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Factor models of cryptocurrency profitability

Authors: Sinelnikova-Muryleva, Elena V.; Kuznetsova, Maria N.; Shilov, Kirill D.;

Factor models of cryptocurrency profitability

Abstract

More than 12 years have passed since the debut of Bitcoin, the first cryptocurrency, but there is still no clear understanding of the essence of cryptocurrencies. At the same time, in recent years, interest in cryptocurrencies has continued to grow, and this financial instrument is becoming more and more attractive to individuals. Therefore, an issue of essence of cryptocurrencies is relevant. The main subject of the study is the profitability of cryptocurrencies. The main aim of this work is to identify the determinants of cryptocurrency returns. To achieve this goal, such tasks as the creation of factors reflecting the characteristics of the cryptocurrency market and the use of multifactor Fama-French models for the analysis of cryptocurrency returns were performed. Based on the collected daily data on capitalization, trading volumes and the price of more than 5,000 cryptocurrencies for the period from 01.04.2014 to 21.06.2021, standard factors based on capitalization indicators, trading volumes and the third momentum were built. The main estimation method is econometric modeling using the least squares method. The obtained results of an empirical study indicate a positive relationship between the profitability of groups of cryptocurrencies and the difference in the yields of the upper and lower 30% of cryptocurrencies according to the third moment. The difference in the yields of the lower and upper 30% of cryptocurrencies by market capitalization has a negative impact on the profitability of groups of cryptocurrencies. The main conclusion of the study is that before the beginning of high volatility period, cryptocurrencies could be considered as an asset for the diversification of market risk, but subsequently the cryptocurrency market began to move co-directionally to the stock market. The scientific novelty of the work stems from presenting an assessment of the impact of modeled factors on various groups (portfolios) of cryptocurrencies over certain periods of time. The study recommends to conduct further analysis of the profitability factors of cryptocurrencies on more homogeneous samples.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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