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The rise and fall of cryptocurrency coins and tokens

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Abstract

Since Bitcoin’s introduction in 2009, interest in cryptocurrencies has soared. One manifestation of this interest has been the explosion of newly created coins and tokens. In this paper, we analyze the dynamics of this burgeoning industry. We consider both cryptocurrency coins and tokens. The paper examines the dynamics of coin and token creation, competition and destruction in the cryptocurrency industry. In order to conduct the analysis, we develop a methodology to identify peaks in prices and trade volume, as well as when coins and tokens are abandoned and subsequently “resurrected”. We also study trading activity. Our data spans more than 4 years: there are 1082 coins and 725 tokens in the data. While there are some similarities between coins and tokens regarding dynamics, there are some striking differences as well. Overall, we find that 44% of publicly-traded coins are abandoned, at least temporarily. 71% of abandoned coins are later resurrected, leaving 18% of coins to fail permanently. Tokens experience abandonment less frequently, with only 7% abandonment and 5% permanent token abandonment at the end of the data. Using linear regressions, we find that market variables such as the bitcoin price are not associated with the rate of introducing new coins, though they are positively associated with issuing new tokens. We find that for both coins and tokens, market variables are positively associated with resurrection. We then examine the effect that the bursting of the Bitcoin bubble in December 2017 had on the dynamics in the industry. Unlike the end of the 2013 bubble, some alternative cryptocurrencies continue to flourish after the bursting of this bubble.

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Notes

  1. Although the market capitalization dropped following the last Bitcoin bubble it sits around $195 billion at the time of writing, which puts cryptocurrencies just below the market capitalization of Wells Fargo & Co.

  2. Foley et al. (2019) find that approximately one-quarter of bitcoin users are involved in illegal activity. They estimate that 46% of bitcoin transactions involve illegal activity. Based on their estimates, the illegal use of bitcoin generates approximately $76 billion of illegal activity per year. In terms of comparison, the scale of the US and European markets for illegal drugs is only slightly larger (Foley et al. 2019).

  3. Rob developed a theoretical model that shows that under uncertainty regarding the size of the market, entry will occur in waves (Rob 1991). Vettas obtained similar results in an extension of the Rob model to a setting with uncertainty on both sides of the market (Vettas 1998).

  4. For a good summary of early work, see the Audretsch and Mata (1995) on the post-entry performance of firms.

  5. See Geroski and the references cited within for a survey of the literature (Geroski 1995).

  6. For an in-depth overview of how the Bitcoin ecosystem works, see Böhme et al. (2015).

  7. This is true as long as at least one such API reports positive trade volume.

  8. This term is particularly confusing because only tokens have ICOs, not coins.

  9. For this analysis we exclude any price or volume rises from peaks occurring in the first week of a coin’s operation, as well as any falls within the last week of its operation. This is to deal with edge effects from the 7-day rolling average used to compute peaks.

  10. For this analysis we exclude any price or volume rises from peaks occurring in the first week of a coin’s operation, as well as any falls within the last week of its operation. This is to deal with edge effects from the 7-day rolling average used to compute peaks

  11. See Fig. 9 for a graphic representation of the latter correlation.

  12. Many of these trends can be seen in Fig. 12. The Bitcoin price was again included as the bottom plot of this figure because it continues to be the market leader and set the trend for other cryptocurrencies. These Bitcoin backed trends are apparent through the examination of high correlations found involving the log transformed Bitcoin price in Table 4.

  13. Tokens typically give access to a product or service. On the other hand, recent research has shown that during the period we analyze, Bitcoin is primarily used for speculative and criminal activity. Hence, it is very unlikely that tokens’ life cycle (i.e., resurrection) affects Bitcoin’s value—and thus it is reasonable to treat the BTC price as exogenous.

  14. We chose 52 day periods in order to have three periods to analyze: the rise, the fall, and the aftermath.

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Authors and Affiliations

  1. Berglas School of Economics, Tel Aviv University, Tel Aviv, Israel

    Neil Gandal

  2. Tandy School of Computer Science, The University of Tulsa, Tulsa, OK, USA

    J. T. Hamrick & Tyler Moore

  3. Department of Computer Science, University College London, London, UK

    Marie Vasek

Authors
  1. Neil Gandal
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  2. J. T. Hamrick
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  3. Tyler Moore
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  4. Marie Vasek
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Correspondence to Tyler Moore.

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We gratefully acknowledge support from the following research grants: US-Israel Binational Science Foundation Grant No. 2016622, US National Science Foundation Award No. 1714291, a Blavatnik Interdisciplinary Cyber Research Center at Tel Aviv University grant, an Intel academic grant for basic research, and a grant from the Sapir Center for Development at Tel Aviv University. We are especially grateful to the editor, Gianna Figa’ Talamanca, and two referees for comments and suggestions that significantly improved the paper. We are grateful to Hadar Fuchs and Arghya Mukherjee for their support in data collection

N. Gandal: Authors listed in alphabetical order.

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Gandal, N., Hamrick, J.T., Moore, T. et al. The rise and fall of cryptocurrency coins and tokens. Decisions Econ Finan 44, 981–1014 (2021). https://doi.org/10.1007/s10203-021-00329-8

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