Abstract
This study investigated the hedging capabilities of green bonds for traditional asset classes in the US financial market from 2022 to 2023. Several portfolio construction methods, including Equal Weights, Genetic Algorithm (GA), and Markowitz Mean-Variance Optimization, were used alongside the DCC-GARCH model to examine time-varying correlations and volatilities. Portfolios including green bonds showed improved risk-adjusted returns, as demonstrated by an improved Sharpe ratio when using the Markowitz MVO approach and the Genetic Algorithm techniques. Notably, the Markowitz MVO approach uncovered a superior efficient frontier with the portfolio containing green bonds, reflecting improved risk management. All the portfolio construction technique further established that green bonds could effectively hedge against extreme losses, with better VaR and CVaR metrics across all portfolios including green bonds. These findings imply that green bonds serve as a valuable hedge against traditional assets like commodities, real estate, and other bonds and optimize portfolios by enhancing risk-adjusted returns and risk management. The study’s insights are specifically relevant for investors and portfolio managers aiming to manage risk exposure and for policymakers supporting the transition to sustainable investments.