This paper presents an agent-based artificial cryptocurrency market in which heterogeneous agents buy or sell cryptocurrencies, in particular Bitcoins. It looks at using an artificial financial market. In this market, there are two typologies of agents, Random Traders and Chartists, which interact with each other by trading Bitcoins. Each agent is initially endowed with a finite amount of crypto and/or fiat cash and issues buy and sell orders, according to their strategy and resources. The number of Bitcoins increases over time with a rate proportional to the real one, even if the mining process is not explicitly modelled.

The model proposed is able to reproduce some of the real statistical properties of the price absolute returns observed in the Bitcoin real market. In particular, it is able to reproduce the autocorrelation of the absolute returns, and their cumulative distribution function. The simulator has been implemented using object-oriented technology, and could be considered a valid starting point to study and analyse the cryptocurrency market and its future evolutions. This artificial financial market can make it easy to study the cryptocurrency market as a whole.

Besides being the first model of a cryptocurrency market following the artificial financial market approach, is the fact that some key stylised facts of Bitcoin real price series are very well reproduced. The computational experiments performed produce price series for which we are unable to reject the hypothesis that they follow a random walk. The autocorrelation of raw returns is very low for all time lags, whereas the autocorrelation of absolute returns is much higher, confirming the presence of volatility clustering. To find out more, download the whitepaper.