Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/324782 
Year of Publication: 
2025
Series/Report no.: 
Staff Reports No. 1153
Publisher: 
Federal Reserve Bank of New York, New York, NY
Abstract: 
This paper investigates the speed of price discovery when information becomes publicly available but requires costly processing to become common knowledge. We exploit the unique institutional setting of hacks on decentralized finance (DeFi) protocols. Public blockchain data provides the precise time a hack's transactions are recorded - becoming public information - while subsequent social media disclosures mark the transition to common knowledge. This empirical design allows us to isolate the price impact occurring during the interval characterized by information asymmetry driven purely by differential processing capabilities. Our central empirical finding is that substantial price discovery precedes common knowledge: approximately 36 percent of the total 24-hour price decline (∼27 percent) materializes before the public announcement. This evidence suggests sophisticated traders rapidly exploit their ability to process complex, publicly available on-chain data, capturing informational rents. We develop a theoretical model of informed trading under processing costs which predicts strategic, slow information revelation, consistent with our empirical findings. Our results quantify the limits imposed by information processing costs on market efficiency, demonstrating that transparency alone does not guarantee immediate information incorporation into prices.
Subjects: 
information asymmetry
price discovery
common knowledge
information processing costs
market microstructure
event study
high-frequency data
cryptocurrency
defi
cybersecurity hacks
market efficiency
JEL: 
G12
G14
G18
G23
L86
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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