The capability to be able to determine the future progression on the worlds stock exchange is an important issue, which has become discernible in the last decades. An important role of this progression lies within the fast advancements in computerized technology. Aforementioned document describes a mechanism used for prediction of the future price of a certain stock. The strategy of trading is build upon this mechanism, and the core of this prediction system is an artificial neural network. Inputs used in this network are indicators derived from technical analysis. This trading system was implemented into historical trades and successfully tested.

The capability to be able to determine the future progression on the worlds stock exchange is an important issue, which has become discernible in the last decades. An important role of this progression lies within the fast advancements in computerized technology.Aforementioned document describes a mechanism used for prediction of the future price of a certain stock. The strategy of trading is build upon this mechanism, and the core of this prediction system is an artificial neural network. Inputs used in this network are indicators derived from technical analysis. This trading system was implemented into historical trades and successfully tested.

The master’s thesis deals about portfolio securities optimalization on Prague stock exchange. After the theoretical part follows global fundamental analysis with the guess of market trends. Next part describes fundemantal analysis on the association´s level. On the basis of fundamental analysis results was created optimized securities portfolio.

My thesis deals with analyses of returns of IPO’s in the Czech capital market. The theoretical section of the thesis contains of circumscription of main terms and methodics for preparations and realizations of IPO. In the analytical section these theoretical findings are applied. This thesis should bring realistic view of returns of IPO’s for investors and evaluate present trends on IPO market.

This thesis deals with design, optimization and testing of an automated trading system intended for trading CFD contracts. The strategy is based on a combination of a moving average and a custom indicator, which gives signals based on convergence of signals of other monitored indicators. The designed automated trading system also contains a simple, but efficient money management. It is responsible for risking a constant portion of current account balance on each trade. The thesis continues with comparison of three ways to optimize chosen input parameters and comparison of performance of the strategy for ten tested market symbols.

This thesis is focused on the design and optimization of automated trading system, which will be traded in FOREX. The aim is to create a business strategy that is relatively safe, stable and profitable. Optimization and testing on historical data are a prerequisite for the deployment into real trading.

This thesis is aimed to exploitation of fundamental analysis in automatic trading. Technical analysis uses historical prices and indicators derived from price for price prediction. On the opposite, fundamental analysis uses various information resources for price prediction. In this thesis, only quantitative data are used. These data sources are namely weather, Forex, Google Trends, WikiTrends, historical prices of futures and some fundamental data (birth rate, migration, \dots). These data are processed with LSTM neural network, which predicts stocks prices of selected companies. This prediction is basis for created trading system. Experiments show major improvement in results of the trading system; 8\% increase in success prediction accuracy thanks to involvement of fundamental analysis.

This master's thesis describes creation of prediction system. This system predicts future market development based on stock exchange data and twitter messages analysis. Tweets from two different sources are analysed by mood dictionaries or via recurrent neural networks. This analysis results and technical analysis of stock exchange data results are used in multilayer neural network for prediction. A business strategy is created and tested based on results of this prediction. Design and implementation of prediction system is described in this thesis. This system achieved revenue increase more than 25 % of some business strategies by tweets analysis. However this improvement applies for certain data and timeframe.

Aim of this thesis is to introduce questions about trading stocks on global stock exchange. It shows up basics ideas, which are necessary to understand the system of trading stocks, building a bussines strategy and its automatization by simple information technology techniques. In the following, there is a description of concept and implementation of business system for testing a trading strategy, which is based on historical market data analysis. The next part of this work is focused on the demonstration system and its expansion possibilities. Whole aplication is created by means of scripting language PHP and Javascript, markup language HTML, using the MySQL database system.

This thesis researches the world coffee and tea trade, especially their flows and trends in consumption and production and trade regulations that affect these flows. This paper is divided into three chapters. The first chapter focuses on the world coffee and tea production, the economic benefits of these commodities for producing countries and the outlook for these markets. Another chapter deals with the coffee and tea market, the development of demand, supply and price is examined. This chapter is also dedicated to the concept of Fair Trade and to the forms of trading on examined markets. It is explained how the commodity exchange, tea auctions and trading on the basis of financial derivatives work. The last chapter investigates the forms of international regulations that have been requested by the global coffee and tea trade.