The work deals with an automatic trading system and adaptive training. Is used both technical and automatic fundamental analyses, therefore as inputs to the neural network is used historical data exchanges and text data from reports. It explains the basics of trading, technical analysis and technical terms. The work deals with technical and fundamental analysis. It contains a description of algorithmic nature, program implementation and experiment with developed trading system. The selected strategy is compared to other approaches.

This thesis deals with the development of application for fundamental analysis of stocks. Main goal of the thesis is to make application, which will be helpful for individual investors in performing fundamental analysis of stocks. It is desktop application, which performs calculations with high precision and it uses free on-line sources of financial data. The application was developed in Java programming language. It will be available as a~freeware alternative to proprietary fundamental analysis software on the market. The first part describes capital market and stock exchange, makes characteristics of stock and explains principle of fundamental analysis of stocks. In the second part, the market research of fundamental analysis software was realized, design and implementation of the application for fundamental analyiss was described and the application was evaluated.

The submitted diploma thesis describes particular types of European energetic exchanges, focuses in depth on principles market in Czech Republic and studies the price development on spot and futures markets. The main idea of this work is to focus on renewable energy sources (RES) and their influence on energetic markets. At first, operational and reliability properties of RES are explained and then their development support is analyzed. Last chapters focus on how the power grid is impacted by RES that are hardly predictable source with local production characteristic. There are also outlined problems originating from irregular production that are linked to a surplus of electric energy, but also on energy shortage caused by bad weather. These problems influence international commerce and reduce the capacity of cross-border profiles.

The thesis deals with design, implementation and optimization of a model based on artificial intelligence and neural networks, which is able to predict future time series prices on a stock market. Main goal is to create an object oriented application for successful future trend prediction of financial derivatives with the use of cooperating methods such as Hurst exponent evaluation and automated market simulation.

The subject of this thesis is to introduce the reader to the issue of possible financial investment in the virtual economy with real funds and design strategies to maximize the initial capital appreciation. The introduction describes the analysis of virtual PED currency, the economy and the system of publicly traded shares. The main part is focused on presenting the results of practical traded investment based on fundamental analysis, speculation about the intrinsic value of the shares and evaluating applied strategies, including the benefits of work.