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Return and volatility connectedness of the non-fungible tokens segments

Author

Listed:
  • Umar, Zaghum
  • Alwahedi, Wafa
  • Zaremba, Adam
  • Vo, Xuan Vinh

Abstract

Non-fungible tokens (NFTs) have garnered attention from investors and the general public. This pioneering study analyzes the connectedness of five NFT segments by employing the TVP-VAR based connectedness approach of Antonakakis et al. (2020) to identify the transmitter and receivers of spillover for both return and volatility of NFT segments. Our results show that Utility NFTs are the main transmitter of spillover, whereas the collectible NFTs are the main recipient of spillover for both return and volatility. Our findings have important implications for both investors and policy makers.

Suggested Citation

  • Umar, Zaghum & Alwahedi, Wafa & Zaremba, Adam & Vo, Xuan Vinh, 2022. "Return and volatility connectedness of the non-fungible tokens segments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 35(C).
    • Handle: RePEc:eee:beexfi:v:35:y:2022:i:c:s2214635022000405
    DOI: 10.1016/j.jbef.2022.100692
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    References listed on IDEAS

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    1. Umar, Zaghum & Gubareva, Mariya & Teplova, Tamara & Tran, Dang K., 2022. "Covid-19 impact on NFTs and major asset classes interrelations: Insights from the wavelet coherence analysis," Finance Research Letters, Elsevier, vol. 47(PB).
    2. Umar, Zaghum & Gubareva, Mariya, 2020. "A time–frequency analysis of the impact of the Covid-19 induced panic on the volatility of currency and cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    3. Umar, Zaghum & Trabelsi, Nader & Alqahtani, Faisal, 2021. "Connectedness between cryptocurrency and technology sectors: International evidence," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 910-922.
    4. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    5. Spierdijk, Laura & Umar, Zaghum, 2014. "Stocks for the long run? Evidence from emerging markets," Journal of International Money and Finance, Elsevier, vol. 47(C), pages 217-238.
    6. Zaghum Umar & Dennis Olson, 2022. "Strategic asset allocation and the demand for real estate: international evidence," Empirical Economics, Springer, vol. 62(5), pages 2461-2513, May.
    7. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    8. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    9. Matthieu Nadini & Laura Alessandretti & Flavio Di Giacinto & Mauro Martino & Luca Maria Aiello & Andrea Baronchelli, 2021. "Mapping the NFT revolution: market trends, trade networks and visual features," Papers 2106.00647, arXiv.org, revised Sep 2021.
    10. David Y. Aharon & Zaghum Umar & Xuan Vinh Vo, 2021. "Dynamic spillovers between the term structure of interest rates, bitcoin, and safe-haven currencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-25, December.
    11. Umar, Zaghum & Jareño, Francisco & González, María de la O, 2021. "The impact of COVID-19-related media coverage on the return and volatility connectedness of cryptocurrencies and fiat currencies," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
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    Cited by:

    1. Qi, Haozhi & Ma, Lijun & Peng, Pin & Chen, Hao & Li, Kang, 2022. "Dynamic connectedness between clean energy stock markets and energy commodity markets during times of COVID-19: Empirical evidence from China," Resources Policy, Elsevier, vol. 79(C).
    2. Menvouta, Emmanuel Jordy & Serneels, Sven & Verdonck, Tim, 2023. "Practicable optimization for portfolios that contain nonfungible tokens," Finance Research Letters, Elsevier, vol. 55(PB).
    3. Umar, Zaghum & Polat, Onur & Choi, Sun-Yong & Teplova, Tamara, 2022. "Dynamic connectedness between non-fungible tokens, decentralized finance, and conventional financial assets in a time-frequency framework," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    4. Fang, Sheng & Cao, Guangxi & Egan, Paul, 2023. "Forecasting and backtesting systemic risk in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 54(C).
    5. Lu, Xunfa & Huang, Nan & Mo, Jianlei & Ye, Zhitao, 2023. "Dynamics of the return and volatility connectedness among green finance markets during the COVID-19 pandemic," Energy Economics, Elsevier, vol. 125(C).

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    More about this item

    Keywords

    Return connectedness; COVID-19; Non-fungible tokens; NFT spillover;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • F3 - International Economics - - International Finance
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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