Cryptocurrency in the System of Money Laundering

Dyntu, Valeriia; Dykyi, Oleh

doi:10.30525/2256-0742/2018-4-5-75-81

Cited by 43 publications

(37 citation statements)

References 5 publications

(5 reference statements)

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“…A cryptocurrency user can have more than one account and perform transactions from different locations at the same time. Contrary to the above views [10], other findings of [11] show that cryptocurrencies do not behave like traditional currencies or commodities and represent a sector that is much more advanced and less speculative.…”

Section: Introductionmentioning

confidence: 65%

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Specifics of Cryptocurrencies from an Accounting, Tax and Financial View in a Globalized Environment

2021

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Research background: With the advancing entrance of digital technologies into all areas of private and business life in the past 10 years a new digital asset referred to as virtual currency or cryptocurrency had been invented. This virtual currency is not yet regulated in most countries and there is a need to establish a legal framework for accounting, taxation and recording of financial transactions so the treatment of transactions with these digital assets is the same across the globalized environment, as different approaches may affect the decision-making of the management and investors or can alter the tax base for income tax purposes. Purpose of the article: The aim of this paper is to compare and discuss the different possible approaches of recording and reporting of the virtual currencies for accounting and tax purposes and to compare the approaches among the Czech Republic, the Slovak Republic and Germany to point out the need for a harmonized solution in a global environment, as dealing with cryptocurrencies is not included in the accounting and tax legal framework in many other countries. Methods: Methods of description, analysis, comparison and synthesis are used to achieve the set aim of the paper. Different approaches to the topic are demonstrated and compared in illustrative Tables. Findings & Value added: The paper highlights the need for a uniform approach for the accounting and tax treatment of virtual currency by comparing the level of legal definitions and different approaches. The most elaborate legal implementation of this topic is in the Slovak Republic where the treatment of virtual currencies is included in the Accounting Act and the Income Tax Act. The Czech Republic approaches cryptocurrencies only on the basis of recommendations from the Ministry of Finance, which is not legally binding to obey. Germany has included cryptocurrencies in the Banking Act, the accounting definition is missing and the tax solution is in the Income Tax Act.

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Section: Introductionmentioning

confidence: 65%

“…Cryptocurrencies involved in the money laundering process is dealt with by [10]. The results of the study showed that cryptocurrency is a suitable tool for money laundering because it provides the currency owner with relative anonymity because it does not require any personal information about the user and his location.…”

Section: Introductionmentioning

confidence: 99%

Specifics of Cryptocurrencies from an Accounting, Tax and Financial View in a Globalized Environment

2021

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“…Bitcoin allows for various money laundering schemes, which virtually blocks the possibility of identifying criminals. The mentioned characteristics of the cryptocurrency encourage legislators around the world to unify the legal system for the use of cryptocurrency as a means of payment [8].…”

Section: Resultsmentioning

confidence: 99%

Cryptocurrencies in the global space: factors and prospects of promotion

et al. 2019

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The article considers the place of cryptocurrency markets in the global economy. The key risks of active implementation of IT achievements in the financial sector were defined. It was shown that cryptocurrencies are associated with settlement operations, investment activities and speculation in the currency markets. It was argued that the availability of equipment for the production of digital currencies, the spread of trust on the part of users and business representatives contribute to the promotion of cryptocurrencies and the penetration of digital currencies in various spheres of economic activity. The attraction of additional resources in the economy in the conditions of insignificant costs for entering the cryptocurrency market that become a factor in the spread of cryptocurrency assets was considered.

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“…The recorded prices in the dataset were collected on a daily basis from 1 January 2018 to 30 June 2021. In this research, we used time-series data from [19] with 1277 records. Table 1 illustrates the dataset specification of the targeted cryptocurrency and Figure 10 shows sample data from the dataset.…”

Section: Datasetmentioning

confidence: 99%

“…There is evidence that the usefulness of different information sets varies between machine learning algorithms, implying that prediction is likely to be much more complicated when a set of machine learning algorithms is used [18]. Despite the widespread use of cryptocurrencies for various types of purchases and transactions around the world, there is no consistent opinion on the definition of cryptocurrency or its legal status [19]. Furthermore, the aforementioned situation exacerbates challenges in criminal investigations of cryptocurrency-based money laundering.…”

Section: Introductionmentioning

confidence: 99%

A Novel Cryptocurrency Price Prediction Model Using GRU, LSTM and bi-LSTM Machine Learning Algorithms

Hamayel

Owda

2021

136

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Cryptocurrency is a new sort of asset that has emerged as a result of the advancement of financial technology and it has created a big opportunity for researches. Cryptocurrency price forecasting is difficult due to price volatility and dynamism. Around the world, there are hundreds of cryptocurrencies that are used. This paper proposes three types of recurrent neural network (RNN) algorithms used to predict the prices of three types of cryptocurrencies, namely Bitcoin (BTC), Litecoin (LTC), and Ethereum (ETH). The models show excellent predictions depending on the mean absolute percentage error (MAPE). Results obtained from these models show that the gated recurrent unit (GRU) performed better in prediction for all types of cryptocurrency than the long short-term memory (LSTM) and bidirectional LSTM (bi-LSTM) models. Therefore, it can be considered the best algorithm. GRU presents the most accurate prediction for LTC with MAPE percentages of 0.2454%, 0.8267%, and 0.2116% for BTC, ETH, and LTC, respectively. The bi-LSTM algorithm presents the lowest prediction result compared with the other two algorithms as the MAPE percentages are: 5.990%, 6.85%, and 2.332% for BTC, ETH, and LTC, respectively. Overall, the prediction models in this paper represent accurate results close to the actual prices of cryptocurrencies. The importance of having these models is that they can have significant economic ramifications by helping investors and traders to pinpoint cryptocurrency sales and purchasing. As a plan for future work, a recommendation is made to investigate other factors that might affect the prices of cryptocurrency market such as social media, tweets, and trading volume.

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Cryptocurrency in the System of Money Laundering

Cited by 43 publications

References 5 publications

Specifics of Cryptocurrencies from an Accounting, Tax and Financial View in a Globalized Environment

Specifics of Cryptocurrencies from an Accounting, Tax and Financial View in a Globalized Environment

Cryptocurrencies in the global space: factors and prospects of promotion

A Novel Cryptocurrency Price Prediction Model Using GRU, LSTM and bi-LSTM Machine Learning Algorithms

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