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

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  • Luisanna Cocco
  • Michele Marchesi

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.

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  • Luisanna Cocco & Michele Marchesi, 2016. "Modeling and Simulation of the Economics of Mining in the Bitcoin Market," Papers 1605.01354, arXiv.org.
  • Handle: RePEc:arx:papers:1605.01354
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    Cited by:

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    2. Pavel Ciaian & d'Artis Kancs & Miroslava Rajcaniova, 2021. "Interdependencies between Mining Costs, Mining Rewards and Blockchain Security," Annals of Economics and Finance, Society for AEF, vol. 22(1), pages 25-62, May.
    3. Hector F. Calvo-Pardo & Tullio Mancini & Jose Olmo, 2022. "Machine Learning the Carbon Footprint of Bitcoin Mining," JRFM, MDPI, vol. 15(2), pages 1-30, February.
    4. Gabriel Mathy, 2023. "Eliminating Environmental Costs to Proof-of-Work-Based Cryptocurrencies: A Proposal," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 49(2), pages 206-220, April.
    5. E. Nadyrova & Е. Надырова, 2018. "Анализ рисков криптовалют и способы их минимизации в современных рыночных условиях // Analysis of Cryptocurrency Risks and Methods of their Mitigation in Contemporary Market Conditions," Review of Business and Economics Studies // Review of Business and Economics Studies, Финансовый Университет // Financial University, vol. 6(3), pages 65-78.
    6. Rico-Peña, Juan Jesús & Arguedas-Sanz, Raquel & López-Martin, Carmen, 2023. "Models used to characterise blockchain features. A systematic literature review and bibliometric analysis," Technovation, Elsevier, vol. 123(C).
    7. Luisanna Cocco & Andrea Pinna & Michele Marchesi, 2017. "Banking on Blockchain: Costs Savings Thanks to the Blockchain Technology," Future Internet, MDPI, vol. 9(3), pages 1-20, June.
    8. Sharif, Arshian & Brahim, Mariem & Dogan, Eyup & Tzeremes, Panayiotis, 2023. "Analysis of the spillover effects between green economy, clean and dirty cryptocurrencies," Energy Economics, Elsevier, vol. 120(C).
    9. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    10. Delgado-Mohatar, Oscar & Felis-Rota, Marta & Fernández-Herraiz, Carlos, 2019. "The Bitcoin mining breakdown: Is mining still profitable?," Economics Letters, Elsevier, vol. 184(C).
    11. Luisanna Cocco & Roberto Tonelli & Michele Marchesi, 2019. "An Agent Based Model to Analyze the Bitcoin Mining Activity and a Comparison with the Gold Mining Industry," Future Internet, MDPI, vol. 11(1), pages 1-12, January.
    12. Marten Risius & Kai Spohrer, 2017. "A Blockchain Research Framework," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 59(6), pages 385-409, December.
    13. Ahmed Ibrahim & Rasha Kashef & Menglu Li & Esteban Valencia & Eric Huang, 2020. "Bitcoin Network Mechanics: Forecasting the BTC Closing Price Using Vector Auto-Regression Models Based on Endogenous and Exogenous Feature Variables," JRFM, MDPI, vol. 13(9), pages 1-21, August.
    14. Malfuzi, A. & Mehr, A.S. & Rosen, Marc A. & Alharthi, M. & Kurilova, A.A., 2020. "Economic viability of bitcoin mining using a renewable-based SOFC power system to supply the electrical power demand," Energy, Elsevier, vol. 203(C).
    15. Zura Kakushadze & Jim Kyung-Soo Liew, 2018. "CryptoRuble: From Russia with Love," Papers 1801.05760, arXiv.org.
    16. Francisco Javier García-Corral & José Antonio Cordero-García & Jaime de Pablo-Valenciano & Juan Uribe-Toril, 2022. "A bibliometric review of cryptocurrencies: how have they grown?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.

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