Here are the 94 factors that are used in the AI paper discussed in this thread. Compustat codes are used, but should be easy to translate using our Line Items spreadsheet.

These factors are also used in many other academic papers. The original paper by Green Et al. is here.

Many of these factors are already available in P123, others should be easily formulated. We’re reviewing them to see which one we should add as pre-defined.

I am compiling an excel spreadsheet with all 94 factors with references. I will share the spreadsheet so that we can all contribute and input the P123 formulas for each factors.

Hello P123 community. This is the working copy for the compiled list of 94Factors. Lets all work together on the P123 formulas. Just put in your username on a factor, if you will be working to create the formula.

I have looked at some meta-studies that have made factor discoveries that can be verified. Among other, Cross-Sectional Asset Pricing (CSAP) which has 161 different factors, Taming the factor Zoo (TFZ), has 97 different factors and Pricing via Machine Learning has 94 factors (APVML).

I’ve collected them in a sheet. There I have sorted them by return. For APVML, I build on the work of Sraby.

I am looking for a simple explanation of what is the finding of each of the studies.
I have found something on CSAP (CSAP Details) and AVPML (94- FactorLab@CityUHK), but not on AQR’s study “TFZ”.
I see that some of the studies overlap, so I can find the explanation in one of the others, but I am looking for some good overview sheets with brief explanations of the findings.
Has anyone made such an outline that they want to share?
And like Sraby, hope more people will help create a joint sheet with the codes of P123 for part of the major studies .