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.

The foreign exchange (Forex) market has over 5 trillion USD turnover per day. In addition, it is one of the most volatile and dynamic markets in the world. Market conditions continue to change every second. Algorithmic trading in Financial markets have received a lot of attention in recent years. However, only few literature have explored the applicability and performance of various dynamic multi-objective algorithms (DMOAs) in the Forex market. This dissertation proposes a dynamic multi-swarm multi-objective particle swarm optimization (DMS-MOPSO) to solve dynamic MOPs (DMOPs). In order to explore the performance and applicability of DMS-MOPSO, the algorithm is adapted for the Forex market. This dissertation also explores the performance of di erent variants of dynamic particle swarm optimization (PSO), namely the charge PSO (cPSO) and quantum PSO (qPSO), for the Forex market. However, since the Forex market is not only dynamic but have di erent con icting objectives, a single-objective optimization algorithm (SOA) might not yield pro t over time. For this reason, the Forex market was de ned as a multi-objective optimization problem (MOP). Moreover, maximizing pro t in a nancial time series, like Forex, with computational intelligence (CI) techniques is very challenging. It is even more challenging to make a decision from the solutions of a MOP, like automated Forex trading. This dissertation also explores the e ects of ve decision models (DMs) on DMS-MOPSO and other three state-of-the-art DMOAs, namely the dynamic vector-evaluated particle swarm optimization (DVEPSO) algorithm, the multi-objective particle swarm optimization algorithm with crowded distance (MOPSOCD) and dynamic non-dominated sorting genetic algorithm II (DNSGA-II). The e ects of constraints handling and the, knowledge sharing approach amongst sub-swarms were explored for DMS-MOPSO. DMS-MOPSO is compared against other state-of-the-art multi-objective algorithms (MOAs) and dynamic SOAs. A sliding window mechanism is employed over di erent types of currency pairs. The focus of this dissertation is to optimized technical indicators to maximized the pro t and minimize the transaction cost. The obtained results showed that both dynamic single-objective optimization (SOO) algorithms and dynamic multi-objective optimization (MOO) algorithms performed better than static algorithms on dynamic poroblems. Moreover, the results also showed that a multi-swarm approach for MOO can solve dynamic MOPs. / Dissertation (MEng)--University of Pretoria, 2019. / Computer Science / MSc / Unrestricted

This thesis presents market stock trading focused on analysis of financial crisis which falls on world's biggest exchange stocks and strategy of trading for a small investor. In the first part of this thesis will be explained priciples of trading on stock markets with modern trading business platformes. I explain economic conections and economy cycles which influence development of financial markets. In second part of thesis I analyse financial crisis fall on stock markets, indexis, commodities (gold, silver, brend crude oil) and currency markets (forex). I appreciate situation in Czech republik and course of czech index PX. Important role has a fundamental and technical analysis. I will analyse and descript modern trends of this business.

Over the last decade, researchers have attempted to show how efficient the markets are by using Fama’s Efficiency Market Hypothesis (EMH). The theory states that an investor cannot increase his returns without taking additional risk. The markets can be efficient in different forms depending on the information included in the traded asset. It is quoted that: "There ain't no such thing as a free lunch". However, the topic still remains disputable since researchers have introduced controversial findings after investigating different markets. Overall, emerging markets have been characterized with higher volatility which consequently declares for market imperfections. Commonly, these market inefficiencies are quickly captured by the eye of the investors who are lurking for potential benefits through exploiting them. These are the so called arbitrage opportunities which exist on different level of impact, depending on the attitude of the market. The existence of arbitrage is clear evidence against Fama’s theory and it has been documented in numerous studies. Unfortunately those events occur rarely and disappear in a matter of seconds, thus; is highly competitive to capitalize. Over the last decade high frequency trading (HFT) became popular on different markets and it allowed traders to make decisions and execute transactions in a matter of milliseconds using algorithms. The market we are interested in is the Forex market which is a decentralized market where currencies from all over the world are traded. Main participants include multinational banks which rely heavily on HFT. The method used to benefit from inefficiency is called triangular arbitrage and it involves selling and buying 3 sets of currency pairs in times when a parity is violated. The goal of this study is to answer the following research question, “Is there a difference in triangular arbitrage opportunities between emerging markets and developed ones?” The main objective of this research is to examine how the number of arbitrage occurrences varies considering different market characteristics. Furthermore, the originality of the research stems from the comparison between strategies using currencies from developed economies and emerging ones. Moreover, the additional academic value comes from the analysis of a new dataset that has not yet been examined. Lastly, our results make an empirical contribution into a country’s economy by reducing market inefficiencies and increasing economic stability. Our sample consists of quantitative data totaling to 2.4 million observations per quotation taken from 2011 and 2013 for currencies picked using a non-probability convenience method based on their property to be converted to EUR and USD currency and availability of information. The research revealed that differences between the two types of market exist, and indicates that the “early” markets possess higher arbitrage activity in contrast to the mature economies. These results should boost the potential for a better trading management and upgrade the profit growth.

This academic paper gives explanation the main points of the foreign exchange market and the FOREX risk management strategies that companies develop. Reading trough this paper we get a clear overview of the Foreign Exchange market, the main players and their function. Get a detailed picture of the Exchange rate system, its development and current status; Hedging strategies and the central roll they have in the foreign exchange risk management of companies.

This thesis deals with the design, implementation and optimization of the automated trading system for the foreign exchange market. Thesis analyses theoretical aspects for the system implementation, including introduction of foreign exchange market, types of market analysis, money management, risk management and technical indicators. The thesis further describes, what is required for development of such system and what important parts the system must contain. The work also describes how the system can be tested and optimised based on historical data.

The master's thesis' objective is to study basics of high-frequency trading, especially trading at foreign exchange market. Project deals with foreign exchange data preprocessing, fundamentals of market data collecting, data storing and cleaning are discussed. Doing decisions based on poor quality data can lead into fatal consequences in money business therefore data cleaning is necessary. The thesis describes adaptive data cleaning algorithm which is able to adapt current market conditions. According to design a modular plug-in application for data collecting, storing and following cleaning has been implemented.

Diploma thesis deals with the creation of an automated trading system for foreign exchange market with the usage of artificial intelligence and elements of technical analysis. In the custom solution design a brokerage company for trading and backtesting is selected with the help of fuzzy logic. For selecting currency pairs for backtesting the strategy on is used method of clustering called self-organizing map. The particular ATS is created in MetaTrader4 platform with the usage of a programming language MQL4 and a FANN library for creating artificial neural networks.

This Master's thesis focuses on applying artificial intelligence tools for the prediction of development financial markets. Major emphasis is placed on evaluating the usability of neural networks to determine the prediction in the foreign exchange markets. It is also provided suggestion for fully automated processing of market data and subsequent submitting of trading orders.