Using an Artificial Financial Market for studying a Cryptocurrency Market

TL;DR

This paper develops an agent-based artificial cryptocurrency market model with heterogeneous traders, capable of replicating key statistical properties of Bitcoin's real market, serving as a tool for future market analysis.

Contribution

It introduces a novel agent-based simulation that reproduces Bitcoin market statistics without explicit mining modeling, offering a new approach for studying cryptocurrency dynamics.

Findings

The model reproduces the autocorrelation of absolute returns.

The model matches the cumulative distribution of returns.

The simulation aligns with real Bitcoin market properties.

Abstract

This paper presents an agent-based artificial cryptocurrency market in which heterogeneous agents buy or sell cryptocurrencies, in particular Bitcoins. 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 her 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.