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An empirical study of risk diffusion in the cryptocurrency market based on the network analysis

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  • Yang, Ming-Yuan
  • Wu, Zhen-Guo
  • Wu, Xin

Abstract

This paper studies the risk diffusion in the cryptocurrency market during the period from 2018 to 2021 based on the network analysis. By comparing the network topologies of cryptocurrency, stock and foreign exchange networks, we find that risks may diffuse more easily in the cryptocurrency market rather than traditional financial markets. We also measure the breadth and depth of risk diffusion for cryptocurrencies, and build panel regression models to identify what contributes to the risk diffusion. Our findings show that cryptocurrencies with large market capitalization, and others that experience decline in prices or low-turnover also contribute to the risk diffusion.

Suggested Citation

  • Yang, Ming-Yuan & Wu, Zhen-Guo & Wu, Xin, 2022. "An empirical study of risk diffusion in the cryptocurrency market based on the network analysis," Finance Research Letters, Elsevier, vol. 50(C).
    • Handle: RePEc:eee:finlet:v:50:y:2022:i:c:s1544612322003890
    DOI: 10.1016/j.frl.2022.103180
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    Cited by:

    1. Yang, Ming-Yuan & Wang, Chengjin & Wu, Zhen-Guo & Wu, Xin & Zheng, Chengsi, 2023. "Influential risk spreaders and their contribution to the systemic risk in the cryptocurrency network," Finance Research Letters, Elsevier, vol. 57(C).
    2. Jalan, Akanksha & Matkovskyy, Roman, 2023. "Systemic risks in the cryptocurrency market: Evidence from the FTX collapse," Finance Research Letters, Elsevier, vol. 53(C).
    3. Pattnaik, Debidutta & Hassan, M. Kabir & Dsouza, Arun & Tiwari, Aviral & Devji, Shridev, 2023. "Ex-post facto analysis of cryptocurrency literature over a decade using bibliometric technique," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    4. Walid Mensi & Mariya Gubareva & Hee-Un Ko & Xuan Vinh Vo & Sang Hoon Kang, 2023. "Tail spillover effects between cryptocurrencies and uncertainty in the gold, oil, and stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
    5. Amogh Shukla & Tapan Kumar Das & Sanjiban Sekhar Roy, 2023. "TRX Cryptocurrency Profit and Transaction Success Rate Prediction Using Whale Optimization-Based Ensemble Learning Framework," Mathematics, MDPI, vol. 11(11), pages 1-27, May.

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    More about this item

    Keywords

    Cryptocurrency market; Risk diffusion; Network analysis;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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