
doi: 10.2139/ssrn.3720758
handle: 10419/242429
Freelancing human experts play an important role in Initial Coin Offerings (ICOs). Expert ratings partially reflect the reciprocal network of ICO members and analysts. Ratings predict ICO success, but highly imperfectly so. Favorably rated ICOs tend to fail when more ratings reciprocate prior ratings. Failure despite strong ratings is also frequent when analysts have a history of optimism, and when reviews strike a particulary positive tone. These findings help illuminate the workings of ICOs for funding new ventures, and the rich data and the specific institutional setup also yield insights pertinent to the literature on equity analysts and rating agencies.
FinTech, D82, Analysts, D83, L26, ddc:330, G24, G14, Initial Coin Offering (ICO), Asymmetric Information
FinTech, D82, Analysts, D83, L26, ddc:330, G24, G14, Initial Coin Offering (ICO), Asymmetric Information
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
