Electronic Finance and Cryptocurrency Market

Abstract

In an age of rapidly changing technological revolutions, where cryptocurrencies and blockchain play key roles, studying the dynamics of cryptocurrency markets at the government level is becoming an urgent need, which is not just a step into the future, but also an opportunity for countries to act forward, based on data analysis and forecasting global economic trends. Every aspect of cryptocurrency - from financial stability to technological innovation - has the potential to transform the global landscape. Studying the interaction of cryptocurrencies with national interests will not only help to determine the positions of countries in this context, but also formulate effective strategies for managing this rapidly developing economic segment. It is important to realize that those states that integrate cryptocurrency market analysis into their strategies can best adapt to the challenges of the modern world and promote their economic prosperity. The purpose of the research is to study how the introduction of digital money into the economy affects the interest of various countries in participating in trading in the cryptocurrency market. To identify the relationship between the integration of such assets into the economy and the desire of host countries to participate in cryptocurrency markets. Consequently, there is a need to analyze the mechanisms of interaction of large economic entities - states - with cryptocurrencies, as well as predict the likely responses in this context of research. Using panel data analysis, to conduct a study of the dynamics of the cryptocurrency market in the digital finance market using the example of 50 countries around the world. To identify the relationship between the attitudes of countries and the dynamics of the cryptocurrency market in order to suggest possible directions for the future development of the studied evolutionary economic sphere. Materials and methods. As a basis for the study, a balanced and informative set of indexes (17 indexes) was identified, which represents the key variables necessary for a more in-depth analysis of the dynamics of cryptocurrency markets in the context of various countries over a period of ten years (2013-2022). The “Cryptocurrency trading volume” index was chosen as the effective index. The set of indexes was selected based on their ability to reflect cryptocurrency trading volumes, investor activity, and each country’s level of involvement in cryptocurrency transactions. The impact of various factors on the volume of transactions with electronic money and digital financial assets was assessed using panel data analysis methods in the Gretl statistical analysis program. Results. As a result of the analysis using the panel data tool, three models were created: a pooled regression model, a fixed-effects model, and a random-effects model. The choice of the best model is made through testing special hypotheses - the Brisch-Pagan test and the Hausman test. The fixed effects model was preferable to the random effects model in this study. The reason is the fixed effects model’s ability to take into account the individual characteristics of each country in the sample, leading to more accurate results. Based on the study of individual fixed effects, three groups of countries were identified: those that have a positive impact on the volume of cryptocurrency trading (for example, the United States and Japan), countries with a neutral impact (for example, Germany), and countries where individual effects have a negative impact (for example, China and Russia). Conclusion. Overall results indicate that countries with advanced digital infrastructure and ease of use of electronic payments, as well as inflationary and cultural influences, may exhibit higher activity in cryptocurrency markets. Based on the fixed effects model and taking into account assumptions about the dynamics in different countries, general conclusions were formulated regarding the index analyzed in this study - the volume of cryptocurrency trading.