G33 - Bankruptcy; LiquidationReturn

One of the elements of company´s evaluation is an analysis of bankruptcy risk metrics. In this study, the accuracy of bankruptcy predictions generated by EBITDA-based and cash flow-based liabilities-coverage ratios is evaluated within a sample of data from the Polish market. The study is based on a sample of 92 companies, in which case a bankruptcy filing was announced in a period between the beginning of 2009 and the end of the first half of 2016. The statistical analysis has confirmed the usefulness of the investigated liabilities-coverage ratios. Even though the sample covers wide variety of businesses, the logit models with only one ratio used as an explanatory variable are capable of identifying bankrupt firms (with one-period-ahead forecast horizon) in about 66-76% of cases. However, this research has not confirmed the supremacy of operating cash flows over EBITDA in predicting financial distress.

This paper analyses debtors who applied for debt relief in the period between 1/1/2012 and 31/12/2013. As there has already been a research related to Moravian and Silesian regions in this matter, it focuses mainly on the debtors from Bohemian regions. It is therefore an analysis of a problem which has not been thoroughly covered nor published yet. New way of declaring bankruptcy, in other words debt relief, for debtors who are unable to repay their debt has been in action since 2008. Since then the number of personal bankruptcies has been gradually rising every year. This paper constitutes only a narrow section of broader research; therefore, only certain characteristics are covered. Those are age and gender of the debtors and the structure of the creditors in all of the regions. The results and information gathered during the research are being analysed and also compared among particular regions.

The paper deals with payment discipline in the building industry in the Czech Republic. The aim of this paper is to identify, compare and evaluate the financial situation of building companies with different payment practices in the Czech Republic in the period 2010 - 2014. The paper uses enterprise and statistical methods. The payment discipline of companies is expressed by a payment index, which is constructed by Bisnode. The results are based on analysis of 1374 companies which are operated in the building industry. The analysis shows that payment habits increase with higher index IN05, Taffler's model, index IN99 and with larger size of the firms. Payment habits of building companies are very good. However, about 2 % of solvent companies have poor payments habits.

One of the elements of company's evaluation is ratio analysis. It includes computation of bankruptcy risk metrics. There are multiple such measures, of which two seem to be quite universal and commonly applied. These are current ratio and indebtedness ratio. In this study, the accuracy of bankruptcy predictions based on these two ratios is evaluated within a sample of data from the Polish market. Also, the safety thresholds (meant as values at which the probability of bankruptcy exceeds fifty percent) are estimated. The study is based on a sample of 84 companies, in which case a bankruptcy filing was announced in a period between the beginning of 2009 and the end of the first half of 2015. This sample of bankrupt firms is compared to the counter-sample of companies in which case no any bankruptcy filing occurred. The statistical analysis has confirmed the usefulness of both ratios. Even though the sample covers wide variety of businesses, the logit models with only one ratio used as an explanatory variable are capable of identifying bankrupt firms in about 70-73% of cases. Our research has also shown that the estimated safety thresholds lie near the typically assumed "rules of thumb".

Market situation and business environment of construction companies influence significantly decisions met by this group of entities. These decisions are reflected in financial statements, later on. The evaluation of financial condition, which aims at diagnosing corporate crisis, must not disregard a market situation. Taking this assumption into account a classification of publicly quoted construction companies using k-means method was conducted. This procedure enabled to divide the examined sample into five clusters of companies characterized by 'the best', 'good', 'acceptable', 'weak' and 'the poorest' financial condition. The application of the aforementioned algorithm helped also to determine levels of financial ratios typical for each cluster. This kind of analytical approach is particularly useful for investors, since it informs how particular companies perform in comparison to their competitors.