Quantitative analysis of cryptocurrencies transaction graph

Amir Pasha Motamed,Behnam Bahrak

doi:10.1007/s41109-019-0249-6

Abstract

Cryptocurrencies as a new way of transferring assets and securing financial transactions have gained popularity in recent years. Transactions in cryptocurrencies are publicly available, hence, statistical studies on different aspects of these currencies are possible. However, previous statistical analysis on cryptocurrencies transactions have been very limited and mostly devoted to Bitcoin, with no comprehensive comparison between these currencies. In this study, we intend to compare the transaction graph of Bitcoin, Ethereum, Litecoin, Dash, and Z-Cash, with respect to the dynamics of their transaction graphs over time, and discuss their properties. In particular, we observed that the growth rate of the nodes and edges of the transaction graphs, and the density of these graphs, are closely related to the price of these currencies. We also found that the transaction graph of these currencies is non-assortative, i.e. addresses do not tend for transact with a particular type of addresses of higher or lower degree, and the degree sequence of their transaction graph follows the power law distribution.

Highlights

Cryptocurrencies have made it possible for a financial system to perform transactions without the need for a centralized authority while keeping the transaction details and money generation clear and publicly available
The graph’s size is closely related to the price in terms of the number of edges and vertices, and when Bitcoin’s price reached 20, 000$ in late 2017 and a peak appeared in its price chart, we can observe a peak in the Monthly Transaction Graph (MTG) size for all five coins
We examined how the cryptocurrencies transaction graphs evolve over time and discussed their dynamics

Summary

Introduction

Cryptocurrencies have made it possible for a financial system to perform transactions without the need for a centralized authority while keeping the transaction details and money generation clear and publicly available. Despite this transparency, people’s identities are hidden, and they can transact anonymously. The system is running by anonymous people, due to computational infeasibility of forging digital signatures and security of cryptography algorithms, transaction alteration is almost impossible This level of security is guaranteed by cryptographic algorithms, and as long as these algorithms are secure, cryptocurrencies integrity is protected

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Conclusion