The Pricing and Performance of Cryptocurrency

Abstract

This paper examines the performance of cryptocurrencies issued in initial coin offerings (ICOs) over a three-year period after the initial exchange listing. Average (median) ICO underpricing amounts to 15% (3%), even though 4 out of 10 ICOs destroy value on the first trading day. Liquidity, market capitalization, and high-low price ratios predict returns. Long-run buy-and-hold returns are positive for the mean and negative for the median. For holding periods between one and twenty-four months, the median ICO depreciates by 30%. Evidently, there is substantial positive skewness in the cryptocurrency market. Further, a size effect emerges from the data as an empirical regularity: Large ICOs are more often overpriced and underperform in the long run.

Keywords:

• Initial coin offering
• token sale
• token offering
• cryptocurrency
• blockchain
• smart contracts

JEL classifications:

• G24
• G32
• K22
• L26

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1 See, for a recent study on the role of venture capital funds in ICOs, Fisch and Momtaz (2019).

2 A number of additional studies looks at the valuation of tokens (Catalini and Gans 2017, 2018; Felix 2018). Others focus on specific aspects of cryptocurrency trading such as the amount of speculation, among many others (Dwyer 2015; Yelowitz and Wilson 2015; Athey et al. 2016; Ciaian, Rajcaniova, and Kancs 2016; Athey, Catalini, and Tucker 2017). A number of studies looks at specific success determinants in ICOs such as CEO loyalty (Momtaz 2018d), emotions (Momtaz 2018a), and trust (Rhue 2018). Yermack (2017) provides a thorough discussion of the corporate governance implications of blockchain technology, and Cong and He (2018) look also at blockchain technology and smart contracts. Li and Mann (2018) develop a theory of ICOs and platform building.

3 Many of the existing studies are limited in that they examine small samples that reflect only a small portion of all ICOs. A comprehensive overview of the ICO market is presented in Momtaz, Rennertseder, and Schroeder (2019).

4 See Momtaz (2019) for a comprehensive introduction to ICOs.

5 Tokens can be classified into three types: 1. Cryptocurrencies are general medium of exchanges such as Bitcoin. 2. Security tokens are equity shares and hence subject to securities regulation. 3. Utility tokens represent by far the greatest share of all issued tokens and are essentially vouchers that can be redeemed for an ICO project's products and services once developed.

6 Momtaz (2018c) and Drobetz, Momtaz, and Schroeder (2019) illustrate the ICO market evolution also in terms of market volume and liquidity.

7 See, for a recent discussion of the computation of abnormal returns in applied finance, Melia, Song, and Tippett (2019). Also, note that market-adjusted BHR, as computed here, may perform better than those estimated from an OLS market model when dealing with ‘thin markets’ (Dissanaike et al. 2018; Drobetz and Momtaz 2019). Some cryptocurrency clearly trade in thin markets.

8 A significant limitation of the coinmarketcap data is, however, that it does not provide fundamental data on the tokens such as the proportion of tokens held by the issuing entity or the number of platform adopters. Moreover, the overlap with other data sources that provide fundamental data is very limited (e.g. there is an overlap of only 20% with ICObench), and hence restricts the possible scope of this study.

9 It is noteworthy that first-day returns reflect the returns on the first-day a cryptocurrency is tracked in the Coinmarketcap database, but this does not necessarily reflect the first day of trading. I thank one of the anonymous referees for pointing this out. However, Coinmarketcap covers all major token exchanges and hence the first day of trading should correspond in most of the cases to the first day a token is tracked on Coinmarketcap.

10 The long-run returns are not driven by a very few coins. For example, more than 40% of all sample coins have long-run returns >100% over an investment horizon of three years.

11 I also adjust BHAR using an equal-weighted market benchmark. This results, however, in very inconsistent estimates given that some digital currencies had daily returns exceeding 300% at some days.

12 Interestingly, the high-low ratios are not indicative of underlying ICO project quality, as discussed below. The high-low ratio outperformers on their first trading day become underperformers in the long run (see next subsection). I also observe significant differences between portfolios based on volatility. High-volatility ICOs have higher first-day returns. For example, the Q4-portfolio creates 8.7% more value on the first trading day than the Q1-portfolio. When we compare the pooled portfolio of Q3 and Q4 to the pooled portfolio of Q1 and Q2, we see a much more pronounced and highly significant difference of 16.2%. These results are untabulated but available upon request.

13 Portfolios based on realized variance are evidence of returns increasing in risk. However, the results are weaker with increasing holding periods. Given the sharp increase in the Sharpe Ratios reported above, this evidence is expected.

Additional information

Funding

I gratefully acknowledge financial support for this research project from the Price Center for Entrepreneurship and Innovation at UCLA.