A Taxonomy of Anomalies and their Trading Costs 2015, Robert Novy-Marx and Mihail Velikov (with data)
…and the Cross-Section of Expected Returns, 2013, Campbell Harvey, Yan Liu, Caroline Zhu (factor list)
A Comparison of New Factor Models, 2014, Kewei Hou, Chen Xue, Lu Zhang
The Supraview of Return Predictive Signals, 2012, Jeremiah Green, John Hand, Frank Zhang
Does Academic Research Destroy Stock Return Predictability? 2012, David McLean, Jeffrey Pontiff
Shrinking the Cross Section, 2017, Serhiy Kozak, Stefan Nagel
Fundamental Analysis and the Cross-Section of Stock Returns: A Data-Mining Approach, 2017, Xuemin (Sterling) Yan, Lingling Zheng
p-Hacking: Evidence from Two Million Trading Strategies, 2017, Tarun Chordia, Amit Goyal, Alessio Saretto
Taming the Factor Zoo: A Test of New Factors, 2017, Guanhao Feng, Stefano Giglio, Dacheng Xiu
Empirical Asset Pricing via Machine Learning, 2019, Shihao Gu, Bryan T. Kelly, Dacheng Xiu
Post blog publication additions:
Time Series Variation in the Factor Zoo, 2022, Bessembinder, Burt, Hrdlicka
Enhancing Stock Market Anomalies with Machine Learning, 2021, Azevedo, Vitor, Hoegner, Christopher
Open Source Cross-Sectional Asset Pricing, 2020, Chen, Andrew, Zimmermann, Tom
The World of Anomalies: Smaller Than We Think?, 2020, Hollstein, Fabian
Zeroing in on the Expected Returns of Anomalies 2020, Chen Andrew, Velikov, Mihail
Anomalies across the globe: Once public, no longer existent? 2020, Jacobs, Heiko, Müllerb, Sebastian
Does it pay to follow anomalies research? Machine learning approach with international evidence? 2020, Tobek, Ondrej, Hronec, Martin
...And Nothing Else Matters? On the Dimensionality and Predictability of International Stock Returns, 2018, Jacobs, Heiko, Müllerb, Sebastian
Replicating Anomalies 2017, Hou, Xue, Zhang
PS.
Please share new ones here @msamonov
thanks @AdamZaremba and @RyanPKirlin for sending over some great ones I missed.