We propose a proxy for global equity mispricing (mispricing $R^2$) based on an instrumented principal component analysis of the return variation of 198 mispricing anomalies. We find that mispricing $R^2$ is higher for countries with lower market development, lower accounting quality, and higher...

We examine the predictability of 299 capital market anomalies enhanced by 30 machine learning approaches and over 250 models in a dataset with more than 500 million firm-month-anomaly observations. We find significant monthly (out-of-sample) returns of around 1.8-2.0%, and over 80% of the models...

I estimate a theory-based behavioral momentum using analysts' predictable underreaction (APU) as a proxy for newswatchers underreaction. The results show that APU strongly predicts analysts' errors and, more importantly, stock returns. A long-short strategy based on APU generates a...

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...

We examine the value of analyst recommendations across 45 countries and 3.8 million firm-month observations from 1994 to 2019. Recommendation-based portfolio strategies lead to highly significant (insignificant) abnormal returns in international markets (in the U.S.). In line with...

Liquidity, the ease of trading an asset, strongly varies between different sizes of stock positions. We analyze this aspect using the Xetra Liquidity Measure (XLM), which calculates daily, weighted spread for impatient traders transacting against the limit order book. For this measure, we have...