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The use of qualitative modeling in solving problems associated with external credit rating
Krejčíř, Jaroslav ; Kulhánek, Lumír (referee) ; Dohnal, Mirko (referee) ; Myšková, Renáta (referee) ; Rejnuš, Oldřich (advisor)
The doctoral dissertation studies applications of the methods of qualitative modelling to solve problems associated with external credit ratings. Qualitative modelling is a tool which can solve tasks under shortage of relevant information items. Correlation analysis is used if relevant data sets are available and complement the qualitative analysis. External credit rating assessments are closely related to possibilities of insolvency of business entities and the subsequent bankruptcies. Mutual interlinks of bankruptcy probabilities and qualitative models are presented in details. Two specific models are given. Due to the adopted legislative measures were also tested match of the ratings from a variety of external credit rating agencies using cluster and correlation analysis. The above mentioned results are used to develop a qualitative model of external credit ratings, which is the main outcome of this dissertation. The results of model scenarios of assessment of the influence of regulation external credit rating on the business entity, investors, as well as regulatory authorities are presented in details.
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Bankruptcy prediction modelling in manufacturing branch
Kulkusová, Martina ; Kuběnka,, Michal (referee) ; Karas, Michal (advisor)
The diploma thesis is aimed at the problematic within the prediction of bankruptcy of companies operating in manufacturing industry in Czech Republic. There are defined terms related to the topic, methods of creating bankruptcy models and selected bankruptcy models in the theoretical part. Analytical part includes testing of the selected bankruptcy models. Thereafter a new bankruptcy model is created, which is subsequently tested and its accuraccy is compared to models from other authors.
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The use of convolutional neural networks for predicting the financial failure of a company
Šebestová, Monika ; Chramcov, Bronislav (referee) ; Lenort, Radim (referee) ; Režňáková, Mária (referee) ; Dostál, Petr (advisor)
The doctoral thesis deals with the use of convolutional neural networks for predicting the financial failure of companies. A bibliometric analysis was used during the processing of the literature review, which enabled a better orientation in scientific works oriented to the methods and approaches used in the past to predict the financial failure of companies. On the basis of the obtained knowledge, a deep learning model based on the GoogLeNet architecture was proposed, with inputs consisting of financial and macroeconomic indicators of companies. The modeling was based on the transfer learning method, in which it is possible to fine-tune the parameters of the pre-established networks to accelerate the learning process of the convolutional neural network. The initial set of financial and macroeconomic indicators was compiled from the variables that were most often used in business failure prediction models in scientific papers. Appropriate statistical methods were used for the specific selection of indicators from which the model is built. Since convolutional neural networks work best with image processing, the quantitative values of the input indicators were graphically interpreted and it was investigated which type of graphical processing is most suitable for predicting the failure of companies. Due to the existence of an unbalanced data set, the effect of the SMOTE method on the accuracy of the model's prediction was analyzed in the thesis. The method was used to increase the number of samples of the minority class of firms. To model the prediction of financial default, several variants of models were proposed, which differed in the form of input data. It was tested how the removal of outliers from the data set, the point in time from which the data come or the method of predictor selection will affect the accuracy of the prediction. The parameters of the resulting model were further fine-tuned so that it was able to classify businesses from new real data. The research conducted showed that using the right type of graphical processing of input data, SMOTE technique and appropriate parameter settings, convolutional neural networks can predict the financial failure of companies with high accuracy.
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Bankruptcy Prediction Modelling Small and Medium Enterprises
Shmatova, Valeriia ; Režňáková, Mária (referee) ; Karas, Michal (advisor)
This thesis explores the issue of corporate bankruptcy in the Czech Republic, including its causes and related legal regulation. The theoretical part of the thesis focuses on bankruptcy models and their creation, including the statistical methods used in these models. In the analytical part, the accuracy of selected bankruptcy models from different authors was tested, a new bankruptcy model was created using logistic regression on samples of small and medium-sized Czech and Slovak companies in the manufacturing industry, and the performance of this new model was subsequently compared to others.
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Personal bankruptcy of a consumer
ŠEDIVÝ, Filip
The bachelor thesis deals with debt relief for non-business individuals. The indebtedness of Czech households is high and growing. If a debtor does not have the means to repay his or her outstanding liabilities, he or she can easily fall into a debt trap. For many of them, the only way out is debt relief, which is one of the options for resolving bankruptcy. For debtors, insolvency represents the chance of a new life without debt if they successfully go through the insolvency process. The bachelor thesis describes the issue of household debt, compares the development of the legal regulation of the insolvency law, explains the basic concepts of insolvency proceedings and describes the process of the insolvency process itself. The practical part focuses on the development of the number (and success rate) of personal bankruptcies, evaluation of the data obtained and testing of hypotheses. The aim of the work is to compare the development of the legal regulation of debt settlement, describe its course and evaluate the use of this insolvency instrument by consumers on the basis of data obtained directly from the insolvency register.
