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Herding behavior in conventional cryptocurrency market, non-fungible tokens, and DeFi assets

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  • Yousaf, Imran
  • Yarovaya, Larisa

Abstract

We examine the static and time-varying herding behavior in three cryptocurrency classes: ‘conventional’ cryptocurrencies, non-fungible tokens, and DeFi assets during the most recent cryptocurrency bubble of 2021. While static herding analysis failed to demonstrate any evidence of herding, the time-varying herding has been identified in conventional cryptocurrencies and DeFi assets for the short investment horizons. The herding asymmetry analysis reveals that herding is not evident in conventional cryptocurrencies and NFT during up/down market, high/low volatility days, and high/low trading days. We only find herding in DeFi assets during the low volatility days.

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  • Yousaf, Imran & Yarovaya, Larisa, 2022. "Herding behavior in conventional cryptocurrency market, non-fungible tokens, and DeFi assets," Finance Research Letters, Elsevier, vol. 50(C).
    • Handle: RePEc:eee:finlet:v:50:y:2022:i:c:s1544612322004822
    DOI: 10.1016/j.frl.2022.103299
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    Cited by:

    1. Bejaoui, Azza & Frikha, Wajdi & Jeribi, Ahmed & Bariviera, Aurelio F., 2023. "Connectedness between emerging stock markets, gold, cryptocurrencies, DeFi and NFT: Some new evidence from wavelet analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    2. Ugolini, Andrea & Reboredo, Juan C. & Mensi, Walid, 2023. "Connectedness between DeFi, cryptocurrency, stock, and safe-haven assets," Finance Research Letters, Elsevier, vol. 53(C).
    3. Yousaf, Imran & Jareño, Francisco & Tolentino, Marta, 2023. "Connectedness between Defi assets and equity markets during COVID-19: A sector analysis," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    4. Yousaf, Imran & Jareño, Francisco & Martínez-Serna, María-Isabel, 2023. "Extreme spillovers between insurance tokens and insurance stocks: Evidence from the quantile connectedness approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    5. 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).
    6. Yousaf, Imran & Jareño, Francisco & Esparcia, Carlos, 2022. "Tail connectedness between lending/borrowing tokens and commercial bank stocks," International Review of Financial Analysis, Elsevier, vol. 84(C).
    7. Jareño, Francisco & Yousaf, Imran, 2023. "Artificial intelligence-based tokens: Fresh evidence of connectedness with artificial intelligence-based equities," International Review of Financial Analysis, Elsevier, vol. 89(C).
    8. Yongzhi Gong & Xiaofei Tang & En-Chung Chang, 2023. "Group norms and policy norms trigger different autonomous motivations for Chinese investors in cryptocurrency investment," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-10, December.
    9. Artor Nuhiu & Florin Aliu & Jakub Horák & Bedri Peci, 2023. "Making Informed Decisions in the Volatile Crypto Market: An Analysis of Portfolio Risk and Return," SAGE Open, , vol. 13(3), pages 21582440231, August.

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    More about this item

    Keywords

    NFT herding; Cryptocurrencies; Non-fungible tokens; DeFi assets; Cryptocurrency bubble;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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