The diploma thesis deals with the design of an automatic trading system for trading on the market of selected commodities, constructed with the help of technical indicators. It also includes system optimization using genetic algorithms to maximize profit and stability. Finally, an economic evaluation of the achieved results is prepared.

Using the example of three commodities and three countries, the purpose of the thesis "Trade with selected commodities with focus on fair trade" is to analyse a chosen commodity market in different states. Focusing on developing countries, the work aims to confirm the validity of theoretical models of the international trade. Moreover, extra attention is paid to the alternative concept of fair trade. The thesis is divided into four chapters with the first giving the theoretical basis for the consequential analysis. The second chapter deals with the fair trade movement, the third part examines the concrete industry in the particular country, and the last chapter studies the consequences of fair trade on producers in the Sub-Saharan region.

This master’s thesis primary deals with a design and a development of own automated trading system which is specialized for commodity markets, especially corn, soybean, wheat and slightly for gold. You can find theoretical basics of technical analysis here, then technical indicators, risk management and trading systems themselves. System is completely designed and programmed in MetaTrader trading platform with using programming language MQL and genetic algorithms. The output of this thesis is portfolio containing six trading strategies which achieved totally 42,4 % increase in three months at the end of year 2014.

This thesis is concerned with the mathematical analysis of electricity and carbon emission markets. We introduce a novel, versatile and tractable stochastic framework for the joint price formation of electricity spot prices and allowance certificates. In the proposed framework electricity and allowance prices are explained as functions of specific fundamental factors, such as the demand for electricity and the prices of the fuels used for its production. As a result, the proposed model very clearly captures the complex dependency of the modelled prices on the aforementioned fundamental factors. The allowance price is obtained as the solution to a coupled forward-backward stochastic differential equation. We provide a rigorous proof of the existence and uniqueness of a solution to this equation and analyse its behaviour using asymptotic techniques. The essence of the model for the electricity price is a carefully chosen and explicitly constructed function representing the supply curve in the electricity market. The model we propose accommodates most regulatory features that are commonly found in implementations of emissions trading systems and we analyse in detail the impact these features have on the prices of allowance certificates. Thereby we reveal a weakness in existing regulatory frameworks, which, in rare cases, can lead to allowance prices that do not conform with the conditions imposed by the regulator. We illustrate the applicability of our model to the pricing of derivative contracts, in particular clean spread options and numerically illustrate its ability to "see" relationships between the fundamental variables and the option contract, which are usually unobserved by other commonly used models in the literature. The results we obtain constitute flexible tools that help to efficiently evaluate the financial impact current or future implementations of emissions trading systems have on participants in these markets.

The goal of this diploma thesis is to analyse the trend of foreign direct investment into mining industry in Africa. In this thesis, I focus solemnly on the extraction of minerals, excluding the oil and gas industry. The analysis looks at the FDI from a historical perspective in the new millennium up to the current situation, which is characteristic for low commodity prices, which subsequently depress the activities of mining corporations. Furthermore, the important part of the thesis is also the projection of future development of FDI, the analysis of the correlation between commodity prices and FDI development and the research of African investment environment. A brief case study regarding the real-life foreign direct investment into copper mining projects in Democratic Republic of the Congo is carried out in the end of this thesis. In this case study I present details about this project, however, also the professional opinion of co-head of mining division at Trafigura, Emmanuel Henry, on the investment environment in Africa in regard to the mining industry and his feelings about the future development of the investment.

My thesis focused on the launch of new brand into commodity markets. Analysing the case study "Nestlé Coffee-mate launch into Czech and Slovak Republics" the thesis created the strategy of entering the market commonly valid for branded goods fighting the increasing power of the private labels. The main goal of the thesis was (not) to recommend Nestlé Česko, s.r.o. to enter Czech and Slovak markets. I made up particular marketing mix studying the commodity market of powdered coffee creamer category in connection with the consumer. Consequently I proposed communication strategy and communication mix. To verify the launch itself I used market test called minimarkets. Minimarkets actually took place at the end of 2008. The market test resulted into my recommendation not to launch Coffee-mate into Czech and Slovak Republic. Key indicators and expectations, so much important for the success of the launch iteself, have not been met during the testing. However, due to the methodologies selected within the thesis, the strategy how to enter the commodity market seems to be applicable onto different commodity categories. Therefore it may be used as a hint during a planning process for new competitive strategies of various brands defending themselves from the private labels.

