IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v654y2024ics0378437124006381.html
   My bibliography  Save this article

Impact of Black Swan Events on Ethereum blockchain ERC20 token transaction networks

Author

Listed:
  • Pradeep, Moturi
  • Dyapa, Uday Kumar Reddy
  • Jalan, Sarika
  • Pradhan, Priodyuti

Abstract

The Ethereum blockchain and its ERC20 token standard have revolutionized the landscape of digital assets and decentralized applications. ERC20 tokens are programmable and interoperable tokens, enabling various applications and token economies. Transaction graphs, representing the flow of the value between wallets within the Ethereum network, have played a crucial role in understanding the system’s dynamics, such as token transfers and the behavior of traders. Here, we explore the evolution of daily transaction graphs of ERC20 token transactions, which sheds light on the trader’s behavior during the Black Swan Events – 2018 crypto crash and the COVID-19 pandemic. By using the tools from network science and differential geometry, we analyze 0.98 billion of ERC20 token transaction data from November 2015 to January 2023. Our analysis reveals an increase in diverse interaction among the traders and a greater adoption of ERC20 tokens in a maturing Ethereum ERC20 financial ecosystem after the Crypto Crash 2018 and the COVID-19 pandemic. Before the crash and the COVID-19 pandemic, most traders interacted with other traders in an isolated or restricted manner, with each trader focusing solely on either buying or selling activities. However, after the crash and during the pandemic, most traders diversely interacted among themselves by participating in both buying and selling activities. In addition, we observe no significant negative impact of the COVID-19 pandemic on user behavior in the financial ecosystem.

