This master’s thesis deals with the technical analysis of Starbucks Corporation, Vodafone Group, Apple and Autodesk stocks, which are tradeable at stock market NASDAQ. At the beginning, this work focuses on theoretical materials, which are then used for elaborating three trading systems and their testing on selected stocks. Conclusion of this thesis contains a selection of trading system for each stock on selected period of time.

This thesis deals with an analysis and prediction of foreign exchange markets. The thesis is based on the fractal market hypothesis and it uses tools based on fractal geometry for prediction of markets. The thesis also describes ways of using advanced methods of artificial intelligence for analyzing markets. The outcome is designed and implemented automatic trading system. The thesis also deals with testing of designed system on historical data and on the latest data as well.

The content of my master´s thesis is the creation of automatic trading system which will be applied on real trading account mainly on financial markets of currency pairs. The thesis is divided to several parts where the theoretical part will introduce the problem of trading on financial markets. Following part analyses needs of small trader on the financial markets, selecting suitable instruments which will be used in automatic trading system. The part of the own solution design will create the mentioned automatic trading system which will be applied on broker´s demo account where the system will be tested mainly on historical data. Based on test results, system will be optimized and in case of usable results of testing also system will be applied on real trading account in trading company.

The goal of this work is to describe approaches to financial market analysis and implement chosen approaches in automatic trading system in the MetaQuote Language environment for Metatrader platform. Another objective is to optimise the designed trading system and test additional rules to achieve maximum profit during minimalization risks.

This thesis deals with use of regression or classification based on support vector machines from machine learning field. SVMs predict values that are used for decisions of automatic trading system. Regression and classification are evaluated for their usability for decision making. Strategy is being then optimized, tested and evaluated on foreign exchange market Forex historic data set. Results are promising. Strategy could be used in combination with other strategy that would confirm decisions for entering and exiting trades.

The main focus of the thesis are approaches to technical analysis, trading systems and it summarizes interesting findings, according to which a FOREX automated trading system was designed and implemented. Optimization and testing were a prerequisite for a real-world deployment, so the automated trading system was tested on historical data and some of its input parameters were optimized for maximum stability and profit.

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.

This thesis analysis the impact of private road transport under emission trading using two different Computable General Equilibrium models. A static multi-region model with special emphasis on the European Union, addresses the welfare impact of road transport under the European Emission Trading System. Including terms-of-trade effects, this model does not account for congestion which is the main externality of road transport. Furthermore, technological details of electricity generation which are an important factor in evaluating climate policies are not included. Therefore, the second model is a static Small Open Economy model of the German economy including congestion effects and detailed technological characteristics of electricity generation. The results of both models highlight the important role of already existing taxes on transport fuels for the evaluation of carbon mitigation measures in road transportation.

Policymakers' action of mitigating and slowing down the continued increase of carbon emission is a significant global priority. One way to internalise the negative externality of pollution is to put a price on greenhouse gases and use the market-based approach of emission trading systems. On the other hand, according to economic reasoning, pollution is an essential tool for economic development. This paper aims to investigate the economic effects of introducing the first international emission trading system of greenhouse gases, the EU emission trading system, by observing the economic growth and gross fixed capital formation. Mankiw, Romer, and Wiel's (1992) theory is utilised in this study and based on cross-country and cross-state panel data between 1999-2012, an empirical analysis using the fixed effects model was followed. The finding shows that the EU emission trading system has a negative effect on the growth of real gross domestic product per capita compared to states and countries not participating in an emission trading system. In addition, the first phase results having a positive effect and the second phase has a negative effect on the economic growth compared to states and countries not participating in an emission trading system. There is no statistical evidence of the effect on gross fixed capital formation as a percentage share of GDP. Organisations can use the findings to decide whether developing countries can afford the consequence of an implemented emission trading system since it tends to slow down growth. However, further research needs to consider the effect of the financial crisis of 2008 and the interpretation of the EU emission trading scheme.

This thesis analyzes how the EU Emissions Trading System (ETS) evolved in response to the European Green Deal, with a particular focus on climate justice. In previous trading periods, the ETS faced extensive criticism from researchers and international environmental organizations, who argued that the system exacerbated social and economic inequalities. However, as part of the Green Deal, the ETS underwent reforms with stricter regulations, clearer targets, and the inclusion of more sectors. The aim of this thesis is to analyze these changes and assess whether the system could now be considered just. The analysis is conducted using a critical approach and an ideal-type analysis, evaluating the ETS according to two justice-based criteria: effectiveness and the equitable distribution of climate change responsibilities. The results indicates that the current form of the emission trading system fails to meet the standards of fairness on both criteria.