An empirical analysis to predict the probability of default

Credit risk measurement has become attractively important during the last 25 years in response to the rapid developments of commercial and financial markets and the increase in the number of financial products. This study examines the importance of the prediction of credit worthiness of SMEs (Small and Medium Sized Enterprises) with the aid of the implementations of Basel II. This paper aims to observe the statistical models of probability of bankruptcy prediction and employ such a prediction model for SMEs by using logit statistical method. The purpose of the model is to determine the financial ratios explaining the probability of bankruptcy; then to interpret the effects of ratios by estimated marginal effects and elasticities. The data used in the analysis includes the bankruptcy events occurred in years: 2002-2006. Empirical results point out that SMEs of Swedish manufacturing industry which are likely to go bankrupt have negative equity; lower power of interest coverage; lower liquid assets, intangible assets, and overall assets; while having higher debt, especially current liabilities in their financial structure. The test statistics show that the estimated logit model in order to predict probability of bankruptcy is statistically significant and successful.Key Words1.Credit Risk2.Default (bankruptcy) Probability3.SMEs4.Financial Ratios and Accounting Data5.Logit Model.