An Agent-Based Artificial Market for Studying Bitcoin Trading

Summary

This paper describes an artificial cryptocurrency market designed to study Bitcoin trading. It models two heterogeneous trader groups, random traders and chartists, who submit buy and sell orders according to their strategies and available Bitcoin or fiat balances. Bitcoin supply grows over time at a rate tied to the real market, although the mining process itself is not represented.

The authors report that the simulation reproduces selected statistical features of Bitcoin absolute returns: their autocorrelation and cumulative distribution. This offers a way to explore how interactions between simple trader types can generate some observed market patterns. The model is presented as a starting point for further analysis, not a full account of cryptocurrency markets; its simplified agent types and unmodeled mining process limit how directly its behavior can be generalized to real trading conditions.

Key ideas

• The artificial market contains random traders and chartists who trade Bitcoin.
• Agents place orders subject to their strategies and available crypto or fiat resources.
• Bitcoin supply grows over time, but the simulation does not model mining explicitly.
• The model reproduces reported features of absolute returns, including autocorrelation and their cumulative distribution.
• Its simplified structure makes it a starting point for study rather than a complete market representation.

Tags

# Using an Artificial Financial Market for studying a Cryptocurrency Market


# Using an Artificial Financial Market for studying a Cryptocurrency Market









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.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.