IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v525y2019icp548-556.html
   My bibliography  Save this article

Exploring disorder and complexity in the cryptocurrency space

Author

Listed:
  • Stosic, Darko
  • Stosic, Dusan
  • Ludermir, Teresa B.
  • Stosic, Tatijana

Abstract

Digital assets termed cryptocurrencies are creating new paradigms for financial transactions as well as alternative means of capital. Despite their increasing relevance in financial situations, a complete understanding of the entire system remains lacking. Here the cryptocurrency market is treated as a complex system and analyzed using methods from statistical physics. The complexity–entropy causality plane (or CH plane) is employed in order to explore disorder and complexity in the space of cryptocurrencies. They are found to exist on distinct planar locations in the representation space, ranging from structured to stochastic-like behavior. The temporal trajectories of entropy and statistical complexity of prices vary drastically with position along the plane. Lastly cryptocurrencies appear to be characterized by ordinal patterns that represent strictly decreasing or increasing trends in price. The present analysis expands the understanding of and helps to quantify varying degrees of complexity in cryptocurrencies.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:548-556
    DOI: 10.1016/j.physa.2019.03.091
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119303279
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2019.03.091?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2009. "Forbidden patterns, permutation entropy and stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2854-2864.
    2. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
    3. 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.
    4. Bariviera, Aurelio F. & Basgall, María José & Hasperué, Waldo & Naiouf, Marcelo, 2017. "Some stylized facts of the Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 82-90.
    5. Neil Gandal & Hanna Halaburda, 2016. "Can We Predict the Winner in a Market with Network Effects? Competition in Cryptocurrency Market," Games, MDPI, vol. 7(3), pages 1-21, July.
    6. Marie Briere & Kim Oosterlinck & Ariane Szafarz, 2015. "Virtual Currency, Tangible Return: Portfolio Diversification with Bitcoins," Post-Print CEB, ULB -- Universite Libre de Bruxelles, vol. 16(6), pages 365-373.
    7. Stephen Chan & Jeffrey Chu & Saralees Nadarajah & Joerg Osterrieder, 2017. "A Statistical Analysis of Cryptocurrencies," JRFM, MDPI, vol. 10(2), pages 1-23, May.
    8. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2010. "Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1891-1901.
    9. Yi-Cheng Zhang, 1999. "Toward a Theory of Marginally Efficient Markets," Papers cond-mat/9901243, arXiv.org.
    10. Kristoufek, Ladislav & Vosvrda, Miloslav, 2016. "Gold, currencies and market efficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 27-34.
    11. Alvarez-Ramirez, J. & Rodriguez, E. & Ibarra-Valdez, C., 2018. "Long-range correlations and asymmetry in the Bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 948-955.
    12. Fry, John & Cheah, Eng-Tuck, 2016. "Negative bubbles and shocks in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 343-352.
    13. Zhang, Yi-Cheng, 1999. "Toward a theory of marginally efficient markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 269(1), pages 30-44.
    14. Zunino, Luciano & Fernández Bariviera, Aurelio & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2012. "On the efficiency of sovereign bond markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(18), pages 4342-4349.
    15. Tang, Yi & Zhao, An & Ren, Ying-yu & Dou, Fu-Xiang & Jin, Ning-De, 2016. "Gas–liquid two-phase flow structure in the multi-scale weighted complexity entropy causality plane," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 324-335.
    16. Zunino, Luciano & Tabak, Benjamin M. & Serinaldi, Francesco & Zanin, Massimiliano & Pérez, Darío G. & Rosso, Osvaldo A., 2011. "Commodity predictability analysis with a permutation information theory approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 876-890.
    17. Sha Wang & Jean-Philippe Vergne, 2017. "Buzz Factor or Innovation Potential: What Explains Cryptocurrencies’ Returns?," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-17, January.
    18. 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.
    19. 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.
    20. Lamberti, P.W & Martin, M.T & Plastino, A & Rosso, O.A, 2004. "Intensive entropic non-triviality measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 334(1), pages 119-131.
    21. 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.
    22. Ribeiro, Haroldo V. & Zunino, Luciano & Mendes, Renio S. & Lenzi, Ervin K., 2012. "Complexity–entropy causality plane: A useful approach for distinguishing songs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2421-2428.
