Enhancing portfolio decision-making: a capital asset pricing model-based clustering analysis

Abstract

Purpose To enhance portfolio decision-making using a capital asset pricing model-based clustering analysis. Design/methodology/approach Capital asset pricing model (CAPM); K-means clustering; agglomerative clustering. Findings Employing clustering along with CAPM to identify varying levels of risk appetite among customers enables the customization of security recommendations, enhancing client satisfaction and portfolio performance. Originality/value By employing multi-factor models as the foundation for clustering, thereby integrating additional dimensions of risk and return.