Analyzing Mutual Funds Behavior and Distinctiveness Across Sectors with Clustering and Hamming Distance: A 27-Year Study

This study examines behavior among mutual funds across five sectors, including energy, utilities, real estate, technology, and healthcare, over a 27-year period (1999–2025). For each year, using daily NAV returns, each fund is regressed against the S&P 500 to separate fund-specific performance from broader market movements. All the resulting residual vectors for each year and fund are clustered together. These annual cluster assignments are then linked across time to construct each fund’s trajectory, showing how its relative performance position shifts from year to year. These trajectories capture long-term behavioral divergence and provide a simple, intuitive visualization. To identify and characterize fund trajectory and distinctiveness, we apply methods based on residual magnitudes, quantile migration patterns, and Hamming distance measures of (cluster, time) fund trajectories. These trajectories reveal how certain funds consistently diverge from market behavior, thereby contributing to portfolio diversity in terms of trajectory separation. We introduce a portfolio Hamming diversification index that measures separation between trajectories. Using trajectories and Hamming distances, we examine how fund behavior changes during major market disruptions, including the dot-com crash (2001), the financial crisis (2009), and the COVID-19 pandemic (2020–2021), and identify sector-specific differences in how fund trajectories respond to these events. The proposed methodology is intended as an exploratory descriptive methodology for studying long-term behavioral trajectories rather than as a replacement for traditional asset-pricing or performance-evaluation models.