Experts or Charlatans? ICO Analysts and White Paper Informativeness

Abstract

White papers are likely the primary source of information provided to potential Initial Coin Offering (ICO) investors in platform-based ventures that may reduce information asymmetry between ICO issuers and investors. We use textual analysis to measure the information content of white paper documents. We examine how an informative white paper content signal and a concurrent potentially biased expert rating signal correlate with measures of ICO funding success, ICO underpricing, and post-ICO performance. Our empirical results suggest that high-quality ICO issuers signal their type by providing more informative white paper content, i.e., excess or new textual information not contained in recent and peer white papers. However, investors rely on the expert ratings signal in their decision to buy tokens that "jams" the white paper informative content signal. Once listed tokens receive a market valuation, white paper informative content is positively associated with our measures for underpricing, returns, and liquidity, while the expert ratings signal is rendered irrelevant.

Keywords: Initial coin offerings, white paper, textual analysis, information content, signaling, expert ratings, platform economy

JEL Classification: G30, M13, O16, K29, K40