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A Mean Field Game Approach to Bitcoin Mining

  • Institut Louis Bachelier
  • Université Paris Dauphine
  • Collège de France

Research output: Contribution to journalArticlepeer-review

Abstract

We present an analysis of the Proof-of-Work consensus algorithm, used on the Bitcoin blockchain, using a mean field game framework. Using a master equation, we provide an equilibrium characterization of the total computational power devoted to mining the blockchain (hashrate). This class of models allows us to adapt to many different situations. The essential structure of the game is preserved across all the enrichments. In deterministic settings, the hashrate ultimately reaches a steady state in which it increases at the rate of technological progress only. In stochastic settings, there exists a target for the hashrate for every possible random state. As a consequence, we show that in equilibrium the security of the underlying blockchain and the energy consumption either are constant or increase with the price of the underlying cryptocurrency.

Original languageEnglish
Pages (from-to)960-987
Number of pages28
JournalSIAM Journal on Financial Mathematics
Volume15
Issue number3
DOIs
Publication statusPublished - 1 Jan 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • bitcoin mining
  • blockchain
  • mean field games

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