IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1803.03088.html
   My bibliography  Save this paper

Classification of cryptocurrency coins and tokens by the dynamics of their market capitalisations

Author

Listed:
  • Ke Wu
  • Spencer Wheatley
  • Didier Sornette

Abstract

We empirically verify that the market capitalisations of coins and tokens in the cryptocurrency universe follow power-law distributions with significantly different values, with the tail exponent falling between 0.5 and 0.7 for coins, and between 1.0 and 1.3 for tokens. We provide a rationale for this, based on a simple proportional growth with birth & death model previously employed to describe the size distribution of firms, cities, webpages, etc. We empirically validate the model and its main predictions, in terms of proportional growth (Gibrat's law) of the coins and tokens. Estimating the main parameters of the model, the theoretical predictions for the power-law exponents of coin and token distributions are in remarkable agreement with the empirical estimations, given the simplicity of the model. Our results clearly characterize coins as being "entrenched incumbents" and tokens as an "explosive immature ecosystem", largely due to massive and exuberant Initial Coin Offering activity in the token space. The theory predicts that the exponent for tokens should converge to 1 in the future, reflecting a more reasonable rate of new entrants associated with genuine technological innovations.

Suggested Citation

  • Ke Wu & Spencer Wheatley & Didier Sornette, 2018. "Classification of cryptocurrency coins and tokens by the dynamics of their market capitalisations," Papers 1803.03088, arXiv.org, revised May 2018.
    • Handle: RePEc:arx:papers:1803.03088
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1803.03088
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Malevergne, Y. & Saichev, A. & Sornette, D., 2013. "Zipf's law and maximum sustainable growth," Journal of Economic Dynamics and Control, Elsevier, vol. 37(6), pages 1195-1212.
    2. Stefan Bornholdt & Kim Sneppen, 2014. "Do Bitcoins make the world go round? On the dynamics of competing crypto-currencies," Papers 1403.6378, arXiv.org.
    3. Ladislav Kristoufek, 2015. "What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-15, April.
    4. Jonathan Chiu & Thorsten V. Koeppl, 2017. "The Economics Of Cryptocurrencies - Bitcoin And Beyond," Working Paper 1389, Economics Department, Queen's University.
    5. Pavel Ciaian & Miroslava Rajcaniova & d’Artis Kancs, 2016. "The economics of BitCoin price formation," Applied Economics, Taylor & Francis Journals, vol. 48(19), pages 1799-1815, April.
    6. Michel Rauchs & Garrick Hileman, 2017. "Global Cryptocurrency Benchmarking Study," Cambridge Centre for Alternative Finance Reports 201704-gcbs, Cambridge Centre for Alternative Finance, Cambridge Judge Business School, University of Cambridge.
    7. Jeffrey Chu & Saralees Nadarajah & Stephen Chan, 2015. "Statistical Analysis of the Exchange Rate of Bitcoin," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-27, July.
    8. Ali, Robleh & Barrdear, John & Clews, Roger & Southgate, James, 2014. "The economics of digital currencies," Bank of England Quarterly Bulletin, Bank of England, vol. 54(3), pages 276-286.
    9. repec:nas:journl:v:115:y:2018:p:1131-1134 is not listed on IDEAS
    10. D'aniel Kondor & M'arton P'osfai & Istv'an Csabai & G'abor Vattay, 2013. "Do the rich get richer? An empirical analysis of the BitCoin transaction network," Papers 1308.3892, arXiv.org, revised Mar 2014.
    11. Abeer ElBahrawy & Laura Alessandretti & Anne Kandler & Romualdo Pastor-Satorras & Andrea Baronchelli, 2017. "Evolutionary dynamics of the cryptocurrency market," Papers 1705.05334, arXiv.org, revised Nov 2017.
    12. Dániel Kondor & Márton Pósfai & István Csabai & Gábor Vattay, 2014. "Do the Rich Get Richer? An Empirical Analysis of the Bitcoin Transaction Network," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-10, February.
    13. Carey Caginalp & Gunduz Caginalp, 2018. "Valuation, Liquidity Price, and Stability of Cryptocurrencies," Papers 1802.09959, arXiv.org.
    14. Chiu, Jonathan & Koeppl, Thorsten V, 2017. "The economics of cryptocurrencies – bitcoin and beyond," Working Paper Series 6688, Victoria University of Wellington, School of Economics and Finance.
    15. Xavier Gabaix, 1999. "Zipf's Law for Cities: An Explanation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(3), pages 739-767.
    16. Spencer WHEATLEY & Didier SORNETTE, 2015. "Multiple Outlier Detection in Samples with Exponential & Pareto Tails: Redeeming the Inward Approach & Detecting Dragon Kings," Swiss Finance Institute Research Paper Series 15-28, Swiss Finance Institute.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Pawe{l} O'swik{e}cimka & Tomasz Stanisz & Marcin Wk{a}torek, 2020. "Complexity in economic and social systems: cryptocurrency market at around COVID-19," Papers 2009.10030, arXiv.org.
