Narrow Results

We propose new multifactor models to explain the accruals anomaly. Our baseline model represents an application of Merton’s ICAPM in which the key factors represent (innovations on) the term and small-value spreads. The model shows large explanatory power for cross-sectional risking premia associated with three accruals portfolio groups. A scaled version of the model shows better performance, suggesting that accruals risk premia are related with the business cycle. Both models compare favorably with popular multifactor models used in the literature, and also perform well in pricing other important anomalies. The risk price estimates of the hedging factors are consistent with the ICAPM framework.

This study investigates two ways that sample selection can impact inferences about market efficiency: (1) unintentional, nonrandom exclusion of observations because of lack of available data for some firm-years (“passive deletion”); and (2) the effects of extreme return observations. The analysis proposes and illustrates a set of simple diagnostic tests designed to assess the sensitivity of estimated hedge portfolio returns to sample composition. These diagnostics are applied to the accrual anomaly and the forecast-to-price anomaly and the results indicate that the forecast-to-price anomaly is not robust to the effects of passive deletion. Moreover, extreme returns — as few as 100 firm-year observations — appear to generate the observed abnormal returns to both strategies.