This thesis focused on general characteristics of technical analysis and the use of its instruments to support making decisions when trading in stock market. Within the theoretic part are processed theoretic solutions which are primarily relevant to technical analysis. At the specific stock item is by the help of proposed application consequently implemented the analysis of individual indicators of technical analysis. At the conclusion is compared the profitability and reliability of used indicators.

This thesis focuses on automated trading systems for foreign exchange markets. It describes theoretical background of financial markets, technical analysis approaches and theoretical knowledge about automated trading systems. The output of the thesis is set of two automated trading systems built for trading the most liquid currency pairs. The process of developing automated trading system as well as its practical start up in Spartacus Company Ltd. is documented in the form of project documentation. The project documentation captures choosing necessary hardware components, their installation and oricess of ensuring smooth operation, as well as the selection and installation of the necessary software resources. In the Adaptrade Builder enviroment there has been shown the process of developing strategies and consequently theirs characteristics, performance, as well as a graph showing the evolution of the account at the time. Selected portfolio strategy has been tested in the MetaTrader platform and in the end of the thesis is offered assessing achievements and draw an overall conclusion.

The thesis deals with the use of genetic algorithms in the process of creating automated trading systems. The emphasis is on testing the robustness of the developed strategies, their practical applicability in the financial markets and minimizing risk through diversification. The output of this work is a portfolio consisting of three strategies that achieved 31.3% return on capital during the fourth quarter of 2014.

This master’s thesis deals with the problems of a technical analysis and its use. The first part of thesis describes theoretical background of the technical analysis and basic concepts and principles of the currency market Forex. The second part is devoted to analyzing the current situation in the environment of currency market. The output of the thesis is a desktop application for the support of technical analysis. The design and development of the application is described in the last part of this thesis.

This diploma thesis deals with theoretical and practical aspect of the Forex market and all important information that is necessary for its understanding and trading on this market, focused on intraday trading with automated trading system. The main goal of this thesis is to create whole information source for beginner forex traders and to describe them all trading risks and the ways how to reduce these risks, for example through the using of money management and creating suitable automated trading strategy. The next part describes fundamental, technical and partly psychological analysis. This part is mainly focused on technical analysis and describing well known and the most widely used indicators of technical analysis. Based on gained knowledge, several automated intraday trading strategies suitable for small initial capital on the most liquid currency pair EUR/USD are designed, tested and evaluated. These strategies are based on technical indicators and its combinations.

This diploma thesis deal with creation of trading strategy proposal results in controlling free financial capital of individual. In this diploma thesis is created a tested trading strategy, which is applicable for forex trading. Trading strategy use technical analysis rules, market profile and order flow chart. This strategy was tested on historical data. After that was used on real trading account with aim of maximum profit.

The main aim of this diploma thesis is to analyze the options of trading Forex by combining fundamental and technical analysis in connection to intraday trading. One of the goals is to identify pros and cons of these analysis. Based on the gained information, design trading portfolio consisting of different strategies. Each strategy will be programmed as automated trading system and optimized and tested on historical price data.

Over a long period of time, researchers have investigated the efficiency of financial markets. The widely accepted theory of the subject is the Efficient Market Hypothesis, which states that prices of financial assets are set efficiently. A common way to test this hypothesis is to analyze the returns generated by technical trading rules which uses historical prices in an attempt to predict future price development. This is also what this study aims to do. Using adjusted daily closing prices ranging over 2007 to 2019 for 5120 stocks listed on the U.S stock market, this study tests a momentum trading strategy called the stochastic oscillator in an attempt to beat a buy and hold strategy of the Russel 3000 stock market index. The stochastic oscillator is constructed in three different ways, the Fast%K, the Fast%D and the Slow%D, the difference being that a smoothing parameter is used in the Fast%D and Slow%D in an attempt to reduce the number of whiplashes or false trading signals. The mean returns of the technical trading strategies are tested against the mean returns of the buy and hold strategy using a non-parametric bootstrap methodology and also, the risk adjusted returns in terms of Sharpe Ratios are compared for the different strategies. The results find no significance difference between the mean returns of the buy and hold strategy and any of the technical trading strategies. Further, the buy and hold strategy delivers a higher risk adjusted return compared to the technical trading strategies, although, only by a small margin. Regarding the smoothing parameter applied to the strategies, it seems to fulfill its purpose by reducing the number of trades and slightly increasing the mean returns of the technical trading strategies. Finally, for deeper insight in the subject, a reading of "The efficiency of financial markets: A dual momentum trading strategy on the Swedish stock market" by Netzén Örn (2018) is recommended.

We use an adversarial expert based online learning algorithm to learn the optimal parameters required to maximise wealth trading zero-cost portfolio strategies. The learning algorithm is used to determine the relative population dynamics of technical trading strategies that can survive historical back-testing as well as form an overall aggregated portfolio trading strategy from the set of underlying trading strategies implemented on daily and intraday Johannesburg Stock Exchange data. The resulting population time-series are investigated using unsupervised learning for dimensionality reduction and visualisation. A key contribution is that the overall aggregated trading strategies are tested for statistical arbitrage using a novel hypothesis test proposed by Jarrow et al. [31] on both daily sampled and intraday time-scales. The (low frequency) daily sampled strategies fail the arbitrage tests after costs, while the (high frequency) intraday sampled strategies are not falsified as statistical arbitrages after costs. The estimates of trading strategy success, cost of trading and slippage are considered along with an offline benchmark portfolio algorithm for performance comparison. In addition, the algorithms generalisation error is analysed by recovering a probability of back-test overfitting estimate using a nonparametric procedure introduced by Bailey et al. [19]. The work aims to explore and better understand the interplay between different technical trading strategies from a data-informed perspective.

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