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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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Investment Environment in the Virtual Real Cash Economy
Lehnert, Filip ; Hlavinka, Roman (referee) ; Budík, Jan (advisor)
The subject of this thesis is to introduce the reader to the issue of possible financial investment in the virtual economy with real funds and design strategies to maximize the initial capital appreciation. The introduction describes the analysis of virtual PED currency, the economy and the system of publicly traded shares. The main part is focused on presenting the results of practical traded investment based on fundamental analysis, speculation about the intrinsic value of the shares and evaluating applied strategies, including the benefits of work.
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Algorithmic Trading Using Twitter Data
Kříž, Jakub ; Plchot, Oldřich (referee) ; Szőke, Igor (advisor)
This master's thesis describes creation of prediction system. This system predicts future market development based on stock exchange data and twitter messages analysis. Tweets from two different sources are analysed by mood dictionaries or via recurrent neural networks. This analysis results and technical analysis of stock exchange data results are used in multilayer neural network for prediction. A business strategy is created and tested based on results of this prediction. Design and implementation of prediction system is described in this thesis. This system achieved revenue increase more than 25 % of some business strategies by tweets analysis. However this improvement applies for certain data and timeframe.
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Adaptive Trading Strategies for Cryptocurrencies
Filip, Marek ; Perešíni, Martin (referee) ; Homoliak, Ivan (advisor)
Obchodní strategie pro kryptoměny bývají založeny na padajícím nebo stoupajícím trhu. Kámen úrazu nastává, když jsou aplikovány na špatný trend v tak nestabilním trhu, jako je ten s kryptoměnami. Tato práce se zabývá možností adaptivních obchodních strategií, které se dokáží přizpůsobit na klesající a stoupající trendy v kryptoměnovém trhu. Analyzováním ceny Bitcoinu a vytvořením metriky risku, kde se díváme na extrémy vytvořené funkce, můžeme dojít k řešení návrhu adaptivních strategií. Zkoumají se jak dlouhodobé, tak krátkodobé možnosti investování. K vyhodnocování strategií a vykreslování časových řad je vytvořen rozšířitelný program pro testování historických dat. Výsledky jsou porovnány s tradičními přístupy, jako je HODL a rebalancování, přičemž bylo zjištěno, že při použití správných kritérií se mohou více než ztrojnásobit. Práce nabízí investorům nové způsoby zisků a zároveň dává čtenářům možnost nahlédnout do tvorby (adaptivních) strategií a jejich zpětného testování v kódu. Předpokládá se, že výsledky práce budou využívány automatizovanými obchodními systémy.
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Trading with Equity CFDs
Zach, Jiří ; Bizoň, Jaromír (referee) ; Budík, Jan (advisor)
The aim of this thesis is to design an investment strategy focused on tool called CFD. The first theoretical part contains basic information about financial derivates and explains basic principles of trading on stock market with contracts for difference. Chapter of the investment analysis explains the methods and rules used in trading. The practical part presents the results of my trading CFDs and evaluated my proposed strategy along with the benefits of work.
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Implementation of effective E-shopping
Moravec, Michal ; Holubář, Jiří (referee) ; Kříž, Jiří (advisor)
The bachelor thesis analyses implementation of effective e-shopping for customers on internet and application the newest trend to e-commerce system for the company. The object of this business work is new modern e-commerce system which bring comfort to customers and shop owner too. And the product of this work is new system and new advertisement and marketing project to do the company well-known. We will get more customers and more orders in our e-commerce.
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Fundamental Analysis of Numerical Data for Automatic Trading
Huf, Petr ; Szőke, Igor (referee) ; Černocký, Jan (advisor)
This thesis is aimed to exploitation of fundamental analysis in automatic trading. Technical analysis uses historical prices and indicators derived from price for price prediction. On the opposite, fundamental analysis uses various information resources for price prediction. In this thesis, only quantitative data are used. These data sources are namely weather, Forex, Google Trends, WikiTrends, historical prices of futures and some fundamental data (birth rate, migration, \dots). These data are processed with LSTM neural network, which predicts stocks prices of selected companies. This prediction is basis for created trading system. Experiments show major improvement in results of the trading system; 8\% increase in success prediction accuracy thanks to involvement of fundamental analysis.
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