مدل های پیش بینی ورشکستگی: آیا قدرت پیش بینی مدل می تواند با استفاده از شاخص پویا بهبود یابد؟

The research was carried out using data of the Czech manufacturing industries obtained from the AMADEUS database for years 2004 to 2011, with each company providing data for up to five years prior to the bankruptcy. Along with investigating the different approach to the selection of indicators for the development of a bankruptcy model, we were also concerned with the selection of a method to develop it. Researching the literature, we found that the most commonly used method is one of linear discrimination analysis, whose precision is improved if applied to normally distributed data without outliers. With financial data, however, these assumptions are difficult to meet. Therefore, a non-parametric boosted-trees method was used to select the predictors and develop the bankruptcy models.