Building a predictive model for bankruptcy

Thesis deals with complex process of creation of new bankruptcy model for predicting business failure, while this process involves selection of quality sample, verification of classification accuracy of already existing bankruptcy models, profile analysis and finally the derivation of specific equation of bankruptcy model. The derivation is performed by using two selected statistical methods, discriminant analysis and logistic regression. Two bankruptcy models Bürger's index DA12 and Bürger's index LR12 were derived by using the mentioned statistical methods. The new models distinct advantage is, unlike already existing and renowned bankruptcy models, that they are focused on classification of micro and small enterprises in terms of Czech Republic, while classification accuracy one year before failure is by individual models 74.8 % and 81.87 %. Derived models have clear interpretation (no grey zone) and easy calculation, which brings a possibility for micro and small entrepreneurs to check their business partners in terms of failure prediction