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On- and Off-Chain Demand and Supply Drivers of Bitcoin Price

Pavel Ciaian et al.

Economics: The Open Access, Open Assessment E-journal2026https://doi.org/10.1515/econ-2025-0169article
ABDC B
Weight
0.50

Abstract

Around three-quarters of Bitcoin transactions occur off-chain. While most empirical studies focus exclusively on on-chain transactions, only few papers analyse off-chain transactions. The empirical evidence of Bitcoin market considering both types of trading strategies remains limited. This paper is one of the first to present an empirical analysis of both on- and off-chain demand and supply-side factors and their short- and long-run relationship with the Bitcoin price. Employing the ARDL approach with daily data from 2019 to 2024, we demonstrate a differentiated contribution of on-chain and off-chain drivers to the Bitcoin price. In the long-run, off-chain demand pressures have a significant relationship with the Bitcoin price. In the short-run, both off-chain demand and supply factors are statistically significantly related to the Bitcoin price. The relationship between blockchain transactions and the Bitcoin price is also present, albeit likely operating through a different channel than off-chain trades. These findings confirm the dual nature of the Bitcoin market, in which price movements are related to both market fundamentals and speculative considerations captured by on- and off-chain trades, respectively.

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https://doi.org/https://doi.org/10.1515/econ-2025-0169

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@article{pavel2026,
  title        = {{On- and Off-Chain Demand and Supply Drivers of Bitcoin Price}},
  author       = {Pavel Ciaian et al.},
  journal      = {Economics: The Open Access, Open Assessment E-journal},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1515/econ-2025-0169},
}

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On- and Off-Chain Demand and Supply Drivers of Bitcoin Price

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.