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Quantinar: a blockchain peer-to-peer ecosystem for modern data analytics

Author

Listed:
  • Raul Bag

    (Humboldt-Universität zu Berlin
    Bucharest University of Economic Studies)

  • Bruno Spilak

    (Humboldt-Universität zu Berlin
    Bucharest University of Economic Studies)

  • Julian Winkel

    (Humboldt-Universität zu Berlin)

  • Wolfgang Karl Härdle

    (Humboldt-Universität zu Berlin
    Bucharest University of Economic Studies
    Singapore Management University
    NUS)

Abstract

The power of data and correct statistical analysis has never been more prevalent. Academics and practitioners require nowadays an accurate application of quantitative methods. Yet many branches are subject to a crisis of integrity, which is shown in an improper use of statistical models, p-hacking, HARKing, or failure to replicate results. We propose the use of a Peer-to-Peer (P2P) ecosystem based on a blockchain network, Quantinar , to support quantitative analytics knowledge paired with code in the form of Quantlets or software snippets. The integration of blockchain technology allows Quantinar to ensure fully transparent and reproducible scientific research.

Suggested Citation

  • Raul Bag & Bruno Spilak & Julian Winkel & Wolfgang Karl Härdle, 2025. "Quantinar: a blockchain peer-to-peer ecosystem for modern data analytics," Computational Statistics, Springer, vol. 40(3), pages 1361-1396, March.
    • Handle: RePEc:spr:compst:v:40:y:2025:i:3:d:10.1007_s00180-024-01529-7
    DOI: 10.1007/s00180-024-01529-7
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    References listed on IDEAS

    as
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    1. Ștefan Găman & Julian Winkel & Xiaorui Zuo & Wolfgang Karl Härdle & Daniel Traian Pele, 2026. "Quantlet: the code snippet knowledge platform," Computational Statistics, Springer, vol. 41(3), pages 1-20, April.

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