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Algorithmic Trading Using Artificial Neural Networks
Poláček, Samuel ; Beneš, Karel (referee) ; Szőke, Igor (advisor)
Algorithmic trading of many kinds of assets is not a new field at all. Domain of neural networks provides many tools, which are usefull in this field. This bachelor thesis discusses cryptocurrency trading algorithms using artificial neural network. In theoretical section of this thesis the basic theory and terms the stock market trading is based on is discussed. After the basic idea of cryptocurrencies is defined and used technical tools are introduced, the practical section starts. Sufficient configuration of neural network topology and hyperparameters values are obtained by many experiments. Subsequently after many experiments with indicators of technical analysis, acceptable neural network input configuration is obtained. Created neural network model combined with defined trading strategy generates profit.
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Algorithmic Trading Using Artificial Neural Networks
Radoš, Daniel ; Plchot, Oldřich (referee) ; Szőke, Igor (advisor)
This master's thesis is focused on algorithmic trading on the forex market using artificial neural networks. In the introduction, there are generally described terms concerning the trading. Subsequently, in the following chapters, the thesis describes the theory of neural networks and their possible use. The practical part contains designed business strategies with neural networks. Inputs used in the network are indicators of technical analysis or directly price level. Business strategies have been implemented and tested. In the conclusion, there are summarized findings of individual business models.
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Algorithmic Trading Using Artificial Neural Networks
Poláček, Samuel ; Beneš, Karel (referee) ; Szőke, Igor (advisor)
Algorithmic trading of many kinds of assets is not a new field at all. Domain of neural networks provides many tools, which are usefull in this field. This bachelor thesis discusses cryptocurrency trading algorithms using artificial neural network. In theoretical section of this thesis the basic theory and terms the stock market trading is based on is discussed. After the basic idea of cryptocurrencies is defined and used technical tools are introduced, the practical section starts. Sufficient configuration of neural network topology and hyperparameters values are obtained by many experiments. Subsequently after many experiments with indicators of technical analysis, acceptable neural network input configuration is obtained. Created neural network model combined with defined trading strategy generates profit.
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Algorithmic Trading Using Artificial Neural Networks
Radoš, Daniel ; Plchot, Oldřich (referee) ; Szőke, Igor (advisor)
This master's thesis is focused on algorithmic trading on the forex market using artificial neural networks. In the introduction, there are generally described terms concerning the trading. Subsequently, in the following chapters, the thesis describes the theory of neural networks and their possible use. The practical part contains designed business strategies with neural networks. Inputs used in the network are indicators of technical analysis or directly price level. Business strategies have been implemented and tested. In the conclusion, there are summarized findings of individual business models.
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Psychology of trading
Jambrich, Jozef ; Zámečník, Petr (advisor) ; Schönfeld, Jaroslav (referee)
Bachelor's thesis deals with psychology of individual trader as the most important part of successful trading, which is often underrated unfortunatelly. This work researches every element of psychology of trading in order to gain useful know-how for beginners or profesional traders. This includes characteristics required to trading, basic emotions or next aspects, which traders often meet during trading seanse. The thesis also analyses the personality of the trader in detail with the questionnaire. The main aim of the research about personality is to find out the frequency of every personal type between traders in Czech and Slovak republic.
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