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From code to market: Network of developers and correlated returns of cryptocurrencies

Author

Listed:
  • Lorenzo Lucchini
  • Laura Alessandretti
  • Bruno Lepri
  • Angela Gallo
  • Andrea Baronchelli

Abstract

"Code is law" is the funding principle of cryptocurrencies. The security, transferability, availability and other properties of a crypto-asset are determined by the code through which it is created. If code is open source, as it happens for most cryptocurrencies, this principle would prevent manipulations and grant transparency to users and traders. However, this approach considers cryptocurrencies as isolated entities thus neglecting possible connections between them. Here, we show that 4% of developers contribute to the code of more than one cryptocurrency and that the market reflects these cross-asset dependencies. In particular, we reveal that the first coding event linking two cryptocurrencies through a common developer leads to the synchronisation of their returns in the following months. Our results identify a clear link between the collaborative development of cryptocurrencies and their market behaviour. More broadly, our work reveals a so-far overlooked systemic dimension for the transparency of code-based ecosystems and we anticipate it will be of interest to researchers, investors and regulators.

Suggested Citation

  • Lorenzo Lucchini & Laura Alessandretti & Bruno Lepri & Angela Gallo & Andrea Baronchelli, 2020. "From code to market: Network of developers and correlated returns of cryptocurrencies," Papers 2004.07290, arXiv.org, revised Dec 2020.
    • Handle: RePEc:arx:papers:2004.07290
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    References listed on IDEAS

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    Cited by:

    1. Andrea Baronchelli, 2021. "Collective intelligence and the blockchain: Technology, communities and social experiments," Papers 2107.05527, arXiv.org.
    2. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    3. Luca Mungo & Silvia Bartolucci & Laura Alessandretti, 2023. "Cryptocurrency co-investment network: token returns reflect investment patterns," Papers 2301.02027, arXiv.org, revised Jan 2023.
    4. Jing, Ruixue & Rocha, Luis E.C., 2023. "A network-based strategy of price correlations for optimal cryptocurrency portfolios," Finance Research Letters, Elsevier, vol. 58(PC).

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