Bankruptcy Prediction Ahead of Global Recession: Discriminant Analysis Applied on Romanian Companies in Timiş County

  • Daniel BRÎNDESCU-OLARIU West University of Timisoara
  • Ionuţ GOLEŢ West University of Timisoara
Keywords: bankruptcy, financial ratios, economic crisis, discriminant analysis, accuracy rate

Abstract

The purpose of this paper is to evaluate the potential of financial ratio analysis performed by employing public data on predicting bankruptcy during the economic crisis period. The population subjected to our study was composed of the 26,980 Romanian companies from Timiş County that submitted financial reports for 2007 to the fiscal authorities. Based on the financial data that was published from these reports by the Romanian Ministry of Public Finance, twelve financial ratios for each of the 26,980 companies have been computed. The twelve ratios were chosen by taking into consideration the recommendations of the literature, as well as the availability of financial data. We were aware of the fact that other sources of information might improve the prediction of bankruptcy, but, as the access of the external stakeholders to such information sources is limited, we decided to search for bankruptcy predictors only within the financial data published online by the Ministry of Finance, which is easily available to everybody. The statistical analysis of the correlation between the values of each financial ratio and the frequency of the bankruptcy event led to the retention of five ratios as possible explanatory variables in a bankruptcy prediction model. The initial analysis also led to the reduction of the target population to 4,327 companies. By means of discriminant analysis, we proposed a model capable of predicting bankruptcy for the target population with an out-of-sample accuracy of 69.3%. Our findings show that the financial statements from one year prior to the beginning of the economic crisis in Romania reflect the weaknesses that make the companies susceptible to bankruptcy. We believe our model to be of practical use, as it is able to accurately discriminate between bankrupt and non-bankrupt firms over a five-year period, by only employing synthetic publicly available financial data.

Author Biographies

Daniel BRÎNDESCU-OLARIU, West University of Timisoara
Faculty of Economics and Business Administration
Ionuţ GOLEŢ, West University of Timisoara
Faculty of Economics and Business Administration

References

Altman, E. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance, 23 (4), 589-609.

Amor, B., Khoury, N., & Savor N. (2009). Modèle Prévisionnel de la Défaillance Financiere des PME Québécoises Emprunteuses. Journal of Small Business and Entrepreneurship, 22 (4), 517–534.

Aziz, M. A., & Dar, H. A. (2006). Predicting corporate bankruptcy: Where we stand? Corporate Governance, 6 (1), 18-33.

Beaver, W. H. (1966). Financial Ratios as Predictors of Failure. Journal of Accounting Research, 4, Empirical Research in Accounting: Selected Studies, (Supplement), 71-111.

Ben-Ameur, H., Bouafi, H., Rostan, P., Theoret, R., & Trabelsi, S. (2008). Assessing the Probability of Default on American Firms: A Logistic Approach. Journal of Theoretical Accounting Research, 3(2), 1-11.

Bradley, D., & Cowdery, C. (2004). Small Business: Causes of Bankruptcy. Technical Report, University of Central Arkansas.

Bradley D., & Rubach, M. (2002). Trade Credit and Small Business: A Cause for Business Failures? Technical Report, University of Central Arkansas. Retrieved from http://www.sbaer.uca.edu/research/asbe/2002/papers/02asbe055.pdf

He, Y., & Kamath, R. (2006). Business failure prediction in the retail industry: an empirical evaluation of generic bankruptcy prediction models. Academy of Accounting and Financial Studies Journal, 10(2), 97-110.

Horrigan, J. (1968). A Short History of Financial Ratio Analysis. The Accounting Review, 43(2), 284-294.

Kahya, E. & Panayiotis, T. (1999). Predicting Corporate Financial Distress: A Time-Series CUSUM Methodology. Review of Quantitative Finance and Accounting, 13, 323-345.

International Monetary Fund (2013). Financial Soundness Indicators. Retrieved from http://elibrary-data.imf.org/DataReport.aspx?c=4160268&d=33120&e=170185

Legault, J., & Veronneau, P. (1986). CA-Score, Un Modele De Prevision De Faillite. Research Report for the Ordre des Comptables Agrees Du Quebec.

Liesz, T. (2002). Really Modified du Pont Analysis: Five Ways to Improve Return on Equity. Proceedings of the Small Business Institute Directors Association Meeting.

National Bank of Romania (2012). Financial Stability Report.

Ohlson, J. (1980). Financial ratios and probabilistic prediction of bankruptcy. Journal of Accounting Research, 18 (1), 109-131.

Rashid, A & Abbas, Q. (2011). Predicting Bankruptcy in Pakistan. Theoretical and Applied Economics, XIII, 9(562), 103–128.

Schumway, T. (2001). Forecasting Bankruptcy More Accurately: A Simple Hazard Model. Journal of Business, 74 (1), 101-124.

Stroe, R., & Bărbuță-Mișu N. (2010). Predicting the Financial Performance of the Building Sector Enterprised – CaseStudy of Galati County (Romania). The Review of Finance and Banking, 2 (1), 29-39.

Ugurlu, M., & Aksoy, H. (2006). Prediction of Corporate Financial Distress in an Emerging Market: The Case of Turkey. Cross Cultural Management: An International Journal, 13 (4), 277-295.

Oficiul Național al Registrului Comerțului (2013). Situaţia statistică a radierilor efectuate în perioada 01.01.2012 - 31.12.2012. Retrieved from http://www.onrc.ro/documente/presa/comunicat_30_01_2013/3-radieri-1.pdf

Published
2013-08-16
How to Cite
BRÎNDESCU-OLARIU, D., & GOLEŢ, I. (2013). Bankruptcy Prediction Ahead of Global Recession: Discriminant Analysis Applied on Romanian Companies in Timiş County. Timisoara Journal of Economics and Business, 6(19), 70-94. Retrieved from http://tjeb.ro/index.php/tjeb/article/view/TJEB19_Aug2013_70to94
Section
Articles