  The world economy is experiencing the novel adoption of distributed
currencies that are free from the control of central banks. Distributed
currencies suffer from extreme volatility, and this can lead to catastrophic
implications during future economic crisis. Understanding the dynamics of this
new type of currencies is vital for empowering supervisory bodies from current
reactive and manual incident responders to more proactive and well-informed
planners. Bitcoin, the first and dominant distributed cryptocurrency, is still
notoriously vague, especially for a financial instrument with market value
exceeding 1 trillion. Modeling of bitcoin overlay network poses a number of
important theoretical and methodological challenges. Current measuring
approaches, for example, fail to identify the real network size of bitcoin
miners. This drastically undermines the ability to predict forks, the suitable
mining difficulty and most importantly the resilience of the network supporting
bitcoin. In this work, we developed Evolutionary Random Graph, a theoretical
model that describes the network of bitcoin miners. The correctness of this
model has been validated using simulated and measure real bitcoin data. We then
predicted forking, optimal mining difficulty, network size and consequently the
network's inability to stand a drastic drop in bitcoin price using the current
mining configuration.
