Probabilistic Prediction of Bankruptcy with Financial Ratios - An empirical study on Swedish market

Abstract

Credit risk measurement has become more important during the last 20 years in response to a worldwide increase in the number of bankruptcies. This paper examines some of bankruptcy prediction models using financial accounting ratios. Logit and LPMs are employed in order to develop these prediction models. The purpose of this study is to assess the effects of the determined financial ratios and the selected industries on bankruptcy events that occurred between 2002 and 2006 in the Swedish market. These effects are calculated by measuring elasticity and marginal effect. In addition to prediction models calculating the effects of industries by means of dummy variables, industry normalized financial ratios are also used in order to control industry differences. The empirical results indicate that the company is more likely to go bankrupt if it is unprofitable, small, highly leveraged, and has liquidity problems and less financial flexibility to invest in itself. Furthermore, a company is more likely to enter bankruptcy if it operates in the wholesale and retail trade industry among the selected industries in our sample.