    2. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    3. Silky Vigg Kushwah & Shab Hundal & Payal Goel, 2024. "Unveiling Interconnectedness and Volatility Transmission: A Novel GARCH Analysis of Leading Global Cryptocurrencies," International Journal of Economics and Financial Issues, Econjournals, vol. 14(3), pages 132-139, May.
    4. Paul Gatabazi & Gaëtan Kabera & Jules Clement Mba & Edson Pindza & Sileshi Fanta Melesse, 2022. "Cryptocurrencies and Tokens Lifetime Analysis from 2009 to 2021," Economies, MDPI, vol. 10(3), pages 1-14, March.
    5. Edgardo Brigatti & Estevan Augusto Amazonas Mendes, 2021. "Testing macroecological theories in cryptocurrency market: neutral models can not describe diversity patterns and their variation," Papers 2111.02067, arXiv.org, revised Jul 2022.
    6. Didier Sornette & Spencer Wheatley & Peter Cauwels, 2019. "The Fair Reward Problem: The Illusion Of Success And How To Solve It," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(03), pages 1-52, May.
    7. Silvia Bartolucci & Andrei Kirilenko, 2019. "A Model of the Optimal Selection of Crypto Assets," Papers 1906.09632, arXiv.org.
    8. Hsieh, Sheng-Feng & Brennan, Gerard, 2022. "Issues, risks, and challenges for auditing crypto asset transactions," International Journal of Accounting Information Systems, Elsevier, vol. 46(C).
    9. Ravi Kashyap, 2024. "The Concentration Risk Indicator: Raising the Bar for Financial Stability and Portfolio Performance Measurement," Papers 2408.07271, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    2. Andrea Flori, 2019. "Cryptocurrencies In Finance: Review And Applications," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(05), pages 1-22, August.
    3. Abeer ElBahrawy & Laura Alessandretti & Anne Kandler & Romualdo Pastor-Satorras & Andrea Baronchelli, 2017. "Evolutionary dynamics of the cryptocurrency market," Papers 1705.05334, arXiv.org, revised Nov 2017.
    4. Zura Kakushadze & Jim Kyung-Soo Liew, 2018. "CryptoRuble: From Russia with Love," Papers 1801.05760, arXiv.org.
    5. Nino Antulov-Fantulin & Dijana Tolic & Matija Piskorec & Zhang Ce & Irena Vodenska, 2018. "Inferring short-term volatility indicators from Bitcoin blockchain," Papers 1809.07856, arXiv.org.
    6. Parthajit Kayal & Purnima Rohilla, 2021. "Bitcoin in the economics and finance literature: a survey," SN Business & Economics, Springer, vol. 1(7), pages 1-21, July.
    7. Chengyi Tu & Paolo DOdorico & Samir Suweis, 2018. "Critical slowing down associated with critical transition and risk of collapse in cryptocurrency," Papers 1806.08386, arXiv.org, revised Nov 2019.
    8. Begušić, Stjepan & Kostanjčar, Zvonko & Eugene Stanley, H. & Podobnik, Boris, 2018. "Scaling properties of extreme price fluctuations in Bitcoin markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 400-406.
    9. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2019. "Exploring disorder and complexity in the cryptocurrency space," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 548-556.
    10. Silvia Bartolucci & Fabio Caccioli & Pierpaolo Vivo, 2019. "A percolation model for the emergence of the Bitcoin Lightning Network," Papers 1912.03556, arXiv.org.
    11. Paulo Ferreira & Éder Pereira, 2019. "Contagion Effect in Cryptocurrency Market," JRFM, MDPI, vol. 12(3), pages 1-8, July.
    12. Abeer ElBahrawy & Laura Alessandretti & Andrea Baronchelli, 2019. "Wikipedia and Digital Currencies: Interplay Between Collective Attention and Market Performance," Papers 1902.04517, arXiv.org, revised Mar 2019.
    13. Stjepan Beguv{s}i'c & Zvonko Kostanjv{c}ar & H. Eugene Stanley & Boris Podobnik, 2018. "Scaling properties of extreme price fluctuations in Bitcoin markets," Papers 1803.08405, arXiv.org.
    14. Laura Alessandretti & Abeer ElBahrawy & Luca Maria Aiello & Andrea Baronchelli, 2018. "Anticipating cryptocurrency prices using machine learning," Papers 1805.08550, arXiv.org, revised Nov 2018.
    15. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2019. "Multifractal behavior of price and volume changes in the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 54-61.
    16. Pieters, Gina & Vivanco, Sofia, 2017. "Financial regulations and price inconsistencies across Bitcoin markets," Information Economics and Policy, Elsevier, vol. 39(C), pages 1-14.
    17. Alexandre Bovet & Carlo Campajola & Jorge F. Lazo & Francesco Mottes & Iacopo Pozzana & Valerio Restocchi & Pietro Saggese & Nicol'o Vallarano & Tiziano Squartini & Claudio J. Tessone, 2018. "Network-based indicators of Bitcoin bubbles," Papers 1805.04460, arXiv.org.
    18. Carlo Campajola & Marco D'Errico & Claudio J. Tessone, 2022. "MicroVelocity: rethinking the Velocity of Money for digital currencies," Papers 2201.13416, arXiv.org, revised May 2023.
    19. Ladislav Kristoufek, 2015. "What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-15, April.
    20. Aniruddha Dutta & Saket Kumar & Meheli Basu, 2020. "A Gated Recurrent Unit Approach to Bitcoin Price Prediction," JRFM, MDPI, vol. 13(2), pages 1-16, February.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1803.03088. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.