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Dynamic predictive pattern of non-fungible tokens: insight from uncertainties, geopolitical risk, and market sentiments

Author

Listed:
  • John Bambir

    (University of Cape Coast)

  • Patrick Kwashie Akorsu

    (University of Cape Coast)

  • John Kingsley Woode

    (University of Cape Coast)

  • Audrey Foriwaa Adjei

    (Southern Illinois University)

Abstract

Responding to the fluctuations in the digital asset markets against the incessant turmoil and the limited studies on the role of varying uncertainty measures in driving these assets, we examine the predictive capacity of uncertainty (world uncertainty, geopolitical risk, crypto volatility, and crypto uncertainty) on the most capitalized and tradable non-fungible tokens (NFTs) (Bored Ape Yacht Club, Bored Ape Kernel Club, Cryptopunks, Doodles, Mutant Ape Yacht Club, and Puddy Penguins) from April 2021 to October 2024. The quantile regression results highlight an adverse (positive) nexus between NFTs and WUI and VCRIX (UCRP and GPR), with WUI being the most robust factor in driving NFTs. The blend of adverse (positive) influence suggests that the NFT market possesses a diverging capacity in terms of hedge and safe haven, with WUI being the most detrimental measure derailing NFT-based investors from such luxury. UCRP positively influences NFTs, while ETH and BTC fail in such capacity. GPR has a limited adverse (positive) influence on BAYC and DUD (MAYC), indicating that only the latter can hedge against GPR. These results support the quantile-on-quantile estimations, highlighting the adaptive and heterogeneous influence of the sample uncertainties on NFTs. The causality-in-quantile results highlighted the predictive capability of all the uncertainty measures, with WUI and UCRP providing the most robust results across most of the quantiles, with GPR and VCRIX possessing limited influence, emphasizing the robust nature of these uncertainty measures on NFTs. These results provide insights into investor heterogeneity and adaptive behavior and the limited potential for diversification within the NFT markets. The results also have implications for NFT-based investors and ventures, speculators, market regulators and policies, and risk management.

Suggested Citation

  • John Bambir & Patrick Kwashie Akorsu & John Kingsley Woode & Audrey Foriwaa Adjei, 2025. "Dynamic predictive pattern of non-fungible tokens: insight from uncertainties, geopolitical risk, and market sentiments," Digital Finance, Springer, vol. 7(3), pages 299-345, September.
  • Handle: RePEc:spr:digfin:v:7:y:2025:i:3:d:10.1007_s42521-025-00134-7
    DOI: 10.1007/s42521-025-00134-7
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    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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