The graduation thesis is primaly focused on problems of specialities of accountancy in joint-stock company in Czech republic. Between these specialities we comprise increases and decreases in the registered capital and distribution of income or payment of loss. The subject of this thesis is the application of accounting, tax and legal enactments on joint-stock company.

In my diploma I analyzed the USA capital market. I concentrated on 5 representative branches of this market - the biotechnology, the food industry, the car industry, the mining and the finances. 12 companies, which quote their share of stocks in the american capital market, were choosed. I tested the efficiency of this capital market and tried to establish the rate of this market´s efficiency. Later the best strategy was added to the rate of capital market´s efficiency. I counted the average decree, the standard deviation, the variation coefficient, the {$\alpha$} coefficient and {$\beta$} coefficient at the choosed share of stocks. I accomplished the correlative and the runs testing, which were supposed to certify the efficiency of market. The certain anomalies as The Day of the Week Effect, The January Effect and The Size Effect were investigated in more detail. Further I was considering if either the active or the passive strategy should have been used. I concluded that the active strategy is better for investors in times of the financial crisis. I also analyzed P/E ratio at choosed companies. The performated testing shows that the american market of shares is effective, it has the form of low efficiency peak-form efficient markets hypothesis.

Diploma thesis is focused on problematics of artificial neural networks and their usage on capital markets. There is a software created as a part of this diploma thesis which can load input data and create neural network that serves for share price forecast. This program is created in numerical computing environment MATLAB. Created neural network is tested under simulation of business model. Results are discussed upon examination of results of simulation.

The folowing work deals with primary public issue of stocks - an external financial source of business activities. This source of finance is defined to the reader as: there are explained advantages and disadvantages of IPO Process, including supposition of succesful enter to the stock exchange. This work is concretly oriented on Pre-filing phase of a company for an enter to the stock exchange with the aim to set a procedure of IPO Process and apply it to a concrete company.

In this diploma thesis I constructed generally usable program for processing economical data through mathematical methods of linear regression in Maple system. Program is used for trend dependency analysis of examined quantities. Via multi-stage algorithmization and implementation of information criterion I created interactive form with user-friendly interface with possibility of straight data import from office suite applications. Functionality of this program is verified on example with specific data collection.

This thesis deals with a fundamental share analysis of the Czech ČEZ Group. The theoretical part summarizes the most frequent techniques and methods of a fundamental share analysis. In the practical part these findings are used to analyze the shares of ČEZ. The core of the fundamental analysis itself lies in the calculation of the intrinsic value of the share. And finally, investment recommendations are proposed on the basis of the comparison between the acquired intrinsic value and the current market price of the shares.

The diploma thesis deals with artificial intelligence utilization for predictions on stock markets.The prediction is unconventionally based on Bayes' probabilistic model theorem and on its based Naive Bayes classifier. I the practical part algorithm is designed. The algorithm uses recognized relations between identifiers of technical analyze. Concretely exponential running averages at 20 and 50 days had been used. The program output is a graphic forecast of future stock development which is designed on ground of relations classification between the identifiers

This master's thesis deals with the analysis of selected rates of shares by using statistical methods including regression analysis and analysis of time series. Using moving averages as technical indicators in technical analysis of securities to predict the future development of rates of shares and finding buy and sell signals that these indicators generate. The results of this work are suggestions for stock trading based on the use of these methods.

This master's thesis deals with artificial neural networks and possibilities of their use on stock market. In next chapters of this thesis there are provided design and implementation of stock prices prediction tool. The implementation is done with use of the MATLAB software. The created prediction tool is then tested in a simple trading simulation and achieved results are discussed in the end

This Master’s thesis deals with the analysis of long-term corporate financing. Described is financing through the capital market securities – by shares and bonds as well as bank loan. The first part compares the theoretical possibilities of external financing, the second part is focused on the analyse of IPO and analysis of IPO which was realized in Czech republic by listed companies.