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ESG, clean energy, and petroleum futures markets: Asymmetric return connectedness and hedging effectiveness

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  • Bhattacherjee, Purba
  • Mishra, Sibanjan
  • Bouri, Elie
  • Wee, Jung Bum

Abstract

This study investigates the asymmetric return connectedness and portfolio implications among environmental, social and governance (ESG) exchange-traded funds (ETFs), clean energy ETFs, and five petroleum futures markets from December 2016 to December 2022. To this end, it uses an asymmetric time-varying approach of connectedness and constructs portfolios using minimum variance portfolio (MVP), minimum correlation portfolio (MCP), and minimum connectedness portfolio (MCoP). The results show that negative return connectedness is stronger than positive ones across most of the sample period, especially around the peak of the COVID-19 pandemic. The dynamic of net connectedness between markets is altered by the pandemic. ESG ETFs are more connected to petroleum futures markets than clean energy ETFs. The connectedness is strong during the COVID-19 outbreak, which suggests the instability of the system of return connectedness during the global health crisis. The minimum connectedness portfolio approach reflects the asymmetric and non-asymmetric return connectedness more than other portfolio approaches. Notably, clean energy and ESG ETF exhibit a safe-haven property under both symmetry and asymmetry in return connectedness. The findings are insightful from investment and policy perspectives.

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  • Bhattacherjee, Purba & Mishra, Sibanjan & Bouri, Elie & Wee, Jung Bum, 2024. "ESG, clean energy, and petroleum futures markets: Asymmetric return connectedness and hedging effectiveness," International Review of Economics & Finance, Elsevier, vol. 94(C).
    • Handle: RePEc:eee:reveco:v:94:y:2024:i:c:s1059056024003678
    DOI: 10.1016/j.iref.2024.103375
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    More about this item

    Keywords

    Asymmetric connectedness; ESG; Clean energy and crude oil; Portfolio management; COVID-19 outbreak; Russia-Ukraine conflict;
    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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