    23. Lahmiri, Salim & Bekiros, Stelios, 2018. "Chaos, randomness and multi-fractality in Bitcoin market," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 28-34.
    24. Chrisment, Antoine M. & Firpo, Marie-Christine, 2016. "Entropy–complexity analysis in some globally-coupled systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 162-173.
    25. Martin, M.T. & Plastino, A. & Rosso, O.A., 2006. "Generalized statistical complexity measures: Geometrical and analytical properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 369(2), pages 439-462.
    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. James, Nick & Menzies, Max & Chin, Kevin, 2022. "Economic state classification and portfolio optimisation with application to stagflationary environments," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    2. Omane-Adjepong, Maurice & Alagidede, Imhotep Paul, 2020. "High- and low-level chaos in the time and frequency market returns of leading cryptocurrencies and emerging assets," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    3. Nick James & Kevin Chin, 2021. "On the systemic nature of global inflation, its association with equity markets and financial portfolio implications," Papers 2111.11022, arXiv.org, revised Jan 2022.
    4. Fernandes, Leonardo H.S. & Araújo, Fernando H.A., 2020. "Taxonomy of commodities assets via complexity-entropy causality plane," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    5. Nick James & Max Menzies & Kevin Chin, 2022. "Economic state classification and portfolio optimisation with application to stagflationary environments," Papers 2203.15911, arXiv.org, revised Sep 2022.
    6. Bariviera, Aurelio F. & Font-Ferrer, Alejandro & Sorrosal-Forradellas, M. Teresa & Rosso, Osvaldo A., 2019. "An information theory perspective on the informational efficiency of gold price," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    7. James, Nick & Menzies, Max & Chan, Jennifer, 2021. "Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    8. Nick James & Max Menzies, 2023. "An exploration of the mathematical structure and behavioural biases of 21st century financial crises," Papers 2307.15402, arXiv.org, revised Sep 2023.
    9. Nick James, 2021. "Dynamics, behaviours, and anomaly persistence in cryptocurrencies and equities surrounding COVID-19," Papers 2101.00576, arXiv.org, revised Feb 2021.
    10. James, Nick & Chin, Kevin, 2022. "On the systemic nature of global inflation, its association with equity markets and financial portfolio implications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    11. de Araujo, Fernando Henrique Antunes & Bejan, Lucian & Stosic, Borko & Stosic, Tatijana, 2020. "An analysis of Brazilian agricultural commodities using permutation – information theory quantifiers: The influence of food crisis," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    12. Zheng, Zhiyong & Lu, Yunfan & Zhang, Junhuan, 2022. "Multiscale complexity fluctuation behaviours of stochastic interacting cryptocurrency price model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    13. Zhao, Xin & Ghaemi Asl, Mahdi & Rashidi, Muhammad Mahdi & Vasa, László & Shahzad, Umer, 2023. "Interoperability of the revolutionary blockchain architectures and Islamic and conventional technology markets: Case of Metaverse, HPB, and Bloknet," The Quarterly Review of Economics and Finance, Elsevier, vol. 92(C), pages 112-131.
    14. Nick James & Max Menzies, 2021. "Efficiency of communities and financial markets during the 2020 pandemic," Papers 2104.02318, arXiv.org, revised Jul 2021.
    15. Nick James & Max Menzies, 2021. "Collective correlations, dynamics, and behavioural inconsistencies of the cryptocurrency market over time," Papers 2107.13926, arXiv.org, revised Dec 2021.
    16. James, Nick, 2021. "Dynamics, behaviours, and anomaly persistence in cryptocurrencies and equities surrounding COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    17. Lahmiri, Salim & Bekiros, Stelios, 2020. "Intelligent forecasting with machine learning trading systems in chaotic intraday Bitcoin market," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    18. Bouri, Elie & Saeed, Tareq & Vo, Xuan Vinh & Roubaud, David, 2021. "Quantile connectedness in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    19. Nick James, 2021. "Evolutionary correlation, regime switching, spectral dynamics and optimal trading strategies for cryptocurrencies and equities," Papers 2112.15321, arXiv.org, revised Mar 2022.
    20. Lima, David H.S. & Aquino, Andre L.L. & Rosso, Osvaldo A. & Curado, Marilia, 2024. "Characterization of task allocation techniques in data centers based on information theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    21. Lahmiri, Salim & Bekiros, Stelios, 2020. "Big data analytics using multi-fractal wavelet leaders in high-frequency Bitcoin markets," Chaos, Solitons & Fractals, Elsevier, vol. 131(C).

