business, Finance, and Economics,”
• The Journal of Finance 32, pp. 875-898. Emmel. A.B.. Muhittin. O.. Reisman. A.. Yolalna. R. (2003). A credit scoring approach for the commercial banking sector. Socio-Economic Planning Sciences. 37. 103-123.
• Frame. S.. Srinivasan. A.. Woosley. L. (2001). Effect of Credit Scoring on Small Business Lending. Journal of
• Money. Credit and Banking. 33. 813-825. Friedland. M. (1996). Credit scoring digs deeper into data. Credit World. 84. 19-23.
• Frydmand. A.. Altman. E.. Kao. D. (1985). Introducing recursive partitioning for financial classification: the case of financial distress. The Journal of Finance. 1. 269-291
• Gentry, J.A., Newbold P. and Whitford D.T., “C lassifying bankrupt firms with funds flow components”, Journal of Accounting Research, Vol. 23, nr. 1, 1985
• Glennon D.. Nigro P. (2005). An analysis of SBA loan defaults by maturity structure. Journal of Financial Services Research. 28. 77-111.
• Gombola, M., Haskins M., Ketz J. and Williams D., “Cash flow in bankruptcy prediction”, Financial Management, 1987
• Jacobson, Tor, Jesper Lindé, and Kasper Roszbach . “Credit Risk versus Capital Requirements under Basel II: Are SME loans and Retail Really Different?” Journal of Financial Services Research, forthcoming, (2004)
• Katz. S.. Lilien. S.. Nelson. B. (1985). Stock market behavior around bankruptcy model distress and recovery predictions. Financial Analysts Journal. 41. 70-74.
• Keasey, K. and R. Watson. 1986. The prediction of small company failure: Some behavioral evidence for the UK.
• Accounting and Business Research 17: 49-57
• Laitinen. E.K. (1992). Prediction of failure of a newly founded firm. Journal of Business Venturing. 7. 323-340.
• Lizal, L. (2002). Determinants of financial distress: What drives bankruptcy in a transition economy?
• The Czech Republic case: William Davidson Lo, A. 1985. Essays in financial and quantitative economics. Ph.D. dissertation, Harvard University.
• Lussier. R.N. (1995). A nonfinancial business success versus failure prediction model for young firms. Journal of
• Small Business Management. 33. 8-20. Micha, B., “Analysis of business failures in France”, Journal of Banking and Finance, Vol. 8, 1984.
• Mossman, Ch.E., Bell G.G., Swartz L.M., and Turtle H., “An empirical comparison of bankruptcy models”, The Financial Review, Vol. 33, nr. 2, 1998.
• OECD Small and Medium Enterprise Outlook 2002, published by OECD Publication Services, France
• Ohlson, James A. financial Ratios and the Probabilistic Prediction of Bankruptcy. Journal of Accounting Research, Vol.18, no. 1(spring, 1980), PP. 109-131.
• Ooghe, H., Joos P. and De Bourdeaudhuij C., “Financial distress models in Belgium: The results of a decade of empirical research”, International Journal of Accounting, Vol. 30, 1995
• P Hutchinson. I Meric. G Meric (1998):The financial characteristics of small firms which achieve quotation on the UK unlisted securities market .Journal of Business Finance & Accounting 15 (1).9-19
• Platt, H. D. and M. B. Platt (1990), “Development of a Class of Stable Predictive Variables: The Case of Bankruptcy
• Prediction,” Journal of Business, Finance and Accounting 17, pp. 31-51. Santomero. A. (1997). Commercial bank risk management: an analysis of the process. Journal of Financial Services Research. 12. 83-115.
• Saurina, Jesùs and Carlos Trucharte, “The Impact of Basel II on Lending to Small-and-Medium- Sized Firms: A Regulatory Policy Assessment Based on Spanish Credit Register Data”, Journal of Finance Services Research 26, 2004
• Shahzad Ijaz, UIMS-PMAS-Arid ,(2013) Assessing the Financial Failure Using Z-Score and Current Ratio:A Case of
• Sugar Sector Listed Companies of Karachi Stock Exchange. World Applied Sciences Journal 23 (6): 863-870
• Schwaiger, Walter S.A. “Basel II: Quantitative Impact Study on Austrian Small and Medium-sized Enterprises.” Technical University of Vienna (2002).
• Srinivasan. V. and Ruparel. B. (1990). CGX: An expert support system for credit granting”. European Journal of
• Operational Research 45. 293 –308. Tam K.Y. (1991). Neural network models and the prediction of bank bankruptcy. Omega. 17. 429-445
• Taffler, R J and Tishaw, H, 1977. Going,Going, Gone: Four Factors Which Predict. Accountancy, 88.
• Troutt, M.D., Rai, A., Zhang, A. (1996). The potential use of DEA for credit applicant acceptance systems.
• Computers and Operations Research, 405-408. Tsaih R.. Liu Y.. Liu W.. Lien Y. (2004):Credit scoring system for small business loans. Decision Support Systems. 38. 91-99.
• Weston. J.F.. Brigham. E.F. (1993):Essentials of managerial finance. Orlando: Dryden Press. Zavgren, C. 1985.
• Assessing the vulnerability of failure of American industrial firms: A logistic analysis. Journal of Business Finance & Accounting 12(1): 19-45. Zopounidis. C. A. (1987): A multicriteria decision-making methodology for the evaluation of the risk failure and an application. Foundations of Control Engineering .12. 45-67.