|
|
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.
|
|
|
Fundamental Analysis for Automatic Trading Systems
Miček, Marek ; Kanich, Ondřej (referee) ; Rozman, Jaroslav (advisor)
This thesis deals with the creation of automatic trading systems which are able to predict market trends for stocks selected in advance. Proper trading strategy of this system is mainly created from the elements of fundamental analysis, such as annual returns of company, it's gains, level of shareholder's equity or total debt. All the stocks are classified by these fundaments, where result of this classification determines whether to buy or sell the stock. For the purpose of this thesis, 5 autamatic trading systems were created in order to compare different approaches to the stock evaluation, managment or diversification of business portfolio. Created systems were properly tested on historical data and, in order to determine their level of complexity, tests were executed in both periods of economic recession and expansion too. All the created systems reported great returns and most of them have potential to generate long-term gains. On the basis of received results, it is possible to make conclusion that fundamental analysis has a high value in the field of automatic trading systems, and it increases the chances of generating a profit.
|
|
|
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.
|
|
|
Fundamental Analysis for Automatic Trading Systems
Miček, Marek ; Kanich, Ondřej (referee) ; Rozman, Jaroslav (advisor)
This thesis deals with the creation of automatic trading systems which are able to predict market trends for stocks selected in advance. Proper trading strategy of this system is mainly created from the elements of fundamental analysis, such as annual returns of company, it's gains, level of shareholder's equity or total debt. All the stocks are classified by these fundaments, where result of this classification determines whether to buy or sell the stock. For the purpose of this thesis, 5 autamatic trading systems were created in order to compare different approaches to the stock evaluation, managment or diversification of business portfolio. Created systems were properly tested on historical data and, in order to determine their level of complexity, tests were executed in both periods of economic recession and expansion too. All the created systems reported great returns and most of them have potential to generate long-term gains. On the basis of received results, it is possible to make conclusion that fundamental analysis has a high value in the field of automatic trading systems, and it increases the chances of generating a profit.
|
guest ::
