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Complex network analysis of cryptocurrency market during crashes

Author

Listed:
  • Mukhia, Kundan
  • Rai, Anish
  • Luwang, S.R.
  • Nurujjaman, Md
  • Majhi, Sushovan
  • Hens, Chittaranjan

Abstract

This paper identifies the cryptocurrency market crashes and analyses its dynamics using the complex network. We identify three distinct crashes during 2017–20, and the analysis is carried out by dividing the time series into pre-crash, crash, and post-crash periods. Partial correlation based complex network analysis is carried out to study the crashes. Degree density (ρD), average path length (l̄), and average clustering coefficient (cc¯) are estimated from these networks. We find that both ρD and cc¯ are smallest during the pre-crash period, and spike during the crash suggesting the network is dense during a crash. Although ρD and cc¯ decrease in the post-crash period, they remain higher than pre-crash levels for the 2017–18 and 2018–19 crashes suggesting a market attempt to return to normalcy. We get l̄ is minimal during the crash period, suggesting a rapid flow of information. A dense network and rapid information flow suggest that during a crash uninformed synchronized panic sell-off happens. However, during the 2019–20 crash, the values of ρD, cc¯, and l̄ did not vary significantly, indicating minimal change in dynamics compared to other crashes. The findings of this study may guide investors in making decisions during market crashes.

