Trust anomalies’ judgment: Social ranking theories for portfolio construction

This paper presents a novel approach to anomaly-based portfolio construction, integrating multiple market anomalies into a unified selection framework. We adapt the Majority Judgment (MJ) method from social choice theory to financial decision-making, ranking stocks based on multiple anomalies, each treated as an independent evaluation criterion. Using 23 years of U.S. equity data and 11 stock anomalies, we construct equal-and value-weighted decile portfolios based on both single-factor breakpoints and MJ rankings. Our empirical results show that MJ-based portfolios consistently outperform single-factor strategies across most configurations and remain robust to changes in reallocation schedules, voter count, and voting system specifications. Comparative experiments highlight that MJ is more resilient to portfolio weighting choices and market regimes include than conventional anomaly aggregation methods and achieves the strongest performance under annual rebalancing. These findings underscore MJ's robustness and scalability in high-dimensional financial decision-making, offering a transparent and interpretable alternative for multi-factor portfolio construction.