This diploma thesis main goal is to predict primary bankruptcy indicators in construction sector based on model. This model is built by advanced classifier methods such as classification trees and logistic regression. Applicability of prediction depends on quality of built model and therefore verification of classification accuracy is essential for bankruptcy prediction. The theoretical part is focused on construction sector in the EU specializing on basic financial analysis including ratio indicators and frequently used models for predicting the bankruptcy of enterprises. The practical part consists of model creation and evaluation for each observed time period. The end of thesis is dealing with model evaluation based on given criteria.

This diploma thesis discusses the analysis of factors influencing foreign direct investment in Visegrad countries. The first part of the thesis defines the basic concepts, their brief characteristics and their distribution in the area of foreign direct investment. Another part of the thesis deals with the qualitative analysis of the investment environment in the Visegrad Group countries followed by a qualitative analysis of selected factors influencing foreign direct investment in Visegrad countries. The last part of this diploma thesis is a quantification of selected factors by multidimensional regression analysis and a regression analysis of panel data. The results obtained show that the main factors influencing foreign direct investment in the Czech Republic are the labor costs, the level of taxation and quality of the institutional environment. In Slovakia and Poland, the main factors are economic growth, the level of taxation and the quality of the institutional environment. In Hungary, the main determinants are economic growth, labor cost, the level of taxation and the quality of institutions. Within all Visegrad countries, the main factors are economic growth, labor cost, the level of taxation and the quality of the institutional environment.

The diploma thesis deals with the identification of influence of the monetary policy on stock markets in the developed countries where central banks accepted usage of the unconventional tools of monetary policy. The effect of monetary policy is observed on stock prices of 200 blue chip stocks of companies emitted in USA, UK, EU and JAP. The influence of the unconventional monetary policy will be examined in empirical part of the diploma thesis via panel regression analysis with focus on verification of portfolio rebalance channel of the transmission mechanism.

Vaněk, P. Determinants of euroization in selected European economies. Diploma thesis. Brno: Mendel University, 2017. The diploma thesis analyzes the determinants of deposit and loan euroization spec-ified by literature. In general terms, unofficial euroization reduces the impacts of monetary policy. The thesis identifies statistically significant determinants by using regression analysis of panel data for four selected euroized countries in Eastern Eu-rope: Bulgaria, Romania, Croatia and Serbia. Based on the results of the analysis, the thesis proposes recommendations to the makers of economic policy in relation to euroization in the selected economies.

The aim of this diploma thesis is to identify the impact of tariff barriers in individual sectors of bilateral trade between Czech Republic and China. For this purpose, bilateral trade between countries is analysed using panel data analysis. The model results confirm the claim of the receding force of duty in favour of increasing the importance the impact of non-tariff barriers on trade.

The diploma thesis examines what is the role of financial development in the context of economic growth. The most influencing factors of the financial development are selected based on panel data regression. Determinants of the financial development represent both the banking sector and the financial markets. Panel of 42 European countries over the 1996-2015 period is analysed. The effect is controlled on the other three groups of countries. The results indicate an~ambiguous impact of the financial development on economic growth. Based on the analysis results recommendations are formulated for policy makers and investors.

The thesis deals with data acquisition from crowdfunding and their analysis. The theoretical part is focused on the description of available technologies and algorithms for data analysis. In the practical part the data collection is realized. Data mining and text mining algorithms are applied in this section for data.

This thesis deals with the design of the corporate network infrastructure to improve its security against potential threats and attacks from both internal and external part of the network and to prevent leak of the sensitive information, so that, to accomplished the requirements of the current GDPR legislation. The proposal includes simplifying identity and access management of the users to the corporate resources and unified, well-arranged management from the side of the network administrators using modern and advanced tools to alert in the real time on unexpected events and anomalies on the network. Solution is implemented in the Microsoft Azure service environment and its funcionality has been verified based on the relevant penetration tests.

The diploma thesis is focused on identifying factors affecting the volume of mortgage loans provided in the Visegrad Group countries. Multiple regression analysis is used to determine main factors affecting volume of mortgage loans in each country and estimation of models. Panel data analysis is used to estimate common factors affecting volume of mortgage loans within all member countries.

Matzke, M. Comparison of Computational Complexity of Selected Data Mining Algorithms, Diploma Thesis. Brno, 2018. This diploma thesis deals with the comparison of the time complexity and the success of the classification of selected algorithms for mining knowledge from data with focus on neural networks and optimal settings for work execution. In the theoretical part, it is essential to get acquainted with the distribution of algorithms, their functionality and complexity. Then follows the selection of algorithms with focus on neural networks and their settings, especially hidden layers, momentum and learning rate. Another part deals with data used for experimental testing, which are both nominal and numerical data, and also real or generated. Also included is the accuracy of measurement and performance measurement of the two assemblies used to test individual experiments. The third part is the testing of the time complexity and the percentage success of the algorithms and the output especially in graphical form followed by analysis and recommendations from the results with focus on the optimal setting against the automatic and initial settings.