A Cardinality-Constrained Portfolio Selection Model Using Golden Eagle Optimizer in Stock Markets

This electronic document is a "live" template and Abstract—In the realm of capital markets, it is imperative for investors to select the most optimal assets considering various portfolio constraints. This paper introduces a model for cardinality-constrained portfolio selection by employing the Golden Eagle Optimizer (GEO) to optimize anticipated returns and the associated risk. To assess the efficacy of the suggested approach, an empirical investigation was carried out by utilizing the three widely recognized benchmark problems (Heng Seng 31, S&P 100, Nikki 225, Dax 100, and FTSE). This involved a performance comparison between the proposed strategy and other contemporary techniques found in the literature. The findings obtained from the study indicate that the GEO approach performs better in addressing large-scale cardinality-constrained portfolio optimization.