Does Green Improve Portfolio Optimisation?

Md Akhtaruzzaman, A.K. Banerjee, Sabri Boubaker and F. Moussa

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Abstract: Our study uses the GARCH-EVT-copula model to develop out-of-sample forecasts for diverse asset classes, including a green asset. To construct optimal portfolios, we apply four different portfolio allocation techniques: equal weighting, minimum variance, global minimum variance (GMV), and certainty equivalence tangency (CET) criteria. The results demonstrate that the GMV portfolio outperforms other portfolios in risk measures. Further, backtesting evidence shows that the portfolio containing a green asset performs better than the benchmark for short horizons. The results have implications for fund managers and policymakers since green asset provides valuable diversification benefits and further the cause of sustainable development. \textcopyright 2023 The Authors

Keywords: benchmarking; CVaR; energy market; environmental economics; financial market; Global minimum; Global optimization; Green asset; green economy; Green finance; Greenness; Minimum variance; optimization; Portfolio optimisation; Portfolio optimization; Risk assessment; Social development; Social development goal; Social development goals (SDGs); sustainable development; VaR (search for similar items in EconPapers)
Date: 2023
Note: View the original document on HAL open archive server: https://normandie-univ.hal.science/hal-04435509v1
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Citations: View citations in EconPapers (5)

Published in Energy Economics, 2023, 124, ⟨10.1016/j.eneco.2023.106831⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04435509

DOI: 10.1016/j.eneco.2023.106831

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