The contribution deals with the analysis of trade companies using artificial neural networks, more specifically Kohonen networks, where the basis for the analysis is primarily the data from evaluating economic performance of a business entity, where each entity strives for increasing its market value. This contribution also estimates the development of trade companies. For the analysis, the data of 11,604 companies in the given sector in the Czech Republic were used. Cluster analysis is carried out using neural networks. From the clusters, those with the highest number of companies were chosen. Subsequently, the analysis of absolute values of selected financial statements items is carried out. From the owners´ point of view, the situation is not positive, as the rate of deposits appreciation is even lower than the risk-free appreciation of 10-year state bonds. In the conclusion, recommendations for trade companies are given.
Authors: Tomáš Krulický, Zuzana Rowland
Keywords: Kohonen networks, neural networks, economic performance of company, trade, cluster analysis