The Algorithm for Comparative Analysis of Spatio-Temporal Characteristics of Cryptocurrency Assets
Chernova N. L., Serhiienko O. A., Volkodav V. Y.

Chernova, Natalia L., Serhiienko, Olena A., and Volkodav, Vladyslav Yu. (2023) “The Algorithm for Comparative Analysis of Spatio-Temporal Characteristics of Cryptocurrency Assets.” The Problems of Economy 4:226–233.
https://doi.org/10.32983/2222-0712-2023-4-226-233

Section: Mathematical methods and models in economy

UDC 336.7,330.4

Abstract:
The current stage of development of the cryptocurrency market is characterized by a number of structural properties and transformations that cause increased interest in cryptocurrency as a means of payment. This payment option allows you to speed up the money transfer operations, requires significantly lower commissions, is not tied to time intervals, effectively solves the problem of settlements with foreign partners in any currencies, and overcomes inflationary risk. The presence of these advantages determines the relevance of studying the cryptocurrency market in order to determine the prospects for improving the modern practice of non-cash electronic payments in Ukraine, which, in turn, will contribute to increasing the level of competitiveness of domestic enterprises. The aim of the publication is to build and implement an algorithm for comparative analysis of the spatio-temporal characteristics of cryptocurrency assets, the use of which will allow to make a reasonable choice of cryptocurrency as a non-cash means of payment. This algorithm contains the following main steps: analysis of the current state and main trends in the development of the cryptocurrency market; determination of a set of basic characteristics with the help of which it is possible to describe cryptocurrency as an object in a multidimensional statistical space; classification of cryptocurrency assets; development of recommendations for the final choice of cryptocurrency as a means of non-cash payments. A comparative analysis of cryptocurrencies is carried out by indicators of risk, profitability, and market capitalization. Classification and ordering of objects in the multidimensional feature space are carried out using cluster analysis algorithms. The structure of the system of cryptocurrency objects in multidimensional space is preliminarily analyzed using agglomerative methods, then a reasonable decision is made on the optimal number of clusters and an iterative clustering algorithm is applied. A division of cryptocurrency objects into four consecutive periods has been obtained, the stability of the composition and structure of the resulting groups in dynamics has been studied. As a result, groups whose characteristics are acceptable from the point of view of the ultimate goal of the study are identified. Within these groups, the cryptocurrencies that can be used for non-cash payments have been identified.

Keywords: cryptocurrency, risk, profitability, market capitalization, multidimensional space, measure of distance, cluster, means of payment.

Fig.: 4. Tabl.: 3. Bibl.: 12.

Chernova Natalia L. – Candidate of Sciences (Economics), Associate Professor, Associate Professor, Department of Software Engineering and Intelligent Control Technologies, National Technical University «Kharkiv Polytechnic Institute» (2 Kyrpychova Str., Kharkіv, 61002, Ukraine)
Email: natacherchum@gmail.com
Serhiienko Olena A. – Doctor of Sciences (Economics), Professor, Professor, Department of Entrepreneurship, Trade and Logistics, National Technical University «Kharkiv Polytechnic Institute» (2 Kyrpychova Str., Kharkіv, 61002, Ukraine)
Email: Elena.Sergienko@khpi.edu.ua
Volkodav Vladyslav Yu. – Postgraduate Student, Department of Entrepreneurship, Trade and Logistics, National Technical University «Kharkiv Polytechnic Institute» (2 Kyrpychova Str., Kharkіv, 61002, Ukraine)
Email: Vladyslav.Volkodav@emmb.khpi.edu.ua

List of references in article

Coinbase. https://www.coinbase.com/
Tradingview. https://www.tradingview.com/markets/cryptocurrencies/
Derzhavna podatkova sluzhba Ukrainy. https://zp.tax.gov.ua/media-ark/news-ark/print-410954.html
“Kryptovaliuta ta svitovyi biznes: khto vzhe pochav vykorystovuvaty tokeny dlia rozrakhunku“ [Cryptocurrency and Global Business: Who Has Already Started Using Tokens for Settlement]. https://rubryka.com/2023/04/25/kryptovalyuta-ta-svitovyj-bizne/
“Top 10 Crypto-Friendly Countries“. https://sanctionscanner.com/blog/top-10-crypto-friendly-countries-787
Lisnichuk, O., and Boiaryn, Yu. “Perevahy ta nedoliky vykorystannia kryptovaliuty na pidpryiemstvakh: suchasnyi dosvid ta perspektyvy rozvytku“ [Advantages and Disadvantages of Using Cryptocurrency in Enterprises: Modern Experience and Prospects for Development]. Stalyi rozvytok ekonomiky. 2019. https://economdevelopment.in.ua/index.php/journal/article/view/57
Ivashchenko, A. I. “Using Cryptocurrency in the Activities of Ukrainian Small and Medium Enterprises in order to Improve their Investment Attractiveness“. Problemi ekonomiki, no. 3 (2016): 267-273.
“Ankur Grover Integrating cryptocurrency payments: A comprehensive guide for businesses“. The Economic Times. https://economictimes.indiatimes.com/markets/cryptocurrency/integrating-cryptocurrency-payments-a-comprehensive-guide-for-businesses/articleshow/104036406.cms?from=mdr
Uzialko, A. “What small businesses should know about cryptocurrency“. Business News Daily. https://www.businessnewsdaily.com/6181-bitcoin-for-small-business.html
Phu, Dao-Le Flecher, Nirjhar, Nigam, and Sondes, Mbarek. “Current trends in accounting for digital/cryptoassets: an empirical analysis of accounting practices from UK, US, Canada and Europe“. BAR Special Issue - Paper Development Workshop on Blockchain: Impact on Accounting and Accountants. The British Accounting Review, 2023.
Yahoo Finance. https://finance.yahoo.com/
Barchart. https://www.barchart.com/