Suggested Citation

  • Pradeep, Moturi & Dyapa, Uday Kumar Reddy & Jalan, Sarika & Pradhan, Priodyuti, 2024. "Impact of Black Swan Events on Ethereum blockchain ERC20 token transaction networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 654(C).
  • Handle: RePEc:eee:phsmap:v:654:y:2024:i:c:s0378437124006381
    DOI: 10.1016/j.physa.2024.130129
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437124006381
    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.2024.130129?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. Paltalidis, Nikos & Gounopoulos, Dimitrios & Kizys, Renatas & Koutelidakis, Yiannis, 2015. "Transmission channels of systemic risk and contagion in the European financial network," Journal of Banking & Finance, Elsevier, vol. 61(S1), pages 36-52.
    2. Warwick McKibbin & Roshen Fernando, 2021. "The Global Macroeconomic Impacts of COVID-19: Seven Scenarios," Asian Economic Papers, MIT Press, vol. 20(2), pages 1-30, Summer.
    3. Rognone, Lavinia & Hyde, Stuart & Zhang, S. Sarah, 2020. "News sentiment in the cryptocurrency market: An empirical comparison with Forex," International Review of Financial Analysis, Elsevier, vol. 69(C).
    4. Jiaqi Liang & Linjing Li & Daniel Zeng, 2018. "Evolutionary dynamics of cryptocurrency transaction networks: An empirical study," Papers 1808.08585, arXiv.org.
    5. Dutta, Pankaj & Choi, Tsan-Ming & Somani, Surabhi & Butala, Richa, 2020. "Blockchain technology in supply chain operations: Applications, challenges and research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    6. Jesse Yli-Huumo & Deokyoon Ko & Sujin Choi & Sooyong Park & Kari Smolander, 2016. "Where Is Current Research on Blockchain Technology?—A Systematic Review," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-27, October.
    7. Barua, Suborna, 2020. "Understanding Coronanomics: The economic implications of the coronavirus (COVID-19) pandemic," MPRA Paper 99693, University Library of Munich, Germany.
    8. Jamal Bouoiyour & Refk Selmi, 2020. "Coronavirus Spreads and Bitcoin's 2020 Rally: Is There a Link ?," Working Papers hal-02493309, HAL.
    9. Conlon, Thomas & McGee, Richard, 2020. "Safe haven or risky hazard? Bitcoin during the Covid-19 bear market," Finance Research Letters, Elsevier, vol. 35(C).
    10. Jiaqi Liang & Linjing Li & Daniel Zeng, 2018. "Evolutionary dynamics of cryptocurrency transaction networks: An empirical study," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-18, August.
    11. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    12. Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
    13. Patil, Kiran & Ojha, Divesh & Struckell, Elisabeth M. & Patel, Pankaj C., 2023. "Behavioral drivers of blockchain assimilation in supply chains – A social network theory perspective," Technological Forecasting and Social Change, Elsevier, vol. 192(C).
    14. Semyon Malamud & Marzena Rostek, 2017. "Decentralized Exchange," American Economic Review, American Economic Association, vol. 107(11), pages 3320-3362, November.
    15. Yukun Liu & Aleh Tsyvinski, 2021. "Risks and Returns of Cryptocurrency," The Review of Financial Studies, Society for Financial Studies, vol. 34(6), pages 2689-2727.
    16. Marco Bardoscia & Paolo Barucca & Stefano Battiston & Fabio Caccioli & Giulio Cimini & Diego Garlaschelli & Fabio Saracco & Tiziano Squartini & Guido Caldarelli, 2021. "The Physics of Financial Networks," Papers 2103.05623, arXiv.org.
    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. Assaf, Ata & Mokni, Khaled & Yousaf, Imran & Bhandari, Avishek, 2023. "Long memory in the high frequency cryptocurrency markets using fractal connectivity analysis: The impact of COVID-19," Research in International Business and Finance, Elsevier, vol. 64(C).
    2. ?ikolaos A. Kyriazis, 2021. "Impacts of Stock Indices, Oil, and Twitter Sentiment on Major Cryptocurrencies during the COVID-19 First Wave," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 133-146.
    3. Akhtaruzzaman, Md & Boubaker, Sabri & Sensoy, Ahmet, 2021. "Financial contagion during COVID–19 crisis," Finance Research Letters, Elsevier, vol. 38(C).
    4. Jiang, Yonghong & Wu, Lanxin & Tian, Gengyu & Nie, He, 2021. "Do cryptocurrencies hedge against EPU and the equity market volatility during COVID-19? – New evidence from quantile coherency analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    5. Lin, Dan & Wu, Jiajing & Xuan, Qi & Tse, Chi K., 2022. "Ethereum transaction tracking: Inferring evolution of transaction networks via link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    6. Chen, Bin-xia & Sun, Yan-lin, 2024. "Risk characteristics and connectedness in cryptocurrency markets: New evidence from a non-linear framework," The North American Journal of Economics and Finance, Elsevier, vol. 69(PA).
    7. Sadananda Prusty & Anubha & Saurabh Gupta, 2021. "On the Road to Recovery: The Role of Post-Lockdown Stimulus Package," FIIB Business Review, , vol. 11(2), pages 206-224, June.
    8. Serdar Neslihanoglu, 2021. "Linearity extensions of the market model: a case of the top 10 cryptocurrency prices during the pre-COVID-19 and COVID-19 periods," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    9. Sudersan Behera & Sarat Chandra Nayak & A. V. S. Pavan Kumar, 2024. "Evaluating the Performance of Metaheuristic Based Artificial Neural Networks for Cryptocurrency Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1219-1258, August.
    10. Wang, Yupeng & Shimokawa, Satoru, 2024. "A trade-off between lives and the economy? Subsidizing dining out under the COVID-19 pandemic in Japan," Food Policy, Elsevier, vol. 124(C).
    11. Neto, David, 2022. "Examining interconnectedness between media attention and cryptocurrency markets: A transfer entropy story," Economics Letters, Elsevier, vol. 214(C).
    12. Peng‐Fei Dai & John W. Goodell & Luu Duc Toan Huynh & Zhifeng Liu & Shaen Corbet, 2023. "Understanding the transmission of crash risk between cryptocurrency and equity markets," The Financial Review, Eastern Finance Association, vol. 58(3), pages 539-573, August.
    13. Kumar Kulbhaskar, Anamika & Subramaniam, Sowmya, 2023. "Breaking news headlines: Impact on trading activity in the cryptocurrency market," Economic Modelling, Elsevier, vol. 126(C).
    14. Zhu, Qingyun & Bai, Chunguang & Sarkis, Joseph, 2022. "Blockchain technology and supply chains: The paradox of the atheoretical research discourse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    15. Vidal-Tomás, David, 2021. "Transitions in the cryptocurrency market during the COVID-19 pandemic: A network analysis," Finance Research Letters, Elsevier, vol. 43(C).
    16. Yan, Chun & Ding, Yi & Liu, Wei & Liu, Xinhong & Liu, Jiahui, 2023. "Multilayer interbank networks and systemic risk propagation: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    17. Shi, Qing & Sun, Xiaoqi & Jiang, Yile, 2022. "Concentrated commonalities and systemic risk in China's banking system: A contagion network approach," International Review of Financial Analysis, Elsevier, vol. 83(C).
    18. Ahmed, Walid M.A., 2021. "How do Islamic equity markets respond to good and bad volatility of cryptocurrencies? The case of Bitcoin," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).
    19. Manavi, Seyed Alireza & Jafari, Gholamreza & Rouhani, Shahin & Ausloos, Marcel, 2020. "Demythifying the belief in cryptocurrencies decentralized aspects. A study of cryptocurrencies time cross-correlations with common currencies, commodities and financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    20. Dobrynskaya, Victoria, 2024. "Is downside risk priced in cryptocurrency market?," International Review of Financial Analysis, Elsevier, vol. 91(C).

    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:654:y:2024:i:c:s0378437124006381. 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.