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PREDICTION OF BANKRUPTCY IN ENTERPRISES OF THE AUTOMOTIVE INDUSTRY
Abstract
The purpose of our research is to analyze the choice of indicators and methods, respectively groups of indicators to predict bankruptcy assumptions in the automotive industry in time period 2002-2011. Predictive models applied in many studies have been unsuccessful. Enterprises of the automotive industry in the application of prediction models can't keep the recommended values of the forecasting methods, incurred in a very different economic environment and a different time. Predictive models are outdated and obsolete. It should be noted that in certain sectors predictive models can function and predict bankruptcy. Selecting of appropriate financial ratio indicators, respectively groups of indicators and using the statistical software SPSS we obtain a correlation matrix and subsequently carry out factor analysis, cluster analysis and discriminant analysis. Factor analysis is an important method in the evaluation of the sector, which allows to reduce the number of factors to a minimum, so as to be sufficiently described the industry. The next step is on the basis of factor analysis perform cluster analysis and classify enterprises into different clusters according to their similarities. Cluster analysis classifies enterprises located in different financial situation into subsets with similar characteristics to form enterprise groups with similar financial situation. Through discriminant analysis, we construct the empirical model at the 27 financial ratio indicators in the automotive industry in time period 2002–2011. Database of businesses we divided into two groups on the basis of the achieved rating level by rating agency Moody's. The impact of the global financial crisis in the automotive industry was observed in period 2007-2010. During this period, we will focus not only on the evaluation of empirical model and the facts which have occurred in individual enterprises, but also on cluster analysis.
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