The goal of this thesis “Futures trading of commodities as a retail trader” is creation of investment suggestion, based on analysis of possibilities, markets and factors influencing the price. In the first part are defined basic terms and information for better orientation on the futures commodity market. In the next part are analysis of the major commodity markets, groups of commodities and detailed analysis of interest commodities – gold and silver. The last third part of the thesis engage in creation of strategy for trading of commodity futures on gold and silver, which is the basic element for the final investment suggestion.

The Paper is focused on company shares value and manipulation with their course on capital market. Theoretical part describes Fundamentals and technical analysis, which are used for identifying share inner value a expected trend in course. Consequently are described forbidden market practices and transactions on capital market according to new legal regulation. Analytic part contains analysis, which identifies inner value of company shares and predicts trend in course. Following analysis are setting measures, which enables company management to realize appreciation of company shares, without making offend against legal regulations of securities course manipulation. Summary contains recommendations and findings, which can be generally used for improving companies positions on capital markets.

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.

The thesis deals with the design and optimization of artificial neural networks (specifically nonlinear autoregressive networks) and their subsequent usage in predictive application of stock market time series.

This diploma thesis describes issues of use of means of artificial intelligence for the decision making support on stock market. It includes theoretical knowledge of technical, fundamental and psychological analysis and artificial intelligence. Based on these facts have been created specific suggestions for the use of artificial neural networks to forecast the future value of the index S&P 500 by using development environment of the MATLAB software.

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 diploma thesis discusses about the possibilities of investing in the capital market with a focus on the foreign exchange market. Analysis of the company, whose output is SWOT analysis, is focused on the economic justification of investments. The essence is the proposal of automatic trading systems that will automatically trade on the basis of information from the market and add value to ivested capital. This automatic trading systems are designed in analytic platform named MetaTrader and their parameters are optimized by genetic algorithms.

This thesis deals with the automatization and comparison of two different strategies for the forex markets, based on the indicator, one from the tools of technical analysis, called Bollinger Bands. Both strategies are first optimized and then compared. Automatization of strategies will be implemented by? using the Meta Quotes Language for MetaTrader broker and its testing will be done on historical data. The goal with this thesis is the operational objective application of the better strategy in the environment of real market.

Objective of this thesis is to make a summary elaboration of particular proposals, which can reform the financial situation of the company and target the elimination of inconvenient financial indicators. In this thesis, there are used the financial analysis methods to parse financial situation of the company. For a consideration of the company financial results are proposed the processes to improve the financial situation of the company.

The aim of this work is to create an automated trading system for trading currency pairs using technical indicators and technical analysis. The proposed trading system is tested and optimized on historical price data. To verify the robustness of the proposed system was used walk-forward analysis. Automatic trading system also uses rules for position sizing and risk management of open positions. Created system is profitabel on historical price data and also in the walk-forward analysis.