  Following the birth of Bitcoin and the introduction of the Ethereum ERC20
protocol a decade ago, recent years have witnessed a growing number of
cryptographic tokens that are being introduced by researchers, private sector
companies and NGOs. The ubiquitous of such Blockchain based cryptocurrencies
give birth to a new kind of rising economy, which presents great difficulties
to modeling its dynamics using conventional semantic properties. Our work
presents the analysis of the dynamical properties of the ERC20 protocol
compliant crypto-coins' trading data using a network theory prism. We examine
the dynamics of ERC20 based networks over time by analyzing a meta-parameter of
the network, the power of its degree distribution. Our analysis demonstrates
that this parameter can be modeled as an under-damped harmonic oscillator over
time, enabling a year forward of network parameters predictions.
