Using data from surveys as well as as real transactions we analyze which and why investors choose funds with performance fees even though these funds may be more expensive. According to agency theory, performance fees could incentivize managers to achieve better returns, but they could also...

We explore the dimensionality of stock returns in North America, Europe, Japan, Pacific, and Emerging Markets on the basis of 240 cross-sectional predictors. Our approach allows us to identify those predictors that are most consistently related to nonmicro-cap stock returns (i.e., independent of...

Prior research has shown that information diffuses gradually across stocks that are economically linked at the industry level. I document a similar pattern when stock portfolios are formed based on characteristics that are used in the anomaly literature (e.g., size, value, asset growth)....

We demonstrate that firm-specific momentum profits are predictable across a wide range of international equity markets when combining information given in a multitude of stock characteristics. This predictor is comparatively simple to compute and can yield significant positive out-of-sample...

We examine the out-of-sample performance of 240 stock market anomalies enhanced by 49 machine learning algorithms and over 260 individually trained models across an international data sample of nearly 1.9 billion stock-month-anomaly observations from 1980 to 2019. We demonstrate significant...