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Automatic System for Cryptocurrency Trading
Mráz, Filip ; Rozman, Jaroslav (referee) ; Hříbek, David (advisor)
The thesis focuses on the creation of an automatic trading system (ATS) that is capable of simulating trading on historical stock exchange data and performing automated trading on the account of a selected broker. The system can statistically process and graphically display achieved results. User operates the system via a clear graphical user interface. Individual trading sessions are managed by the system in separate subprocesses. ATS implements 5 trading strategies of varying complexity, which are responsible for managing the trading decisions. Strategies use elements of technical analysis to interpret historical price move- ments, which serve as the basis for making buying and selling decisions. The fifth strategy utilizes a trained XGBoost model for its decision-making. Implemented strategies were tho- roughly tested on historical data, selecting periods with different market moods and price volatilities. Test results did not reveal any consistently profitable strategy, instead defining the strategies as high-risk.
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Automatic Cryptocurrencies Trading
Vorobiev, Nikolaj ; Hrubý, Martin (referee) ; Rozman, Jaroslav (advisor)
This thesis focuses on the trading in the cryptocurrency market. The theoretical part of the thesis describes the principles of trading, technical analysis, trading systems and recurrent neural networks. After conducting a search of brokers, Binance is chosen as a trading broker and real-time data provider; CryptoDataDownload is chosen as a historical data provider. After getting acquainted with the technologies used, elements of information trading systems are designed, enabling communication with remote servers and with each other, for the purpose of trading, obtaining and concurrent processing of user's, historical or real-time data. The resulting systems should provide to the user manual, semi-automatic (according to the plan) or automatic (according to the decisions of recurrent neural network, learned on historical data) trading and ability to respond to a change in the market. Furthermore, the thesis moves to the practical level, including implementation and experiments on created systems. In the final part of the thesis, the results are evaluated and the possibilities for improvement and expansion are described.
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Prediction of Values on a Time Line
Maršová, Eliška ; Bařina, David (referee) ; Zemčík, Pavel (advisor)
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.
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Automatic Cryptocurrencies Trading
Vorobiev, Nikolaj ; Hrubý, Martin (referee) ; Rozman, Jaroslav (advisor)
This thesis focuses on the trading in the cryptocurrency market. The theoretical part of the thesis describes the principles of trading, technical analysis, trading systems and recurrent neural networks. After conducting a search of brokers, Binance is chosen as a trading broker and real-time data provider; CryptoDataDownload is chosen as a historical data provider. After getting acquainted with the technologies used, elements of information trading systems are designed, enabling communication with remote servers and with each other, for the purpose of trading, obtaining and concurrent processing of user's, historical or real-time data. The resulting systems should provide to the user manual, semi-automatic (according to the plan) or automatic (according to the decisions of recurrent neural network, learned on historical data) trading and ability to respond to a change in the market. Furthermore, the thesis moves to the practical level, including implementation and experiments on created systems. In the final part of the thesis, the results are evaluated and the possibilities for improvement and expansion are described.
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Application of technical analysis on algorithmic trading
Šíla, Jan ; Krištoufek, Ladislav (advisor) ; Křehlík, Tomáš (referee)
The thesis takes on the question of profitability of algorithmic trading based on trend and momentum indicators and examines whether or not it is possible to acquire systematic profits. It reviews the development of relevant literature over the last 100 years to determine whether the inner workings of the market can be quantified and plausibly modelled. On three major U.S. stock indices are then tested several different strategies to determine whether in the long- term, passive investment can be outperformed by active trading. Merit of the work lies in backtesting several strategies and interpreting the results according to unique characteristics of the indices.
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The use of technical analysis on the financial market
VOJTA, Petr
Successful investors use technical analysis to make money on the financial market. Presentation explains the uses of technical analysis and theories deployed in trading on the financial market. The main aim is to show advantages, disadvantages and suitability of these strategies. All of this is done by using technical indicators, risk and money management used to protect traders from losses and backtested on historical data. An effective use of technical analysis presupposes that course changes are not random but follow a specific trend which change in time. The aim is to build an automatic trading strategy based on technical analysis following technical indicators. Correctly used technical analysis helps traders to predict trends as well as trend changes before they happen and to use this method for reaching exceptional returns. Strategy setting is based on oscillator Parabolic SAR with special setting values. The strategy was applied on EUR/USD currency pair and four hour time frame (H4 graph). Strategy was tested on historical data and optimized with added money management. Finally backtested on historical data and reached every tested year profit. Absolute net reached profit in years 2016, 2017, 2018 was 17 844USD, which represents 178 % account evaluation.
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Application of technical analysis on algorithmic trading
Šíla, Jan ; Krištoufek, Ladislav (advisor) ; Křehlík, Tomáš (referee)
The thesis takes on the question of profitability of algorithmic trading based on trend and momentum indicators and examines whether or not it is possible to acquire systematic profits. It reviews the development of relevant literature over the last 100 years to determine whether the inner workings of the market can be quantified and plausibly modelled. On three major U.S. stock indices are then tested several different strategies to determine whether in the long- term, passive investment can be outperformed by active trading. Merit of the work lies in backtesting several strategies and interpreting the results according to unique characteristics of the indices.
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Automated business systems in Forex
Bleha, Lukáš ; Čechura, Lukáš (advisor) ; Kateřina, Kateřina (referee)
The thesis characterize the international foreign exchange market Forex and systems used in the market for capital appreciation. In the first part is discussed why this market is so specific and how is trade. After that gradually resolves the issue of automated trading systems. The target is to declare important facts for creating the system. Of those, then practical part obtains data, where develops automated trading system step by step from the outset. The main target is to develop a system that can make a profit in real terms. All procedures are used as are used in practice. It is focused on creating landing rules, analysis, optimization, programming and special testing. The results then indicate the quality of the whole system. When the results are adequate, the system is trading in real terms and in real time. On this part already connected final part, and it is evaluate the results. Based on the success or failure are suggested additional recommendations for further utilization of the created system.
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Prediction of Values on a Time Line
Maršová, Eliška ; Bařina, David (referee) ; Zemčík, Pavel (advisor)
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.
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Online trading using automated trading systems
Polák, Tomáš ; Palovský, Radomír (advisor) ; Sova, Martin (referee)
This work deals with the online automated trading systems in the Forex. In the theoretical section are explained basic concepts necessary for understanding of the international currency market and the basic tools used by professionals to analyze the behavior of prices. In the practical part, author construct two profitable automated systems based on different approaches according to generally accepted standards and prove that it is possible on the basis of simple-blade business model to program a robot to safely and regularly evaluates the financial resources. The results will be compared with the performance of a standard open source AOS.
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