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Vlpyv deliaceho bodu na klasifikáciu bankrotných firiem pomocou logitového modelu
Dolnáková, Paulína
Dolnáková, P. Impact of the threshold on the classification of bankruptcy companies using the logit model. Master thesis. Brno: Mendel University, 2021. The thesis is dedicated to creating and optimization of a predictive bankruptcy logit model. The model is based on 3 840 companies from Central Europe, among which 47 went bankrupt in 2017. To compare the quality of classification, the individual models are created both on the whole data set, but also using the division of data into training and validation subsets. We used the proportion 60/40 in which 60% of companies form a training subset and the remaining 40% of companies form a validation subset. Also, a 70/30 proportion was used. In the case of dividing the whole data set into training and validation subsets, a one thousand simulations were created. Using these strategies, separate models are created for individual monitored years, based on data from one to three years before the moment of possible bankruptcy. The quality of the classification of created models is assessed by total accuracy, sensitivity, and the AUC criterion. The influence of the threshold value on the quality of the classification is clearly presented on the individual models.
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The current effectivness of bankruptcy prediction models in the conditions of Central and Eastern Europe
Honzíček, Štěpán ; Kuběnka,, Michal (referee) ; Karas, Michal (advisor)
Bachelor’s thesis describes issues of bankruptcy risk. It fleshes out key concepts related to bankrupt, introduces financial analysis like a instrument of evaluation enterprise financial situation and specifically deals with prediction bankruptcy models. Metodology of model construction is introduced and ROC curves as an efficiency testing method. Case study makes evaluation of accuracy for five chosen models in sector small and medium enterprises manufacturing industry of central and eastern Europe. Concluding part narrates possibility modification of models for accuracy increase.
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Breaking-up activity of firm and the transaction cost
Kosturák, Matej ; Koubek, Ivo (advisor) ; Kocourek, David (referee)
In my work I focus on the essential components of the bankruptcy and insolvency problem. The basis for understanding of mentioned problem was study of capital structure and it's connection with world of insolvency. Secondly I focus on different aspects of qualitative analysis of bankruptcy, starting with definition of different terms, many times unprofessionally misused, followed by description of four main processes of bankruptcy. These processes connect fundamental causes of bankruptcy with financial and nonfinancial consequences. For an economic paper, it is quiet extensively concerned with insolvency law, concretely with new Czech norm, which is in force since 2008. From legal definition of default, through initiation of insolvency proceeding to the individual options of solution, the reader can clearly understand the core of this paper. As particular contribution I regard part of the paper, where I examine 160 cases of Czech companies and persons under liquidation process. Among the most significant conclusion I consider finding of quite significant differences in the court proceedings of Czech courts, the length of the insolvency proceedings and each of its phases and the ratio of satisfied claims of secured as well as unsecured creditors.
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An Economic Analysis of the Cross-Border Insolvency Proceedings within the context of the Changes of the Council Regulation (EC) No 1346/2000
Juhás, Juraj ; Richter, Tomáš (advisor) ; Břízová, Pavla (referee)
The content of this bachelor thesis is an economic analysis of the cross-border insolvency proceeding held according to the Council regulation (EC) No 1346/2000 on insolvency proceeding and proposals of its amendment. It is focused mainly on changes regarding the possibility to request an opening secondary proceeding and changes regarding the insolvency of groups of companies. A basic framework for evaluation of a profitability of a secondary proceeding opening for a concrete creditor was introduced at the end of the chapter II. It involves three main factors: ratio of relative shares on the realization of debtor assets in the case a secondary proceeding was opened and in the case I was not opened; additional incomes caused by the fact that the debtor assets were administered as a whole (the assets were not liquidated by parts in several parallel insolvency proceedings) and transaction costs. The proposed changes of the cross-border insolvency law in the European Union concerning a limitation of the right to request the opening of a secondary proceeding and obligatory cooperation between proceedings regarding a member of the same group of companies are then evaluated with respect to this basic framework.
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Bankruptcy Prediction Modelling in the Manufacturing Industry
Tichá, Barbora ; Bartoš, Vojtěch (referee) ; Karas, Michal (advisor)
This diploma thesis deals with the issue of bankruptcy prediction of small and medium-sized enterprises operating in the manufacturing industry in selected Central European countries. The theoretical part of the thesis defines the concepts related to the prediction of bankruptcy and methods of model creation. The analytical part of the work includes testing the accuracy of selected bankruptcy model by other authors and creating a new bankruptcy model. The accuracy of the newly created model is then compared with the accuracy of selected models by other authors.
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