IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v63y2024ics1544612324003258.html
   My bibliography  Save this article

On co-dependent power-law behavior across cryptocurrencies

Author

Listed:
  • Grobys, Klaus

Abstract

Using daily returns on large-cap altcoins, this paper uses power-law functions to model cryptocurrency-specific exposure to events exhibiting potentially large standard deviations. Since our analysis provides evidence for power-law behavior in the returns on cryptocurrencies, co-fractality analysis is employed to explore potential co-dependencies in the heavy-tailed part of return distributions. The findings indicate that the potential arrival of events exhibiting large standard deviations in Bitcoin returns can hardly be diversified using other sample altcoins. Other altcoins exhibit very similar features in terms of co-dependencies. Further results show that co-fractal behavior is not specific to any subsample.

Suggested Citation

  • Grobys, Klaus, 2024. "On co-dependent power-law behavior across cryptocurrencies," Finance Research Letters, Elsevier, vol. 63(C).
  • Handle: RePEc:eee:finlet:v:63:y:2024:i:c:s1544612324003258
    DOI: 10.1016/j.frl.2024.105295
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612324003258
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2024.105295?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    2. Grobys, Klaus, 2023. "Correlation versus co-fractality: Evidence from foreign-exchange-rate variances," International Review of Financial Analysis, Elsevier, vol. 86(C).
    3. Klaus Grobys & Niranjan Sapkota, 2020. "Predicting cryptocurrency defaults," Applied Economics, Taylor & Francis Journals, vol. 52(46), pages 5060-5076, October.
    4. Liu, Weiyi & Liang, Xuan & Cui, Guowei, 2020. "Common risk factors in the returns on cryptocurrencies," Economic Modelling, Elsevier, vol. 86(C), pages 299-305.
    5. Grobys, Klaus & Dufitinema, Josephine & Sapkota, Niranjan & Kolari, James W., 2022. "What’s the expected loss when Bitcoin is under cyberattack? A fractal process analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    6. Grobys, Klaus & Ahmed, Shaker & Sapkota, Niranjan, 2020. "Technical trading rules in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 32(C).
    7. Beneki, Christina & Koulis, Alexandros & Kyriazis, Nikolaos A. & Papadamou, Stephanos, 2019. "Investigating volatility transmission and hedging properties between Bitcoin and Ethereum," Research in International Business and Finance, Elsevier, vol. 48(C), pages 219-227.
    8. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    9. Cheng, Qing & Liu, Xinyuan & Zhu, Xiaowu, 2019. "Cryptocurrency momentum effect: DFA and MF-DFA analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    10. 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.
    11. Mandelbrot, Benoit B, 1972. "Correction of an Error in "The Variation of Certain Speculative Prices" (1963)," The Journal of Business, University of Chicago Press, vol. 45(4), pages 542-543, October.
    12. Dirk G. Baur & Thomas Dimpfl, 2021. "The volatility of Bitcoin and its role as a medium of exchange and a store of value," Empirical Economics, Springer, vol. 61(5), pages 2663-2683, November.
    13. Cai, Zongwu & Juhl, Ted, 2023. "The distribution of rolling regression estimators," Journal of Econometrics, Elsevier, vol. 235(2), pages 1447-1463.
    14. 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.
    15. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis," Finance Research Letters, Elsevier, vol. 29(C), pages 68-74.
    16. Grobys, Klaus, 2023. "A Fractal and Comparative View of the Memory of Bitcoin and S&P 500 Returns," Research in International Business and Finance, Elsevier, vol. 66(C).
    17. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    18. Eugene F. Fama, 1963. "Mandelbrot and the Stable Paretian Hypothesis," The Journal of Business, University of Chicago Press, vol. 36, pages 420-420.
