Geertsema, PaulLu, Helen2024-05-292024-05-2920200378-426610.1016/j.jbankfin.2020.105934http://hdl.handle.net/20.500.12127/7479We consolidate a large number of mean-significant anomalies into cluster portfolios. More than a third of cluster portfolios remain significant under the Hou et al. (2020) five-factor model — the best performing among six benchmark models tested. A best-first search yields nine factors that subsume all cluster portfolios as well as all significant anomalies, demonstrating the feasibility of a parsimonious description of average realised returns. The expected growth factor (EG) and a cluster portfolio linked to accruals are prominent factors that improve pricing performance. The search-generated model produces a monthly maximum squared Sharpe ratio of 0.51, considerably higher than current benchmark models.enAnomaliesCorrelationCluster AnalysisMachine LearningAsset PricingJournal of Banking & Finance1872-6372317171306732