Title: Multiobjective optimization of ESG bond portfolios: A copula-based dynamic Nelson-Siegel approach Authors:  Andreas Stephan - Linnaeus University (Sweden) [presenting]
Maziar Sahamkhadam - Linnaeus University (Sweden)
Abstract: A copula-based pricing framework is presented for forecasting bond returns and optimizing multiobjective bond portfolios (MOBPs). Utilizing a copula-based dynamic factor model, we generate step-ahead forecasts for zero-coupon bond yields, which are applied to price both callable and non-callable fixed-coupon bonds. These simulated bond prices serve as inputs for convex multiobjective portfolio optimization, incorporating key criteria such as average returns, Conditional Value-at-Risk (CVaR), distance-to-default, transaction costs, and option-adjusted duration and convexity. Applying our methodology to a dataset of 879 environmental, social, and governance (ESG) bonds denominated in Euros from January 2016 to July 2024, we demonstrate that the proposed MOBP approach consistently outperforms an equally weighted (EQW) benchmark in terms of higher returns and Sharpe ratios while effectively mitigating tail risk. Notably, our framework improves portfolio resilience during market turbulence, such as the COVID-19 pandemic and the Russo-Ukrainian war, underscoring its applicability in risk-sensitive sustainable investing.