kbhola/lppls-ci_tactical_asset_allocation

LPPLS-CI for Tactical Asset Allocation

Hello!

All of the project dependencies are encapsulated in a conda environment named avoiding_bubbles. Whatever system is hosting this project will need an installation of anaconda or miniconda if you would like to install and activate the avoiding_bubbles environment. Setup instructions are below.

Setup

Prerequisites

Conda installation instructions can be found here: https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html

Creating conda env

From the project root run:

conda env create -f environment.yml && conda activate avoiding_bubbles

Next open the jupyter notebook:

jupyter notebook

You should now be able to browse to http://localhost:8888 and view the research project. All of the interesting things you will want to review live in the lppls-ci-for-tactical-asset-allocation.ipynb jupyter notebook. Navigate there within the jupyter UI and run all the cells!

Project Structure

lppls-ci-for-tactical-asset-allocation                      <- Project Root
├── data                                                    <- A place for storing CSVs accessed by the project notebook
|   └── *                 
├── README.md                         
├── environment.yml                                         <- An export of the conda env
├── lppls-ci-for-tactical-asset-allocation.ipynb            <- Jupyter notebook where all the project research lives

Note on the data/ Dir

All of the data generated by the notebook is cached in the data/ directory. If you would like the notebook to fetch/generate fresh data, you can delete the universe.csv and/or the confidence.csv file(s). The notebook should detect that the file(s) no longer exist and refetch or regenerate accordingly.