Tato diplomová práce se zabývá problematikou obchodování na komoditních trzích. Řešení problematiky spočívá ve využití umělé inteligence, konkrétně neuronových sítí, k technické analýze vývoje ceny vybrané komodity a snaze o co nejpřesnější predikci budoucího vývoje ceny pro podporu investičního rozhodování. Model neuronové sítě je vytvořen a použit pro predikci v programu MATLAB.

The South African white maize market is considered to be significantly more volatile than any other agricultural product traded on the South African Futures Exchange (SAFEX). This accentuates the need to effectively manage price risk, by means of hedging, to ensure a more profitable and sustainable maize production sector (Geyser, 2013:39; Jordaan, Grové, Jooste, A. & Jooste, Z.G., 2007:320). However, hedging at lower price levels might result in significant variation margins or costly buy–outs in order to fulfil the contract obligations. This challenge is addressed in this study by making use of technical analysis, focusing on the development of a practical and applicable composite technical indicator with the purpose of improving the timing of price risk management decisions identified by individual technical indicators. This may ultimately assist a producer in achieving a higher average hedge level compared to popular individual technical indicators. The process of constructing a composite indicator was commenced by examining the prevailing tendency of the market. By making use of the Directional Movement Index (DMI), as identified in the literature study, the market was found to continually shift between trending prices (prices moving either upwards or downwards) and prices trading sideways. Consequently, implementing only a leading (statistically more suitable for trading markets) or lagging (statistically more suitable for trending markets) technical indicator may generate false sell signals, as demonstrated by the application of these technical indicators in the white maize market. This substantiated the motivation for compiling a composite indicator that takes both leading and lagging indicators into account to more accurately identify hedging opportunities. The composite indicator made use of the Relative Strength Index (RSI) and Stochastic oscillator as leading indicators, and the Exponential Moving Average (EMA) and Moving Average Convergence Divergence (MACD) as lagging indicators. The results validated the applicability of such a composite indicator, as the composite indicator outperformed the individual technical indicators in the white maize market. The composite indicator achieved the highest average hedge level, the lowest average sell signals generated over the entire period, as well as the highest average hedge level as a percentage of the maximum price over the entire period. Hence, the composite indicator recognised hedging opportunities more accurately compared to individual technical indicators, which ultimately led to higher achieved hedging levels. / MCom. (Risk management), North-West University, Potchefstroom Campus, 2014

The South African white maize market is considered to be significantly more volatile than any other agricultural product traded on the South African Futures Exchange (SAFEX). This accentuates the need to effectively manage price risk, by means of hedging, to ensure a more profitable and sustainable maize production sector (Geyser, 2013:39; Jordaan, Grové, Jooste, A. & Jooste, Z.G., 2007:320). However, hedging at lower price levels might result in significant variation margins or costly buy–outs in order to fulfil the contract obligations. This challenge is addressed in this study by making use of technical analysis, focusing on the development of a practical and applicable composite technical indicator with the purpose of improving the timing of price risk management decisions identified by individual technical indicators. This may ultimately assist a producer in achieving a higher average hedge level compared to popular individual technical indicators. The process of constructing a composite indicator was commenced by examining the prevailing tendency of the market. By making use of the Directional Movement Index (DMI), as identified in the literature study, the market was found to continually shift between trending prices (prices moving either upwards or downwards) and prices trading sideways. Consequently, implementing only a leading (statistically more suitable for trading markets) or lagging (statistically more suitable for trending markets) technical indicator may generate false sell signals, as demonstrated by the application of these technical indicators in the white maize market. This substantiated the motivation for compiling a composite indicator that takes both leading and lagging indicators into account to more accurately identify hedging opportunities. The composite indicator made use of the Relative Strength Index (RSI) and Stochastic oscillator as leading indicators, and the Exponential Moving Average (EMA) and Moving Average Convergence Divergence (MACD) as lagging indicators. The results validated the applicability of such a composite indicator, as the composite indicator outperformed the individual technical indicators in the white maize market. The composite indicator achieved the highest average hedge level, the lowest average sell signals generated over the entire period, as well as the highest average hedge level as a percentage of the maximum price over the entire period. Hence, the composite indicator recognised hedging opportunities more accurately compared to individual technical indicators, which ultimately led to higher achieved hedging levels. / MCom. (Risk management), North-West University, Potchefstroom Campus, 2014

This work deals with the prediction of numerical series whose application is suitable for prediction of stock prices. They explain the procedures for analysis and works with price charts. Also explains the methods of machine learning. Knowledge is used to build a program that finds patterns in numerical series for estimation.