IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2401.04702.html
   My bibliography  Save this paper

Scaling Laws And Statistical Properties of The Transaction Flows And Holding Times of Bitcoin

Author

Listed:
  • Didier Sornette
  • Yu Zhang

Abstract

We study the temporal evolution of the holding-time distribution of bitcoins and find that the average distribution of holding-time is a heavy-tailed power law extending from one day to over at least $200$ weeks with an exponent approximately equal to $0.9$, indicating very long memory effects. We also report significant sample-to-sample variations of the distribution of holding times, which can be best characterized as multiscaling, with power-law exponents varying between $0.3$ and $2.5$ depending on bitcoin price regimes. We document significant differences between the distributions of book-to-market and of realized returns, showing that traders obtain far from optimal performance. We also report strong direct qualitative and quantitative evidence of the disposition effect in the Bitcoin Blockchain data. Defining age-dependent transaction flows as the fraction of bitcoins that are traded at a given time and that were born (last traded) at some specific earlier time, we document that the time-averaged transaction flow fraction has a power law dependence as a function of age, with an exponent close to $-1.5$, a value compatible with priority queuing theory. We document the existence of multifractality on the measure defined as the normalized number of bitcoins exchanged at a given time.

Suggested Citation

  • Didier Sornette & Yu Zhang, 2024. "Scaling Laws And Statistical Properties of The Transaction Flows And Holding Times of Bitcoin," Papers 2401.04702, arXiv.org.
    • Handle: RePEc:arx:papers:2401.04702
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2401.04702
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nicholas Barberis & Wei Xiong, 2009. "What Drives the Disposition Effect? An Analysis of a Long‐Standing Preference‐Based Explanation," Journal of Finance, American Finance Association, vol. 64(2), pages 751-784, April.
    2. Rainer Böhme & Nicolas Christin & Benjamin Edelman & Tyler Moore, 2015. "Bitcoin: Economics, Technology, and Governance," Journal of Economic Perspectives, American Economic Association, vol. 29(2), pages 213-238, Spring.
    3. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    4. Shefrin, Hersh & Statman, Meir, 1985. "The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence," Journal of Finance, American Finance Association, vol. 40(3), pages 777-790, July.
    5. A. I. Saichev & D. Sornette, 2010. "Generation-by-generation dissection of the response function in long memory epidemic processes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 75(3), pages 343-355, June.
    Full references (including those not matched with items on IDEAS)

    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. Shoji, Isao & Kanehiro, Sumei, 2016. "Disposition effect as a behavioral trading activity elicited by investors' different risk preferences," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 104-112.
    2. Lepone, Grace & Tian, Gary, 2020. "Usage of conditional orders and the disposition effect in the stock market," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    3. Youki Kohsaka & Grzegorz Mardyla & Shinji Takenaka & Yoshiro Tsutsui, 2017. "Disposition Effect and Diminishing Sensitivity: An Analysis Based on a Simulated Experimental Stock Market," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 18(2), pages 189-201, April.
    4. Barberis, Nicholas & Xiong, Wei, 2012. "Realization utility," Journal of Financial Economics, Elsevier, vol. 104(2), pages 251-271.
    5. Markus Dertwinkel-Kalt & Jonas Frey, 2020. "Optimal Stopping in a Dynamic Salience Model," CESifo Working Paper Series 8496, CESifo.
    6. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.
    7. Jonathan E. Ingersoll Jr. & Lawrence J. Jin, 2014. "Realization Utility with Reference-Dependent Preferences," Papers 1408.2859, arXiv.org.
    8. Jean-Philippe Bouchaud & Damien Challet, 2016. "Why have asset price properties changed so little in 200 years," Papers 1605.00634, arXiv.org.
    9. Vassilis A. Efthymiou & George N. Leledakis, 2014. "The price impact of the disposition effect on the ex-dividend day of NYSE and AMEX common stocks," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 711-724, April.
    10. Cary Frydman & Nicholas Barberis & Colin Camerer & Peter Bossaerts & Antonio Rangel, 2012. "Using Neural Data to Test a Theory of Investor Behavior: An Application to Realization Utility," NBER Working Papers 18562, National Bureau of Economic Research, Inc.
    11. Choi, Darwin, 2019. "Disposition sales and stock market liquidity," Journal of Financial Markets, Elsevier, vol. 45(C), pages 19-36.
    12. Francisco Gomes & Michael Haliassos & Tarun Ramadorai, 2021. "Household Finance," Journal of Economic Literature, American Economic Association, vol. 59(3), pages 919-1000, September.
    13. Kahya, Evrim Hilal & Ekinci, Cumhur, 2022. "Disposition bias among Borsa Istanbul investors: What do we know about type, size and trading frequency?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 35(C).
    14. Jakusch, Sven Thorsten & Meyer, Steffen & Hackethal, Andreas, 2019. "Taming models of prospect theory in the wild? Estimation of Vlcek and Hens (2011)," SAFE Working Paper Series 146, Leibniz Institute for Financial Research SAFE, revised 2019.
    15. He, Wen & Li, Yan, 2020. "Comparing with the average: Reference points and market reactions to above-average earnings surprises," Journal of Banking & Finance, Elsevier, vol. 117(C).
    16. James Bashall & Gizelle D. Willows & Darron West, 2018. "The Extent to Which Professional Advice Can Reduce the Disposition Effect: An Emerging Market Study," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2), pages 229-249, August.
    17. Servaas van Bilsen & Roger J. A. Laeven & Theo E. Nijman, 2020. "Consumption and Portfolio Choice Under Loss Aversion and Endogenous Updating of the Reference Level," Management Science, INFORMS, vol. 66(9), pages 3927-3955, September.
    18. repec:cup:judgdm:v:12:y:2017:i:2:p:118-127 is not listed on IDEAS
    19. Beatrice Boumda & Darren Duxbury & Cristina Ortiz & Luis Vicente, 2021. "Do Socially Responsible Investment Funds Sell Losses and Ride Gains? The Disposition Effect in SRI Funds," Sustainability, MDPI, vol. 13(15), pages 1-14, July.
    20. Enrico Giorgi & Thorsten Hens, 2006. "Making prospect theory fit for finance," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(3), pages 339-360, September.
    21. Summers, Barbara & Duxbury, Darren, 2012. "Decision-dependent emotions and behavioral anomalies," Organizational Behavior and Human Decision Processes, Elsevier, vol. 118(2), pages 226-238.

    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:2401.04702. 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.