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March 6, 2026Research in International Business and Finance2 citationsOpen Access

Investigating the Connectedness of Oil Price Shocks with Clean and Dirty Cryptocurrencies

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AŠAleksandar Ševi掊Željko ŠevićAFAthanasios Fassas

Key Points

  • The aim is to analyze how oil price shocks affect the interconnectedness of clean and dirty cryptocurrencies before, during, and after the COVID-19 pandemic.
  • Analyzed five clean and five dirty cryptocurrencies from October 2017 to April 2024
  • Utilized decomposed and partial connectedness measures
  • Applied time-varying parameter vector autoregression (TVP-VAR) models to evaluate relationships among variables
  • Oil price shocks significantly impacted cryptocurrencies during the pandemic compared to before and after
  • Clean cryptocurrencies showed net receipt of shocks, while dirty ones were net transmitters
  • The distinction between clean and dirty cryptocurrencies diminished during the crisis but reemerged post-COVID

Abstract

There is a strong impetus to make cryptocurrencies more environmentally friendly, and in our study it is has been analyzed whether commodity price shocks have varying impacts on clean and dirty cryptocurrency interconnectedness before, during and after the COVID-19 pandemic. Using the decomposed and partial connectedness measure we evaluate the connectedness of oil price shocks, demand, supply and risk, as well as five clean and five dirty cryptocurrencies from October 2017 until April 2024. The spikes in demand and disruptions in oil supply lead to price increases. Oil shocks have the largest impact on sampled crypto products during the COVID-19 period, as opposed to pre- and post-pandemic years, and they demonstrate a stronger influence on selected cryptocurrencies than internal crypto-to-crypto dynamics. During the crisis, the difference between clean and dirty cryptocurrencies becomes less relevant when compared to no-crisis periods. We also find that clean cryptocurrencies are net recipients of shocks, while dirty counterparts, dominated by Bitcoin and Ethereum, are net transmitters, especially during the recovery phase. Our findings are relevant for supporting the transition to clean cryptocurrencies and contribute to a better understanding of dynamic interconnectedness. • Examines the decomposed and partial connectedness • Uses time-varying parameter vector autoregression (TVP-VAR) models • Highlights the heterogeneity in cryptos’ responses to oil price fluctuations • Total Connectedness Index peaks during the COVID-19 pandemic • The distinctions between clean and dirty cryptocurrencies reemerged post-COVID

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Cite This Study

Šević et al. (2026) studied this question.

synapsesocial.com/papers/69aa6f3c531e4c4a9ff5945bhttps://doi.org/10.1016/j.ribaf.2026.103351
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