We evaluate the relation between 133 anomalies/factors and market states using a sample of 57 countries from 1980 to 2019. The vast majority (96 of 133; 50 significant at the 5% level) performs better in bad times; 9 anomalies perform significantly better in good times, including market, size, value, and momentum. The value-weighted four-factor alpha amounts to 47.7 (31.8) bps in bad (good) times. 92.9% of the performance gain in bad times is driven by the anomaly short side. Findings are robust to controlling for sentiment or recession indicators and highlight the importance of mispricing in explaining anomaly returns.

We evaluate the relative and absolute performance of competing factor-based asset pricing models in international regions and globally. Our holistic analysis controls for model transaction costs and incorporates both right-hand-side tests (based on maximum squared Sharpe ratios) and left-hand-side tests (individual return predictors, composite mispricing proxies). The overall view of the tests shows that recently proposed models tend to perform better than classical models, but otherwise perform comparably. This finding, the performance of the models in some of the LHS tests as well as further results collectively suggest the need for new powerful asset pricing models for global equity markets.