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Quantile connectedness of artificial intelligence tokens with the energy sector

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Listed:
  • Farooq Malik
  • Zaghum Umar

Abstract

Artificial intelligence (AI) tokens are digital assets that integrate AI capabilities by operating on decentralized networks using AI algorithms in order to automate tasks, make intelligent decisions, and swiftly adapt based on data. Given that AI tokens are energy intensive assets, in this paper, we explore how major AI tokens are connected to oil, natural gas, and biofuel under extreme market movements using daily data from June 2019 to March 2024. We find that AI tokens are net transmitters of shocks while the entire energy sector is the net receiver of shocks at the return level. However, both AI tokens and oil are net transmitters of shocks at the volatility level. We also show that total dynamic connectedness significantly increased during the start of COVID‐19 pandemic and the Russian‐Ukraine war. Our quantile‐based connectedness analysis further shows that return and volatility connectedness is considerably higher at low and high quantiles, indicating that shocks to AI tokens spread more intensely during extreme market movements. These results indicate that AI tokens are subject to contagion and thus offer inadequate portfolio diversification under major market movements.

Suggested Citation

  • Farooq Malik & Zaghum Umar, 2025. "Quantile connectedness of artificial intelligence tokens with the energy sector," Review of Financial Economics, John Wiley & Sons, vol. 43(2), pages 135-146, April.
    • Handle: RePEc:wly:revfec:v:43:y:2025:i:2:p:135-146
    DOI: 10.1002/rfe.1224
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