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Project Preparation for Financing from EU Funds
Pagáčová, Iveta ; Hruška, Vladan (referee) ; Režňáková, Mária (advisor)
The Bachelor’s thesis approaches the possibilities of project co-financing using the financial resources from EU funds. The introductory chapter deals with the concept of EU regional policy, further there are particular European funds presented and connection to the Czech system of programme documents. The Fundamental, practical part of the thesis concerns with the selection of a suitable operational programme and the processing of materials necessary for the completion of the Grant Application Form. Particular steps that the applicant must accomplish before his application is passed are also mentioned as well as the conditions for the recipient of the grant.
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Evaluation of Business Financial Support
Gregor, Štěpán ; Víška, Jiří (referee) ; Režňáková, Mária (advisor)
The goal of this thesis is the analysis of small and medium enterprises financial support with respect to the Joint Regional Operational Programme as an bearer of regional support, which is financed from the European Union and the following list of recommendations within the frame of the realization stage of the project cycle that are generalized especially at the level of the final user as the beneficiary of the support.
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Scoring of the Firm’s Financial Risk
Dodek, Radim ; Kříž, Václav (referee) ; Režňáková, Mária (advisor)
This Bachelor diploma is focused on comparison of chosen scoring indicators and selecting those, which describes the real financial situation of the metallurgical companies. The output of the diploma is to compare particular. Visual Basic application has been developed to counting scoring indicators.
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Patent Value Determinants
Štefánková, Stanislava ; Korytárová, Jana (referee) ; Němec, Daniel (referee) ; Polednáková, Anna (referee) ; Režňáková, Mária (advisor)
The dissertation extends the line of research in the field of patent valuation by interconnecting two main strands, the evaluation of quality of patent rights based on their characteristics on one hand, and monetary valuation of patents as assets on the other hand. Moreover, the dissertation proposes and verifies the idea that the value of a patent is driven also by the ability of its owner to use the competitive advantage gained. The aim is to identify characteristics of Czech corporate patents and their owners that affect their value and to propose a way to implement this knowledge in monetary patent valuation. The effect of several ex ante and ex post indicators on patent's life was analysed employing survival analysis methods. Factors that significantly affect the lifespan of patents of Czech companies were identified using the Cox proportional hazard model. The company’s ability to benefit from competitive advantage was measured by its return on assets and return on equity, which were described by a linear mixed model. Finally, the combined effect of patent characteristics and the firm’s ability to materialize the competitive advantage on patent renewal was analysed employing the joint model for longitudinal and censored data. The results revealed positive effect on the chance of patent renewal of patent backward citation, and the concordance level between patents' technological-class codes and those of their antecedent, i.e., documents it refers to. Conversely, the size of the patent portfolio and the number of inventors have a negative effect on the chance of patent renewal. Small and medium businesses’ patents are less likely to be renewed. The effect of the patent family size, the age of the company and the patent pendency time is time-dependent, it initially lowers the chance of renewal, but its strength gradually weakens. The economic life of patents was predicted based on the results of the joint model using Monte Carlo simulation, furthermore, the implications for monetary patent and business valuation were discussed regarding its investment value.
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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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Financial Planning in a Logistics Company
Sedláčková, Kristýna ; Karas, Michal (referee) ; Režňáková, Mária (advisor)
The diploma thesis deals with the creation of a financial plan for a logistics company that will merge with another company. The first part of the thesis focuses on theoretical knowledge necessary for the creation of a financial plan. The second part presents description about the researched company, including strategic and financial analysis. Based on this information, two financial plans are created. The last part of the thesis compares both variants of the financial plan.
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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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Performance Evaluation of a Trucking Company
Vlasáková, Adriana ; Hamáčková, Zuzana (referee) ; Režňáková, Mária (advisor)
The thesis is focused on the performance evaluation of a trucking company. It is divided into three parts. In the first part the concepts related to the performance of the company and its evaluation are presented. In the second part, the analysed company and its two competitors are presented. Next, a strategic and financial analysis is performed. The results of the financial analysis are compared with competitors in the industry. In the third part, suggestions for improving and maintaining the performance of the company are given.
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Performance Evaluation of a Food Production Company
Holcová, Renáta ; Syrová, Renata (referee) ; Režňáková, Mária (advisor)
The subject of the diploma thesis is the performance evaluation of a family-based food production company. The theoretical part of the thesis defines terms related to the performance evaluation performance and also focuses on the specifics of a family business. In the analytical part, the thesis is focused on the introduction of the company and the analysis of the company's performance by the method of comparison with competing companies. The output of this section is a performance summary using the company's strengths and weaknesses and the identification of opportunities and threats. In the part of proposal, the proposed project for the strategic management of the company is elaborated, which aims to improve the performance evaluation within the internal processes of increasing the performance in the analyzed company.
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