HIGHLIGHTS
- who: Vitor Azevedo from the Department of Business Studies and Economics, Technical University Kaiserslautern, Gottliebu2011Daimleru2011Strau00dfe, Kaiserslautern, Germany have published the paper: Enhancing stock market anomalies with machine learning, in the Journal: (JOURNAL)
- what: The authors 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 firmmonth anomaly observations. The authors show the performance of both individual anomalies and the linear baseline factor (Sect 4). The authors focus on investigating the additional performance of machine_learning algorithms compared to traditional factor . . .
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