    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. Fathi, Masoumeh & Grobys, Klaus & Äijö, Janne, 2025. "A common component of Fama and French factor variances," The North American Journal of Economics and Finance, Elsevier, vol. 75(PA).
    2. Grobys, Klaus, 2023. "A Fractal and Comparative View of the Memory of Bitcoin and S&P 500 Returns," Research in International Business and Finance, Elsevier, vol. 66(C).
    3. Grobys, Klaus, 2023. "A multifractal model of asset (in)variances," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    4. Sabiou M. Inoua & Vernon L. Smith, 2022. "Perishable goods versus re-tradable assets: A theoretical reappraisal of a fundamental dichotomy," Chapters, in: Sascha Füllbrunn & Ernan Haruvy (ed.), Handbook of Experimental Finance, chapter 15, pages 162-171, Edward Elgar Publishing.
    5. Klaus Grobys, 2021. "When the blockchain does not block: on hackings and uncertainty in the cryptocurrency market," Quantitative Finance, Taylor & Francis Journals, vol. 21(8), pages 1267-1279, August.
    6. Grobys, Klaus, 2021. "What do we know about the second moment of financial markets?," International Review of Financial Analysis, Elsevier, vol. 78(C).
    7. Grobys, Klaus, 2023. "Correlation versus co-fractality: Evidence from foreign-exchange-rate variances," International Review of Financial Analysis, Elsevier, vol. 86(C).
    8. Grobys, Klaus, 2024. "A universal exponent governing foreign exchange rate risks," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    9. Klaus Grobys, 2024. "Science or scientism? On the momentum illusion," Annals of Finance, Springer, vol. 20(4), pages 479-519, December.
    10. Ahmed, Mohamed Shaker & El-Masry, Ahmed A. & Al-Maghyereh, Aktham I. & Kumar, Satish, 2024. "Cryptocurrency volatility: A review, synthesis, and research agenda," Research in International Business and Finance, Elsevier, vol. 71(C).
    11. Sabiou M. Inoua, 2020. "News-Driven Expectations and Volatility Clustering," JRFM, MDPI, vol. 13(1), pages 1-14, January.
    12. Wu, Xu & Zhang, Linlin & Li, Jia & Yan, Ruzhen, 2021. "Fractal statistical measure and portfolio model optimization under power-law distribution," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    13. Sabiou Inoua, 2023. "News-driven Expectations and Volatility Clustering," Papers 2309.04876, arXiv.org.
    14. Sabiou M. Inoua & Vernon L. Smith, 2022. "Perishable goods versus re-tradable assets: A theoretical reappraisal of a fundamental dichotomy," Chapters, in: Sascha Füllbrunn & Ernan Haruvy (ed.), Handbook of Experimental Finance, chapter 15, pages 162-171, Edward Elgar Publishing.
    15. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    16. Hayley Jang & Young Hoon Lee & Rodney Fort, 2019. "Winning In Professional Team Sports: Historical Moments," Economic Inquiry, Western Economic Association International, vol. 57(1), pages 103-120, January.
    17. De Backer, Stijn & Rocha, Luis E.C. & Ryckebusch, Jan & Schoors, Koen, 2025. "On the potential of quantum walks for modeling financial return distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 657(C).
    18. Alexander Eastman & Brian Lucey, 2008. "Skewness and asymmetry in futures returns and volumes," Applied Financial Economics, Taylor & Francis Journals, vol. 18(10), pages 777-800.
    19. Ortobelli, Sergio & Rachev, Svetlozar & Schwartz, Eduardo, 2000. "The Problem of Optimal Asset Allocation with Stable Distributed Returns," University of California at Los Angeles, Anderson Graduate School of Management qt3zd6q86c, Anderson Graduate School of Management, UCLA.
    20. Fergusson, Kevin, 2020. "Less-Expensive Valuation And Reserving Of Long-Dated Variable Annuities When Interest Rates And Mortality Rates Are Stochastic," ASTIN Bulletin, Cambridge University Press, vol. 50(2), pages 381-417, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:eee:finlet:v:63:y:2024:i:c:s1544612324003258. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.