A Copula-Augmented Nelson–Siegel Model for ESG Bond Portfolio Optimization

This article presents a novel copula-based no-arbitrage pricing framework for forecasting bond returns and optimizing bond portfolios. Extending the dynamic Nelson-Siegel model with regular vine copulas for term structure dependencies, we generate step-ahead forecasts for zero-coupon bond yields, which we subsequently apply to obtain and simulate the no-arbitrage prices for both callable and non-callable fixed-coupon bonds. These simulated bond prices serve as inputs for a novel convex multiobjective portfolio optimization, incorporating key criteria such as ESG score, average return, Conditional Value-at-Risk (CVaR), distance-to-default, transaction cost, and option-adjusted duration and convexity. Applying our methodology to a dataset of 879 corporate bonds denominated in euros from January 2016 to July 2024, we demonstrate that the suggested copula-based no-arbitrage pricing framework takes advantage of the yield curve non-linear dependence structure and offers bond portfolios that consistently outperform those portfolios based on the classical dynamic Nelson-Siegel approach and an equally weighted (EQW) benchmark in terms of higher returns and Sharpe ratios while effectively reducing tail risk.