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Time-frequency extreme risk spillover network of cryptocurrency coins, DeFi tokens and NFTs

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  • Qiao, Xingzhi
  • Zhu, Huiming
  • Tang, Yiding
  • Peng, Cheng

Abstract

This study examines the time-frequency extreme risk spillover network among cryptocurrency coins, decentralized finance and non-fungible tokens via wavelet-based quantile causality analysis. We derive the following empirical results. First, long-lived coins dominate cryptocurrencies’ upside and downside risk networks. Second, yield farming tokens exacerbate decentralized finance's depreciation risk but hedge risk in the medium term. Metaverse-related non-fungible tokens are the center of NFTs’ upside risk network but reverse in the long term. Third, traditional concepts affect the depreciation risk, and emerging concepts drive market prosperity in the long run. Overall, these can provide investors with diversified strategies and risk management suggestions.

Suggested Citation

  • Qiao, Xingzhi & Zhu, Huiming & Tang, Yiding & Peng, Cheng, 2023. "Time-frequency extreme risk spillover network of cryptocurrency coins, DeFi tokens and NFTs," Finance Research Letters, Elsevier, vol. 51(C).
    • Handle: RePEc:eee:finlet:v:51:y:2023:i:c:s1544612322006651
    DOI: 10.1016/j.frl.2022.103489
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    Cited by:

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    2. Ali, Shoaib & Al-Nassar, Nassar S. & Naveed, Muhammad, 2024. "Bridging the gap: Uncovering static and dynamic relationships between digital assets and BRICS equity markets," Global Finance Journal, Elsevier, vol. 60(C).
    3. Elsayed, Ahmed H. & Hoque, Mohammad Enamul & Billah, Mabruk & Alam, Md. Kausar, 2024. "Connectedness across meme assets and sectoral markets: Determinants and portfolio management," International Review of Financial Analysis, Elsevier, vol. 93(C).
    4. Mensi, Walid & Gubareva, Mariya & Kang, Sang Hoon, 2024. "Frequency connectedness between DeFi and cryptocurrency markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 93(C), pages 12-27.
    5. Zhongzheng, Wang, 2023. "Extreme risk transmission mechanism between oil, green bonds and new energy vehicles," Innovation and Green Development, Elsevier, vol. 2(3).
    6. Elie Bouri & Matteo Foglia & Sayar Karmakar & Rangan Gupta, 2024. "Return-Volatility Nexus in the Digital Asset Class: A Dynamic Multilayer Connectedness Analysis," Working Papers 202432, University of Pretoria, Department of Economics.
    7. Jalan, Akanksha & Matkovskyy, Roman, 2023. "Systemic risks in the cryptocurrency market: Evidence from the FTX collapse," Finance Research Letters, Elsevier, vol. 53(C).
    8. Dhoha Mellouli & Imen Zoglami, 2024. "The Dynamics of Connectivity between Traditional Cryptocurrencies and NFTs: Validation of the Connectivity Model by Quantiles and Frequencies," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 131-154.
    9. Lei, Heng & Xue, Minggao & Ye, Jing, 2024. "The nexus between ReFi, carbon, fossil energy, and clean energy assets: Quantile time–frequency connectedness and portfolio implications," Energy Economics, Elsevier, vol. 132(C).
    10. Ghaemi Asl, Mahdi & Raheem, Ibrahim D. & Rashidi, Muhammad Mahdi, 2023. "Do stochastic risks flow between industrial and precious metals, Islamic stocks, green bonds, green stocks, clean investments, major foreign exchange rates, and Bitcoin?," Resources Policy, Elsevier, vol. 86(PA).
    11. Proelss, Juliane & Sévigny, Stéphane & Schweizer, Denis, 2023. "GameFi: The perfect symbiosis of blockchain, tokens, DeFi, and NFTs?," International Review of Financial Analysis, Elsevier, vol. 90(C).
    12. Foglia, Matteo & Maci, Giampiero & Pacelli, Vincenzo, 2024. "FinTech and fan tokens: Understanding the risks spillover of digital asset investment," Research in International Business and Finance, Elsevier, vol. 68(C).

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    More about this item

    Keywords

    Cryptocurrency; DeFi tokens; NFTs; Wavelet; Quantile causality network;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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