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FinTech a AML z právní perspektivy / FinTech and AML from a legal perspectiveZacpal, Mikuláš January 2020 (has links)
and keywords FinTech and AML from a legal perspective The subject matter of this thesis is the impact of regulations preventing money laundering and terrorism financing in the field of FinTech. The goal is to analyse these regulations and to offer a critical standpoint which would reflect the technological development in the financial sector and take into consideration the cost of adhering to these regulations. With this objective in mind, the first chapter defines the concept of FinTech, breaks down its specifics and provides typical examples of the financial services currently fitting this definition. In the second chapter, the obligations stemming from the AML/CFT rules are defined along with an evaluation of their impact on obliged persons. The current and future possibilities of remote identification which represents the simplest way of acquiring a client are further evaluated in a separate chapter. In the last part, this paper analyses the applicability of the AML/CFT Act in relation to neobanking, crowdfunding and crypto-assets. The paper concludes by summarizing the findings, formulating views on the current state of the topic, and presenting suggestions for future development. Money laundering and terrorism financing are detrimental social phenomena affecting the FinTech sector. The...
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Zdanění příjmů v souvislosti s kryptoaktivy / Income taxation related to cryptoassetsMikulecký, Kristián January 2022 (has links)
This diploma thesis deals with the legal aspects of income tax for natural and legal persons in contexts which may arise when dealing with cryptoassets of all kinds. The modern phenomenon of cryptoassets has been the subject of much discussion, especially in recent times, but legislation and comprehensive methodologies governing procedure for taxation of income are lacking. Therefore, the main objective of this thesis is to analyse income tax on cryptoassets for natural and legal persons. If we reformulate this objective into a question, it would be: How do we correctly tax income from cryptoassets for natural and legal persons? Within the framework of my thesis, I also had to deal with the technological and legal aspects of cryptoassets and taxes. The concept of a cryptoasset, including its definition and content, is still a matter of debate even now, more than 10 years after its creation. Similarly, it was necessary to analyse the Czech legislation and determine what a cryptoasset is from the point of view of Czech law within the framework of the thesis. By analysing the legislation and professional publications and using the deductive method, I came to the conclusion that the current legal framework in the Czech Republic is sufficient to answer the main question. The most frequent operations with...
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Prediktivní síla strojového učení v kryptoaktivech / Predictive Power of Machine Learning in CryptoassetsDuda, Miroslav January 2021 (has links)
The work attempts to forecast the sign of the price change for cryptoasset time series through classification. The main purpose is to find evidence concerning market efficiency of the cryptoasset markets, potential trading strategies, and differences between the modelled assets. Supporting vector machines, random forests, and multilayer perceptron models are used. An additional model aggre- gates the results of the previous three. Bitcoin, Ether, XRP, and Binance Coin are the modelled cryptoassets. The input variables include transformed daily closing prices up to five lags, trading volumes, volatility, and moving averages. Random forest models perform the best, followed by supporting vector ma- chines, and multilayer perceptrons. Aggregation does not produce improved forecasting performance. The two older assets, Bitcoin and Ethereum, are found to be less forecastable than the newer, Binance Coin and XRP. Dif- ferences between the assets exist as exhibited through forecastability. Higher classification accuracies are not found to imply better trading performance. JEL Classification C15, C69, G13, G14, G17 Keywords cryptoassets, machine learning, forecasting, cryptocurrencies Title Predictive Power of Machine Learning in Cryp- toassets
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Ekonomická analýza Bitcoinu / The Principle and Economic Analysis of BitcoinJiang, Jinggang January 2021 (has links)
The development of Internet technology has promoted the progress of all aspects of society. Under the background of Internet finance, the traditional financial model is changing, such as currency payment. With the deepening of Internet technology, the virtualization of money is deepening, and the market entry, trading and payment methods are also subverting the tradition. Bitcoin as a new means of payment began to appear in the public eye. It is a challenge to the traditional way of trading supported by Internet technology. Despite the constant controversy since its inception, Bitcoin still occupies a place with its unique advantages - Asymmetric encryption, decentralization,transparency of transaction records and so on. In the eyes of opponents, Bitcoin is more of a highly speculative asset, and as it becomes progressively more difficult to mine, the cost of mining is increasing. However, in the eyes of supporters, it is a reliable means of payment, not subject to government supervision, nor will it produce a virtual transaction record. From the regulator's point of view, it is more like a shelter for unscrupulous people to evade regulation and commit money laundering and crime. It is undeniable that in just a few years, Bitcoin has developed to a certain scale,has a certain industrial chain...
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