No abstract

Sustainable growth rate is a maximum growth rate that one enterprise may achieve with a given set of financial policies. The growth of an enterprise per rate higher than sustainable growth rate may lead to financial troubles, insolvency, even to the enterprise bankruptcy. In order to be able to finance a rapid growth, the enterprise will have to issue new shares, increase indebtedness, change its dividend policy, increase production efficiency or improve the asset turnover ratio. The enterprise growth per rate lower than sustainable may lead to a stagnation of the enterprise. The main goal of this paper is to show a sustainable growth rate calculation methodology and to apply this methodology in the determination of a sustainable growth rate in 2011 and 2012 for 60 enterprises in Serbia belonging to the agricultural and food sectors. Likewise, this paper is concerned with the comparison of the enterprise sustainable growth rate per stated sectors, the determination of existence of possible differences in their height in 2012 in relation to 2011 and with an overview of inflation effect on sustainable growth rate per selected sectors. All this is done in order to assess sustainable growth of agricultural and food sectors in the years under consideration. Research results indicate that possibilities for the sustainable growth were scarce or there was no real sustainable growth in agricultural and food sectors in 2011 and 2012.

Decision trees made by visualizing the decision-making process solve a problem that requires more successive decisions to be made. They are also used for classification and to solve problems usually addressed by regression analysis. One of the problems of classification that arises is the proper classification of bankrupt companies and non-bankruptcy companies, which  is then used to predict the likelihood of bankruptcy. The paper uses a random forests decision tree to predict bankruptcy of companies in the Republic of Serbia. The research results show the high predictive power of the model with as much as 98% average prediction accuracy, and it is recommended for auditors, investors, financial institutions and other stakeholders to predict bankruptcy of companies in Republic of Serbia.

Abstract:There are numerous models which are under contemporary usiness conditions used for assessment of creditworthiness and orecasting bankruptcy possibility of a enterprise. One of these models is Altman Z -score model. On the basis of adjustments of original model for ossibility of bankruptcy forecasting, which is applicable just to nterprises with whose stocks are traded on organized market, a modified model was developed which is applicable only to enterprises with whose tocks are not traded on organized market. Altman made additional modification of model and formulated Z'' score model that is applied on roduction and unproductive enterprises, as well as on enterprises that perate in developing countries. Stated models separate financially uccessful enterprises from those that are threatened by bankruptcy roceedings. On the basis of Z'' score model Altman classified credit rating f enterprises and with it developed Z'' score adjusted model. In this aper, we conducted the analyses of credit rating for 33 enterprises in estructuring and 90 enterprises that are not in restructuring, by using Z'' core adjusted model, as well as determined possibility of occurrence of ankruptcy of enterprise on the basis of Z' score model. Authors concluded hat approximately 57% of analyzed enterprises in restructuring have the owest credit rating, while possibility of occurrence of bankruptcy in the next two years for those enterprises is more than 90%. On the other hand, pproximately 60% of enterprises which are not in restructuring have high credit rating and operate in safe zone, while approximately 6% of nterprises have the lowest credit rating with high possibility of ccurrence of bankruptcy in the next two years.

Turbulent conditions on the Serbian market, the deep consequences of the global economic crisis that have shaken the already weakened economy are strong reasons for constant monitoring of business in Serbia. Identifying financial problems in a company that lead to bankruptcy reduces the risk of potential losses. The aim of the paper is to compare the Altman model and the Zmijewski model that are applied in companies in Serbia and by that to conclude which one gives better results for predicting bankruptcy. Also, the paper will examine the significance of individual ratios in models using correlation analysis.The results of the survey showed that the accuracy of predicting the bankruptcy of the Altman model for emerging markets on Serbian companies undergoing bankruptcy proceedings, is high, 88.68% for one and 79.25% for two years before the initiation of bankruptcy proceedings. The accuracy of the Zmijewski model is slightly higher than the Altman model for one year before the initiation of bankruptcy proceedings and amounts to 90.57%. Two years before bankruptcy, the Zmijewski model's accuracy is the same as with the Altman model (79.25%). When it comes to the overall sample (undergoing bankruptcy proceedings companies and non-bankruptcy companies), the average accuracy of the Zmijewski model is higher than the Altman model (89.62% > 85.22%). Based on Pearson's correlation coefficient, we have established that one year before initiating bankruptcy, there is almost an impeccably perfect positive relationship between the ratio of working capital and total assets on one side, and Z’’- score on the other. The Zmijewski coefficient has an almost perfect negative relationship with the indebtedness ratio. By observing both models, it can be concluded that companies in Serbia had a problem with liquidity, indebtedness and the impossibility of returning the invested funds, which contributed to the poor financial situation and initiation of bankruptcy proceedings.