Machine Learning Toolbox in Asset Pricing

ML_toolbox is an open-source framework written in Python for the flexible replication of the results documented in Gu et al. (2020), Empirical Asset Pricing via Machine Learning. The toolbox provides the user with a flexible and fully automated process for i) sourcing the required raw data, ii) cleaning and processing the data, iii) creating the 94 features used in Gu et al. (2020), and iv) replicate key results of different machine learning models. Currently, ~ 80 option features in Bali, Beckmeyer, and Weigert (2023) are incorporated into the toolbox.

Note: The Github repository is currently overhauled and hence in private mode. If you are interested in getting access please do reach out via Email.