A novel utility-based approach for enhanced indexation

This paper proposes an enhanced index tracking framework based on a novel weighted cumulative utility area ratio (WCUAR) criterion to address the limitations in existing stochastic dominance approaches. By decomposing return distributions into gain and loss regions for pairwise asset comparisons and applying centroid-based weights, our method effectively captures asymmetric investor risk preferences. To reflect real-world investment conditions, we further integrate the cardinality constraint and transaction cost into the optimization framework. Empirical analysis on DJIA and S&P 500 datasets show that WCUAR-based strategies consistently outperform both benchmark indices and competing models across diverse market environments. These results highlight the method’s ability to balance investor preferences with computational feasibility, offering a practical tool for constructing robust enhanced index tracking portfolios.