Abstract
Blockchain-based fundraising transforms the way issuers raise capital from the public, promising to reduce transaction costs, expand financial access, and reshape issuer-investor interactions. Despite these promises, the blockchain finance market is currently plagued by severe asymmetric information and is rife with fraudulent and low-quality issuers who exploit this friction. This chapter explores the reasons for the severe asymmetric information in this market and discusses the extent to which signaling and analysts can address it. It suggests that the effectiveness of signaling is limited due to the low costs of producing and disseminating signals and investors' inability to verify biased signals ex ante and punish biased signals ex post. These limitations make analysts a vital source for reducing asymmetric information but they, too, appear to suffer from significant problems - ranging from conflicts of interest to lack of transparency to low competence and expertise - which hinder their effectiveness in reducing asymmetric information. The chapter concludes with the policy implications arising from these observations, which can also guide policy-makers in addressing emerging blockchain-based fundraising mechanisms, such as non-fungible token (NFT) offerings.
| Original language | English |
|---|---|
| Title of host publication | The Cambridge Handbook of Law and Policy for NFTs |
| Publisher | Cambridge University Press |
| Pages | 161-178 |
| Number of pages | 18 |
| ISBN (Electronic) | 9781009279215 |
| ISBN (Print) | 9781009279178 |
| DOIs | |
| State | Published - 17 Oct 2024 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© Cambridge University Press & Assessment 2024. All rights reserved.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
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SDG 10 Reduced Inequalities
Keywords
- Blockchain
- Cryptoassets
- Fundraising
- ICOs
- INO
- NFT offerings
- NFTs
- Securities regulation
ASJC Scopus subject areas
- General Social Sciences
- General Computer Science
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