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Side Effects and Interactions: Exploring the Relationship between Dirty and Green Cryptocurrencies and Clean Energy Stock Indices

Author

Listed:
  • Rui Dias

    (Instituto Superior de Gestão, (ISG - Business and Economics School), CIGEST, Lisbon, Portugal and ESCAD – Instituto Politécnico da Lusofonia, Lisbon, Portugal)

  • Mariana Chambino

    (School of Business and Administration, Instituto Politécnico de Setúbal, Setúbal, Portugal)

  • Rosa Galvão

    (Department of Accounting and Finance, School of Business and Administration, Instituto Politécnico de Setúbal, Setúbal, Portugal)

  • Paulo Alexandre

    (Department of Accounting and Finance, School of Business and Administration, Instituto Politécnico de Setúbal, Setúbal, Portugal)

  • Mohammad Irfan

    (Business School, NSB Academy, India)

Abstract

This study aimed to assess whether renewable energy cryptocurrencies such as Cardano (ADA), Ripple (XRP), IOTA (MIOTA), and Stellar (XLM) can be considered hedging assets and safe havens for cryptocurrencies classified as "dirty", such as Bitcoin Cash (BCH), Bitcoin (BTC) Litcoin (LTC), Ethereum (ETH), Ethereum Classic (ETC) and the clean energy stock indices WILDERHILL Clean Energy (ECO) and Clean Energy Fuels (CLNE), from July 6, 2018, to July 6, 2023. The results show that the movements decreased significantly during the Stress period, which includes the events of 2020 and 2022. The Cardano cryptocurrency shows moderate movements, indicating stability and diversification, while Stellar shows moderate movements that suggest resilience. Conversely, XRP shows varied movements, requiring some caution, while IOTA stands out for significant movements associated with sustainable assets. These results interest players operating in these markets when they want to diversify and rebalance their portfolios.

Suggested Citation

  • Rui Dias & Mariana Chambino & Rosa Galvão & Paulo Alexandre & Mohammad Irfan, 2024. "Side Effects and Interactions: Exploring the Relationship between Dirty and Green Cryptocurrencies and Clean Energy Stock Indices," International Journal of Energy Economics and Policy, Econjournals, vol. 14(3), pages 411-416, May.
    • Handle: RePEc:eco:journ2:2024-03-41
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Cryptocurrencies; Clean Energies; Comovements; Safe Haven; Portfolio Rebalancing;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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