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.
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