    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. 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.
    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. 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.
    4. Fernandes, Leonardo H.S. & de Araujo, Fernando H.A. & Tabak, Benjamin M., 2021. "Insights from the (in)efficiency of Chinese sectoral indices during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    5. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2018. "Nonextensive triplets in cryptocurrency exchanges," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1069-1074.
    6. Fernandes, Leonardo H.S. & Araújo, Fernando H.A., 2020. "Taxonomy of commodities assets via complexity-entropy causality plane," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    7. Argyroudis, George S. & Siokis, Fotios M., 2019. "Spillover effects of Great Recession on Hong-Kong’s Real Estate Market: An analysis based on Causality Plane and Tsallis Curves of Complexity–Entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 576-586.
    8. James, Nick & Menzies, Max & Chan, Jennifer, 2021. "Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    9. Rodolfo Angelo Magtanggol Iii De Guzman & Mike K. P. So, 2018. "Empirical Analysis Of Bitcoin Prices Using Threshold Time Series Models," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(04), pages 1-24, December.
    10. Nick James & Kevin Chin, 2021. "On the systemic nature of global inflation, its association with equity markets and financial portfolio implications," Papers 2111.11022, arXiv.org, revised Jan 2022.
    11. James, Nick & Menzies, Max & Chin, Kevin, 2022. "Economic state classification and portfolio optimisation with application to stagflationary environments," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    12. Nick James & Max Menzies, 2021. "Efficiency of communities and financial markets during the 2020 pandemic," Papers 2104.02318, arXiv.org, revised Jul 2021.
    13. Nick James & Max Menzies & Kevin Chin, 2022. "Economic state classification and portfolio optimisation with application to stagflationary environments," Papers 2203.15911, arXiv.org, revised Sep 2022.
    14. Zunino, Luciano & Ribeiro, Haroldo V., 2016. "Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 679-688.
    15. James, Nick & Chin, Kevin, 2022. "On the systemic nature of global inflation, its association with equity markets and financial portfolio implications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    16. Nick James & Max Menzies, 2021. "Collective correlations, dynamics, and behavioural inconsistencies of the cryptocurrency market over time," Papers 2107.13926, arXiv.org, revised Dec 2021.
    17. Higor Y. D. Sigaki & Matjaz Perc & Haroldo V. Ribeiro, 2019. "Clustering patterns in efficiency and the coming-of-age of the cryptocurrency market," Papers 1901.04967, arXiv.org.
    18. Li, Mu-Yao & Cai, Qing & Gu, Gao-Feng & Zhou, Wei-Xing, 2019. "Exponentially decayed double power-law distribution of Bitcoin trade sizes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    19. Zunino, Luciano & Bariviera, Aurelio F. & Guercio, M. Belén & Martinez, Lisana B. & Rosso, Osvaldo A., 2016. "Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 1-9.
    20. Siokis, Fotios M., 2018. "Credit market Jitters in the course of the financial crisis: A permutation entropy approach in measuring informational efficiency in financial assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 266-275.

    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:phsmap:v:525:y:2019:i:c:p:548-556. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.