Suggested Citation

  • Mukhia, Kundan & Rai, Anish & Luwang, S.R. & Nurujjaman, Md & Majhi, Sushovan & Hens, Chittaranjan, 2024. "Complex network analysis of cryptocurrency market during crashes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 653(C).
    • Handle: RePEc:eee:phsmap:v:653:y:2024:i:c:s0378437124006046
    DOI: 10.1016/j.physa.2024.130095
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    as
    1. Babajide Fowowe & Mohammed Shuaibu, 2016. "Dynamic spillovers between Nigerian, South African and international equity markets," International Economics, CEPII research center, issue 148, pages 59-80.
    2. Ji, Qiang & Guo, Jian-Feng, 2015. "Oil price volatility and oil-related events: An Internet concern study perspective," Applied Energy, Elsevier, vol. 137(C), pages 256-264.
    3. Y. Shapira & D. Y. Kenett & E. Ben-Jacob, 2009. "The Index cohesive effect on stock market correlations," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 72(4), pages 657-669, December.
    4. Young Bin Kim & Jun Gi Kim & Wook Kim & Jae Ho Im & Tae Hyeong Kim & Shin Jin Kang & Chang Hun Kim, 2016. "Predicting Fluctuations in Cryptocurrency Transactions Based on User Comments and Replies," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-17, August.
    5. Singh, Vipul Kumar & Nishant, Shreyank & Kumar, Pawan, 2018. "Dynamic and directional network connectedness of crude oil and currencies: Evidence from implied volatility," Energy Economics, Elsevier, vol. 76(C), pages 48-63.
    6. Caporale, Guglielmo Maria & Gil-Alana, Luis & Plastun, Alex, 2018. "Persistence in the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 46(C), pages 141-148.
    7. Yarovaya, Larisa & Matkovskyy, Roman & Jalan, Akanksha, 2021. "The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    8. Dimitrios Louzis, 2015. "Measuring spillover effects in Euro area financial markets: a disaggregate approach," Empirical Economics, Springer, vol. 49(4), pages 1367-1400, December.
    9. Hemendra Gupta & Rashmi Chaudhary, 2022. "An Empirical Study of Volatility in Cryptocurrency Market," JRFM, MDPI, vol. 15(11), pages 1-14, November.
    10. Ahmad, Wasim & Mishra, Anil V. & Daly, Kevin J., 2018. "Financial connectedness of BRICS and global sovereign bond markets," Emerging Markets Review, Elsevier, vol. 37(C), pages 1-16.
    11. Esmaeilpour Moghadam, Hadi & Mohammadi, Teymour & Feghhi Kashani, Mohammad & Shakeri, Abbas, 2019. "Complex networks analysis in Iran stock market: The application of centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    12. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Gabauer, David, 2019. "Cryptocurrency market contagion: Market uncertainty, market complexity, and dynamic portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 37-51.
    13. Zhang, Dayong & Broadstock, David C., 2020. "Global financial crisis and rising connectedness in the international commodity markets," International Review of Financial Analysis, Elsevier, vol. 68(C).
    14. Huang, Wei-Qiang & Zhuang, Xin-Tian & Yao, Shuang, 2009. "A network analysis of the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2956-2964.
    15. Stefano Martinazzi & Andrea Flori, 2020. "The evolving topology of the Lightning Network: Centralization, efficiency, robustness, synchronization, and anonymity," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-18, January.
    16. Shu, Min & Zhu, Wei, 2020. "Real-time prediction of Bitcoin bubble crashes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    17. Bech, Morten L. & Atalay, Enghin, 2010. "The topology of the federal funds market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5223-5246.
    18. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2018. "Collective behavior of cryptocurrency price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 499-509.
    19. Ashadun Nobi & Sungmin Lee & Doo Hwan Kim & Jae Woo Lee, 2014. "Correlation and Network Topologies in Global and Local Stock Indices," Papers 1402.1552, arXiv.org.
    20. Shahzad, Syed Jawad Hussain & Hernandez, Jose Areola & Rehman, Mobeen Ur & Al-Yahyaee, Khamis Hamed & Zakaria, Muhammad, 2018. "A global network topology of stock markets: Transmitters and receivers of spillover effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 2136-2153.
    21. Kulkarni, Saumitra & Pharasi, Hirdesh K. & Vijayaraghavan, Sudharsan & Kumar, Sunil & Chakraborti, Anirban & Samal, Areejit, 2024. "Investigation of Indian stock markets using topological data analysis and geometry-inspired network measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    22. Corbet, Shaen & Meegan, Andrew & Larkin, Charles & Lucey, Brian & Yarovaya, Larisa, 2018. "Exploring the dynamic relationships between cryptocurrencies and other financial assets," Economics Letters, Elsevier, vol. 165(C), pages 28-34.
    23. Rai, Anish & Mahata, Ajit & Nurujjaman, Md & Majhi, Sushovan & Debnath, Kanish, 2022. "A sentiment-based modeling and analysis of stock price during the COVID-19: U- and Swoosh-shaped recovery," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    24. Yi, Shuyue & Xu, Zishuang & Wang, Gang-Jin, 2018. "Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 98-114.
    25. Tong, Zhongwen & Chen, Zhanbo & Zhu, Chen, 2022. "Nonlinear dynamics analysis of cryptocurrency price fluctuations based on Bitcoin," Finance Research Letters, Elsevier, vol. 47(PB).
    26. Tomaso Aste, 2019. "Cryptocurrency market structure: connecting emotions and economics," Papers 1903.00472, arXiv.org.
    27. Evrim Mandaci, Pinar & Cagli, Efe Caglar, 2022. "Herding intensity and volatility in cryptocurrency markets during the COVID-19," Finance Research Letters, Elsevier, vol. 46(PB).
    28. Khanra, Pitambar & Ghosh, Subrata & Alfaro-Bittner, Karin & Kundu, Prosenjit & Boccaletti, Stefano & Hens, Chittaranjan & Pal, Pinaki, 2022. "Identifying symmetries and predicting cluster synchronization in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    29. Tomaso Aste, 2019. "Cryptocurrency market structure: connecting emotions and economics," Digital Finance, Springer, vol. 1(1), pages 5-21, November.
    30. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2017. "Asymmetric volatility connectedness on the forex market," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 39-56.
    31. Mahata, Ajit & Rai, Anish & Nurujjaman, Md. & Prakash, Om, 2021. "Modeling and analysis of the effect of COVID-19 on the stock price: V and L-shape recovery," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    32. Ashadun Nobi & Seong Eun Maeng & Gyeong Gyun Ha & Jae Woo Lee, 2013. "Random Matrix Theory and Cross-correlations in Global Financial Indices and Local Stock Market Indices," Papers 1302.6305, arXiv.org.
    33. Papana, Angeliki & Kyrtsou, Catherine & Kugiumtzis, Dimitris & Diks, Cees, 2017. "Financial networks based on Granger causality: A case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 65-73.
    34. C. Baek & M. Elbeck, 2015. "Bitcoins as an investment or speculative vehicle? A first look," Applied Economics Letters, Taylor & Francis Journals, vol. 22(1), pages 30-34, January.
    35. Liu, Haitao, 2008. "The complexity of Chinese syntactic dependency networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 3048-3058.
    36. Leonardo H. S. Fernandes & Werner Kristjanpoller & Benjamin Miranda Tabak, 2023. "Asymmetric Multifractal Cross-Correlation Dynamics Between Fiat Currencies And Cryptocurrencies," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 31(01), pages 1-20.
    37. Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019. "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 257-272.
    38. Dror Y Kenett & Michele Tumminello & Asaf Madi & Gitit Gur-Gershgoren & Rosario N Mantegna & Eshel Ben-Jacob, 2010. "Dominating Clasp of the Financial Sector Revealed by Partial Correlation Analysis of the Stock Market," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-14, December.
    39. Ji, Qiang & Geng, Jiang-Bo & Tiwari, Aviral Kumar, 2018. "Information spillovers and connectedness networks in the oil and gas markets," Energy Economics, Elsevier, vol. 75(C), pages 71-84.
    40. Mahata, Ajit & Bal, Debi Prasad & Nurujjaman, Md, 2020. "Identification of short-term and long-term time scales in stock markets and effect of structural break," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    41. Salam Rabindrajit Luwang & Anish Rai & Md. Nurujjaman & Om Prakash & Chittaranjan Hens, 2024. "High-Frequency Stock Market Order Transitions during the US-China Trade War 2018: A Discrete-Time Markov Chain Analysis," Papers 2405.05634, arXiv.org.
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