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A large number of neoclassical, behavioral, and bias-based theories try to explain the tendency of small, value, and winner stocks to outperform big, growth, and loser stocks, three well-known characteristic anomalies. Because the theories often predict similar relationships between a stock’s propensity to contribute to the anomalies and a set of correlated firm characteristics, existing studies focusing on single theories do not tell us which theory is most successful in explaining the anomalies. To fill this gap, we use a new non-parametric methodology to run a horse race between the theories. In the first step, we use statistical leverage analysis to find out which stocks are ultimately responsible for the anomalies. In the second, we use the firm characteristics suggested by the theories to forecast the identity of the anomaly drivers, with the purpose of determining which theory is most supported by the data. We find that behavioral theories are most convincing in explaining the size and book-to-market anomalies, while no theory is convincing in explaining the momentum anomaly.

Which stocks drive the size, value, and momentum anomalies and for how long? Evidence from a statistical leverage analysis