This thesis deals with problems of automatic trading system for trading on commodity exchange. Automated trading system for the purpose of this thesis is based on the principle of adaptive moving average. This principle is processed initially at a theoretical level, then the thesis analyzes the problem of making automated trading system and risks of online trading. The final section describes implementation and testing of automatic trading system.

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.

In Finance, the use of Automated Trading Systems (ATS) on markets is growing every year and the trades generated by an algorithm now account for most of orders that arrive at stock exchanges (Kissell, 2020). Historically, these systems were based on advanced statistical methods and signal processing designed to extract trading signals from financial data. The recent success of Machine Learning has attracted the interest of the financial community. Reinforcement Learning is a subcategory of machine learning and has been broadly applied by investors and researchers in building trading systems (Kissell, 2020). In this thesis, we address the issue that deep reinforcement learning may be susceptible to sampling errors and over-fitting and propose a robust deep reinforcement learning method that integrates techniques from reinforcement learning and robust optimization. We back-test and compare the performance of the developed algorithm, Robust DDPG, with UBAH (Uniform Buy and Hold) benchmark and other RL algorithms and show that the robust algorithm of this research can reduce the downside risk of an investment strategy significantly and can ensure a safer path for the investor’s portfolio value.

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.

Focus of master's thesis is usability of automated trading of commodities with automated trading systems – expert advisors. Thesis describe theoretical background of commodity markets, trading principles, technical analysis of market, design and implementation of strategy as expert advisor. In conclusion, results are analyzed.

This diploma thesis deals with theoretical and practical aspects of the commodity mar-ket. The automated trading system is designed and described there, which is focused on oil trades. The theoretical background as technical analysis, technical indicators descrip-tion or money management in trading, are described. The practical part of the thesis is focused on the analysis of oil market and the proposition of several strategies. These strategies are implemented subsequently to MQL4 language and tested on historical data.

The thesis deals with designing an automated trading system, especially for intra-day trading the currency markets. The aim is to create a comprehensive theoretical background, practical work knowledge can be used to develop appropriate automated trading system. The thesis is an emphasis on technical and partly a psychological analysis of currency markets. Designed system will be suitably optimized to maximize profits and stability of applications on the most liquid currency pairs.

This master thesis deals with design of automated trading system for currency trading. The thesis includes testing of this system on historical data and its optimization for achieving stability and profit. Thesis is divided into theoretical, analytical and practical part. The goal of the first part is to provide theoretical knowledge of the currency market, methods for analysis of the currency market and to define fundamental terminology. Second part describes properties of technical analysis indicators and introduces optimization and testing methods for automated trading systems. The last part is focused on design, implementation, optimization and testing of the automated trading systems.

This diploma thesis deals with the technical analysis with the emphasis on creating, testing and using of trading systems. Its objective is to find out whether it is possible for a trader to design and trade his own profitable trading system with widely accessible tools and methods. First part of the thesis concentrates among other things on the explanation of stock valuation principles, description of tested shares and time period. The second and third chapters fully describe the process of trading system development and the analysis of results of both trading systems. Last chapter is devoted to the interconnection of European stock markets, which is explored by the means of correlation analysis among different stock indexes. The correlation coefficients show a strong link of the markets and the rising level of integration of European markets.

Purpose: Our main purpose is to explore, describe and analyze the organizational conduct when implementing automated trading systems (ATS) in companies, investigate the organizational challenges arising from this, and the effects these have on a successful diffusion. As the extent of implementing ATS in the Swedish financial industry has not been explored to any greater extent, it is therefore also imperative to explore this; which will be seen as a secondary purpose to this article. Background: The study is based on innovation and diffusion theories, as well as those of power structures and organization. Further, an explanation of ATS and its dynamics is provided and discussed to facilitate a definition of the term. Method: The research has been carried out as an exploratory, descriptive and analytical qualitative study. We have conducted case studies of 7 companies that are implementing, or evaluating the implementation, of ATS. The data was collected through interviews. Conclusion: The majority of the case companies are in the clarifying and routinizing stages of the innovation process. What is found unique with ATS is that it can be implemented partly. The dimensions found central to a smooth diffusion in the companies are the required level of competence-sharing and complexity of implementation.