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A Mean Field Games Model for Cryptocurrency Mining

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  • Zongxi Li
  • A. Max Reppen
  • Ronnie Sircar

Abstract

We propose a mean field game model to study the question of how centralization of reward and computational power occur in Bitcoin-like cryptocurrencies. Miners compete against each other for mining rewards by increasing their computational power. This leads to a novel mean field game of jump intensity control, which we solve explicitly for miners maximizing exponential utility, and handle numerically in the case of miners with power utilities. We show that the heterogeneity of their initial wealth distribution leads to greater imbalance of the reward distribution, and increased wealth heterogeneity over time, or a "rich get richer" effect. This concentration phenomenon is aggravated by a higher bitcoin mining reward, and reduced by competition. Additionally, an advantaged miner with cost advantages such as access to cheaper electricity, contributes a significant amount of computational power in equilibrium, unaffected by competition from less efficient miners. Hence, cost efficiency can also result in the type of centralization seen among miners of cryptocurrencies.

Suggested Citation

  • Zongxi Li & A. Max Reppen & Ronnie Sircar, 2019. "A Mean Field Games Model for Cryptocurrency Mining," Papers 1912.01952, arXiv.org, revised Jan 2022.
  • Handle: RePEc:arx:papers:1912.01952
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    References listed on IDEAS

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    1. Lin William Cong & Zhiguo He, 2019. "Blockchain Disruption and Smart Contracts," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1754-1797.
    2. Guillermo Gallego & Garrett van Ryzin, 1997. "A Multiproduct Dynamic Pricing Problem and Its Applications to Network Yield Management," Operations Research, INFORMS, vol. 45(1), pages 24-41, February.
    3. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
    4. Lin William Cong & Zhiguo He & Jiasun Li & Wei Jiang, 2021. "Decentralized Mining in Centralized Pools [Concentrating on the fall of the labor share]," The Review of Financial Studies, Society for Financial Studies, vol. 34(3), pages 1191-1235.
    5. Olivier Guéant & Pierre Louis Lions & Jean-Michel Lasry, 2011. "Mean Field Games and Applications," Post-Print hal-01393103, HAL.
    6. Arrow, Kenneth J. & Chang, Sheldon, 1982. "Optimal pricing, use, and exploration of uncertain natural resource stocks," Journal of Environmental Economics and Management, Elsevier, vol. 9(1), pages 1-10, March.
    7. Bruno Biais & Christophe Bisière & Matthieu Bouvard & Catherine Casamatta, 2019. "The Blockchain Folk Theorem," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1662-1715.
    8. Lode Li, 1988. "A Stochastic Theory of the Firm," Mathematics of Operations Research, INFORMS, vol. 13(3), pages 447-466, August.
    9. Deshmukh, Sudhakar D & Pliska, Stanley R, 1980. "Optimal Consumption and Exploration of Nonrenewable Resources under Uncertainty," Econometrica, Econometric Society, vol. 48(1), pages 177-200, January.
    10. Guillermo Gallego & Ming Hu, 2014. "Dynamic Pricing of Perishable Assets Under Competition," Management Science, INFORMS, vol. 60(5), pages 1241-1259, May.
    11. Easley, David & O'Hara, Maureen & Basu, Soumya, 2019. "From mining to markets: The evolution of bitcoin transaction fees," Journal of Financial Economics, Elsevier, vol. 134(1), pages 91-109.
    12. Barabási, A.L & Jeong, H & Néda, Z & Ravasz, E & Schubert, A & Vicsek, T, 2002. "Evolution of the social network of scientific collaborations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 311(3), pages 590-614.
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    Cited by:

    1. Charles Bertucci & Louis Bertucci & Jean-Michel Lasry & Pierre-Louis Lions, 2020. "Mean Field Game Approach to Bitcoin Mining," Papers 2004.08167, arXiv.org.
    2. Rene Carmona, 2020. "Applications of Mean Field Games in Financial Engineering and Economic Theory," Papers 2012.05237, arXiv.org.
    3. Hansjörg Albrecher & Dina Finger & Pierre-Olivier Goffard, 2022. "Blockchain mining in pools: Analyzing the trade-off between profitability and ruin," Working Papers hal-03336851, HAL.

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