Pricing Data Assets Decentralized: The Brain-in-a-Vat Thought Experiment as a Framework

As data emerges as a novel factor of production, the issues of data asset ownership, valuation, and circulation have increasingly become focal points in financial research and policy-making. This paper employs the theoretical metaphor of a “brain without a vat” to map distributed cognition, information flows, and decentralized governance onto the data asset market, thereby constructing an analytical framework for decentralized data asset pricing.Drawing on on-chain transaction data from decentralized data trading platforms (e.g., Ocean Protocol, Streamr, Numerai) spanning 2019–2024, and extending the analysis with panel data from 600 firms, we test the core hypotheses through multivariate regression, event studies, and difference-in-differences/event-time designs (DID/event-time).The principal findings include: platform activity exerts a significant positive effect on the pricing efficiency of data assets; corporate application intensity likewise significantly enhances pricing efficiency; and both liquidity and governance participation positively contribute to price discovery. Event study results indicate that critical events (such as the launch of new datasets or major DAO votes) generate significant positive abnormal returns on event dates, with the conclusions remaining robust under multiple validation checks.