Modeling and Simulation of the Economics of Mining in the Bitcoin Market

TL;DR

This paper develops an agent-based model to simulate the Bitcoin mining economy, capturing key market behaviors and hardware evolution effects, including price dynamics and energy costs.

Contribution

It introduces a novel agent-based simulation of Bitcoin mining economics, incorporating hardware generations and reproducing key market phenomena.

Findings

Reproduces Bitcoin price stylized facts like fat tails and volatility clustering.

Models the impact of hardware evolution on mining costs and energy consumption.

Simulates historical Bitcoin price peaks and hardware-related economic factors.

Abstract

In January 3, 2009, Satoshi Nakamoto gave rise to the "Bitcoin Block Chain" creating the first block of the chain hashing on his computers central processing unit (CPU). Since then, the hash calculations to mine Bitcoin have been getting more and more complex, and consequently the mining hardware evolved to adapt to this increasing difficulty. Three generations of mining hardware have followed the CPU's generation. They are GPU's, FPGA's and ASIC's generations. This work presents an agent based artificial market model of the Bitcoin mining process and of the Bitcoin transactions. The goal of this work is to model the economy of the mining process, starting from GPU's generation, the first with economic significance. The model reproduces some "stylized facts" found in real time price series and some core aspects of the mining business. In particular, the computational experiments performed are able to reproduce the unit root property, the fat tail phenomenon and the volatility clustering of Bitcoin price series. In addition, under proper assumptions, they are able to reproduce the price peak at the end of November 2013, its next fall in April 2014, the generation of Bitcoins, the hashing capability, the power consumption, and the mining hardware and electrical energy expenses of the Bitcoin network.