m6_public

Code for "Probabilistic forecasting of cross-sectional returns: A Bayesian dynamic factor model with heteroskedasticity"

Setup

• create a conda environment
• conda create --name <envname> --file requirements.txt
• in etc, copy eod.yml.sample to eod.yml and add your API key for https://eodhd.com
• jupyter notebook to start the notebook server
• open the main notebook in notebooks
  • set the "PATH_TO_REPO" variable in the first cell
  • run all cells